2016 : WHAT DO YOU CONSIDER THE MOST INTERESTING RECENT [SCIENTIFIC] NEWS? WHAT MAKES IT IMPORTANT?

Scientists and engineers continue to make progress in the battle against the overload of confusing choices that plague modern society. In response to well-known studies from the 1990s and 2000s which found that, when presented with too many choices, people often opt to choose nothing at all; efforts in both the research and commercial worlds became focused around mining behavioral “big data.”

Now, intelligent systems can predict what people want before they want it, so rather than showing a choice of navigational options on a website and forcing the consumer to select options and choose among them, the smart app simply shows the two or three choices that are just right for that person. And, rather than scanning all of the news put forward by a reputable news outlet, readers are shown just the right article, personalized for them, so they don’t have to think about how they will stay up to date. Just the movie or video game match you want to watch at this moment appears before your eyes right as you settle into your chair, set at just the temperature you want with just the food you were craving. You don’t even have to give it a second thought! And of course, your voting choices are arrayed out for you in your favorite color scheme.

And it doesn’t stop with reading. Your vacation planning is figured out for you now as well. In the past, before Intelligent Planning, you would never have thought your dream location was a small town in Kansas, but that is indeed your top recommendation, and so of course that is where you and your loved ones will have the best time. This way the people who designed the systems won’t feel crowded in their vacation spots in Kauai.

So, the science news is all good, except for the anti-science Huxley protesters who had contrary thoughts, but that information was not in the essay you wanted to read.

This was the science news essay you wanted to read (based on essays you’ve recently read, thoughts you’ve recently had, the el grande burrito currently in your intestinal tract, and the promotion you did not get last month at work).

And this is the science news essay that I wanted to write. (AIGenerator ™)

Gentle reminder: contrary thoughts experienced during the consumption of this essay will be reported.

The digital revolution progresses at full pace and reshapes our societies. Many countries have invested in data-driven governance. The common idea is that "more data is more knowledge, more knowledge is more power, and more power is more success." This "magic formula" has promoted the concept of a digitally empowered "benevolent dictator" or "wise king," able to predict and control the world in an optimal way. It seems to be the main reason for the massive collection of personal data, which companies and governments alike have engaged in. 

The concept of the benevolent dictator implies that democracy would be overhauled. I certainly agree that democracy deserves a digital upgrade, but in recent years many voices in the IT industry have even claimed that democracy is an "outdated technology," which needs to be bulldozed. Similar arguments have been put forward by politicians in various countries. There is now an acute danger that democracy would be ended in response to challenges and threats such as climate change, resource shortages, and terrorism. A number of countries come to mind.

However, recent data-driven analyses show that democracy is not a luxury, in contrast to what has been claimed by increasingly many people before. Democracy pays off. A study by Heinrich Nax and Anke Schorr, using high-performance computers, reveals "short-run economic incentives to de-democratization for the most economically and democratically developed nations. [However,] These short-run boosts come with intermediate-run reductions of political capitals and with long-run reductions in growth." In other words: demolishing democracy would be a terrible and costly mistake.

Therefore, the anti-democratic trend in many countries is dangerous and needs to be stopped. First, because ending freedom, participation, and justice would end in socio-political instability and finally in revolution or war. (Similar instabilities have already occurred during the transition from the agricultural to the industrial society and from there to the service society.) Second, because the above "magic formula" is based on flawed assumptions.

Society is not a machine. It cannot be steered like a car. Interaction—and the resulting complex dynamics of the system—changes everything. We know this, for example, from spontaneous breakdowns of traffic flow. Even if we could read the minds of all drivers, such "phantom traffic jams" could not be prevented. But there is a way to prevent them, based on the use of suitable driver assistant systems: distributed control approaches, using Internet of Things technology, real-time data and suitable real-time feedback, together with knowledge from complexity science.

The paradigm of data-driven optimization would work perhaps if we knew the right goal function; moreover, the world would have to change slowly enough, it would have to be sufficiently well predictable, and simple enough. However, all these preconditions are not fulfilled. As we continue to network the world, its complexity grows faster than the data volume, the processing power and the data that can be transmitted. Many aspects of the world are emergent and hardly predictable. The world is quickly changing by innovation, and we need even more of it! Not even the goal function is well-known: should it be gross national product per capita or sustainability, power or peace, average lifespan or happiness? In such cases, (co-)evolution, adaptation, and resilience are the right paradigms, not optimization.

Decision-makers around the globe need to be aware of these things, to save democracy, to get better information systems on the way than those that are based on mass surveillance and brute-force data mining; to argue for interdisciplinary and global collaboration; for approaches built on transparency and trust; for open and participatory systems, because they mobilize the capacity of the entire society; and for systems based on diversity and pluralism, because they promote innovation, societal resilience, and collective intelligence.

If we don't manage to get things on the right way, we may lose many societal, economic, legal and cultural achievements of the past centuries; we might see one of the darkest periods of human history; something much worse than "1984—Big Brother is watching you": a society, in which we might lose our freedom, enslaved by a "citizen score" that would give us plus or minus points for everything we or our friends and partners do; where the government and big corporations would determine how we should live our lives.

These days, physics seems to find itself in a situation similar to that faced by physicists at the turn of the 19th century, just before the dawn of quantum mechanics and general relativity. In 1894, the co-discoverer of the constancy of the speed of light and first American Nobel laureate in physics, Albert Michelson, stated, “It seems probable that most of the grand underlying principles of physical science have been firmly established.” Many, if not most, physicists at that time believed that the handful of experimental anomalies that seemed to violate those principles were minor details that would eventually be explained by the paradigm of classical physics. Within a generation, history showed that quantum mechanics and Einstein’s theory of relativity had to be invented, and classical physics had to be overthrown, in order to explain those minor experimental details.

In 2012, I spent a year on sabbatical at Princeton due to an invitation by David Spergel, one of the lead scientists of the WMAP space satellite. The satellite was designed to make, at the time, the most precise measurements of the afterglow of the Big Bang, the ripples in the cosmic microwave background radiation (CMB), which according our standard model of cosmology would later develop into the vast structures in our universe, to which there is remarkable agreement. Our best theory of the early universe, cosmic inflation, is armed with the most precise physics known to us, general relativity and quantum field theory. Both theories have been independently tested with beyond hair-thin accuracy.

Despite the success of inflation in predicting a handful of features that was observed by WMAP, similar to the end of the 19^th century, some nagging anomalies persist. At Princeton, my colleagues and I spent that year wrestling with those anomalies to no avail. But I forgot about them after a discussion with David who comforted me with the sentiment that the WMAP anomalies are probably due to some unaccounted experimental systematic rather than some strange phenomenon in the sky. David also warned, “if the anomalies persist in the PLANCK satellite, then we will have to take them more seriously.” Well, in 2014 the Planck satellite made an even more precise measurement of the CMB anisotropies and came back with the arguably the most nagging in the suite of anomalies-the hemispherical anomaly. What’s that?

The undulations in the CMB reflect a prediction from cosmic inflation that, aside from those tiny waves, on the largest distance scales the universe looks the same in every direction and at every vantage point in space. This prediction is consistent with one of the pillars of modern cosmology, the Cosmological Copernican Principle. During the epoch that the CMB anisotropies were formed, they too are supposed to, on average look the same in every direction. The theory of cosmic inflation generically predicts this feature. This means that if one divides the sky into two arbitrary hemispheres, we should see the same statistical features of the anisotropies in both hemispheres.

However, both WMAP and Planck see a difference in the amount of anisotropies in different hemispheres in the sky. This feature is in tension one of the most powerful attributes of inflation, whose rapid expansion of space-time smooths out any large-scale directional preference, while democratically sprinkling the space-time fabric with the same amount of ripples in every direction. With some decorative tweaking, it is possible to modify inflation to account for the anomaly, but this seems to be at odds with what inflation was invented for-to make the early universe smooth enough and see the tiny anisotropies that later become galaxies. One might think that this would be a great opportunity for alternative theories of the early universe, such as bouncing/cyclic cosmologies to rise to the occasion and explain the anomalies, but so far, there is no compelling alternative.

Recently, on planet Earth at the Large Hadron Collider in Geneva, the ATLAS, and CMS experiments both reported an “anomaly” when protons collide on energy scales close to 1 trillion electron volts. The experiments see the predicted production of elementary particles that standard quantum field theory of elementary particle interactions predict, with the exception of an excess production of light. Unfortunately, if this observation persists with statistical significance, we will need physics beyond our standard model to explain.

Both of these anomalies, to me and my theoretical colleagues, is a good thing. Will it mean simple, yet less than pretty fix ups of our current “standard models”? Might it be one of our super theories, such as, supersymmetry, strings, loop quantum gravity or GUTS to come to the rescue? Could it be that both anomalies are connected in some yet unseen way? Maybe the anomalies will point us in a direction that our current mode of thinking has yet to do. Whatever it may be, if the anomalies persist, this is exciting times to be a theorist.

Completely unexpected—and hence potentially interesting—was my reaction to the scientific news in Simon Gächter and Benedikt Herrmann’s compelling paper entitled “Reciprocity, culture and human cooperation: previous insights and a new cross-cultural experiment” in the Philosophical Transactions of the Royal Society.

The authors were dealing with a classical question in social science, that is, the “Tragedy of the Commons,” or the conflict between individual interest and collective interest in dealing with common resources. This is a well established conundrum in contemporary behavioral economics and evolutionary sociobiology that is usually solved by (now) classical experimental results about cooperation, trust and altruistic punishment.

There is a vast literature showing how direct and indirect reciprocity are important tools for dealing with human cooperation. Many experiments have shown that people use “altruistic punishment” to sustain cooperation, that is, they are willing to pay without receiving anything back just in order to sanction those who don’t cooperate, and hence promote pro-social behavior.

Yet, Gächter and Herrmann showed in their surprising paper that in some cultures, when people were tested in cooperative games (such as the “public good game”), the people who cooperated were punished, rather than the free-riders.

In some societies, people prefer to act anti-socially and they take actions to make sure that the others do the same! This means that cooperation in societies is not always for the good: you can find cartels of anti-social people who don’t care at all for the common good and prefer to cooperate for keeping a status quo that suits them even if the collective outcome is a mediocre result.

As an Italian with first-hand experience living in a country where, if you behave well, you are socially and legally sanctioned, this news was exciting, even inspiring … perhaps cooperation is not an inherent virtue of the human species. Perhaps, in many circumstances, we prefer to stay with those who share our selfishness and weaknesses and to avoid pro-social altruistic individuals. Perhaps it's not abnormal to live outside a circle of empathy.

So what’s the scientific “news that stays news”: Cooperation for the collective worse is as widespread as cooperation for a better society! 

When fear and tension rise across racial and ethnic divisions, as they have in recent years, genetic arguments to explain behavioral differences can quickly become popular. However, we know racial and ethnic groups may also be exposed to vastly different experiences, also likely to strongly impact behavior. Despite seemingly inexhaustible interest in the nature/nurture debate, we are only starting to learn how the interaction of genes with experience may alter the potential of individuals, and to see how individual decision making styles can alter the potential wealth of nations.      

A captivating news image I saw this year depicted two sets of identical twins, mixed up as infants, raised in separate families in Colombia. The men and their families assumed they were fraternal twins, who share genes only as much as siblings and therefore do not look alike. Only in adulthood, did the young men discover the mistake and find their identical twin brothers through the recognition of friends. One mixed pair of twins grew up in the city and the other in countryside with far more modest resources. We are all, of course, eager to know how these different environments altered these men’s personalities, preferences, intelligence, and decision making when their genes were the same. We are all probably fairly comfortable with the idea that trauma, hardship, or parenting style could impact our emotional development and our emotional patterns even in adulthood. However, it is less clear how early experience might affect how we think and make decisions. Is one identical twin more likely to save his money, repeat a mistake, take a short cut, buy lottery tickets, or stubbornly resist changing his mind because he was raised in a different situation? Or would the identical twin pair make the same choice regardless of upbringing? The answers from these twins are still emerging and the sample is, of course, anecdotally small. If we definitively knew the answer to these questions we might change how we view parenting and investment in childcare and education.

A growing body of work now effectively models this “twins raised apart” situation in genetically identical strains of inbred mice or genetically similar rats. Rodents get us away from our cultural biases and can be raised in conditions that model human experience of adversity and scarcity in infancy and childhood. In one early life stress model, the mother rodent is not given adequate nesting material and moves about the cage restlessly, presumably in search of more bedding. In other models, the rodent pups are separated from the mother for portions of the day or are housed alone after weaning. These offspring are then compared to offspring that have been housed with adequate nesting material and have not been separated more than briefly from their mother or siblings.

Investigators first focused early life adversity research in rodent models on emotional behavior. This research found that early life adversity increased adult stress and anxiety-like behavior. More recent studies, including some from my own lab, find that early life adversity can also impact how rodents think—the way they solve problems and make decisions. Rats and mice that have been subjected to greater early life stress tend to be less cognitively flexible (stubbornly applying old rules in a laboratory task after new rules are introduced) and they may also be more repetitive or forgetful. Some of the differences in behavior have been found to fade as the animals get older but others grow stronger and persist into adulthood.

I would hesitate to say that one group was smarter, since it is hard to determine what would be an optimal style for a wild rodent. We might see stubborn, inflexible or repetitive behavior as unintelligent in a laboratory test. In some real world situations, the same behavior might become admirable as “grit” or perseverance.

Competing theories attempt to explain these changes in emotional behavior, problem solving, and decision making. The brains of the mice that experienced adversity may be dysfunctional, in line with evidence of atrophy of frontal neurons after stress.  Alternatively, humans and rodents may show positive adaptation to adversity. In one model currently growing in popularity, a brain developing under adversity may adopt a “live fast-die young” strategy that favors earlier maturation and short-term decision making. In this adaptive calibration model, animals that are genetically identical might express different set of genes in their brain and develop different neural circuits in an attempt to prepare their brain for success in the kind of environment in which they find themselves. It is unclear how many different possible trajectories might be available or when or how young brains are integrating environmental information. However, based on this adaptive calibration model, in lean times versus fat times you might expect a single species to “wire-up” different brains and display different behaviors without requiring genetic change or genetic selection at the germline level (level of eggs and sperm).

Why should we care? This data might explain population level economic behavior and offer a powerful counter narrative to seductive genetic explanations of success. Another piece of captivating news out this year was Nicholas Wade’s review of Garret Jones’ Hive Mind in the Wall Street Journal. Reading this review, I learned that national savings rates correlate with average IQ scores even if individual IQ scores do not; the subtitle is “How your nation’s IQ matters so much more than your own.” In his review, Wade (not Jones) suggests we need to look to “evolutionary forces” to explain IQ and its correlated behavioral differences. The well controlled data from experiments in mice and rats suggest we also look to early life experience. Rodents are not known for their high IQ, but the bottom line is what intelligence they have is sensitive to early life experience, even when we hold germline genetics constant. Putting these rodent and human findings together, one might hypothesize that humans exposed to instability or scarcity in early life are developing brains that are wired for shorter term investment and less saving. Thus, rather than dismissing the successes and failures of nations to slow changing genetic inheritance, we might foster a brighter future by paying more attention to the quality of early life experiences.  

In 2014 a group of big data scientists (including myself), representatives of big data companies, and the heads of National Statistical Offices from nations in both the northern and southern hemispheres, met within the United Nations headquarters and plotted a revolution. We proposed that all of the nations of the world begin to measure poverty, inequality, injustice, and sustainability in a scientific, transparent, accountable, and comparable manner. Surprisingly, this proposal was approved by the UN General Assembly in 2015, as part of the 2030 Sustainable Development Goals.

This apparently innocuous agreement is informally known as the Data Revolution within the UN, because for the first time there is an international commitment to discover and tell the truth about the state of the human family as a whole. Since the beginning of time, most people have been isolated, invisible to government and without information about or input to government health, justice, education, or development policies. But in the last decade this has changed. As our UN Data Revolution report, titled “A World That Counts,” states:

Data are the lifeblood of decision-making and the raw material for accountability. Without high-quality data providing the right information on the right things at the right time, designing, monitoring and evaluating effective policies becomes almost impossible. New technologies are leading to an exponential increase in the volume and types of data available, creating unprecedented possibilities for informing and transforming society and protecting the environment. Governments, companies, researchers and citizen groups are in a ferment of experimentation, innovation and adaptation to the new world of data, a world in which data are bigger, faster and more detailed than ever before. This is the data revolution.

More concretely, the vast majority of humanity now has a two-way digital connection that can send voice, text, and most recently, images and digital sensor data because cell phone networks have spread nearly everywhere. Information is suddenly something that is potentially available to everyone. The Data Revolution combines this enormous new stream of data about human life and behavior with traditional data sources, enabling a new science of “social physics” that can let us detect and monitor changes in the human condition, and to provide precise, non-traditional interventions to aid human development.

Why would anyone believe that anything will actually come from a UN General Assembly promise that the National Statistical Offices of the member nations will measure human development openly, uniformly, and scientifically? It is not because anyone hopes that the UN will manage or fund the measurement process. Instead we believe that uniform, scientific measurement of human development will happen because international development donors are finally demanding scientifically sound data to guide aid dollars and trade relationships. 

Moreover, once reliable data about development start becoming familiar to business people, we can expect that supply chains and private investment will begin paying attention. A nation with poor measures of justice or inequality normally also has higher levels of corruption, and a nation with a poor record in poverty or sustainability normally also has a poor record of economic stability. As a consequence, nations with low measures of development are less attractive to business than nations with similar costs but better human development numbers.

Historically we have always been blind to the living conditions of the rest of humanity; violence or disease could spread to pandemic proportions before the news would make it to the ears of central authorities. We are now beginning to be able to see the condition of all of humanity with unprecedented clarity. Never again should it be possible to say “we didn’t know.” No one should be invisible. This is the world we want—a world that counts.

A year and half ago, the scientific community and the press trumpeted the claim by a team of scientists that they had found definitive proof that the universe began with a Big Bang followed by a period of accelerated expansion, known as inflation. Their proof was that the light produced in the infant universe and collected by their detectors exhibited a distinctive pattern of polarization that could only be explained if the large scale structure of the universe was set when the temperature and density of the universe were extraordinarily high, just as posited in the Big Bang inflationary picture.

Over the ensuing year, though, it became clear that the claim was a blunder: in searching for a cosmic signal from the distant universe, the team had not taken proper account of the polarization of light that occurred nearby when it passed through the dust in our Milky Way on the way to their detectors. The new claim from the team, published in recent months, is that there is no sign of the cosmic polarization they had been seeking despite an extensive search with extraordinarily sensitive detectors.

The retraction received considerable attention but the full import of the news has not been appreciated: we now know that the Big Bang cannot be what we thought it was.

The prevailing view has been that the Big Bang was a violent high-energy event during which space, time, matter and energy were suddenly created from nothing in a distorted, non-uniform distribution. To account for the undistorted nearly uniform universe we actually observe, many cosmologists hypothesize a period of rapid stretching (inflation) just after the bang when the concentration of energy and matter was still very high. If there were inflationary stretching only, the universe would become perfectly smooth, but there is always quantum physics in addition to stretching and quantum physics resists perfect smoothness.

At the high concentrations of energy required for inflation, random quantum fluctuations keep generating bumps and wiggles in the shape of space and the distribution of matter and energy that should remain when inflation ends. The quantum-generated irregularities should appear today as hot spots and cold spots in the pattern of light emanating from the early universe, the so-called cosmic background radiation. Indeed, the hot and cold spots have been observed and mapped in numerous experiments since the COBE satellite detected the first spatial variations in the cosmic background radiation temperature in 1992.

The problem is that, when the concentration of energy is high, the quantum-generated distortions in space should modify the way light scatters from matter in the early universe and imprint a spiraling pattern of polarization across the cosmos. It was the detection of this spiraling pattern (referred to as B-mode) that was claimed as proof of the Big Bang inflationary picture, and then retracted. The failure to detect the B-mode pattern means that there is something very wrong with the picture of a violent Big Bang followed by a period of high energy-driven inflation. Whatever processes set the large-scale structure of the universe had a to be a gentler, lower-energy process than has been supposed.

Simply lowering the energy concentration at which inflation starts, as some theorists have suggested, only leads to more trouble. This leaves more time after the Big Bang for the non-uniform distribution of matter and energy to drive the universe away from inflation. Starting inflation after the Big Bang and having enough inflation to smooth the universe becomes exponentially less likely as the energy concentration is lowered. The universe is more likely to emerge as too rough, too curved, too inhomogeneous compared to what we observe.

Something more radical is called for. Perhaps an improved understanding of quantum gravity will enable us to understand how the Big Bang and inflation can be discarded in favor of gentler beginning. Or perhaps the Big Bang was actually a gentle bounce from a previous period of contraction to the current period of expansion. During a period of slow contraction, it is possible to smooth the distribution of space, matter and energy and to create hot spots and cold spots without creating any B-modes at all.

As the news sinks in, scientists will need to rethink depending on whether forthcoming, more sensitive efforts to detect a B-mode pattern find anything at all. Whatever is found, our view of the Big Bang will be changed, and that is newsworthy.

Physicists have spent the last 100 years attempting to reconcile Einstein’s theory of general relativity, which describes the large-scale geometry of spacetime, with quantum mechanics, which deals with the small-scale behavior of particles. It’s been slow going for a century, but now, suddenly, things are happening.           

First, there’s ER=EPR. More idea than equation, it’s the brainchild of physicists Juan Maldacena and Leonard Susskind. On the left-hand side is an Einstein-Rosen bridge, a kind of geometric tunnel connecting distant points in space, otherwise known as a wormhole. On the right are Einstein, Rosen, and Podolsky, the three physicists who first pointed out the spooky nature of quantum entanglement, wherein the quantum state of two remote particles straddles the distance between them. Then there’s that equals sign in the middle. Boldly it declares: spacetime geometry and the links between entangled particles are two descriptions of the same physical situation. ER = EPR appears brief and unassuming, but it’s a daring step toward uniting general relativity and quantum mechanics—with radical implications.         

Intuitively, the connection is clear. Both wormholes and entanglement flout the constraints of space. They’re shortcuts. One can enter a wormhole on one side of the universe and emerge from it on the other without having to traverse the space in between. Likewise, measuring one particle will instantaneously determine the state of its entangled partner, even if the two are separated by galaxies.

The connection becomes more intriguing when viewed in terms of information. For maximally entangled particles, the information they carry resides simultaneously in both particles but in neither alone; informationally speaking, no space separates one from the other. For particles that are slightly less than maximally entangled, we might say there is some space between them. As particles become less and less entangled, information becomes more and more localized, words like “here” and “there” begin to apply and ordinary space emerges.

One hundred years ago, Einstein gave us a new way to think about space—not as the static backdrop of the world, but as a dynamic ingredient. Now, ER=EPR gives us yet a newer interpretation: what we call space is nothing more than a way to keep track of quantum information. And what about time? Time, physicists are beginning to suspect, may be a barometer of computational complexity.

Computational complexity measures how difficult it is to carry out a given computation—how many logical steps it takes, or how the resources needed to solve a problem scale with its size. Historically, it’s not something physicists thought much about. Computational complexity was a matter of engineering—nothing profound. But all that has changed, thanks to what’s known as the black hole firewall paradox—an infuriating dilemma that has theoretical physicists pulling out their hair.

As a black hole radiates away its mass, all the information that ever fell in must emanate back out into the universe, scrambled amongst the Hawking radiation; if it doesn’t, quantum mechanics is violated. The very same information must reside deep in the black hole’s interior; if it doesn’t, general relativity is violated. And the laws of physics decree: information can’t be duplicated. The firewall paradox arises when we consider an observer, Alice, who decodes the information scrambled amongst the Hawking radiation, then jumps into the black hole where she will find, by various accounts, an illegal information clone or an inexplicable wall of fire. Either way, it’s not good.

But Alice’s fate recently took a turn when two physicists, Patrick Hayden and Daniel Harlow, wondered how long it would take her to decode the information in the radiation. Applying a computational complexity analysis, they discovered that the decoding time would rise exponentially with each additional particle of radiation. In other words, by the time Alice decodes the information, the black hole will have long ago evaporated and vanished, taking any firewalls or violations of physics with it. Computational complexity allows general relativity and quantum mechanics to peacefully coexist.

Hayden and Harlow’s work connects physics and computer science in a totally unprecedented way. Physicists have long speculated that information plays a fundamental role in physics. It’s an idea that dates back to Konrad Zuse, the German engineer who built the world’s first programmable electronic computer in his parent’s living room in 1938, and the first universal Turing machine three years later. In 1967, Zuse wrote a book called Calculating Space, in which he argued that the universe itself is a giant digital computer. In the 1970s, the physicist John Wheeler began advocating for “it from bit”—the notion that the physical, material world is, at bottom, made of information. Wheeler’s influence drove the burgeoning field of quantum information theory and led to quantum computing, cryptography and teleportation. But the idea that computational complexity might not only describe the laws of physics, but actually uphold the laws of physics, is entirely new.

It’s odd, on glance, that something as practical as resource constraints could tell us anything deep about the nature of reality. And yet, in quantum mechanics and relativity, such seemingly practical issues turn out to be equally fundamental. Einstein deduced the nature of spacetime by placing constraints on what an observer can see. Noticing that we can’t measure simultaneity at a distance gave him the theory of special relativity; realizing that we can’t tell the difference between acceleration and gravity gave him the curvature of spacetime. Likewise, when the founders of quantum mechanics realized that it is impossible to accurately measure position and momentum, or time and energy, simultaneously, the strange features of the quantum world came to light. That such constraints were at the heart of both theories led thinkers such Arthur Stanley Eddington to suggest that at its deepest roots, physics is epistemology. The new computational complexity results push further in that direction.

So that’s the news: a profound connection between information, computational complexity and spacetime geometry has been uncovered. It’s early to say where these clues will lead, but it’s clear now that physicists, computer scientists and philosophers will all bring something to bear to illuminate the hidden nature of reality.

Our planet is growing itself a brain. That process is accelerating, and the project will determine the future of humans and many other species.

The major Internet and space technology corporations, among others, have confirmed multi-billion-dollar investments to bring low-cost broadband Internet to every square meter of Earth's surface within ten years. They are building the railway tracks and freeways of the 21st century—but at global scale, and with breathtaking speed.

Five billion human minds are therefore about to come online, mostly via sub-$50 smartphones. And unlike the two billion who preceded them, their first experience of the Internet may not be clunky text, but high-resolution video and a fast connection to whatever grabs their imagination.

This is a social experiment without historical precedent. Most of us built our Internet habits on top of years of exposure to newspapers, books, radio and TV. Many of those soon to come online are currently illiterate. Who is going to win their attention and to what consequence? Local language versions of social media, wikipedia, Porn? Video games? Marketing come-ons? Government propaganda? Addictive distractions? Free education? Conversations with mentors in other countries empowered by real-time machine translation?

It's certainly possible to imagine a beautiful scenario in which: For the first time in history every human can have free access to the world's greatest teachers in their own language; people discover the tools and ideas to escape poverty and bigotry; growing transparency forces better behavior from governments and corporations; the world starts to gain the benefit of billions of new minds able to contribute to our shared future; global interconnection begins to trump tribal thinking.

But for that to have even a chance of happening, we need to get ready to engage in the mother of all attention wars. Every global company, every government and every ideology has skin in this game. It could play out in many different ways, some of them ugly.

What's unique and significant is that we have a roadmap. It's now clear that we will not need to physically wire the planet. Satellites, possibly aided by drones and balloons, are about to get the job done a lot faster. We can therefore be certain that a massive transformation is about to hit. We better get ready.

We used to think of memory as a veridical record of events past, like a videotape in our heads that is always on hand to be re-played. Of course, we knew this memory to be far more fragile and incomplete than a real videotape: we forget things, and many events don’t even get stored in the first place. But when we replay our memories, we feel sure that what we do recall really happened. Indeed, our entire legal system is built on this belief.

Three scientific discoveries in the past century have changed that picture: two some time ago, and one—the “news”—that is very recent. Some time ago, we learned that memory is not a record so much as a re-construction. We don’t recall events so much as reassemble them, and in doing so, crucial aspects of the original event may get substituted—it wasn’t Georgina you ran into that day, it was Julia; it wasn’t Monte Carlo, it was Cannes; it wasn’t sunny, it was actually overcast—it rained later, remember? Videotapes never do that—they get ragged and perhaps skip sections or lose information but they don’t make things up.

It has also been known for some time now—since the 1960s in fact—that the act of re-activating a memory renders it temporarily fragile, or “labile.” In its labile state, a memory is vulnerable to disruption, and might be stored again in an altered form. In the laboratory, this alteration is usually a degradation, induced by some memory-unfriendly agent like a protein-synthesis inhibitor. We knew such drugs could affect the formation of memories, but it is more surprising that they can also disrupt a memory after it has been formed, albeit only when it has been re-activated.

The story doesn’t end there. Very recently, it has been shown that memories aren’t just fragile when they have been re-activated, they can actually be altered. Using some of the amazing new molecular genetic techniques that have been developed in the past three decades, it has become possible to identify which subset of neurons participated in the encoding of an event, and later experimentally re-activate only these specific neurons, so that the animal is forced (we believe) to recall the event. During this re-activation, scientists have been able to tinker with these memories so that they are different from the original ones. So far, these tinkerings have just involved changing emotional content, such that, for example, a memory for a place that was neutral becomes positive, or for one that was positive becomes negative, so that the animal subsequently seeks out or avoids those places. However, we are not far from trying to actually write new events into these memories, and it seems likely that this will be achievable.

It may seem odd that memories are so plastic and vulnerable to change. Why would we evolve a strange, disconcerting, system like this? Why can’t memory be more like a videotape, so that we can trust it more? We don’t know the answer for sure yet, but evolution doesn’t care about veracity, it only cares about survival, and it usually has a good reason for what may seem like odd design features.

The advantages of the constructive nature of memory seem obvious: rather than the enormous storage capacity required to remember every “pixel” of a life experience, it is a far more economical use of our synapses to stockpile a collection of potential memory ingredients, and then to simply record each event in the form of a recipe: take a pinch of a Southern French beach, add a dash of an old school friend, mix in some summer weather… etc. The labile nature of memory is more curious, but many theoretical neuroscientists think it may allow construction of super-memories, called semantic memories, which are agglomerations of individual event-memories that combine to form a more general, overarching piece of knowledge about the world. After a few visits to the Mediterranean you learn that it is usually sunny, and so the odd incidence of overcast gloom gets washed out, and fades from recollection. Your behavior thus becomes adapted not to a specific past event but to the general situation, and you know on holiday to pack sunscreen and not umbrellas.

The fabricated, labile nature of memory is at once a reason for amazement and concern. It is amazing to think that the brain in constantly and busily re-assembling our past, such that that past is not really the one we think it is. It is also concerning, because this constructed past seems extraordinarily real—almost as real as our present—and we base our behavior on it trustingly.

Thus, an eye-witness will make confident assertions based solely on recollection that lead to the lifelong incarceration of another person, and nobody worries about this except neuroscientists. It is also amazing/concerning that as scientists and doctors, we are now on the threshold of memory editing: being able to alter a person’s life memories in a selective manner.

The therapeutic potential of this is exciting—imagine being able to surgically reduce the pain of a traumatic memory? But we could also reach into the brain and change a person’s past, and in doing so change who they are. These are technologies to use with care. However, one could argue that the fabricated and labile nature of our memories means that perhaps we aren’t really who we think we are, anyway.

Could the color of a cheap dress create a meaningful scientific controversy? In 2015 a striped, body-hugging, £50 dress did just that. In February, Scottish mother Cecilia Bleasdale sent her family a poor quality photo of a dress she bought for her daughter’s wedding. Looking at the same image, some people saw the stripes as blue and black; others as white and gold. Quickly posted online, “that dress” was soon mentioned nearly half a million times. This simple photo had everything a meme needs to thrive: it was easy to pass on, accessible to all, and sharply divided opinions. #thedress was indeed called the meme of the year and even a “viral singularity.” Yet it did not die out as fast as it had risen. Unlike most viral memes, this one prompted deeper and more interesting questions.

Scientists quickly picked up on the dispute and garnered some facts. Seen in daylight, the actual dress is indisputably blue and black. It is only in the slightly bleached out photograph that white and gold is seen. In a study of 1,400 respondents who’d never seen the photo before, 57 percent saw blue and black, 30 percent saw white and gold, and about 10 percent saw blue and brown. Women and older people more often saw white and gold.

This difference is not like disputes over whether the wallpaper is green or blue. Nor is it like ambiguous figures such as the famous Necker cube, which can be seen tilted towards or away from the viewer, or the duck/rabbit or wife/mother-in-law drawings. People can typically see these bistable images either way, and flip their perception between views, getting quicker with practice. Not so with “that dress.” Only about 10 percent of people could switch colors. Most saw the colors resolutely one way and remained convinced that they were “right.” What was going on became a genuinely interesting question for the science of color vision.

Vision science has long shown that color is not the property of an object, even though we go on speaking as though it is. In fact, color emerges from a combination of the wavelengths of light emitted or reflected from an object and the kind of visual system looking at it. A normal human visual system, with three cone types in the retina, concludes “yellow” when any one of an indefinite number of different wavelength combinations affects its color-opponent system in a certain way. This means that a species with more cone types, such as the mantis shrimp which has about sixteen types, would see many different colors when humans would see only the same shade of yellow.

When people are red-green “color blind,” with only two cone types instead of three, we may be tempted to think they fail to see its real color. Yet there is no such thing. There are even rare people (mostly women) who have four cone types. Presumably they can see colors that the rest of us cannot even imagine. This may help us accept that the dress is not intrinsically one color or the other, but still provides no clue as to why people see it so differently.

Could the background in the photo be relevant? In the 1970s, Edwin Land (inventor of the Polaroid camera) showed that the same colored square appears to be a different color depending on the other squares surrounding it. This relates to an important problem that evolution has had to solve. If color information is to be useful, an object must look the same color on a bright sunny day as on an overcast one, yet the incident light is yellower at midday and bluer from a gloomy or evening sky. So our visual systems use a broad view of the scene to assess the incident light and then discount that when making color decisions, just like the automatic white balance (AWB) in modern cameras.

This, it turns out, may solve the great dress puzzle. It seems that some people take the incident light as yellowish, discounting the yellow to see blue and black, while others assume a bluer incident light and see the dress as white and gold. Do the age and sex differences provide any clues as to why? Are genes or people’s lifetime experiences relevant? This controversy is still stimulating more questions.

Was it a step too far when some articles suggested that #thedress could prompt a "world-wide existential crisis" over the nature of reality? Not at all, for color perception really is strange. When philosophers ponder the mysteries of consciousness they may refer to qualia—private, subjective qualities of experience. An enduring example is “the redness of red” because the experience of seeing color provokes all those questions that make the study of consciousness so difficult. Is someone else’s red like mine? How could I find out? And why, when all this extraordinary neural machinery is doing its job, is there subjective experience at all? I would guess that “that dress” has yet more fun to provide.

The most long-range portentous event of 2015 was NASA’s New Horizons spacecraft arrowing by Pluto, snapping clean views of the planet and its waltzing moon system. It carries an ounce of Clyde Tombaugh's ashes, commemorating his discovery of Pluto in 1930. Tombaugh would have loved seeing the colorful contrasts of this remarkable globe, far out into the dark of near-interstellar space. Pluto is now a sharply-seen world, with much to teach us.

As the spacecraft zooms near an iceteroid on New Year’s Day, 2019, it will show us the first member of the chilly realm beyond, where primordial objects quite different from the wildly eccentric Pluto also dwell. These will show us what sort of matter made up the early disk that clumped into planets like ours—a sort of family tree of worlds. But that’s just an appetizer.

New Horizons is important not just for completing our first-look at every major world in the solar system. It points outward, to a great theatre in the sky, where the worlds of the galaxy itself are on display.

Beyond Pluto looms a zone where the Sun’s mass acts as a giant lens, its gravitation focusing the light of other stars to a small area. Think of it as gravity gathering starlight into an intense pencil, focused down as dots on a chilly sphere. Einstein calculated such gravitational bending of light in 1912, though Newton knew the effect should occur in his own theory of mechanics and optics.

Images of whole galaxies made by this effect were not discovered until 1988. Such magnification of light from a star and the planets near it naturally creates a telescope of unparalleled power. It can amplify images by factors that can vary from a hundred million to a quadrillion, depending on frequency.

This suggests using such power to study worlds far across the interstellar reaches. We have already detected over two thousand planets around other stars, thanks to the Kepler mission and other telescopes. We can sense the atmospheres of some, when they pass across our view of their stars, silhouetted against that glare. Many more will come.

Our space telescopes envisioned for the next several decades can only tease out information about a planet at interstellar distances by studying how light reflects or absorbs changes. At best, such worlds will be dots of faint light.

But at the lensing distance, under enormously better resolution, we can see the worlds themselves—their atmospheres and moons, their seas and lands, perhaps even their cities.

Hearty New Horizons now zooms along at about 15 kilometers a second, or more usefully said, at about three Astronomical Units (AU, the distance between Earth and our sun) in a year, relative to the sun. The focus spot of the sun is 550 AU out, as Einstein predicted in 1936. New Horizons will take 180 years to get to that focus and be long dead as its nuclear power supply fades. So future missions to put a telescope out there demands speeds ten or more times faster. (Voyager, flying after thirty-eight plus years, is only 108 AU away from earth.)

We know of ways to propel spacecraft to such speeds. Most involve flying near the sun and picking up velocity by firing rockets near it, or getting a boost from its intense light using unfurled solar sails, and other astro-tricks. Those feats we can fashion within decades, if we wish.

Our goal could be to put an observing spacecraft that can maneuver out at the focus of “God’s zoom lens”—a 70 billion mile long telescope that light takes over three days to traverse. An observing spacecraft could see whatever is behind the sun from it, many light years away.

This would vastly improve our survey of other worlds, to pick off strings of stars and examine their planets. Using the sun as a lens works on all wavelengths, so we could look for signs of life—say, oxygen in an atmosphere—and perhaps even eavesdrop on aliens’ radio stations, squawking into the galactic night.

A first, such a telescope could scrutinize Alpha Centauri’s planets, if it has some, the next big step before trying to travel there. The craft could trace out a spiral pattern perpendicular to its outward path, slightly shifting its position relative to scan the Alpha Centauri system. Then look further still—because the focus effect remains beyond 550 AU, as a spacecraft moves outward, still seeing the immense magnifications.

New Horizons maybe the best-named spacecraft of all, for it does indeed portend fresh, bold perspectives.

The news cycle regularly features stories about reinventing 21^st century cities. Amongst societal issues, perhaps only education is targeted more frequently for reform. And for good reason.

Since 2008, more people have lived in cities than not. By the end of this century, cities will generate nearly 90 percent of population growth and 60 percent of energy consumption. While these bustling hubs of humanity function as the planet’s innovation centers, they’re also responsible for the lion’s share of environmental damage. By some estimates, today’s cities generate around 75 percent of global carbon dioxide emissions, alongside countless other pollutants. They consume vast expanses of forests, farmland, and other landscapes while fouling rivers, oceans, and soils. In short, if we don’t get cities right, it’s hard to imagine a healthy future for humanity, let alone the biosphere.

A Tale of Two Cities

By my reading, most of the press surrounding the reinvention of cities can be grouped into two seemingly disparate camps. One camp calls for cities that are “smart,” “digital,” and “high-tech.” Here the emphasis is on information and communication technologies with the potential to boost urban functioning. Fueled by the recent tsunami of civic data—climate information, traffic patterns, pollution levels, power consumption, etc.—key arenas cited for high-tech interventions include flows of people, energy, food, water, and waste. Advocates imagine cities that can talk, providing live status updates for pollution, parking, traffic, water, power, and light. Thanks to such innovations as ultra-low power sensors and web-based wireless networks, smart cities are rapidly becoming reality.

From the other camp we hear about the need for “green,” “biophilic,” even “wild” cities where nature is conserved, restored, and celebrated. Of course, cities have traditionally been places where the wild things aren’t, engineered to wall humans off from the natural world. Yet recent and rapidly accumulating research documents the positive health impacts of regular contact with urban nature. Benefits include reduced stress levels, stronger immune systems, and enhanced learning. Perhaps most important are the myriad physical, mental, and emotional benefits that appear to be essential to a healthy childhood. Proponents of the green city camp also point out that many of the pressing issues of our time—among them climate change, species extinctions, and habitat loss—will not, indeed cannot, be addressed unless people understand and care about nearby nature.

So there you have it. Big Data versus Mother Nature. Two views on the future of cities, apparently residing at opposite ends of the spectrum. One values technological innovation, the other biological wisdom and nature connection. Yet, upon closer inspection, these perspectives are far from mutually exclusive. Indeed they’re complementary.

High-Tech Meets Nature-Rich

It’s entirely possible for cities to be both high-tech and nature-rich. Today, few proponents of green cities claim that we need to go “back to nature.” Rather they argue for going forward into a future rich in both technology and nature. New terms like “technobiophilic cities” and “nature-smart cities” are emerging to describe this blended concept, urban settings where the natural and digital are embraced simultaneously.

Yes, nature-smart cities will have plenty of green roofs, green walls, and interconnected green spaces. Seeding native plants attracts native insects, which in turn entices native birds and other animals, transforming backyards, schoolyards, and courtyards into miniature ecosystems. These nuggets of urban nature, in addition to improving the health of humans, are the last good hope for scores of threatened species.

In addition, cities rich in nature can leverage smart technologies to help urbanites switch to renewable energy sources—wind, sun, water, and geothermal. Green transportation reduces carbon emissions and improves the environment. Green buildings can act like trees, running on sunlight and recycling wastes, so that cities function like forests.

Interestingly, both views of our collective urban future highlight the importance of an informed and engaged citizenry. Digital technologies and big data have potential to put control back in the hands of individuals—for example, through greater participation in local governance (“E-Governance”). Similarly, citizen scientists and citizen naturalists can play important roles restoring plants and animals, as well as monitoring these species and making adjustments to improve the quality and quantity of nearby nature. Here, then, is a potent pathway to help people act on the basis of robust scientific data (and boost science literacy along the way).

In short, there’s much more than hot air in all the news about reimagining the future of cities. At least within urban settings, Mother Nature and Big Data have the potential to make excellent bedfellows. Indeed our survival, and that of much of Earth’s biodiversity, may just depend on consummating this union. If successful, we’ll witness the birth of a new kind of city, one in which both people and nature thrive.

The new biotech tool called “gene drive” changes our relation to wild species profoundly. Any gene (or set of genes) can be forced to “drive” through an entire wild population. It doesn’t matter if the trait the genes control is deleterious to the organism. With one genetic tweak to its germline, a species can even be compelled to go extinct.

The technique works by forcing homozygosity. Once the genes for a trait are homozygous (present on both chomosomes) and the parents are both homozygous, they will breed true for that trait in all their descendents. Artificially selecting for desired traits via homozygosity is what breeders do. Now there’s a shortcut.

In effect, gene-drive genes forbid the usual heterozygosity in cross-bred parents. In any two parents, if one of them is gene-drive homozygous, all their offspring will be gene-drive homozygous and will express the gene-drive trait. Proviso: it only works with sexually reproducing species—forget bacteria. And it only spreads quickly enough in rapidly reproducing species—forget humans.

The mechanism was first described in 2003 as a potential tool by Austin Burt of Imperial College London. The way it works is that a “homing endonuclease gene” cuts the DNA in the adjoining chromosome and provides the template for the DNA repair, thus duplicating itself. In Richard Dawkins terms, it is an exceptionally selfish gene. Heterozygous becomes homozygous, and after several generations the gene is present in every individual of the population. The phenomenon is common in nature.

Gene drive shifted from an interesting concept to a powerful tool with the arrival in the last few years of a breakthrough in genome editing called CRISPR-Cas9. Suddenly genes could be edited easily, cheaply, quickly, and with great precision. It was a revolution in biotech.

In 2014 George Church and Kevin Esvelt at Harvard published three papers spelling out the potential power of CRISPR-enabled gene drive and the kind of public and regulatory oversight needed to ensure its responsible deployment. They also encouraged the development of an “undo” capability. Ideally the effects of an initial gene drive release could, if desired, be reversed before it spread too far with the release of a countermanding secondary gene drive.

The benefits of gene drive could be huge. Vector-borne scourges like malaria and dengue fever could be eliminated by eliminating (or just adjusting) the mosquitoes that carry them. Food crops could be protected by reversing herbicide-resistance in weeds. Wildlife conservation would be able to cure one of its worst threats—the alien invasive rats, mice, ants, etc. that are massively destructive to native species on ocean islands. With gene drive the invaders could be completely extirpated (driven extinct locally), and the natives would be protected permanently.

Developments are coming quickly. A team at Harvard proved that gene drive works in yeast. A team at UC San Diego inadvertently proved that it works in fruit flies. Most importantly, Anthony James at UC Irvine and colleagues showed that malaria mosquitoes could be altered with gene drive so that they no longer carry the disease. Kevin Esvelt is developing a project to do the same with white-footed mice, which are the wildlife reservoir for Lyme disease in humans; if they are cured, humans will be as well.

The power to permanently change wild populations genetically is a serious matter. There are ecological questions, ethical issues, and many technical nuances that have to be sorted out thoroughly. Carefully, gradually, they will be.

Humanity has decided about this sort of thing before. Guinea worms are a horrible parasite that used to afflict 2.5 million people, mostly in Africa. In 1980 disease control experts set about eliminating the worms totally from the world, primarily through improved water sanitation. That goal of deliberate extinction is now on the brink of completion. One of the strongest advocates of the project, President Jimmy Carter, declared publicly, “I would like the last Guinea worm to die before I do.”

Gene drive is not a new kind of power, but it is a new level of power. And a new level of responsibility.

If you were on a selection committee tasked with choosing someone to hire (or to admit to your university, or to receive a prize in your field), and it came down to two candidates who were equally qualified on objective measures, which candidate would you be most likely to choose?

__A) The one who shared your race
__B) The one who shared your gender
__C) The one who shared your religion
__D) The one who shared your political party or ideology

The correct answer, for most Americans, is now D. It is surely good news that prejudice based on race, gender, and religion are way down in recent decades. But it is very bad news—for America, for the world, and for science—that cross-partisan hostility is way up.

My nomination for “news that will stay news” is a paper by political scientists Shanto Iyengar and Sean Westwood, titled “Fear and Loathing Across Party Lines: New Evidence on Group Polarization.” Iyengar and Westwood report four studies (all using nationally representative samples) in which they gave Americans various ways to reveal both cross-partisan and cross-racial prejudice, and in all cases cross-partisan prejudice was larger.

First they used a measure of implicit attitudes (the Implicit Association Test), which measures how quickly and easily people can pair words that are emotionally good versus bad with words and images associated with Blacks vs. Whites. They also ran a new version of the test that swapped in words and images related to Republicans vs. Democrats, instead of Blacks vs. Whites. The effect sizes for cross-partisan implicit attitudes were much larger than cross-race. If we focus just on White participants who identified with a party, the cross-partisan effect was about 50 percent larger than the cross-race effect. When Americans look at each other or try to listen to each other, their automatic associations are more negative for people from the “other side” than they are for people of a different race.

In another study they had participants read pairs of fabricated resumes of graduating high school seniors and select one to receive a scholarship. Race made a difference—Black and White participants generally preferred to award the scholarship to the student with the stereotypically Black name. But Party made an even bigger difference, and always in a tribal way: 80 percent of the time, partisans selected the candidate whose resume showed that they were on their side, and it made little difference whether their co-partisan had a higher or lower GPA than the cross-partisan candidate.

In two additional studies Iyengar and Westwood had participants play behavioral economics games (the “trust game” and the “dictator game”). Each person played with what they thought was a particular other person, about whom they read a brief profile including the person’s age, gender, race, and political ideology. Race and ideology were manipulated systematically. Race made no difference, but partisanship mattered a lot: people were more trusting and generous when they thought they were playing with a co-partisan than a cross-partisan.

This is extremely bad news for America because it is very hard to have an effective democracy without compromise. But rising cross-partisan hostility means that Americans increasingly see the other side not just as wrong but as evil, as a threat to the very existence of the nation, according to Pew Research. Americans can expect rising polarization, nastiness, paralysis, and governmental dysfunction for a long time to come.

This is a warning for the rest of the world because some of the trends that have driven America to this point are occurring in many other countries, including: rising education and individualism (which make people more ideological), rising immigration and ethnic diversity (which reduces social capital and trust), and stagnant economic growth (which puts people into a zero-sum mindset).

This is extremely bad news for science and universities because universities are usually associated with the left. In the United States, universities have moved rapidly left since 1990, when the left-right ratio of professors across all departments was less than two to one. By 2004, the left-right ratio was roughly five to one, and it is still climbing. In the social sciences and humanities it is far higher. Because this political purification is happening at a time of rising cross-partisan hostility, we can expect increasing hostility from Republican legislators toward universities and the things they desire, including research funding and freedom from federal and state control.

Tribal conflicts and tribal politics took center stage in 2015. Iyengar and Westwood help us understand that tribal conflicts are no longer just about race, religion, and nationality. Cross-partisan prejudice should become a focus of concern and research. In the United States, it may even be a more urgent problem than cross-racial prejudice. 

A policeman saw a drunk man looking for something under a streetlight and asked what the drunk lost. The drunk says “I lost my keys” and they both look under the streetlight together. After a while the policeman asks “Are you sure you lost them here?” The drunk replies “No, I lost them in the park.” The policeman says “Why are you searching here?” The drunk replies, "this is where the light is!”

For decades this search strategy has been employed both by drunks and by neutrino hunters, with no keys in sight and few key insights. In 1916 Einstein published the second of his General Relativity papers. One hundred years later, using Einstein’s predictions, we are at the precipice of “weighing” the last elementary particle whose mass is unknown. Isn't this old news? Don’t we know all the fundamental particle masses already after measuring the Higgs boson’s mass? Well, yes and no.

Looking at the Standard Model, we see 16 massive particles (quarks), leptons (like electrons), and bosons (such as the photon), plus the Higgs boson charted together in a table reminiscent of Mendeleev’s Periodic Table of the Elements, except in the case of the quarks, bosons, and leptons on the table, there is no periodicity, no apparent ordering at work here.

Three of the six leptons (“small” in Greek; particles that don’t participate in the Strong nuclear force) are the three “generations” of neutrinos: electron, muon, and tau neutrinos. As integral as they are to the foundations of matter, we are in the dark about their masses. A particle’s mass is arguably its most distinctive property, so this lacuna is rightly seen as an embarrassment for physics. That is about to change.

Neutrinos change their flavor (generation-type) from one flavor to another as they sail through the cosmos. This is phenomenon is called “oscillation”. The 2015 Nobel Prize in Physics went to Takaaki Kajita and Arthur B. McDonald "for the discovery of neutrino oscillations, which shows that neutrinos have mass”. Their work devastatingly refutes claims presented in John Updike’s poem “Cosmic Gall”. Sorry John—while they remain small, neutrinos do have mass after all. Thanks to Kajita and McDonald, not only do we know neutrinos have mass, their work gives us a lower limit on their masses. At least one of the three neutrinos must have a mass bigger than about one-twentieth of an electron volt (physicists use Einstein’s relationship E=mc² to convert masses to equivalent energies).

This is quite svelte.The next heaviest elementary particle is the electron, whose mass is ten million times larger! Most importantly, these lower limits on neutrino masses give experimentalists thresholds to target. All that’s left is to build a scale sensitive enough to weigh them.

Neutrinos are generated in nuclear reactions such as fusion and radioactive decay. The ultimate reactor, of course, was the biggest cauldron of them all: the Big Bang. Like light, neutrinos are stable. Their lifetimes are infinite because, like light, there is nothing for them to decay into.

Since it’s impossible to collect enough neutrinos to weigh them in a terrestrial laboratory, cosmologists will use massive galaxy clusters as their scales. Sprinkled amidst the luminous matter in the clusters are innumerable neutrinos. Their masses can be measured using gravitational lensing, a direct consequence of Einstein’s General Theory. All matter, dark and luminous, gravitationally deflects light.

The gravitational lensing effect rearranges photon trajectories, as Eddington showed during the 1919 total Solar eclipse. Star positions were displaced from where they would’ve been seen in the absence of the Sun’s warping of space-time. The light that should’ve been there was lensed; the amount of movement told us the mass of lens.

What kind of light should we use to weigh poltergeist particles like neutrinos? There certainly aren’t enough neutrinos in our Solar System to bend the Sun’s light. The most promising light source of all is also the oldest and most abundant light in the universe: the “3 Kelvin” Cosmic Microwave Background (CMB). These cosmic photons arose from the same ancient cauldron that produced the neutrinos plying the universe today. The CMB is “cosmic wallpaper”, a background against which the mass of all matter in the foreground galaxy clusters, including neutrinos, can be measured.

In 2015 the Planck satellite showed powerful evidence for gravitational lensing of the CMB using a technique that is eventually guaranteed to detect neutrino masses. This technique, based on the CMB’s polarization properties, will dramatically improve in 2016 thanks to a suite of experiments deploying tens of thousands of detectors cooled below 0.3 Kelvin at the South Pole and in the Chilean Atacama desert.

Neutrinos are also the very paradigm of Dark Matter: they’re massive, they’re dark (they only interact with light via gravity) and they are neutral; all required properties of Dark Matter. While we know that neutrinos are not the dominant form of the cosmos’ missing mass, they are the only known form of Dark Matter.

After we measure their masses will use neutrinos to thin the herd of potential Dark Matter candidates. Just as there are many different types of ordinary matter, ranging from quarks to atoms, we might expect there are also several kinds of Dark Matter. Perhaps there is a “Dark” Periodic Table.

The hunt is on to directly detect Dark Matter, and several exciting upgrades to liquid noble gas experiments are coming online in 2016. Perhaps there will be detections. But so far the direct detection experiments have only produced upper limits. In the end, neutrinos just might be the only form of Dark Matter we ever get to “see”.

The next century of General Relativity promises to be as exciting as the first. “Spacetime tells matter how to move; matter tells spacetime how to curve” said John Archibald Wheeler. We’ve seen what the curvature is. Now we just need to find out what’s the matter. And where better to look for lost matter than where the Dark is.

The most thought-provoking scientific meeting I went to in 2015 was Emergent Quantum Mechanics, organised in Vienna by Gerhard Groessing. This is the go-to place if you’re interested in whether quantum mechanics dooms us to a universe (or multiverse) that can be causal or local but not both, or whether we might just make sense of it after all. The big new theme was emergent global correlation. What is this, and why does it matter?

The core problem of quantum foundations is the Bell tests. In 1935, Einstein, Podolsky and Rosen noted that if you measured one of a pair of particles that shared the same quantum mechanical wave function then this would immediately affect what could be measured about the other, even if it were some distance away. Einstein held that this “spooky action at a distance” was ridiculous, so quantum mechanics must be incomplete. This was the most cited paper in physics for decades. In 1964 the Irish physicist John Bell proved that if particle behavior were explained by hidden local variables, their effects would have to satisfy an inequality that would be broken in some circumstances by quantum mechanical behavior. In 1974, Clauser, Horne, Shimony, and Holt proved a related theorem that limits the correlation between the polarization of two photons, assuming that this polarization is carried entirely by and within them. Freedman and Clauser showed this was violated experimentally, followed by Aspect, Zeilinger and many others. These “Bell tests” convince many physicists that reality must be weird; maybe non-local, non-causal, or even involving multiple universes.

For example, it’s possible to entangle photon A with photon B, then B with C, then C with D, and measure that A and D are correlated, despite the fact that they didn’t exist at the same time. Does this mean that when I measure D, some mysterious influence reaches backward in time to A? The math doesn’t let me use this to send a message backwards in time to order the murder of my great-grandfather (the no-signalling theorem becomes a kind of “no-tardis theorem”) but such experiments are still startlingly counterintuitive.

At EMQM15, a number of people advanced models according to which quantum phenomena emerge from a combination of local action and global correlation. As the Nobel prizewinner Gerard ‘t Hooft put it in his keynote talk, John Bell assumed that spacelike correlations are insignificant, and this isn’t necessarily so. In Gerard’s model, reality is information, processed by a cellular automaton fabric operating at the Planck scale, and fundamental particles are virtual particles—like Conway’s gliders but in three dimensions. In a version he presented at the previous EMQM event in 2013, the fabric is regular and its existence many break gauge invariance just enough to provide the needed long-range correlation. The problem was that the Lorentz group is open, which seemed to prevent the variables in the automata being bitstrings of finite length. In his new version, the automata are randomly distributed. This was inspired by an idea of Steven Hawking’s on balancing the information flows into and out of black holes.

In a second class of emergence models, the long-range order comes from an underlying thermodynamics. Gerhard Groessing has a model in which long-range order emerges from subquantum statistical physics; Ariel Caticha has a model with a similar flavor, which derives quantum mechanics as entropic dynamics. Ana Maria Cetto looks to the zero-point field and sets out to characterise active zero-point field modes that sustain entangled states. Bei-Lok Hu adds a stochastic term to semiclassical gravity, whose effect after renormalisation is nonlocal dissipation with colored noise.

There are others. The quantum crypto pioneer Nicolas Gisin has a new book on quantum chance in which he suggests that the solution might be nonlocal randomness: a random event that can manifest itself at several locations. My own suspicion is that it might be something less colorful; perhaps the quantum vacuum just has an order parameter, like a normal superfluid or superconductor. If you want long-range order that interacts with quantum systems, we have quite a few examples and analogues to play with.

But whether you think the quantum vacuum is God’s computer, God’s bubble bath, or even God’s cryptographic keystream generator, there’s suddenly a sense this year of excitement and progress, of ideas coming together, of the prospect that we might just possibly be able to replace magic with mechanism.

There may be a precedent. For about forty years after Galileo, physics was a free-for-all. The old Ptolemaic certainties had been shot away and philosophers’ imaginations ran wild. Perhaps it would be possible, some said, to fly to America in eight hours in a basket carried by swans? Eventually, Newton wrote the Principia and spoiled all the fun. Theoretical physics has been stuck for the past forty years, and imaginations have been running wild once more. Multiple universes that let stuff travel backwards in time without causing a paradox? Or perhaps it’s time for something new to come along and spoil the fun. 

In terms of sheer unfulfilled promise, interdisciplinary research has to stand as one of the most frustrating examples in the world of social research. The promise can be put simply. The challenges we face in modern society, from responding to climate change through to anti-microbial resistance via so many issues to do with economic, social, political, and cultural well being do not come in disciplinary packages. They are complex and require an integrated response drawing on different levels of enquiry. And yet we persist in organizing ourselves in academic siloes and risk looking like those blind men groping an elephant. As Garry Brewer pithily observed back in 1999, “The world has problems, universities have departments.”

The reasons this promise lies unfulfilled are equally clear. Building an academic career requires immersion in a speciality with outputs (articles, books, talks) that win the approval of peers. Universities are structured in terms of departments, learned societies champion a single discipline, and funding agencies prioritize specific work from those who have built the right kind of credibility in this context. There is, quite literally, a coordination problem here. And this means interdisciplinary work is hard to do well, often falling between stools and sometimes lost in arcane debate about its very nature swapping “inter” for “multi,” “cross,” “trans,” “post,” and other candidate angels to place on the head of this pin. 

This isn’t equally true for all disciplines. Some have overcome these hurdles for years—neuroscience, bioinformatics, cybernetics, and biomedical engineering, and more recently we have seen economics taking a behavioral turn while moral philosophy has drawn increasingly on experimental psychology. However, the bulk of the social sciences have proved peculiarly resistant despite how suitable their problem domains are to multi-level inquiry.

The good news is we are seeing substantial shifts in this terrain that could last, triggered in part by the rise of big data and new technology. Social researchers are agog at the chance to listen to millions of voices, observe billions of interactions, and to analyze patterns at a scale never seen before. But to engage seriously requires new methods and forms of collaboration, with a consequent erosion of the once insurmountable barrier between quantitative and qualitative research. An example comes from Berkeley, where Nick Adams and his team are analyzing how violence breaks out in protest movements—an old sociological question, but now with a database (thanks to the number of Occupy movements in the US) that is so large the only way to analyze the material feasibly requires a Crowd Content Analysis Assembly Line (combining crowd sourcing and active machine learning) to code vast corpora of text. This new form of social research, drawing on computational linguistics and computer science to convert large amounts of text into rich data, could lead to insights in a vast array of social and cultural themes of our time.

Moreover these shifts might stick if we continue to see centers of excellence focusing on data intensive social research, like D-Lab at Berkeley or the Institute for Quantitative Social Science at Harvard show how institutions can reconfigure themselves to respond to this opportunity. As Gary King (Director of the latter) has put it:

The social sciences are undergoing a dramatic transformation from studying problems to solving them; from making do with a small number of sparse data sets to analyzing increasing quantities of diverse, highly informative data; from isolated scholars toiling away on their own to larger scale, collaborative, interdisciplinary, lab-style research teams; and from a purely academic pursuit focused inward to having a major impact on public policy, commerce and industry, other academic fields, and some of the major problems that affect individuals and societies.

More structural change will follow these innovations. Universities around the world having long invested in social science infrastructure are looking to these models so as to combine and merge efforts more effectively via multi-disciplinary research centers and collaborative teams. And we are seeing changes in funders’ priorities too. The Wellcome Trust, for instance, now offers the Hub Award to support work that “explores what happens when medicine and health intersect with the arts, humanities and social sciences.”

Of course the biggest shaper of future research comes at a national level. In the UK the proposed implementation of a “cross-disciplinary fund” alongside a new budget to tackle “global challenges” may indicate the Government’s seriousness of interdisciplinary intent. Details will follow, and they may prove devilish. But the groundswell of interest, sustained by opportunities in data intensive research, is undeniable.

So interdisciplinary social research should increasingly become the norm, notwithstanding the fact that specialism will still be important. After all we need good disciplines to do good synthetic work. But if this hope is fulfilled we might see how social sciences could coalesce into a more singular social science and be more fully engaged with problem domains first, and departmental siloes second.

Climate collapse demands a supply of energy that is far cheaper than fossil fuels, resistant to bad weather and natural disaster, and sustainable in fuel inputs and pollution outputs. Can a new poorly understood technology from a stigmatized field fulfil the need? The Low Energy Nuclear Reaction (LENR) could help at large scale very quickly.

In 1989 Pons and Fleischmann provided an initial glimpse of an unexpected and poorly understood reaction dubbed "cold fusion," which makes lots of heat and very little radiation.

LENR is being pursued quietly by many large aerospace companies, leading automakers, startup companies and to a lesser extent, national labs.

Over the years many teams have observed the reaction by various means, and a consistent, though unexpected, pattern has emerged. Experiments have become more repeatable, more diverse, more unambiguous, and higher in energy.

There are no expensive or toxic materials or processing steps, so it could be the step beyond fossil fuels we have been waiting for. No government regulated materials are used, so a quick path to commercialization is possible.

Familiarity with hot fusion led to initial false expectations. Early very hasty replication work at MIT was declared a failure when heat but no high energy neutrons were detected. The reaction requirements were not known at first and many attempts failed to reach fuel loading and ignition energy requirements. Even when the basic requirements were met, nano-scale features varied in materials and made the reaction hard to reproduce. Pons & Fleischmann had trouble repeating their own excess energy results after they used up their initial lucky batch of palladium. Today we understand better how material defects create required high energy levels.

In many experiments with LENR, observed excess heat drastically exceeds known or feasible chemical reactions. Experiments have gone from milliwatts to hundreds of watts. Ash products have been identified and quantitatively compared to energy output. High energy radiation has been observed, and is entirely different than hot fusion.

Dr. McKubre at SRI International teased out the required conditions out of the historical data. To bring forth LENR reactions that produce over-unity energy, a metal lattice heavily loaded with Hydrogen isotopes, driven far out of equilibrium by some excitation system involving proton flux and probably electromigration of lattice atoms as well.

A great quantitative characterization of the outputs was Dr. Miles' meticulous 1995 experiment at China Lake. LENR releases Helium-4 and heat in the same proportion as familiar hot fusion, but neutron emissions and gamma rays at least 6 orders of magnitude less than expected.

Successful excitation systems included heat, pressure, dual lasers, high currents and overlapping shock waves. Materials have been treated to create and manipulate flaws, holes, defects, cracks, and impurities, increase surface area, and provide high flux of protons and electron current. Solid transition metals host the reaction, including Nickel and Palladium.

Ash includes ample evidence of metal isotopes in the reactor that have gained mass as if from neutron accumulation, as well as enhanced deuterium and tritium. Tritium is observed in varying concentrations. Weak X-rays are observed along with tracks from other nuclear particles.

LENR looks like fusion judging as a chemist might, by the inputs Hydrogen and output Helium-4 and transmutation products. It looks not-at-all like fusion when judging it as a plasma physicist might—by tell-tale radioactive signatures.

Converting Hydrogen to Helium will release lots of energy no matter how it is done. LENR is not zero-point energy or perpetual motion. The question is whether that energy can be released with affordable tools.

Plasma physicists understand hot thermonuclear fusion in great detail. Plasma interactions involve few moving parts, and the environment is random so it's effect is zeroed out. In contrast, modeling the LENR mechanism will involve solid-state quantum mechanics in a system of a million parts, being driven far out of equilibrium. In LENR a nano-scale particle accelerator can't be left out of the model. A theory for LENR will rely on intellectual tools that illuminate x-ray lasers or high temperature superconductors or semiconductors.

Many things need to be cleared up. How is the energy level concentrated enough to initiate a nuclear reaction? What is the mechanism? How do output energies in the MeV range come out as obvious high energy particles? Dr. Peter Hagelstein at MIT has been working hard at a "Lossy Spin Boson Model" for many years to cover some of these gaps.

Robert Godes at Brillouin Energy suggests a theory that matches observations and suggests an implementation. The "Controlled Electron Capture Reaction." Protons in a metal matrix are trapped to a fraction of an Angstrom under heat and pressure. A proton can capture an electron and become an ultra-cold neutron that remains stationary, but without the charge. That allows another proton to tunnel in and join it, creating heavier Hydrogen and heat. That creates deuterium which goes to tritium to Hydrogen-4. Hydrogen-4 is new to science and is predicted (and observed?) to beta decay to Helium-4 in about 30 milliseconds. All this yielding about 27 meV in total per atom of Helium-4, as heat.

The proton-electron capture reaction is common in the sun, and predicted by super-computer simulation at PNNL. It is the reverse of free-neutron beta decay. Such a reaction is highly endothermic- absorbing 780 keV from the immediate surroundings.

Fission experts expect hot neutrons to break fissile atoms up. LENR does it backwards—ultra cold neutrons (which cannot be detected by neutron detectors, but can readily be confirmed by isotope changes) are targets for Hydrogen.

Hence Helium is produced with the tools of chemistry and without overcoming the Coulomb positive-particle repulsion force. And without requiring or producing radioactive elements.

It is strange that LENR is neglected by the DOE, industry and the Pentagon. But no stranger than the history of nuclear power—if it weren't for the leadership Admiral Rickover, and his personal friends in Congress, nuclear fission power for submarines and power plants would never have seen the light of day. The best endowed institutions rarely disrupt the status-quo.

Progress is being made quickly by private enterprise in lieu of government support. Sadly that means you cannot stay up to date relying on a subscription to "Science." But stay tuned.

A defining feature of science is its capacity to evolve in response to new developments. Historically—changes in technological capacities, quantitative procedures, and scientific understanding have all contributed to large-scale revisions in the conduct of scientific investigations. Pressure is mounting for further improvements. In disciplines such as medicine, psychology, genetics, and biology researchers have been confronting findings that are not as robust as they initially appeared. Such shrinking effects raise questions not only about the specific findings they challenge, but more generally about the confidence that we can have in published results that have yet to be re-evaluated.

In attempting to understand its own limitations, science is fueling the consolidation of an emerging new discipline: meta-science. Meta-science, the science of science, attempts to use quantifiable scientific methodologies to elucidate how current scientific practices influence the veracity of scientific conclusions. This nascent endeavor is joining the agendas of a variety of fields including medicine, biology, and psychology—each seeking to understand why some initial findings fail to fully replicate. Meta-science has its roots in the philosophy of science and the study of scientific methods, but is distinguished from the former by its reliance on quantitative analysis and from the latter by its broad focus on the general factors that contribute to the limitations and successes of scientific investigations.

This year the most ambitious meta-scientific study to date was published in Science by Brian Nosek and the Open Science Collaboration. A large-scale effort in psychology sought to replicate 100 “quasi-randomly” selected studies from three premier journals and found that less than half (39 percent) of the studies reached traditional levels of significance when replicated. This study is noteworthy because it directed the lens of science not at any particular phenomena but rather at the process of science itself. In this sense, it represents one of the first major implementations of evidence-based meta-science.  Although it is certain to have a major impact on science, only time will tell how it will be remembered.

Although I am enthusiastic about the meta-scientific goals that this study exemplifies, I worry that major limitations in its design and implementation may have produced a misleadingly pessimistic assessment of the health of the field of psychology. Numerous factors may have contributed to an underestimation of the reliability of the findings, including: variations in the skills and motivations of the replicating scientists, limitations in the statistical power of the replications, and perhaps most importantly, questions regarding the fidelity with which the original methods were reproduced. Although the authors attempted to vet their replication procedure with the originating lab, many of the replicated studies were conducted without the originating lab’s endorsement, and these unapproved efforts disproportionately contributed to the low replication estimate. 

Even the studies that used procedures that were approved by the originating laboratories still may have been lacking in fidelity. For example, one of the more well-known findings that failed to replicate involved the observation that exposing people to an anti free will message can increase cheating. I am particularly familiar with this example, (and perhaps biased to defend it) as I was a co-author of the original study. Although we signed off on the replication protocol, we subsequently discovered a small but important detail that was left out of the replicating procedure. In the original study, but not the replication, the anti free will message was framed as part of an entirely different study. We have recently found that people are less likely to change their beliefs about free will when the anti free will message is introduced as part of the same study. Apparently people are reluctant to change their mind on this important topic if they feel coerced to do so. In this context it is notable that in the replication study, the anti free will message failed to significantly discourage participants from believing in free will in the first place, and thus could hardly have been expected to produce the further ramification of increased cheating. I suspect that a big portion of failures to replicate may involve the omission of similar small but important methodological details. 

As the emerging field of meta-science moves forward, it will be important to refine techniques for understanding how disparities between original studies and replications may contribute to difficulties in reproducing results. Increasing the transparency of originally conducted studies, through methods such as detailed pre-registration, is likely to make it easier for replication teams to understand precisely how the project was originally implemented. However, it will also be important to develop methods for evaluating the fidelity of the reproductions themselves.

Another important next step for meta-science is the implementation of prospective replication experiments that systematically investigate how new hypotheses fair when tested repeatedly across laboratories. Prospective replication experiments will help to overcome potential biases inherent in selecting which published studies to replicate while simultaneously illuminating various factors that may govern the replicability of scientific findings, including variations in population sample, researcher investment and reproduction fidelity.

More generally, as we adopt a more meta-scientific perspective, researchers will hopefully increasingly appreciate that just as a single study cannot irrefutably demonstrate the existence of a phenomenon, neither can a single failure to replicate disprove it. Over time, scientists will likely become increasingly comfortable with meticulously documenting and (ideally) pre-registering all aspects of their research. They will see the replication of their work not as a threat to their integrity but rather as testament to their work’s importance. They will recognize that replicating other findings is an important component of their scientific responsibilities. They will refine replication procedures to not only discern the robustness of findings, but to understand their boundary conditions, and the reasons why they sometimes (often?) decline in magnitude. Even if history discerns that the original foray into meta-science was significantly lacking, ultimately meta-science will surely offer deep insights into the nature of the scientific method itself.

The variously attributed Platinum Rule holds that we should do unto others as they would have us do unto them. The most important news is that there is growing evidence that every endeavor involving social connection—friendship and marriage, education, health care, organizational leadership, interracial relationships and international aid, to name a few—is more effective to the extent that it adheres to this behavioral guide. The reason that the beneficial consequences of holding to the rule will remain important news is that the Platinum Rule is not simple and hewing to it is tough, especially in an individualist culture that fosters the wisdom of one’s own take on reality. Following the dictates of the Platinum Rule is so tough, in fact, that we routinely ignore it and then find it surprising and newsworthy when a new study discovers its truth all over again.

The challenge of holding to the Platinum Rule begins with the realization that it is not the Golden Rule—do unto others as you would have them do unto you. The Golden Rule is also a good behavioral guide and one that shows up across the religious traditions (e.g., in Judaism—what is hateful to you, do not do to your neighbor; in Confucianism—do not do to others what you do not want done to yourself). Yet built into the very foundation of the Golden Rule is that the assumption that what is good, desirable, just, respectful, and helpful for ME will also be good, desirable, just, respectful and helpful for YOU (or should be, and even it isn’t right now, trust me, it will be eventually).

Even with good friends or partners this is often not the case. For example, from your perspective you may be certain you are giving me support and fixing my problem. Yet what I would prefer and find supportive and have you do unto me is for you to listen to me and my analysis of the problem. And in the many cases in which we now strive to connect with people across social class, sexual orientation, race, ethnicity, religion, and region of the world, some disconnect between how you think you should treat people and how they would like to be treated is almost certainly the case. Doing unto others as they would have you do unto them requires knowledge of others, their history and circumstances, what matters to them, appreciating and acknowledging the value of difference, and accommodating one’s actions accordingly.

At the base of the successful application of the Platinum Rule is the realization that one’s own way is one way and may not be the only or the best way. Yes, not all ways are good; some are uninformed, corrupt and evil. Yet the findings from cultural science are increasingly robust. There is more than one good or right or moral way to raise a child, educate a student, cope with adversity, motivate a workforce, develop an economy, build a democracy, be healthy and experience well-being.

For many of us, what is good for me and what I assume will be good for you too is likely grounded in what cultural psychologists call a WEIRD perspective, that is, a Western, Educated, Industrialized, Rich and Democratic perspective. For the 75 percent of the world’s population who cannot be so classified, (i.e., the majority of the world, including, for example, many people in North America without a college degree or with non-Western heritage), who I am, what matters to me, what I hope to be, and what I would most like done unto me may not match what seems so obviously and naturally good and appropriate from the WEIRD perspective.

Beyond knowledge of the other and the appreciation of difference, the Platinum Rule requires something even harder—holding my own perspective at bay while thinking and feeling my way into the position of the other and then creating space for this perspective. Such effort requires a confluence of cognitive, affective and motivational forces. Some researchers call this psychological work perspective taking, some empathy, some compassion, still others social or emotional intelligence. Whatever the label, the results are worth the effort.

When colleges ask students from working class or underrepresented minority backgrounds to write about matters to them or to give voice to their worries about not fitting in college, they are happier, healthier, and outperform students not given these opportunities. Managers who encourage employees to reflect on the purpose and meaning of their work have more effective teams than those who don’t. The odds of persuading another in an argument are greater if you acknowledge the opponent’s moral position before asserting your own. Research from across the social sciences supports the idea that just recognizing the views, values, needs, wants, hopes, or fears of others can produce better teaching, medicine, policing, team leadership, and conflict resolution. Taking their views into account may change the world.

Perhaps even more newsworthy than the successes of understanding what matters to others are the many Platinum Rule fails. Government and private donors distributed billions following the 2010 earthquake in Haiti, much of it spent doing what the donors believed they would do if they were in the place of those devastated by the disaster. One notable project was a campaign to underscore the good health consequences of hand washing to people without soap or running water. Many humanitarians now argue that relief efforts would be less costly and more effective if instead of giving people what donors think they need–water, food, first aid, blankets, training—they delivered what the recipients themselves say they need. In most cases, this is money.

Whether independent North Americans who, according to some surveys, are becoming more self-focused by the year can learn the value of the Platinum Rule is an open question. To this point, the science suggests it would be moral, efficient, and wise.

Every year, more women than men become college-educated. The disparity is already prevalent across North America and Europe, and the trend is beginning to spread across the world more widely. At the University of Texas at Austin where I teach, the sex ratio is 54 percent women to 46 percent men. This imbalance may not seem large at first blush. But when you do the math it translates into a hefty 17 percent more women than men in the local mating pool. Speculations about reasons range widely. They include the gradual removal of gender discrimination barriers and women’s higher levels of conscientiousness (relative to men’s) that translate into better grades and superior college app qualifications. Whatever the causes turn out to be, the disparity is creating a dramatic and unintended mating crisis among educated women.

We must look deeply into our mating psychology to understand the far-reaching consequences of the sex ratio imbalance. Women and men both have evolved multiple mating strategies; some of each gender pursue casual hook-ups, some committed partnerships. Some alternate at different times of their lives, and some do both simultaneously. And although a few social scientists deny the data, research overwhelmingly shows that men harbor, on average, a greater desire for sexual partner variety. Men experience more frequent sexual thoughts per day, have more sexual fantasies involving multiple partners, and more readily sign up for online dating sites for the sole goal of casual sex. So, a surplus of women among educated groups caters precisely to this dimension of men’s sexual desires because the rarer gender is always better positioned to get what they want on the mating market. In places like large cities in China, with their surplus of men, women can better fulfill their desires while many men remain frustrated and mateless. Context matters. For every surplus of women in places like Manhattan, there exist pockets where men outnumber women, such as schools of engineering or the software companies of Silicon Valley. But when there are not enough men to go around, women predictably intensify their sexual competition. The rise of the hookup cultures on college campuses and online dating sites like Tinder, Adult Friend Finder, and Ashley Madison is no coincidence.

Gender differences in sexual psychology are only part of the problem. Additional elements of the mating mind exacerbate it. A key cause stems from the qualities women seek in committed mateships. Most women are unwilling to settle for men who are less educated, less intelligent, and less professionally successful than they are. The flip side is that men are less exacting on precisely these dimensions, choosing to prioritize, for better or worse, other evolved criteria such as youth and appearance. So the initial sex ratio imbalance among educated groups gets worse for high achieving women. They end up being forced to compete for the limited pool of educated men not just with their more numerous educated rivals, but also with less educated women whom men find desirable on other dimensions.

The depletion of educated men worsens when we add the impacts of age and divorce to the mating matrix. As men age, they desire women who are increasingly younger than they are. Intelligent, educated women may go for a less accomplished partner for a casual fling, but for a committed partner they typically want mates their own age or a few years older, and at least as educated and career-driven. Since education takes time, the sex ratio imbalance gets especially skewed among the highly educated—those who seek advanced degrees to become doctors, lawyers, or professors, or who climb the corporate ladder post-MBA. And because men are more likely than women to remarry following divorce and to marry women increasingly younger than they are—three years at first marriage, five at second, eight at third—the gender-biased mating ratio skews more sharply with increasing age.

One of the most profound puzzles in modern physics is to describe the quantum nature of spacetime. A real challenge here is that of finding helpful experimental guidance. Interestingly, we are just now on the verge of gaining key new experimental information about classical spacetime, in new and important regimes—and this tantalizingly also offers a possibility of learning about quantum spacetime as well.

Of course, the community has been abuzz about the possible discovery of a new particle at LHC, seen by its disintegration into pairs of photons. If this is real—and not just a fluctuation—there’s a slim chance it is even a graviton in extra dimensions, which, if true, could well be the discovery of the century. While this would indeed be a probe of quantum spacetime, I’ll put this aside until more data reveals what is happening at LHC.

But on the long-distance front, we are clearly entering a new era in several respects. First, miles long instruments built to detect gravitational waves have just reached a sensitivity where they should be able to see these spacetime ripples, emitted from collisions and mergers of distant black holes and neutron stars. In fact, there have been very recent hints of signals seen in these detectors, though the physics community eagerly awaits a verifiable signal. Once found, these will confirm a major prediction of Einstein’s general relativity, and open a new branch of astronomy, where distant objects are studied by the gravitational waves they emit. There is also the possibility that precise measurements of the microwave radiation left over from the Big Bang will reveal gravity waves, though the community has backpedaled from the premature announcement of this in 2014, and so the race may well be won by the earth-based gravity-wave detectors. Either way, these developments will be very exciting to watch.

The possibility of even more profound tests of general relativity exists with another new “instrument,” the Event Horizon Telescope, which is being brought on line to study the four million solar mass black hole at the center of our Milky Way galaxy. Instrument is in quotes because the EHT is really a network of radio telescopes, which combine to make a telescope the size of planet Earth. This will offer an unprecedentedly sharp focus on both our central black hole, and on the six billion solar mass black hole at the center of the nearby elliptical galaxy M87. In fact, with the telescopes that have been networked so far, we are beginning to see structure whose size is close to that of the event horizon of our central black hole. EHT should ultimately probe gravity in a regime where it gets extremely strong—so strong that the velocity that objects need to escape its pull is approaching the speed of light. This will give us a new view on gravity in a regime where it has so far not been well tested.

Even more tantalizing is the possibility that EHT will start to see effects that begin to reveal a more basic quantum reality underlying spacetime. For the 2014 Edge Question, I wrote that apparently our fundamental concept of spacetime is ready for retirement, and it needs to be replaced by a more basic quantum structure. There are multiple reasons for this. One very good one is the crisis arising from the attempt to explain black hole evolution within present day physics; our current foundational principles, including the idea of spacetime, come into sharp conflict with each other when describing black holes. While Stephen Hawking initially predicted that quantum mechanics must break down when we account for emission of particles of “Hawking radiation” from a black hole, there are now good indications that it should not be abandoned. And if quantum mechanics is to be saved, this tells us that quantum information must be able to escape a black hole as it radiates particles—and this confronts our understanding of spacetime.

The need for information to escape an evaporating black hole conflicts with our current notions of how fields and particles move in spacetime; here, escape is forbidden by the prohibition of faster-than-light travel. A key question is how the familiar spacetime picture of a black hole must be modified to allow such escape. The modifications must apparently extend out at least to the event horizon of a black hole. Some have postulated that the new effects abruptly stop right there, at the horizon, but this abruptness is rather unnatural, and leads to other apparently crazy conclusions associated with what has been recently renamed the “firewall” scenario. A more natural scenario, though, is that the usual spacetime description is also modified in a region that extends outward beyond the black hole horizon, at least through the region where gravity is very strong; the size of this region is perhaps a few times the horizon radius. So, in short, the need to save quantum mechanics indicates quantum modifications to our current spacetime description that extend into the region that EHT observations will be probing! Important problems are to improve understanding of the nature of these alterations to the familiar spacetime picture, and to determine more carefully their possible observability via EHT’s measurements.

We live at a remarkable moment in history. Our scientific instruments have allowed us to see the far reaches of the cosmos and to study the tiniest particles. In both cases, they have revealed a surprising simplicity, at odds with the most popular theoretical paradigms. I believe this simplicity to be a clue to a new scientific principle, whose discovery will represent the next revolution in physics and in our understanding of the universe.

It is not without irony that at the very moment the observational situation is clearing so beautifully, the theoretical scene has become overwhelmingly confused. Not only are the most popular models very complicated and contrived, they are also being steadily ruled out by the new data. Some physicists appeal to a “multiverse” in which all possible laws of physics are realized somewhere since then, they hope, there would at least be one region like ours. It seems more likely to me that the wonderful new data is pointing us in the opposite direction. The cosmos isn’t wild and unpredictable, it is incredibly regular. In its fundamental aspects, it may be as simple as an atom and, in time, every bit as possible to understand.

Our most powerful-ever microscope, the Large Hadron Collider (LHC), has just found the Higgs boson. This particle is the basic quantum of the Higgs field, a medium which pervades space and endows particles with mass and properties like electric charge. As fundamental to our understanding of particle physics as the Higgs field is, it is equally important to our understanding of cosmology. It makes a big contribution to the energy in empty space, the so-called dark energy, which astronomical observations reveal to be a weirdly tiny, yet positive, number. Furthermore, according to the LHC measurements and the standard model of particle physics, the Higgs field is delicately poised on the threshold of instability in today’s universe.

The discovery of the Higgs boson was a triumph for the theory of quantum fields, the amalgamation of quantum mechanics and relativity which dominated 20th century physics. But quantum field theory has great trouble explaining the mass of the Higgs boson and the energy in empty space. In both cases, the problem is essentially the same. The quantized vibrations of the known fields and particles become wild on small scales, contributing large corrections to the Higgs boson mass and to the dark energy density and generally giving them values much greater than those we observe.

To overcome these problems, many theorists have postulated new particles, whose effects would almost precisely cancel those of all the known particles, “protecting” the mass of the Higgs boson and the value of the dark energy from quantum effects. But the LHC has looked for these extra partner particles and, so far, failed to find them. It seems that nature has found a simpler way to tame quantum phenomena on short distances, in a manner which we have yet to fathom.

Meanwhile, our most powerful-ever telescope, the Planck satellite, has scanned the universe on the largest visible scales. What it has revealed is equally surprising. The whole shebang can be quantified with just six numbers: the age and temperature of the cosmos today; the density of the dark energy and the dark matter (both mysterious, but simple to characterize); and the strength, and slight dependence on scale, of the tiny initial variations in the density of matter from place to place as it emerged from the big bang.  None of the complications, like gravitational waves or the more involved density patterns expected in many models, appear to be there. Again, nature has found a simpler way to work than we can currently understand.

The largest scale in physics—the Hubble length—is defined by the dark energy. By accelerating the expansion of the cosmos, the dark energy carries distant matter away from us and sets a limit to what we will ultimately see.  The smallest scale in physics is the Planck length, the miniscule wavelength of photons so energetic that two of them will form a black hole. While exploring physics down to the Planck length is beyond the capabilities of any conceivable collider, the universe itself probed this scale in its earliest moments. So the simple structure of the cosmos is likely to be an indication that the laws of physics become simple at this extreme.

All the complexity in the world, including stars, planets and life, apparently resides in the “messy middle.”  It is a striking fact that the geometric mean of the Hubble and Planck lengths is the size of a living cell: the scale on which we live, where nature is at her most complex.

What is exciting about this picture is that it requires a new kind of theory, one which is simple at both the smallest and largest scales, and very early and very late cosmological times so that it is capable of explaining these properties of our world. In fact, there are more detailed hints from both theory and data that, at these extremes, the laws of physics should become independent of scale.  Such a theory won’t be concerned with kilograms, meters or seconds, only with information and its relations. It will be a unified theory, not only of all the forces and particles but of the universe as a whole. 

On July 14 of this year, NASA’s New Horizons spacecraft flew within 7,800 miles of Pluto, after traversing 3 billion miles since its 2006 launch, and it began sending back astonishing and detailed images of mountains and plains composed of ice from the last planet in our system to be explored. But, for me, this was not the most newsworthy aspect of its mission.

The science involved in accomplishing this feat is amazing. New Horizons is an engineering marvel, with radioisotope power generation, sophisticated batteries, optical and plasma scientific instruments, complex navigation and telemetry, and so on. Its primary missions—all successfully completed—were to map the surface of Pluto and its main moon, Charon; to characterize the geology and composition of these bodies; and to analyze the atmosphere of these bodies. In the process, New Horizons has also shed light on the formation of our solar system. 

It took an army of scientists and engineers working for over a decade to design, build, and manage the probe. Of course all these people, and many others around the world, took enormous pleasure and satisfaction, and experienced tremendous wonder, in seeing the resulting photographs and data from so far away. 

We succeed in this kind of exploration of our solar system so reliably nowadays that this sort of satisfaction seems to us routine, feels like just a bump in the road of our endless inquiry. But the exploration of Pluto is, alas, just a bump in the road in another, rather more dispiriting way.

Most Americans (58 percent in a Pew survey conducted in 2011) are supportive of space exploration, valuing both its contributions to science and to national pride. And most Americans (59 percent) think that sending astronauts into space is desirable (in a 2015 Pew survey). Yet, Americans and their politicians appear unwilling to spend more money on this; results from a 2014 General Social Survey indicate that just 23 percent of Americans think we should spend more.  By contrast, 70 percent of Americans think we should spend more on education and 57 percent think we should spend more on health. NASA’s budget has been roughly constant in real dollars since 1985 (it is now 0.5 percent of the federal budget), but it is well below its peak in 1965, when it was over 4 percent of the federal budget (and it’s below even the 1 percent level of 1990). 

The captivating photos of Pluto occupied a week or so in the news cycle in the middle of the summer, and we’ve moved on. What really amazes me about the news from Pluto is that there are not more people who find this accomplishment astonishing, that there is not even more sustained support for space exploration.  NASA’s entirely sensible push to make both manned and unmanned space exploration reliable, standardized, and safe has also had the unfortunate side effect of making it routine and even boring for many people. For me, this fact— brought into relief once again by the mapping of Pluto—is the real newsworthy part of this discovery. 

My paternal grandfather, who was born in Greece in the 1890s (and was orphaned not long after), used to tell me that he simply could not believe that he had heard about the first heavier-than-air flight of the Wright brothers when it happened in 1903 and that he had also watched the moon landing in 1969. This was the same man who fought in World War I and who would tell me stories about how his unit was transferred from Ankara to Kiev on horseback “when the Bolsheviks revolted” and about how, during World War II, he kept his family alive in Athens “when the Nazis invaded.”  But space exploration interested him more because, well, it was so much more optimistic.  Humans went from riding on a beach with a plane made of canvas and bicycle parts to traversing space with a lunar lander in sixty-six years. It amazed him, having witnessed it first hand—and the pace and sheer wonder astonish me even as I write this.

I realize of course that the great accomplishments in space exploration of the 1960s and 70s were largely motivated by the Cold War. I realize as well that many people are now arguing that private enterprise should take over space exploration. And I know that commitment to space exploration is low because many see better uses for our money. Is it better to vaccinate children, care for the poor, or invest in public health or medical research, rather than invest in space exploration? Part of my response is the customary one that science and discovery are the ultimate drivers of our wealth and security. But my main response is that this is a false dichotomy. The real question is whether we would rather wage war or colonize Mars. Which would be, and should be, more newsworthy? In this, I think my grandfather had it right.

One of the scientific heroes of our time is Pieter van Dokkum, professor in the Yale astronomy department and author of a recent book, Dragonflies. The book is about insects, illustrated with marvelous photographs of real dragonflies taken by van Dokkum in their natural habitats. As an astronomer he works with another kind of dragonfly. The Dragonfly Observatory is an array of ten sixteen-inch refractor telescopes arranged like the compound eye of an insect dragonfly. The refracting lenses are coated with optical surface layers designed to give them superb sensitivity to faint extended objects in the sky. For faint extended objects, the Dragonfly Observatory is about ten times more sensitive than the best large telescopes. The Dragonfly is also about a thousand times cheaper. The ten refractors cost together about a hundred thousand dollars, compared with a hundred million for a big telescope.

The Dragonfly Observatory recently finished a search for faint dwarf galaxies orbiting within the gravitational field of our own galaxy. About fifty dwarf companions to our galaxy were discovered, more than were expected from computer models of galactic evolution. Each dwarf galaxy is embedded in a halo of dark matter whose mass can be determined from the observed velocities of the visible stars. The dwarf galaxies have about a hundred times more dark mass than visible mass, compared with the ratio of ten to one between dark and visible mass in our own galaxy. The Dragonfly observations reveal a universe with an intense fine-structure of dark-matter clumps, much clumpier than the standard theory of big-bang cosmology had predicted.

So it happens that a cheap small observatory can make a big new discovery about the structure of the universe. If the cost-effectiveness of an observatory is measured by the ratio of scientific output to financial input, the Dragonfly wins by a large factor. This story has a moral. The moral is not that we should put all our money into small observatories. We still need big telescopes and big organizations to do world-class astronomy. The moral is that a modest fraction of the astronomy budget, perhaps as much as a third, should be reserved for small and cheap projects. From time to time a winner like Dragonfly will emerge.

Early this year an old friend, a professor of neurology, sent me an article from a medical journal, “Surgical Neurology International," at first glance, predictably, a concoction of specialist language. The “Turin Advanced Neuromodulation Group” is describing “Cephalosomatic Anastomosis” (CSA), to be performed with “a nanoknife made of a thin layer of silicon nitride with a nanometer sharp-cutting edge.”

Only slowly it becomes clear they are talking about something rather unexpected: “Kephale,” Greek for head, “Somatikos,” Greek for body, “Anastasis,” Latin for resurrection—that prosaic CSA stands for...a complete head transplantation. And that reverberated with me, the implications being literally mind-boggling.

There is that "most interesting" aspect: the thought of a functioning brain reconnected to an entirely new body does open up any number of speculations. And has done so in countless SciFi books and B movies. But there is a lot to consider.

The author, Italian surgeon Sergio Canavero, announced a few months later that he had a suitable donor for the head part, and suddenly made it sound quite real, adding tangible details: the operation was to be done in China, requiring a team of 150 specialists, taking 36+ hours and costing $15+ million...to be performed in 2017.

Then it really hit the mass media. Many responses revolved around the ethics of such an action, using the F-word a lot (and I mean “Frankenstein”) and debating the scientific details of the spinal cord fusion.

My stance on the ethical side is biased by a personal moment: In the mid-90s I visited Stephen Hawking in Cambridge for a project and he later visited in Santa Barbara—both interactions, up-close, left me with an overpowering impression. There was that metaphor of "the mind being trapped in a body," playing out in all its deep and poignant extreme—the most intelligent of minds weighed down so utterly by the near useless shell of a body. A deep sadness would overcome anyone witnessing that, far beyond the Hollywood movie adaption.

There is the rub then: who could possibly argue against this man choosing to lengthen his lifetime and gain a functioning body, should such an option exist? Could anyone deny him the right to try, if medicine were up to the task?

In reality Hawking is not a candidate even in theory, his head being afflicted by the disease as well, but he does serve as a touching and tragic example of that ethical side.

Another personal connection for me is this—imagine: critical voices called it “playing God.” Human hubris. Where would all the donors come from? Is this medicine just for the rich?

Now consider: the first operation leads to the recipient dying after eighteen days. It is being repeated and the subsequent 100 operations lead to nearly 90 percent of the patients not surviving the two-year mark.

No, that is not a prognostication for CSA, but I am recalling the events from nearly fifty years ago: It was December, 1967 when Christiaan Neethling Barnard performed the first human heart transplantation, the eyes of the world upon him, his face plastered on magazine covers across the globe. I was ten and remembered his double-voweled name as much as the unfathomable operation itself. He was met with exactly the same criticism, the identical ethical arguments.

After the dismal survival rate the initial enthusiasm turned around and a year later those condemning the practice were gaining. Only after the introduction of Cyclosporine to vastly improve the immune rejection issues did the statistics turn in his favor and tens of thousands such operations have since been performed.

I consider that an important aspect in this: every stage of progress has had critical voices loudly extrapolating curves into absurdity—back then, as now, there is immediate doomsday talk of “entire prison populations harvested for donors,” and such.

Sadly, watching videos of Canavero on the Web is rather cringeworthy. Slinging hyperbolae of "the world will never be the same," naming his procedure heaven and gemini, then squashing a banana representing a damaged spinal cord versus a neatly sliced one to illustrate his ostensibly easy plan. He repeatedly calls it "fusing spaghetti" and even assessed the chances for his Russian donor at "90 percent to walk again."

The Guardian mentions “he published a book, Donne Scoperte, or Women Uncovered, that outlined his tried-and-tested seduction techniques.” It seems rather clear that there is little place for levity when he belittles the details and glosses over the reality: millions of quadriplegic victims are eyeing very closely what the chances are to truly re-fuse spinal cords. That alone is probably worth a great deal of energy, effort, time and expense.

The story here is not about one celebrity poser. In my view it cannot happen by 2017, by far. But 2027, 37, 47? Looking backward you can see the increase in complexity that makes it almost inevitable to think: this will be possible. And then the truly interesting questions come into play...

If phantom limbs bring serious psychological issues, what would an entire phantom body conjure up? The self-image is such a subtle process, the complexity of signals, fluids, and messenger chemistry, how could it all possibly attain a state remotely stable, let alone "normal"?

Christiaan Barnard, who asked why anyone would choose such a risky procedure, said:

 For a dying person, a transplant is not a difficult decision. If a lion chases you to a river filled with crocodiles, you will leap into the water convinced you have a chance to swim to the other side. But you would never accept such odds if there were no lion.

Me, I dread even just the waiting room at the dentist. But thirty years hence, maybe I would opt for the crocodiles as well. If Hawking can survive longer—by all means, he should. Some other characters I can think of—their best hope lies in acquiring a new head. Thus, I am of two minds about complete head transplants.

These days see a tremendous number of significant scientific news, and it is hard to say which one has the highest significance. Climate models indicate that we are past crucial tipping points and are irrevocably headed for a new, difficult age for our civilization. Mark Van Raamsdonk expands on the work of Brian Swingle and Juan Maldacena, and demonstrates how we can abolish the idea of spacetime in favor of a discrete tensor network, thus opening the way for a unified theory of physics. Bruce Conklin, George Church and others have given us CRISPR, a technology that holds the promise for simple and ubiquitous gene editing. Deep Learning starts to tell us how hierarchies of interconnected feature detectors can autonomously form a model of the world, learn to solve problems, and recognize speech, images and video.

It is perhaps equally important to notice where we lack progress: sociology fails to teach us how societies work, philosophy seems to have become barren and infertile, the economical sciences seem to be ill-equipped to inform our economic and fiscal policies, psychology does not comprehend the logic of our psyche, and neuroscience tells us where things happen in the brain, but largely not what they are.

In my view, the 20th century’s most important addition to understanding the world is not positivist science, computer technology, spaceflight, or the foundational theories of physics. It is the notion of computation. Computation, at its core, and as informally described as possible, is very simple: every observation yields a set of discernible differences.

These, we call information. If the observation corresponds to a system that can change its state, we can describe these state changes. If we identify regularity in these state changes, we are looking at a computational system. If the regularity is completely described, we call this system an algorithm. Once a system can perform conditional state transitions and revisit earlier states, it becomes almost impossible to stop it from performing arbitrary computation. In the infinite case, that is, if we allow it to make an unbounded number of state transitions and use unbounded storage for the states, it becomes a Turing Machine, or a Lambda Calculus, or a Post machine, or one of the many other, mutually equivalent formalisms that capture universal computation.

Computational terms rephrase the idea of "causality," something that philosophers have struggled with for centuries. Causality is the transition from one state in a computational system into the next. They also replace the concept of "mechanism" in mechanistic, or naturalistic philosophy. Computationalism is the new mechanism, and unlike its predecessor, it is not fraught with misleading intuitions of moving parts.

Computation is different from mathematics. Mathematics turns out to be the domain of formal languages, and is mostly undecidable, which is just another word for saying uncomputable (since decision making and proving are alternative words for computation, too). All our explorations into mathematics are computational ones, though. To compute means to actually do all the work, to move from one state to the next.

Computation changes our idea of knowledge: instead of treating it as justified true belief, knowledge describes a local minimum in capturing regularities between observables. Knowledge is almost never static, but progressing on a gradient through a state space of possible world views. We will no longer aspire to teach our children the truth, because like us, they will never stop changing their minds. We will teach them how to productively change their minds, how to explore the never ending land of insight.

A growing number of physicists understand that the universe is not mathematical, but computational, and physics is in the business of finding an algorithm that can reproduce our observations. The switch from uncomputable, mathematical notions (such as continuous space) makes progress possible. Climate science, molecular genetics, and AI are computational sciences. Sociology, psychology, and neuroscience are not: they still seem to be confused by the apparent dichotomy between mechanism (rigid, moving parts) and the objects of their study. They are looking for social, behavioral, chemical, neural regularities, where they should be looking for computational ones.

Everything is computation.

This year I had the wonderful and shocking awareness that I’m not only connected to microbes but, in a way, I’m so dependent on them, I sort of am them.

Darwin gave me the understanding that I’m related to the rest of the beasts of the earth, but work on the microbiome released in 2015, impressed me with how much a part of me microbes really are and how much I look to them for my very existence.

It started with the spooky information a short while back, that there are 10 times as many of them in me as there are me in me; at least if you compare the number of their cells in me to the number of mine in me.

From what I read, they’re so specialized that the microbes in the crook of my arm are more like the ones in the crook of your arm than they are like the microbes in my own hand.

Then came the discovery that before long I’ll be able to get a fecal transplant, or maybe simply take a poo pill, to relieve all kinds of disturbances in my body—possibly even obesity, should it ever win the war against my self control.

And there was the equally strange news that I give off a cloud of microbes wherever I go—and if they settle on a surface, someone could take a reading and record a kind of fingerprint of my personal microbiome, after I’d left the scene.

They’re ubiquitous little guys. There are, I believe, more of them pound for pound than any other living thing on earth, and we can’t even see them.

And they’re powerful. One kind of microbe expands when wet, and a pound or two of them could lift a car a couple of feet off the ground. You could change your tire with them.

We’ve planted a flag on a new New World. The last frontier has just changed again, from outer space, to the brain, to an invisible world, without which there would be no world as we know it.

Hi, guys.

2015 marks the hundredth anniversary of Einstein's announcement of the theory of general relativity. General relativity describes the force of gravity in terms of the curvature of space and time: the presence of matter warps the underlying fabric of the universe, causing light to curve and clocks to slow down in the presence of matter. General relativity supplies us with a physical theory that allows us to describe the cosmos as a whole; it predicts the existence of exotic objects such as black holes; it even supports closed timelike curves that in principle allow travel backward in time. General relativity is a tremendous scientific success story, and its hundredth anniversary has been marked by multiple articles, television shows, scientific conferences, and more to celebrate Einstein's achievement.

Unmentioned in this celebration is the darker story. As soon as Einstein announced his elegant theory, other physicists began trying to reconcile general relativity with quantum mechanics. Quantum mechanics is the physical theory that governs matter at its smallest and most fundamental scales. The last century has also seen tremendous advances in the application of quantum mechanics to study elementary particles, solid state physics, the physics of light, and the fundamental physics of information processing. Pretty much as soon as the print on Einstein's papers had dried, physicists began trying to make a quantum theory of gravity. They failed.

The first theories of quantum gravity failed because scientists did not understand quantum mechanics very well. It was not until a decade after Einstein's results that Erwin Schroedinger and Werner Heisenberg provided a precise mathematical formulation of quantum mechanics. By the beginning of the 1930s, Paul Dirac had formulated a version of quantum mechanics that incorporated Einstein's earlier—and by definition less general—theory of special relativity. Throughout the next half century, in the hands of physicists such as Richard Feynman and Murray Gell-Mann, this special-relativistic version of quantum mechanics, called quantum field theory, provided dramatic advances in our understanding of fundamental physics, culminating by the mid 1970s in the so-called Standard Model of elementary particles. The Standard Model unifies all the known forces of nature apart from gravity: it has been triumphantly confirmed by experiment again and again.

What about a quantum theory of gravity, then? After Dirac, when physicists tried to extend the successful techniques of quantum field theory to general relativity, they failed. This time, they failed because of a knotty technical problem. One of the peculiarities of quantum field theory is that when you try calculate the value of some observable quantity such as the mass of the electron, the naive answer that you obtain is infinity.

Looking more closely, you realize that the interactions between the electron and other particles, such as photons (particles of light), have to be taken into account: these interactions “renormalize” the mass of the electron, making it finite. Renormalization works beautifully in the case of quantum field theory, allowing the prediction of quantities such as the mass of the electron to more than six digits of accuracy. But renormalization fails utterly in the case of quantum gravity: quantum gravity is not renormalizable. Infinity remains infinity. Fail.

More recent decades of failure to quantize general relativity have yielded tantalizing clues. Perhaps the best known result that combines quantum mechanics and gravity is Stephen Hawking's famous proof that black holes are not absolutely black, but in fact emit radiation.

Hawking radiation is not a theory of quantum gravity, however, but of quantum matter moving about on a classical spacetime that obeys Einstein's original non-quantum equations. Loop quantum gravity solves some of the problems of quantum gravity, but exacerbates others: it has a hard time including matter in the theory, for example. Speaking as someone made of matter, I object to theories that do not include it.

One of the primary appeals of String Theory is that it naturally contains a particle that could be identified with the graviton, the quantum of gravity. Sadly, even the most enthusiastic followers of String Theory admit that it is not yet a full self-consistent theory but rather a series of compelling mathematical observations called—with an apparently complete lack of irony—`miracles.'

Long-time practitioners of quantum gravity have advised me that if one wishes to publish in the field, any advance that claims to improve on one aspect of quantum gravity must be offset by making other problems worse, so that net effect is negative. If economics is the dismal science, then quantum gravity is the dismal physics.

The last few years leading up to the centennial of failing to quantize gravity have seen a few glimmers of hope, however. Quantum information is the branch of physics and mathematics that describes how systems represent and process information in a quantum mechanical fashion. Unlike String Theory, quantum information is in fact a theory: it proceeds by orderly conjecture and mathematical proof, with close contact to experiment. Quantum information can be thought of as the universal theory of discrete quantum systems, systems that can be represented by bits or quantum bits.

Recently, researchers in quantum gravity and quantum information have joined forces to show that quantum information theory can provide deep insights into problems such as black hole evaporation, the holographic principle, and the AdS-CFT correspondence. (If these subjects sound esoteric, that's because they are.) Encouragingly, the advances in quantum gravity supplied by quantum information theory do not yet seem to be counterbalanced by back-sliding elsewhere.

We have no idea whether this attempted unification of qubits and gravitons will succeed or fail. Empirical observation of the last century of failure to quantize gravity suggests the latter. With any luck, however, the next hundred years of quantizing gravity will not be so dismal.

News stories are by their nature ephemeral. Whipped up by the media (whether mass or social), they soon dissipate, like ripples on the surface of the sea. More significant and durable are the great tides of social change and technological progress on which they ride. It is these that will continue to matter in decades and generations to come. Fortunately, like real tides, they are more predictable too.

One such inexorable trend is our changing relationship with the natural world—most vividly represented by the ongoing debate about whether humanity's impact has been so profound as to justify the christening of a new geological epoch: the Anthropocene. Whether or not a consensus emerges in the next few years, it will do so eventually, for our effect on the planet will only grow. This is in part because our technological capabilities continue to expand, but an even more important driver is our evolving collective psyche.

Since Darwin showed us that we are products of the natural world rather than its divinely appointed overlords, we have become reticent to fully impose our will, fearful of our own omnipotence and concerned that we will end up doing more harm than good. But however determinedly we draw such red lines we might as well be trying, Canute-like, to hold back the sea. For whatever is beyond the pale today will eventually come to seem so natural that it will barely register as news—even if it takes the death of the old guard to usher in a new way of thinking. To future generations, genetic engineering of plants and animals (and humans) will seem as natural as selective breeding is today, and planetary-scale geoengineering will become as necessary and pervasive as the construction of dams and bridges.

As for our place in nature, so too for our relationship with technology. Recent progress in artificial intelligence and bionics, in particular, have led to a great deal of soul-searching about who—or what—is in charge, and even what it means to be human. The industrial revolution saw machines replace human physical labor, but now that they are replacing mental labor too, what will be left for people to do? Even those who don't fear for their jobs might be angry when they discover that their new boss is an algorithm.

Yet since the invention of the wheel humans have lived in overwhelmingly happy and productive symbiosis with the technologies they have created. Despite our ongoing appetite for scare stories, we will continue to embrace such innovations as the primary source of improvements in our collective well being. In doing so we will come to see them as natural extensions of ourselves—indeed as enablers and enhancers of our humanity—rather than as something artificial or alien. A life lived partly in virtual reality will be no less real than one viewed through a pair of contact lenses; a person with a computer inserted in their brain, rather than merely into their pocket, will be seen as no less human than someone with a pacemaker; and stepping into a vehicle or aircraft without a human at the controls will come to be seen not as reckless but as benignly reassuring. We are surely not too far from the day when Edge will receive its first contribution from a genetically enhanced author or an artificial intelligence. That too will be big news, but not for long.

Thus, humanity is subject to two inexorably rising tides: a scientific and technological one in which the magical eventually becomes mundane, and a psychological and social one in which the unthinkable becomes unremarkable. Individual news stories will continue to make noise, but will come and go like breaking waves. Meanwhile beneath them, inconspicuous in their vastness, the twin tides of technological and social change will continue their slow but relentless rise. For generations to come they will go on testing and extending the boundaries of human knowledge and acceptance, causing both trepidation and wonder. This will be the real story of our species and our age.

Some 2000 years ago, probably 23 BCE, the Roman poet Horace (Quintus Horatius Flaccus) published some poems, and they stayed forever as he predicted himself: “have built a monument which will last longer than ore” (Exegi monumentum aere perennius). Although these words about his odes were not exactly an expression of modesty, he was right. The most famous ode (number 11 of the first book) is also one of the shortest with only eight lines. Everyone knows the words enjoy the day (carpe diem); these two words imply more than just having fun, but to actively grasp the opportunities of the day and to “seize the present” as someone has translated into English.

This ode of Horace starts with the energetic advice not to ask questions that cannot be answered. This is an eternal reminder not only for scientists, i.e., very old news that have to be repeated regularly. Science is to discover right and good questions, indeed often unasked questions, before trying to give an answer. But what are criteria for right questions? How do we know that a question can be answered and does not belong to the realm of irrationality? How can a mathematician trust his mind that a proof will be possible, and then he spends years to find it? Apparently, the power of implicit knowledge or intuition is much stronger as we are usually inclined to believe. It is attributed to Albert Einstein to have said: “The intuitive mind is a sacred gift and the rational mind is a faithful servant. We have created a society that honors the servant and has forgotten the gift.

In poetry we often find representations of such implicit knowledge and intuition with high scientific value opening new windows of potential discoveries. It just has to be harvested. If read (better even spoken) with an open mind, poetry can serve as a direct bridge, an effortless link between the different cultures. Thus, poetry does not belong to the humanities only, (if at all); poems in all languages express anthropological universals and cultural specifics in a unique way, and they provide insights into the human nature, the mode of thinking and experiencing, often shadowed by a castrated scientific language.

After his warning with respect to questions that cannot be answered Horace suggests that one should not fall into the trap to gamble; one simply should accept reality (ut melius quidquid erit pati), and he gives the frustrating but good advice to bring our great hopes into a smaller space (spatio brevi spem longam reseces). This is hard to take as scientists always want to go beyond not accepting the limits of our mental power. But it is good to be always reminded that our evolutionary heritage has dictated limits of reasoning and insights which have to be accepted and which should be the basis of modesty.

Such limits are also pointed out in other cultures; for instance more than 2000 years ago Laozi in the Daodejing says: “To know about not knowing is the highest” (in pinyin with indication of the tones: zhi-1 bu-4 zhi-1, shang-4). To accept such an attitude is not easy, and it may be impossible to suppress the search for causality as expressed by the French poet Paul Verlaine: It is the greatest pain not to know why (C'est bien la pire peine de ne savoir pourquoi).

Apparently, poets (of course not all of them) have some knowledge about our mental machinery which can guide scientific endeavors. But there is also a problem which is language itself: Can poetry be translated? Can even scientific language be translated veridically? Of course not. Take the English translation seize the present of carpe diem. Does the English present cover equivalent connotations in Chinese, German or any other language? The English present evokes different associations compared to the German “Gegenwart” or the Chinese “xianzai”. Present is associated with sensory representations, whereas “Gegenwart” has a more active flavor; the component “warten” refers either to take care of something" or "to wait for something", and it is thus also past and future oriented. The Chinese “xianzai” is associated with the experience of existence in which something is accessible by its perceptual identity; it implies a spatial reference indicating the here as the locus of experience, and it is also action oriented. Although the different semantic connections are usually not thought of explicitly, they still may create a bias within an implicit frame of reference.

What follows? It is necessary to realize that the language one uses, also in scientific discourse, is not neutral with respect to what one wants to express. But this is not a limitation; if one knows several languages, and a scientist knows several languages anyway, it is a rich source of creativity. Some sentences, however, do not suffer from translations; they are easily understood and they last forever. When Horace says that while we talk the envious time is running away (dum loquimur fugerit invida aetas), one is reminded of scientific (and political) discussions full of words with not too much content; not exactly new news.

In a recent U.S. Supreme Court hearing regarding affirmative action in higher education, a Justice posed the question, “What unique perspective does a minority student bring to a physics class?” If physics were the work of robots, the answer would be none. But physics, as all of science, is approached with the biases and perspectives that make us human. Both disciplined and spontaneous, science is an intuitive as well as a systematic undertaking.

It is the people who comprise physics graduate schools, institutes, and faculty—their interests, their backgrounds, their agendas—who drive the direction of physics research and scholarship. And it does not take much imagination to picture what different directions this research might take, were the pool of scientists not heterogeneous.

Science has become increasingly collaborative in a way that makes diversity a paramount necessity. Until recently it was the work of single individuals, primarily white males from northern Europe. It was rare to find a published paper with two authors and one with more than three was essentially unheard of. A change began at the time of World War II and it has grown since then.

Large science collaborations encompassing diversity of gender, race and ethnicity have become a new norm. ATLAS, a group that has been a major contributor to CERN’s discovery of the Higgs boson consists of 3,000 physicists from 175 institutions in 38 countries working harmoniously together. Even though a single large instrument such as a particle accelerator or a large telescope is not required in biology, we see parts of the field moving in the same direction with the Human Genome or Human Microbiome project. A different kind of complexity, the assembling of disparate parts of the pattern is needed there.

The news is that science’s success in such endeavors is creating a recognized model for international collaboration, climate change being the most conspicuous example.

The diversity in approach engendered by diversity in background has been a powerful combination in science. It is no secret that in a fairly recent past if physics graduate school admission had been based on achievement tests, the entering class would have been composed almost entirely of students from mainland China. Most of these schools believed that such a homogeneous grouping would not have benefited either the students or the field. It would have reinforced conformity rather than encouraging the necessary originality and entrepreneurship. It would have reinforced conformity rather than challenge assumptions.

Science’s future, both in the classroom and in research, is tied to an increased ability to achieve diversity in gender, race, ethnicity, and class. If those communities of learning are not established in a classroom setting, science will suffer.

If a central problem in the contemporary world could be defined, it might be called adapting ourselves to algorithmic reality. The world is marked by an increasing presence of technology and the key question is whether we will have an empowering or enslavening relation with it. To have an enabling relation, we may need to mature and grow in new ways. The fear is that just as human-based institutions can oppress, so too might technology-orchestrated realities, and in fact this case might be worse. Blockchain technology is the newest and most emphatic example of algorithmic reality, news that makes us consider our relation with technology more seriously.

Blockchain technology (the secure distributed ledger software that underlies cryptocurrencies like Bitcoin) connotes the Internet II: the transfer of value, as a clear successor position to the Internet I: the transfer of information. This means that all human interaction regarding the transfer of value, including money, property, assets, obligations, and contracts could be instantiated in blockchains for quicker, easier, less costly, less risky, and more auditable execution. Blockchains could be a tracking register and inventory of all the world’s cash and assets. Orchestrating and moving assets with blockchains concerns both immediate and future transfer, whereby entire classes of industries, like the mortgage industry, might be outsourced to blockchain-based smart contracts, in an even more profound move to the automation economy. Smart contracts are radical as an implementation of self-operating artificial intelligence, and also through their parameter of blocktime, rendering time too to be assignable rather than fixed.

Blockchains thus qualify as the most important kind of news, the news of the new—something that changes our thinking; causes us to pause; where in a moment we instantly sense that now things might be forever different as a result.

Singularity-class science and technology breakthroughs are news of the new. It is revolutionary what advances like deep learning, self-assembling nanotechnology, 3D printed synthetic biological life, the genome and the connectome, immersive virtual reality, and self-driving cars might do for us. However impressive though, these are context-specific technologies. So when a revolution comes along that is as general and pervasive as to possibly reorchestrate all of the patterns of life, that is noticeable news of the new, and that is blockchains.

In existing as a new general class of thing, blockchains reconfigure the definition of what is it is be new. Perhaps we did not even know what the new, or news, was before, or how new something could be. We see the elegance of Occam’s razor in redefining what it is to be new. The medium and the message are simultaneously the message; the message is stronger because it has reconfigured its own form. The blockchain redefines what it is to be new because the medium and message create an entirely new reality and possibility space for how to do things. Where previously there were only hierarchical models for organizing large-scale human activity, blockchains open up the possibility of decentralized models, and hybrid models; and not just improved current methods, but an expansive invitation to new projects. The blockchain news of the new is that we are in a whole new possibility space of diversity and decentralization, no longer confined to hierarchy as a solitary mode of coordination.

Blockchains as a class of the new startle us with the discomfort and fear of the unknown because it is not clear if blockchain technology is good or bad news. Even more fearful is perhaps the implication that in fact it is us who will determine whether the news is good or bad. The underlying technology is as any other technology, itself neutral or at least pliable in dual-use for both helpful and limiting purposes. Blockchains invite the possibility of action, and more deeply, the responsibility of action. We are developing the sensibility of the algorithmically-aware cryptocitizen, where the expansion of the apparatus of our thought and maturity is proportional to the force of the new experience to be mastered.

Cryptocitizen sensibility and the blockchain news of the new invite the possibility of our greater exercise of freedom and autonomy, and rethinking authority. In a Crypto Copernican turn, we can shift the assumed locus of authority from being outside ourselves in external parties to instead residing within our own self. This is the Enlightenment that Kant was after, an advance not just in knowledge but also in authority-taking. A Cambrian explosion of experimentation in new models of economics and governance could ensue. Blockchains, being simultaneously global and local, could coordinate the effort, equitably joining the diversity of every permutation of micropolis with the cohesion of the macropolis, in connected human activity on digital smartnetworks.

When we have an encounter with the new, that is indeed news. This is the news that we crave and seek above all else, an encounter with the sublime that reconfigures our reality. The galvanizing essence of the blockchain news of the new is the possibility of our further expansion into our own potentiality. The Crypto Enlightenment is the kind of authority-taking change we can make within ourselves as a maturation towards the realization of an empowering relationship with technology. 

The all-consuming news story in biology this year—this decade really—is the discovery of the CRISPR/Cas9 system and its practical application for gene editing. At least three other essays in this book mention or refer to this new technology; there have been numerous articles in the popular press. Most of that attention has been directed at the tremendous and potentially dangerous power of this new technology: it allows "editing" the DNA of genomes, including those of humans, in a way that would be permanent—that is heritable through generations.

All this attention on the possible uses and misuses of CRISPR/Cas9 has obscured the real news—which is, in a way, old news. CRISPR/Cas9 is the fruit of years of fundamental research conducted by a few dedicated researchers who were interested in the arcane field of bacterial immunity. Not immunity to bacteria as you might at first think, but how bacteria protect themselves against attack by viruses. Weird as it may seem, there are viruses that specialize in attacking bacteria. Just as most viruses we know about are specific to one species or another—you can’t catch a cold from your dog—there are viruses that only infect bacteria, in fact only certain types of bacteria. These have a special name—phage. And they have a long history in the development of molecular biology and genetics. Indeed molecular biology began with the study of phage and its ability to insert its genome into the genome of bacteria—even before Watson and Crick’s famous articulation of DNA as the molecule of heredity.

For the past forty years restriction enzymes, another family of bacterial proteins, have been the mainstay of the biotech industry, and they too were discovered first as an early example of bacterial mechanisms to protect themselves against invading viruses. And they were also discovered in university research laboratories devoted to fundamental basic research. CRISPR/Cas9 however is a more sophisticated mechanism, approaching that of the immune system of higher animals: it is adaptive, in the sense that a bacterium and the other bacteria it generates by dividing can "learn" and destroy the DNA of the genome of a particular type of phage after it has been attacked by that phage once. The researchers who discovered CRISPR/-Cas9 and recognized its potential value as a gene editing tool in living things other than bacteria were not searching for some new technology, they were after a deeper understanding of a fundamental question in prokaryotic (microbial) biology and evolution—the back and forth competition between bacteria and the viruses that invade them. Could that be any more arcane sounding?

It is also important to recognize that this was not a serendipitous discovery, a happy accident along the way. This is often the case made for supporting fundamental research—that you never know where it might lead, serendipity intervenes so often. But this is a false conception and CRISPR/Cas9 is a perfect example of why. This was no simple accident resulting from good luck or happenstance. It was the fruit of hard and sustained labor, of whole careers devoted to understanding the fundamental principles of life. Work in this area goes back thirty years, and the particular groups that discovered CRISPR/Cas9 were looking for precisely such an adaptive, immune-like response in bacteria. Understanding the value of restriction enzymes, as these researchers would have, was a sensible leap to appreciating the value of a potentially even more sophisticated DNA-based protective system. This is how research works—neither by accident nor by purpose—it is the result of hard work at every level of inquiry. Indeed advances are often unpredictable, but that doesn’t make them merely lucky. Certainly not like winning some type of lottery.

We continue to have this misguided debate about fundamental versus applied research as if they were two spigots that can be operated independently. They are one pipeline, and our job is to keep it flowing. This is old news, but we should never tire of saying it. And in this case it created the biggest news in biology in a decade—CRISPR/Cas-9.

Thomas Hobbes’s uncomfortable view of human nature looks remarkably prescient in the light of new discoveries in Kenya. Back in the mid 17th century—before anyone had any inkling of deep time or the destabilization of essential identity that would be brought about by an understanding of the facts of human evolution (i.e. before the idea was possible that nature was mutable)—Hobbes argued that we were fundamentally beastly (selfish, greedy, cruel) and, in the absence of certain historically-developed and carefully nurtured institutional structures, would regress to live in a state of nature, in turn understood as a state of perpetual war.

We can assume that John Frere would have agreed with Hobbes. Frere, we may read (and here Wikipedia is orthodox, typical and, in a critical sense, wrong), “was an English antiquary and a pioneering discoverer of Old Stone Age or Lower Paleolithic tools in association with large extinct animals at Hoxne, Suffolk in 1797.” In fact, while Frere did indeed make the first well-justified claim for a deep-time dimension to what he carefully recorded in situ, saying that the worked flints he found dated to a “very remote period indeed,” he did not think they were tools in any neutral sense, stating that the objects were “evidently weapons of war, fabricated and used by a people who had not the use of metals.”

Frere’s sharp-edged weapons can now be dated to Oxygen Isotope Stage 11—in other words, to a period lying between 427 and 364 thousand years ago—and even he might have been surprised to learn that the people responsible were not modern humans, but a species, Homo erectus, whose transitional anatomy would first come to light through fossil discoveries in Java a century later. Subsequent archaeological and palaeoanthropological work (significant aspects of it pioneered by Frere’s direct descendant, Mary Leakey) has pushed the story of genus Homo back ever further, revealing as many as a dozen distinct species (the number varies with the criteria used).

Alongside the biological changes runs a history, or prehistory, of technology. It has usually been supposed that this technology, surviving mainly as modified stone artifacts, was a product of the higher brain power that our human ancestors displayed. According to Darwin’s sexual selection hypothesis, female hominins favored innovative male hunters, and the incremental growth in intelligence led, ultimately, to material innovation (hence the evocative but not taxonomic term, Homo faber—Man the Maker).

So powerful was this idea that, although chipped stone artifacts dating to around 2.6 million years ago have been known for some time, there was a strong presumption that genus Homo had to be involved. This is despite the fact that the earliest fossils with brains big enough to be classified in this genus dated at least half a million years later. It was a fairly general hunch within palaeoanthropology that the genus Homo populations responsible for early chipped-stone technologies had simply not yet been discovered. Those few of us who, grounded in the related field of theoretical archaeology, thought differently, remained reliant on a very broad kind of consilience to counter this ex silencio assumption.

So to me it was wonderful news when, in May 2015, Sonia Harmand and co-workers published an article in Nature entitled “3.3-million-year-old stone tools from Lomekwi 3, West Turkana, Kenya,” because the strata at their site date to a period when no one seriously doubts that australopithecines, with their chimp-sized brains, were the smartest of the savannah-dwelling hominins. The discovery shows unambiguously that technology preceded, by more than one million years, the expansion of the cranium that is traditionally associated with the emergence of genus Homo.

Harmand et al follow current convention in naming their artifacts tools, rather than offensive weapons. This apparently more neutral terminology is, I think, a reflex of our continual and pervasive denial of Hobbes’s truth. Hobbes obviously did not have the information available to understand the time-depths or the bio-taxonomic and evolutionary issues involved, but had he known about Lomekwi 3 he would probably have called it differently, as Frere subsequently did at Hoxne.

The pre-human emergence of weapons technology makes functional and evolutionary sense. We are not talking about choosing appropriate twigs for the efficient extraction of termites, or the leaves best suited to carrying water, but about the painstaking modification of fine-grained igneous rocks into sharp-edged or bladed forms whose principal job was to part flesh from flesh and bone from bone.

If the word hunting helps gloss the reality of what such sharp stone artifacts were used for, then we can reflect on the type of hunting recently documented from the Aurora stratum at the site of Gran Dolina (Atapuerca), Spain. Here, Palmira Saladie Balleste and co-workers recently reported (Journal of Human Evolution, 2012) on a group of Homo antecessor (or, arguably, erectus) who fed on individuals from, presumably, a rival group. The age profile of the victims was “similar to the age profiles seen in cannibalism associated with intergroup aggression in chimpanzees,” that is, those eaten were infants and immature individuals.

That much of the data on early, systematic, endemic violence in our deeper (and shallower) prehistory comes as a surprise is due to the pervasive myth about the small-scale band societies of the archaeological past having somehow been egalitarian. This idea has an odd genealogy that probably goes back to the utopian dreaming of Hobbes’s would-be intellectual nemesis, Jean-Jacques Rousseau, with his ideas of harmony and purity in nature, and his belief that the savage state of humanity was noble rather than decadent.

Rousseau, like Hobbes, lacked the possibility of an evolutionary perspective, and also dealt in more or less essentialist assertions. But once we have to bridge from wild primate groups to early human ancestors, the tricky question of the roots of egality arises. If the chimpanzees and gorillas that can be studied in the wild have clear status hierarchies that are established, maintained and altered by force, including orchestrated murder and cannibalism, then how could fair play magically become a base-line behavior?

Somewhere along the way, it seems to have been forgotten that the 19^th century founders of modern socio-cultural anthropology, Lewis Henry Morgan, Edward Burnett Tylor, and Edvard Westermarck, recorded all kinds of unfairness in indigenous North American and Pacific societies: we may not want the Tlingit and Haida, Ojibwa and Shawnee to have had slaves, for instance, but avoiding mentioning it in modern textbooks does a great disservice to the original ethnographic accounts (and the slaves).

Returning to the news from Lomekwi 3, we can now see that technology was not just a figural but a literal arms race. Reanalyzing the take-off in cranial capacity that began around 2 million years ago, we can see that blades and choppers needed to be already available to replace the missing biology—the massive ripping canines and heavy jaw muscles that previously hampered, in direct bio-mechanical terms, the expansion of the braincase. As Frere would immediately have understood, these artifacts included weapons, perhaps predominantly and pre-eminently. Only by postulating high-level competition between groups can we understand the dramatic adaptive radiation of hominin types and the fact that, ultimately, only one hominin species survived.

The paradox is that, by sharpening the first knives to extend the range of possible forms of aggression, we opened up a much broader horizon, in which technology could be used for undreamed-of purposes. Yet Hobbes’s instinct that our nature was borne of war, and Frere’s conclusion that the world’s primal technology was offensive, should not be ignored. In the artificial lulls when atavism is forced into abeyance we are happy to forget Hobbes’s admonition that it is only through the careful cultivation of institutions that stable peace is at least possible.

When prehistoric humans arrived in America they found a continent populated by mammoths, wooly rhinos, giant sloths, sabertooths, horses, and camels. By the time Columbus arrived, all of these species were extinct, due mainly to human hunting. But today, paleobiologists are sequencing the genomes of these extinct species. Furthermore, genetic engineering is approaching the point where genetically engineered versions of these extinct species may walk the Earth again. This year's big news—cloning of a dead pet dog—is thus merely a small beginning.

In the near future, the news will concern what paleo-DNA specialist Beth Shapiro dubs "de-extinction": generating living organisms bearing genes recovered from extinct species. Paleo-DNA (the somewhat degraded DNA recovered from bones or hair of extinct species) can be extracted from recently extinct species like mammoths and those exterminated by humans during historical times including passenger pigeons, dodos or thylacines (Jurassic Park fans note: the truly ancient DNA from dinosaurs is too degraded to currently allow sequencing). Trace amounts of DNA can be recovered, amplified and sequenced. Key genes could then be engineered into cells of the closest living relatives (Asian elephants for mammoths) to produce shaggy, cold tolerant elephants. This is nearly within technological reach today. Although birds pose unique challenges (being unclonable with current technologies), the de-extinction of passenger pigeons or moas (3.5 m tall flightless birds exterminated by hunting when the Maori arrived in New Zealand) appears within our technical grasp, and major de-extinction projects for these species are already underway.

So should we do it? Shapiro's recent book How to Clone a Mammoth provides an excellent introduction to the arguments. Given the polarized opinions generated by reintroducing wolves to Yellowstone, one can easily imagine diversity of public reactions to reintroducing sabertooth tigers or giant cave bears. I think that the best "pro" arguments are ecological—by reviving lost species we can restore habitats damaged or destroyed as our species spread over the planet. Mammoth-like elephants stomping through the tundra of Siberia's Paleozoic Park would benefit the environment by slowing the process of permafrost melting and the attendant carbon release. From a purely scientific, curiosity-driven viewpoint, de-extinction will offer biological and ecological insights available in no other way. Economically, tourists would pay top dollar to watch moas wandering the beech forests of New Zealand, or mammoths roaming Siberia. The con arguments are mostly practical (why spend money reviving extinct species rather than saving living endangered species?) or techno-fearful (humans shouldn't play god), but nonetheless passionately advocated.

By far the most significant issues will concern extinct hominids like Neanderthals, and society needs to prepare for the challenging ethical questions raised by such research. In 1997 researchers at Svante Pääbo's paleo-DNA lab in Leipzig made the news by sequencing mitochondrial DNA from Neanderthals. Today, after breathtaking technological progress, a full Neanderthal genome is available online. Even more exciting, in 2010 Pääbo's group discovered Denisovans, a previously-unknown Asian hominid species, based on DNA extracted from a tiny finger bone. The discovery of Denisovans from paleo-DNA makes it crystal clear that when modern humans emerged from Africa, they encountered a world inhabited by multiple near-human species—all of them now extinct.

Recovering the genome sequence of an extinct hominid species is exciting because it provides answers to a host of biological questions concerning which stones and bones (the previous mainstay of paleoanthropology) will remain forever mute. For example, it seems likely based on pigmentation genes that Neanderthals had light skin and some had red hair. Paleo-DNA has clarified that some interbreeding probably occurred when the first modern humans migrated out of Africa and encountered Neanderthals. As a result, all non-African human populations bear traces of Neanderthal DNA in their genomes (and many Asians bear additional Denisovan DNA). Similarly, the issue of whether Neanderthals had spoken language has divided scholars for decades. Although the case remains far from closed, we now know that Neanderthals shared the derived human version of the FOXP2 gene which enhances our speech motor control. This suggests that Neanderthals were able at least to produce complex vocalizations, even if they lacked modern, syntactic language. Such findings have fueled an ongoing sea-change in contemporary interpretations of Neanderthals—from oafish thugs to smart, resourceful near-humans. 

Paleo-DNA sequencing has changed not only our understanding of Neanderthals, but of ourselves. Neanderthals were not modern humans: they lacked the rapid cultural progress characterizing our species, and thus presumably some of our cognitive capacities. But what precisely were these differences? Do these differences make us, the survivors, "human?" Or were Neanderthals human, but "differently abled?" Certainly, with the bodies of Olympic wrestlers and brains slightly larger than modern humans, they'd be first picks for your rugby scrum; perhaps they had unique cognitive abilities as well. Progress will be rapid in addressing these issues, because each new insight into the genetic basis of the human brain yields parallel insights into our understanding of Neanderthal brains—and of the cognitive differences between the two.

But the truly deep ethical issues concern the possible de-extinction of Neanderthals or other extinct hominids. From a scientific viewpoint this would promise insights into hominid evolution and human nature unimaginable a decade ago. But from a legal viewpoint it would involve creating humans expressing Neanderthal genes, and thus require human cloning already forbidden in many countries. But few doubt that, within this century, genetic engineering of our own species will be both technologically possible and ethically acceptable in at least some sub-cultures. Clearly, a human expressing Neanderthal genes (as many of us already do!) would retain all basic human rights, but the moral and ethical implications raised by Neanderthals in the workplace (or on college football teams) might easily eclipse those raised by racism or slavery.

Clearly paleo-DNA will remain in the news for the foreseeable future, offering scientific insights and posing unprecedented ethical quandaries. It will thus behoove all thinking people (especially politicians drafting legislation) to become acquainted with the technology and the biological facts before forming an opinion.

2015 saw the publication of an impressive tour d’horizon of global ecology. Covering many areas, it assesses human impacts on the loss of biodiversity, the subject that falls within my expertise. Like all good reviews, it’s well documented, comprehensive, and contains specific suggestions for future research. Much of it has a familiar feel, though it’s a bit short on references from Nature and Science. But that’s not what makes this review news. Rather, it’s because it reached a well-defined 1.2 billion people around plus uncountable others. That’s a billion with a “b,” likely putting the citation impact statistics of other recent science stories into the shade. The publication is “On care for our common home” and its author is better known as Pope Francis.

How much ecology is there in this? And how good is it? Well, the word “ecology” (or similar) appears eighty times, “biodiversity” twelve, and “ecosystem” twenty-five. There’s a 1400 word section on the loss of biodiversity—the right length for a letter to Nature.

The biodiversity section starts with a statement that the “earth’s resources are also being plundered because of short-sighted approaches to the economy, commerce and production.” It tells us that deforestation is a major driver of species loss. As for the importance of the topic, it explains why a diversity of species are import as sources of food, medicines and other uses, while “different species contain genes which could be key resources in years ahead for meeting human needs and regulating environmental problems.” A high rate of extinction raises ethical issues, particularly those involving where our current actions limit what future generations can use or enjoy.

We learn that most of what we know about extinction comes from studying birds and mammals. In a sentence that E.O. Wilson might have written, it praises the small things that rule the world. “The good functioning of ecosystems also requires fungi, algae, worms, insects, reptiles and an innumerable variety of microorganisms. Some less numerous species, although generally unseen, nonetheless play a critical role in maintaining the equilibrium of a particular place.”

There is no point in a complete catalogue, but this short list exemplifies its insights and comprehensiveness.

Knocking pieces from any complex system—in this case species from ecosystems—can have unexpected effects.

Technology has benefits, but the idea of unbridled technological optimism was my Edge choice two years ago of an “idea that must die.” Bergoglio expresses that eloquently with “We seem to think that we can substitute an irreplaceable and irretrievable beauty with something which we have created ourselves.”

We not only destroy habitats, but we massively fragment those that remain behind. The solution is to create biological corridors.

“When certain species are exploited commercially, little attention is paid to studying their reproductive patterns in order to prevent their depletion and the consequent imbalance of the ecosystem.”

There has been significant progress in establishing protected areas on land and in the oceans.

There are concerns about the Amazon and the Congo, the last remaining large blocks of tropical forests. There are concerns about replacing native forests with tree plantations that are so much poorer in species.

Overfishing and discarding large amounts of bycatch diminish the oceans’ ability to support fisheries. Human actions physically damage the seabed across vast areas, massively changing the composition of the species that live there.

It ends with a statement that might be from a Policy Forum in Science arguing as it does for increased effort and funding. 

Greater investment needs to be made in research aimed at understanding more fully the functioning of ecosystems and adequately analysing the different variables associated with any significant modification of the environment. Because all creatures are connected, each must be [conserved], for all … are dependent on one another. … This will require undertaking a careful inventory of the species which it hosts, with a view to developing programmes and strategies of protection with particular care for safeguarding species heading towards extinction.

In this, I’ve changed only the word “cherished” to “conserved.”

Reading the biodiversity section again, having just finished teaching my graduate conservation class, made me think it would make an outstanding course outline next year. Its coverage is impressive, its topics of global significance. Its research is strikingly up to date and hints at very active controversies. To answer my questions: yes, there is lots of ecology and it’s of a very high order, too.

The publication’s other lengthy sections include sections on pollution, climate change, water, urbanization, social inequality and its environmental consequences, both the promise and threat of technology, inter-generational equity, policies both local and global. All these topics would appear in a course on global ecology. This is not why the publication made news.

Rather, it’s an incontestable statement of the importance of science in shaping what are the ethical choices of our generation—both for Catholics and those of us who are not. It appeals for all religions and all scientists to grasp this enormity of the problems that the science of ecology has uncovered and to seek their solutions urgently. The author deserves the last word—and it is a good one—on how we should do that:

Nonetheless, science and religion, with their distinctive approaches to understanding reality, can enter into an intense dialogue fruitful for both. Given the complexity of the ecological crisis and its multiple causes, we need to realize that the solutions will not emerge from just one way of interpreting and transforming reality. ... If we are truly concerned to develop an ecology capable of remedying the damage we have done, no branch of the sciences and no form of wisdom can be left out, and that includes religion and the language particular to it.

Research in developmental and comparative psychology has discovered that the humble pointing gesture is a key ingredient for the capacity to develop and use human language, and indeed for the very possibility of human social interaction as we know it.

Pointing gestures seem simple. We use them all the time. I might point when I give someone directions to the station, when I indicate which loaf of bread I want to buy, or when I show you where you have spinach stuck in your teeth. We often accompany such pointing gestures with words, but for infants who are not yet able to talk these gestures can work all on their own.

Infants begin to communicate by pointing at about nine months of age, a year before they can produce even the simplest sentences. Careful experimentation has established that prelinguistic infants can use pointing gestures to ask for things, to help others by pointing things out to them, and to share experiences with others by drawing attention to things that they find interesting and exciting.

Pointing does not just manipulate the other’s focus of attention, it momentarily unites two people through a shared focus on something. With pointing, we do not just look at the same thing, we look at it together. This is a particularly human trick, and it is arguably the thing that ultimately makes social and cultural institutions possible. Being able to point and to comprehend the pointing gestures of others is crucial for the achievement of “shared intentionality,” the ability to build relationships through the sharing of perceptions, beliefs, desires, and goals.

Comparative psychology finds that pointing (in its full-blown form) is unique to our species. Few non-human species appear to be able to comprehend pointing (notably, domestic dogs can follow pointing while our closest relatives among the great apes cannot), and there is little evidence of pointing occuring spontaneously between members of any species other than our own. It appears that only humans have the social-cognitive infrastructure needed to support the kind of cooperative and prosocial motivations that pointing gestures presuppose.

This suggests a new place to look for the foundations of human language. While research on language in cognitive science has long focused on its logical structure, the news about pointing suggests an alternative: that the essence of language is found in our capacity for the communion of minds through shared intentionality. At the center of it is the deceptively simple act of pointing, an act that must be mastered before language can be learned at all.

Your brain is predictive, not reactive. For many years, scientists believed that your neurons spend most of their time dormant and wake up only when stimulated by some sight or sound in the world. Now we know that all your neurons are firing constantly, stimulating one another at various rates. This intrinsic brain activity is one of the great recent discoveries in neuroscience. Even more compelling is what this brain activity represents: millions of predictions of what you will encounter next in the world, based on your lifetime of past experience.

Many predictions are at a micro level, predicting the meaning of bits of light, sound, and other information from your senses. Every time you hear speech, your brain breaks up the continuous stream of sound into phonemes, syllables, words, and ideas by prediction. Other predictions are at the macro level. You’re interacting with a friend and, based on context, your brain predicts that she will smile. This prediction drives your motor neurons to move your mouth in advance to smile back, and your movement causes your friend’s brain to issue new predictions and actions, back and forth, in a dance of prediction and action. If predictions are wrong, your brain has mechanisms to correct them and issue new ones.

If your brain didn’t predict, sports couldn’t exist. A purely reactive brain wouldn’t be fast enough to parse the massive sensory input around you and direct your actions in time to catch a baseball or block a goal. You also would go through life constantly surprised.

The predictive brain will change how we understand ourselves, since most psychology experiments still assume the brain is reactive. Experiments proceed in artificial sequences called “trials,” where test subjects sit passively, are presented with images, sounds, words, etc., and make one response at a time, say, by pressing a button. Trials are randomized to keep one from affecting the next. In this highly controlled environment, the results come out looking like the subject’s brain makes a rapid, automatic response, followed by a controlled choice about 150 milliseconds later, as if the two responses came from distinct systems in the brain. These experiments fail to account for a predicting brain, which never sits awaiting stimulation, but continuously prepares multiple, competing predictions for action and perception, while actively collecting evidence to select between them. In real life, moments or “trials” are never independent because each brain state influences the next. Most psychology experiments are therefore optimized to disrupt the brain’s natural process of prediction.

The predictive brain presents us with an unprecedented opportunity for new discoveries about how a human brain creates a human mind. New evidence suggests that thoughts, feelings, perceptions, memories, decision-making, categorization, imagination, and many other mental phenomena, which historically are treated as distinct brain processes, can all be united by a single mechanism, prediction. Even our theory of human nature is up for grabs, as prediction deprives us of our most cherished narrative: the epic battle between rationality and emotions to control behavior.

The most exciting recent scientific news is about science itself: how it is funded, how scientists communicate with another, how findings get distributed to the public—and how it can go wrong. My own field of psychology has been Patient Zero here, with well-publicized cases of fraud, failures to replicate important studies, and a host of concerns, some of them well-founded, about how we do our experiments and analyze our results.

There’s a lot to complain about with regard to how this story has played out in the popular press and over social media. Psychology—and particularly social psychology—has been unfairly singled out. The situation is at least as bad in other fields, such as cancer research. More importantly, legitimate concerns have been exaggerated and used by partisans on both the left and the right to dismiss any findings that don’t fit their interests and ideologies.

But it’s a significant story, and a lot of good can come from it. It’s important for non-scientists to have some degree of scientific literacy, and this means more than a familiarity with certain theories and discoveries. It requires an appreciation of how science works, and how it stands apart from other human activities, most notably religion. A serious public discussion of what scientists are doing wrong and how they can do better will not only lead to better science, it will help advance scientific understanding more generally.

Surprising images of dwarf planet Pluto from a flyby of the New Horizons spacecraft put space exploration back in the headlines as one of the biggest science stories of 2015. Instead of a barren, frigid globe, Plato proved to be colorful, contrasty, and complex, with diverse geological structure including mountains, valleys, and plains of water and nitrogen ice, evidence of past and present glacial flows, possible volcanoes spewing water ice from a warmer core, and a thin atmosphere that extends hundreds of miles above the planetary surface. Similar insights are being gleaned from Chiron and the smaller of Pluto's five moons.           

2015 also brought Pluto news of a more arcane sort. The historic 24-inch Clark refractor telescope of Lowell Observatory was refurbished and opened to the public for viewing. Why mention Lowell and Earth-based optical astronomy? As a young Lowell employee, Clyde Tombaugh discovered Pluto in 1930 on photographic plates taken with a Lowell instrument. For many, telescopes, whether optical leviathans or the modest backyard variety, are spaceships for the eye and mind that provide a compelling sensory immediacy lacking in the pricier technological tour de force of a spacecraft. Recall the aesthetic impact of the starry night viewed from a dark country path or seeing Saturn for the first time through a telescope. Although modern Earth-based telescopes continue to provide astronomical breakthroughs, old telescopes and the observatories that house them survive as domed, verdigris-covered cathedrals of science. The Pluto flyby of 2015 is an occasion to celebrate space exploration new and old, and the value of looking upward and outward. 

The end of the year saw two stories about pathogens, one hopeful and the other less so. The hopeful one is the advancing ability to insert genes that are desirable (from humans’ point of view) into organisms and facilitating that gene’s spread through the population.

Consider the case of malaria, a focus of current efforts. Inserting a gene that inhibits the spread of malaria into a mosquito genome is helpful, but to only a limited degree: if the gene doesn’t spread in wild populations, then its effects will be fleeting. If, however, mosquitoes are released that have the gene in question as well as genes that facilitate the spread of the gene, then the effects can be long-lasting.

The less hopeful case is so-called “super-gonorrhea,” strains of the pathogen that are resistant to the antibiotics currently in use. As is well known, the use of antibiotics gives an advantage to strains of pathogens that are resistant. The tools we use to treat disease become the means by which we make the diseases harder to treat. Cases of super-gonorrhea have appeared in England, leading to a certain amount of concern.

Malaria still infects tens of millions of people and causes hundreds of thousands of deaths. Of course global climate change and political strife are important issues, but pathogens still account for millions of lives lost around the world.

Historically, as illustrated by the super-gonorrhea case, fighting pathogens has been something of an arms race: humans build better weapons, pathogens evolve counter-strategies. The present age is seeing a confluence of a number of advances that hold the promise of turning the arms race into something that might be more like a winnable war. First is progress in genetics, including techniques for inserting genes into genomes. Second is a sophisticated understanding of evolution and a fluorescence of ideas about how to harness it: in the past, evolution worked against us, as in the case of resistant strains of pathogens. We are becoming better at harnessing it. And third is a growing sophistication in thinking about systems. It is unlikely that the same sorts of mistakes will be made in the past, in which simplistic ecological interventions led to somewhat disastrous outcomes, as in the case of cane toads in Australia. Our view of ecosystems is more humble and more sophisticated than ever before.

It seems likely that pathogens, of one sort or another, are likely to be important for a substantial period of time: this is because they are moving targets with tremendous capacity for harm. On the other hand, recent advances hold the promise of taming them in a way that we have not previously seen.

Science is never fixed in place: it must always move forward, and in that sense it is always “news.” What makes science news in a journalistic sense, however, tends to be biased by current concerns, economic interests, and popular fears and hopes.

It is no surprise that research into the brain, in particular, continues to be the focus of much media attention—not only for the obvious reason of its central role in the very fabric of evolved life and of its infinite complexity, but also because of the culturally strong need to understand the biological bases of human behavior. This has led to many excessively positive claims for, and overinterpretations of, necessarily partial, provisional findings about brain mechanisms. The prefix “neuro” now twists into pseudo-scientific shape all aspects of human behavior, from aesthetics to economics, as if the putative cerebral correlates for all that we do explained to us what we are. Of course there are worthwhile and important avenues to explore here; but reports in the mainstream media can hardly do justice to their scientific, methodological, and conceptual complexity.

Yet truly newsworthy neuroscience does get reported. The publication in a June 2015 issue of Nature of the discovery of a lymphatic system within the central nervous system is hugely important, and was acknowledged as such in more mainstream venues. Science Daily titled its report of the discovery “Missing link found between brain, immune system; major disease implications,” with the blurb, “In a stunning discovery that overturns decades of textbook teaching, researchers have determined that the brain is directly connected to the immune system by vessels previously thought not to exist. The discovery could have profound implications for diseases from autism to Alzheimer's to multiple sclerosis.”

We might need to take with a few grains of salt this last sentence—the sort of claim that reflects comprehensible wishful thinking rather than actual reality, typical of what constitutes fast-burning “news.” On the other hand, few discoveries do “overturn decades of textbook learning”—and this one probably does. The fact that established learning can be explicitly overturned is important in itself, for it is easy to forget that most work goes on within given frameworks, on the basis of assumptions rather than with an eye to the need always to question precisely those assumptions that are taken for granted. This particular discovery emphasizes at last the need to understand connections between the nervous and immune systems, and can only push forward the development of the still merely burgeoning field of neuroimmunology. Precisely because of the highly specialized nature of research and clinical care, brain facts tend to be understood apart from body facts, in a Cartesian fashion, as if one were really apart from the other. This piece of news reminds us that we can only understand one as an aspect of the other; and that we need to take seriously, in scientific terms, phenomena such as the placebo and nocebo effects, and the role of the psyche in the evolution of mental and physical disease generally.

And in turn, this goes to show that what we each take to be scientific news—that is, news about our understanding of the world and ourselves—is a function of what we expect it to look like. 

If we knew that AK-47-wielding terrorists were destined to kill 1,000 people in the U.S. in 2016—a thinkable possibility—then we should be afraid . . . albeit 1/10^th as afraid of other homicidal gun violence (which kills more than 10,000), and 1/30^th as fearful of riding in a motor vehicle, where more than 30,000 Americans die each year. Yet several recent surveys indicate we are much less fearful of the greater, everyday threats than of the dreaded horror.

The hijacking of our rationality by fears of terrorist guns highlights an important and enduring piece of scientific news: we often fear the wrong things.

Shortly after 9/11, when America was besieged by fear, I offered a calculation: If we now flew 20 percent less and instead drove half those unflown miles, then—given the greater safety of scheduled airline flights—we could expect about 800 more people to die on our roads. A German colleague, Gerd Gigerenzer, later checked that prediction. He reported that, actually, in the year after 9/11 “an estimated 1,500 Americans died on the road in the attempt to avoid the fate of the [246] passengers who were killed in the four fatal flights.” Long after 9/11, the terrorists were still killing us.

Why? Why do we fear flying, when, for most of us, the most dangerous part of our trip is the drive to the airport? Why do terrorist fears so effectively inflate our stereotypes of Muslims, inflame us/them thinking, and make many of us Christians forget the ethics of Jesus (“I was a stranger and you welcomed me”)?

Underlying our exaggerated fears is the “availability heuristic”: We fear what’s readily available in memory. Vivid, cognitively available images—a horrific air crash, a mass slaughter—distort our judgments of risk. Thus, we remember—and fear—disasters (tornadoes, air crashes, attacks) that kill people dramatically, in bunches, while fearing too little the threats that claim lives one by one. We hardly notice the half-million children quietly dying each year from rotavirus, Bill Gates once observed—the equivalent of four 747s full of children every day. And we discount the future (and its future weapon of mass destruction, climate change).

If only such deaths were more dramatic and immediate. Imagine (to adapt one mathematician’s suggestion) that cigarettes were harmless—except, once in every 25,000 packs, for a single cigarette filled with dynamite. Not such a bad risk of having your head blown off. But with 250 million packs a day consumed worldwide, we could expect more than 10,000 gruesome daily deaths (the approximate actual toll of cigarette smoking)—surely enough to have cigarettes banned.

News-fed, cognitively available images can make us excessively fearful of infinitesimal risks. And so we spend an estimated $500 million per U.S. terrorist death but only $10,000 per cancer death. As one risk expert explained, “If it’s in the news, don’t worry about it. The very definition of news is ‘something that hardly ever happens.’”

It’s entirely normal to fear violence from those who despise us. But it’s also smart to be mindful of the realities of how most people die, lest the terrorists successfully manipulate our politics. With death on their minds, people exhibit “terror management.” They respond to death reminders by derogating those who challenge their worldviews. Before the 2004 election, reported one research team, reminders of 9/11 shifted people’s sympathies toward conservative politicians and antiterrorism policies.

Media researcher George Gerbner’s cautionary words to a 1981 congressional subcommittee ring true today: “Fearful people are more dependent, more easily manipulated and controlled, more susceptible to deceptively simple, strong, tough measures and hard-line postures.”

Ergo, we too often fear the wrong things. And it matters.

The publication in 2015 of a new paper from Leicester University, "The Anthropocene Biosphere," provides more evidence that the changes wrought upon the climate by human civilization are set to bring down a sixth mass extinction. According to the paper’s co-author, geologist Peter Haff, we have already entered a period of fundamental changes to the planetary system that may continue to change the world beyond our imagination, a fear echoed by Adelaide University’s John Long in the New Scientist last month. All of us can provide anecdotal evidence of the shifts that are changing our environment. Today I received a call from a friend in Engadin, Switzerland, where Nietzsche wrote Thus Spoke Zarathustra. In late December, at an altitude of 2,000 metres, there is no snow. In Hyde Park, the daffodils are in bloom.

As the artist, environmentalist, and political activist Gustav Metzger has been saying for many years, it is no longer enough just to talk about ecology, we need to create calls to action. We must consider the potential for individual and collective agency to effect changes in our behavior, and to develop adaptive strategies for the Anthropocene age. To quote Gustav Metzger, “we need to take a stand against the ongoing erasure of species, even though there is little chance of ultimate success. It is our privilege and our duty to be at the forefront of the struggle.” We must fight against the disappearances of species, languages and entire cultures. We must battle against the homogenization of our world. We must understand this news as part of a broader continuum. The French historian Fernand Braudel advocated the “longue durée,” a view of history which relegates the historical importance of “news events” beneath slow shifts, and occasional crises, in the grand underlying structures of human civilisation. Extinction is a phenomenon that belongs to the “longue durée” of the Anthropocene, the symptoms of which we are now beginning to experience as news. By connecting the news to the “longue durée” we can formulate strategies to transform our future and avert the most catastrophic scenarios of extinction. By understanding the news we can act upon it.

Art is one means by which we reimagine existing paradigms to accommodate new discoveries, the thread linking news events to the “longue durée.” Art is also a means of pooling knowledge and it is, like literature, news that STAYS news. It is the means by which we adjust existing paradigms to accommodate new discoveries, the thread connecting the now to the past and to the future.

When Shelley stated that “poets are the unacknowledged legislators of the world” he meant something like this: that writers and artists have the capacity to reimagine news in ways that change the way that we perceive the world, the way we think and act.

Among my great inspirations is Félix Fénéon, a fin-de-siècle French editor (and the first publisher of James Joyce in France), art critic (he discovered and popularised the work of Georges Seurat), and anarchist (put on trial, he escaped prosecution after famously directing a series of barbs at the prosecutor and judge, to the jury’s great entertainment). Félix Fénéon, was a master of transformation. He transformed the news into world literature via his series of prose poems: In 1906 he was the anonymous author of a series of three-line news items published in the Paris newspaper Le Matin, which have since become famous. These brief reports adapt stories of contemporary murder and misery into prose poems that will last forever.

Through their adaptation of the literary and rhetorical devices of rhythm, prosody, and hard-edged juxtaposition, Fénéon transforms minor news items—by themselves petty, random, isolated—into history.

Lawrence Durrell’s Alexandria Quartet transformed the Copernican breakthroughs of Einstein and Freud into fiction. By translating events which are ephemeral and local in their initial impact into that which is universal and enduring, we can make news into culture. John Dos Passos gave lasting form to events that seemed characterised by their fleeting immediacy. In his U.S.A. trilogy Dos Passos pioneered new styles of writing that sought to capture the experience of living in a society overwhelmed by the proliferation of print media, television and advertising. In his “newsreel” sections, the author collages newspaper clippings and popular song lyrics; elsewhere he pursues his experiments in what he called the “camera eye,” a stream of consciousness technique that attempts to replicate the unfiltered receptivity of the camera, which makes no distinction between what is important and what is not. Later this material is transformed into stories. The film-maker Adam Curtis told me that the U.S.A. trilogy identifies “the great dialectic of our time, which is between individual experience and how those fragments get turned into stories... It’s like when you live through an experience you have no idea what it means. It’s only later, when you go home, that you reassemble those fragments into a story. And that’s what individuals do, and it’s what societies do. It’s what the great novelists of the nineteenth century, like Tolstoy, wrote about. They wrote about that tension between how an individual tells the story of an event themselves, out of fragments, and how society then does it.”

The Lebanese-American poet, painter, novelist, urbanist, architect and activist Etel Adnan speaks about the process of transformation as the “beautiful combination of a substratum that is permanent and something that changes on top. There is a notion of continuity in transformation.” In Etel Adnan’s telling, transformation describes the relationship between the “longue durée” of history, news events in the present, and action that can transform the future. Adnan shows us how dialogue can produce new strategies that can preserve difference, can help to act against extinction, while also acknowledging that change is inevitable. If we are to develop radical new strategies to address one of the most important issue of our time, then it is urgent now that we go beyond the fear of pooling knowledge between disciplines. If we do not pool knowledge, then the news is just news: each new year will bring reports of another dead language, another species lost. While writing this text I received an email in the form of a poem from Etel Adnan which expresses this beautifully:

Where do the news go? 

News go where angels go
News go into the waste-baskets of foreign embassies
News go in the cosmic garbage that the universe has become
News go (unfortunately) into our heads

Etel Adnan

The 23 October 2015 issue of the journal Science reported a feel-good story about how some children in India had received cataract surgery and were able to see.  On the surface, there is nothing in this incident that should surprise us.  Ready access to cataract surgery is something we take for granted.  But the story is not that simple. 

The children had been born with cataracts.  They had never been able to see.  By the time their condition was diagnosed — they came from impoverished and uneducated families in remote regions — the regional physicians had told the parents that it was too late because the children were past a critical period for gaining vision. 

Nevertheless, a team of eye specialists visited the area and arranged for the cataract surgery to be performed even on teenagers.  Now, hundreds of formerly blind children are able to see.  After having the surgery four years earlier, one young man of 22 can ride a bicycle through a crowded market. 

The concept of a critical period for developing vision was based on studies that David Hubel and Torsten Wiesel performed on cats and monkeys.  The results showed that without visual signals during a critical period of development, vision is impaired for life.  For humans, this critical window closes tight by the time a child is eight years old.  (For ethical reasons, no comparable studies were run on humans.)  Hubel and Wiesel won a Nobel Prize for their work.  And physicians around the world stopped performing cataract surgery on children older than 8 years.  The data were clear.  But they were wrong.  The results of the cataract surgeries on Indian teenagers disprove the critical period data.

In this light, an apparent “feel-good” story becomes a “feel-bad” story about innumerable other children who were denied the cataract surgery because they were too old.  Consider all the children who endured a lifetime of blindness because of excessive faith in misleading data.

The theme of excessive faith in data was illustrated by another 2015 news item.  Brian Nosek and a team of researchers set out to replicate 100 high profile psychology experiments that had been performed in 2008.  They reported their findings in the 28 August 2015 issue of Science.  Only about a third of the original findings were replicated and even for these, the effect size was much smaller than the initial report.

Other fields have run into the same problem.  A few years ago the journal Nature reported a finding that the majority of cancer studies selected for review could not be replicated.  In October 2015, Nature devoted a special issue to exploring various ideas for reducing the number of non-reproducible findings.  Many others have taken up the issue of how to reduce the chances of unreliable data.

I think this is the wrong approach.  It exemplifies the bedrock bias: a desire for a firm piece of evidence that can be used as a foundation for deriving inferences.

Scientists appreciate the tradeoff between Type I errors (detecting effects that aren’t actually present — false positives) and Type II errors (failing to detect an effect that is present — false negatives).  When you put more energy into reducing Type I errors, you run the risk of increasing Type II errors, missing findings and discoveries.  Thus we might change the required significance level from .05 to .01, or even .001, to reduce the chances of a false positive but in so doing we would greatly increase the false negatives. 

The bedrock bias encourages us to make extreme efforts to eliminate false positives, but that approach would slow progress.  A better perspective is to give up the quest for certainty and accept the possibility that any datum may be wrong.  After all, skepticism is a mainstay of the scientific enterprise.

I recall a conversation with a decision researcher who insisted that we cannot trust our intuitions; instead, we should trust the data.  I agreed that we should never trust intuitions (we should listen to our intuitions but evaluate them), but I didn’t agree that we should trust the data.  There are too many examples, as described above, where the data can blind us. 

What we need is the ability to draw on relevant data without committing ourselves to the validity of those data.  We need to be able to derive inferences, make speculations, and form anticipations, in the face of ambiguity and uncertainty.  And to do that, we will need to overcome the bedrock bias.  We will need to free ourselves from the expectation that we can trust the data.

I am not arguing that it’s okay to get the research wrong — witness the consequence of all the Indian children who suffered unnecessary blindness.  My argument is that we shouldn’t blind ourselves to the possibility that the data might be wrong.  The team of Indian eye specialists responded to anecdotes about cases of recovered vision and explored the possible benefits of cataract surgery past the critical period.

The heuristics-and-biases community has done an impressive job of sensitizing us to the limits of our heuristics and intuitions.  Perhaps we need a parallel effort to sensitize us to the limits of the data — a research agenda demonstrating the kinds of traps we fall into when we trust the data too much.  This agenda might examine the underlying causes of the bedrock bias, and possible methods for de-biasing ourselves.  A few cognitive scientists have performed experiments on the difficulty of working with ambiguous data but I think we need more: a larger, coordinated research program.

Such an enterprise would have implications beyond the scientific community.  We live in an era of Big Data, an era in which quants are taking over Wall Street, an era of evidence-based strategies. In a world that is becoming increasingly data-centered, there may be value in learning how to work with imperfect data. 

In 1974, Stephen Hawking proved that black holes were not black. Rather, quantum mechanics required that black holes would slowly lose their mass via a really neat mechanism: the gravity of a black hole would create a pair of particles outside the black hole, one particle with negative mass and the other with positive mass, and the former would fall inside the black hole, and the latter would move away from the black hole. The net effect was to decrease the mass of the black hole, and its mass would go to zero eventually.

Hawking realized that a zero-mass black hole was a big no-no, because such an entity could only be a naked singularity that completely destroyed the information inside the black hole. One of the fundamental principles of quantum mechanics—the same theory that tells us black holes evaporate—is “unitarity”, which means that information is conserved. But if a black hole destroys information in the final stages of its evaporation, then information cannot be conserved. Unitarity would be violated if a black hole were to evaporate completely.

Hawking then made a mistake: he argued that we have to accept a violation of unitarity in black hole evaporation. But unitarity is a really fundamental principle of quantum physics. Unitarity has many implications, one of which is that if unitarity is violated, so is the conservation of energy. And a little violation of unitarity is like being “just a little pregnant;” it has a tendency to get larger, very much larger. Leonard Susskind of Stanford University pointed out that a tiny violation of unitarity would give rise to a disastrous positive feedback of violation of energy: if one were to turn on a microwave oven, so much energy would be created out of nothing—conservation of energy does not hold, remember—that the Earth would be blown apart!

Obviously, this cannot happen. Information and hence energy must be conserved. But many black holes have been detected, so they must evaporate. How is this dilemma to be resolved?

There is an obvious resolution, namely that all observed black holes are the mass of the Sun or larger, and such black holes will last billions of trillions of years before they approach a naked singularity. What if the universe came to an end in a Big Crunch singularity before any black holes had time to evaporate completely?

This resolution of the black hole evaporation dilemma has a host of fascinating implications. First, it means that the Dark Energy, whatever it is, will eventually turn off. In an ever-accelerating universe, there will be no Big Crunch singularity, and all black holes will eventually evaporate.

Second, the great Israeli physicist Jacob Bekenstein—the man whose work suggested to Hawking that he should investigate the possibility of black hole evaporation—has proved mathematically that if event horizons exist, then the entropy of the universe must approach zero as a Big Crunch singularity is approached. But the Second Law of Thermodynamics says that entropy can never decrease, much less approach zero at the end of time. Thus, if the Second Law holds forever—which it does—then event horizons cannot exist. The absence of event horizons can be shown mathematically to imply that the universe must be spatially finite.

The absence of event horizons also incidentally, almost in passing, resolves the problem of how the information inside a black hole gets out: if there are no event horizons, there is literally no barrier to getting out. We should keep in mind that the assumption that a black hole is bounded by an event horizon is just that: an assumption, not an observed fact. If the universe ends in a Big Crunch, the information inside a black hole just would not get out until near the Big Crunch. No observation today can show that the information is forever bound to being inside the black hole. A claim that event horizons exist is like a guy’s claim that he is immortal: one would have to wait until the end of time to confirm the claim.

So by merely accepting the obvious resolution of Hawking’s Dilemma, and applying the standard laws of physics, we infer that the universe is spatially finite, that the Dark Energy will eventually turn off, that the universe will end in a Big Crunch, and that event horizons do not exist. Various physicists have pointed each of these facts over the past decade, but these implications seem to have escaped the science journalists. Eventually, the information will leak out. Hopefully before the end of time.

At the close of the year 2015, in close succession, two rockets left the ground, crossed the Karman line (at 100 km altitude) into space, and return intact under their own power to a soft landing on the surface of the earth. In the space business, new rockets are launched at regular intervals, but the now-imminent launch of a used rocket is important news.

In December of 1966, Theodore B. Taylor complained that the high cost of sending anything into even low Earth orbit was “roughly equivalent to using jet transport planes to carry freight from, let us say, Madrid to Moscow, making one flight every few weeks, throwing away each aircraft after each flight, and including the entire construction and operation costs of several major airports in the cost of the flights!” 

The now-abandoned Space Shuttle was a reusable spacecraft but failed to reduce launch costs and violated one of the cardinal rules of transport: separate the passengers from the freight. Some day, we will look back and recognize one of the other roadblocks to an efficient launch system: separating the propellant from the fuel. 

There is no reason the source of reaction mass (propellant) has to be the same as the source of energy (fuel). Burning a near-explosive mix of chemicals makes the process inherently dangerous and places a hard limit on specific impulse (ISP), a measure of how much acceleration can be derived from a given amount of propellant/fuel. It is also the reason that the original objective of military rocketry—“to make the target more dangerous than the launch site”—took so long to achieve.

The launch business has been crippled, so far, by a vicious circle that has limited the market to expensive payloads—astronauts, military satellites, communication satellites, and deep space probes—consigned by customers who can afford to throw the launch vehicle away after a single use. Reusable rockets are the best hope of breaking this cycle and moving forward on a path leading to low-cost, high-duty-cycle launch systems where the vehicle carries inert propellant, and the energy source remains on the ground. 

All the advances in autonomous control, combustion engineering, and computational fluid dynamics that allowed these two rockets to make a controlled descent, after only a handful of attempts, are exactly what will be needed to develop a new generation of launch vehicles that leave chemical combustion behind to ascend on a pulsed energy beam. 

We took an important first step in this direction in 2015.

This year, the New York Times, Wall Street Journal, Los Angeles Times, and other prominent news outlets around the world granted an abnormally high level of media coverage to scientific news about the world’s great ice sheets. The news conveyed was not good.

Through unprecedented new images, field measurements, and modeling capabilities, we now know that Greenland and Antarctica, remote as they are, have already begun the process of redefining the world’s coastlines. More than a billion people—and untold impacts to economies, ecosystems, and cultural legacies—will be altered, displaced or lost in the coming generations.

Five studies in particular commanded especial attention. One showed that the floating ice shelves ringing Antarctica (which do not affect sea level directly, but do prevent billions of tons of glacier ice from sliding off the continent into the ocean) are thinning, their bulwarking ability compromised. Another found pervasive blue meltwater rivers gushing across the ice surface of Greenland through the use of drones, satellites, and extreme field work. A major NASA program (called “Oceans Melting Glaciers” or OMG) showed that the world’s warming oceans—which thus far have absorbed most of the heat from rising global greenhouse gas emissions—are now melting the big ice sheets from below, at the undersides of marine-terminating glaciers. A fourth study used historical air photographs to map the scars of 20^th century deglaciation around the edges of the Greenland ice sheet, showing that its pace of volume loss has accelerated. A fifth, very long time-horizon study used advanced computer modeling to posit that the massive Antarctic ice sheet may even disappear completely in coming millennia, should we choose to burn all known fossil fuel reserves.

That last scenario is extreme. But should we choose to bring it to reality, the world’s oceans would rise an additional 200 feet. To put 200 feet of sea level rise into perspective, the entire Atlantic seaboard, Florida, and Gulf Coast would vanish from the United States, and the hills of Los Angeles and San Francisco would become scattered islands. Even five or ten feet of sea level rise would change or imperil the existence of coastal populations as we currently know them. Included among these are major cities like New York, Newark, Miami, and New Orleans in the USA; Mumbai and Calcutta in India; Guangzhou, Guangdong, Shanghai, Shenzen, and Tianjin in China; Tokyo, Osaka, Kobe, and Nagoya in Japan; Alexandria in Egypt; Hai Phòng and Ho Chi Minh City in Vietnam; Bangkok in Thailand; Dhaka in Bangladesh; Abidjan in Côte d'Ivoire, Lagos in Nigeria, and Amsterdam and Rotterdam in The Netherlands. The risk is not simply of rising water levels, but also the enhanced reach of storm surges (as illustrated by the hurricane Katrina and superstorm Sandy); and of private capital and governments ceasing to provide insurance coverage for flood-vulnerable areas.

Viewed collectively, these studies and others like them, tell us four things that are interesting and important.

The first is that ice sheets are leaky, meaning it seems unlikely that increased surface melting from climate warming can be countered by significant retention or refreezing of water within the ice mass itself.

The second is that the pace of global sea level rise, which has already nearly doubled over the past two decades (and currently rising approximately 3.2 mm/year, on average), is clearly linked to the shrinking ice volumes of ice sheets.

The third is that warming oceans represent a hitherto unappreciated feedback to sliding ice.

The fourth is that the process of ice-triggered sea level rise is not only ongoing, but accelerating. Many glaciologists now fear that earlier estimates of projected sea level rise (about 1 foot if we act aggressively now to curb emissions, about 3.2 feet if we do not) by the end of this century.

Sea level rise is real, it’s happening now, and is here to stay. Only its final magnitude remains for us to decide. 

In 2015, we crossed the threshold of the first million people who had their genomes sequenced. Beyond that, based on the fast pace of progress in sequencing technology, it is projected that we’ll hit 1 billion people sequenced by 2025. That seems formidable, but quite likely given that the velocity of DNA reading innovation has exceeded Moore’s Law. However, the big problem we have is not amassing billions of people’s genome sequences. It is how to understand the significance of each of the 6 billion letters that comprise a human genome.

About 98.5% of our genome is not made of genes, so it doesn’t directly code for proteins. But most of this non-coding portion of the genome influences, in one way or another, how genes function. While it’s relatively straightforward to understand the tiny portion of the genome—genes—that code for proteins, the non-coding elements are far more elusive.

So the biggest breakthrough in genomics—Science Magazine’s 2015 Breakthrough of the Year—is the ability to edit a genome via so-called CRISPR technology with remarkable precision and efficiency. While we’ve had genome editing technologies for several years, including zinc finger nucleases and TALENS, they were not straightforward to use or could achieve a high rate of successful editing in the cells that were exposed. The precision problem also extended to the need to avoid editing in unintended portions of the genome, so called off-target effects. Enter CRISPR and everything has quickly changed.

Many genome editing clinical trials are now underway or will soon be to treat medical conditions for which treatment or a cure has proven remarkably challenging. These include sickle cell disease, thalassemia, hemophilia, HIV, and some very rare metabolic diseases. Indeed, the first person whose life was saved was a young girl with leukemia who had failed all therapies attempted until she had her T cells genome edited (using TALENS) with a very successful response. George Church and his colleagues at Harvard were able to edit 62 genes of the pig’s genome to make it immunologically inert, such that the whole idea of transplanting an animal’s organ into humans—xenotransplantation—has been resurrected. A number of biotech and pharma companies (Vertex, Bayer, Celgene and Novartis), have recently partnered with the editing company startups (CRISPR Therapeutics, Editas Medicine, Intellia Therapeutics, Caribou Biosciences) to rev up clinical programs.

But the biggest contribution of genome editing, and specifically with CRISPR, is to catapult the field of functional genomics forward. Not understanding the biology of the DNA letters is the biggest limitation of our knowledge base in the field. So many interesting DNA sequence variant “hits” have been discovered but overshadowed by uncertainty. Determining functional effects of the VUS—variants of unknown significance—has moved as a very sluggish pace, with too much of our understanding of genomics based on population studies rather than on pinpointing the biology and potential change in function due to an altered (compared with the reference genome) DNA letter.

Now we’ve recently seen how we can systematically delete genes to find out which are essential for life. From that we learned that only about 1600 (8%) of the nearly 19,000 human genes are truly essential. All of the known genes implicated in causing or contributing to cancer can be edited, and indeed that systematic assessment is well underway. We have just learned how important the 3-D structure of DNA is for cancer vulnerability by using CRISPR to edit out a particular genomic domain. What’s more is that we can now generate a person’s cells of interest (from their blood cells, via induced pluripotent stem cells)—be make heart, liver, brain, or whatever the organ/tissue of interest. When this is combined with CRISPR editing, it becomes a remarkably powerful tool that takes functional genomics to an unprecedented level.

What once was considered the “dark matter” of the genome is about to get illuminated. The greatest contribution of genome editing will ultimately be to understand the 6 billion letters that comprise our genome.

In 2010, in England alone, it was estimated that mental illness cost over £100 billion to the economy. Around the same time, the cost in the US was estimated at $318 billion annually. It is important that we do what we can to reduce this burden. However, we have mostly been going about it the wrong way because the predominant models of mental illness do not work. They are mostly based on the assumption that there are discrete underlying causes, but this approach to mental illness reflects an essentialist bias that we readily apply when trying to understand complexity.

It seems trite to point out that humans are complex biological systems and that the way we operate requires sophisticated interactions at many different levels. It is even more remarkable then, that it has taken over 100 years of research and effort to finally recognize that when things break down, they involve multiple systems of failure and yet, until the last couple of years, many practitioners in the psychiatric industry of Western culture have been reluctant to abandon the notion that there are qualitatively distinct mental disorders that have core causal dysfunctions. Or at least that’s how the treatment regimes seem to have been applied.

Ever since Emil Kraepelin at the end of the 19th century advocated that mental illnesses could be categorized into distinct disorders with specific biological causes, research and treatment has focused efforts on building classification systems of symptoms as a way of mapping the terrain for discovering the root biological problem and corresponding course of action. This medical model approach led to development of clinical nosology and the accompanying diagnostic manuals such as the Diagnostic and Statistical Manual of Mental Disorder (DSM)—the most recent fifth version published in 2013. However, that very same year, the National Institute of Mental Health announced that it would no longer be funding research projects that relied solely on the DSM criteria. This is because the medical model lacks validity.

A recent analysis by Denny Borsboom in the Netherlands revealed that 50 percent of the symptoms of the DSM are correlated, indicating that comorbidity is the rule, not the exception, which explains why attempts to find biological markers for mental illness either through genetics or imaging have proved largely fruitless. It does not matter how much better we build our scanners, or refine our genetic profiling, as mental illness will not be reducible to Kraepelin’s vision. Rather, new approaches consider the way symptoms have causal effects between them rather than arising from an underlying primary latent variable.

Approaches to mental illness are changing. It is not clear what will happen to the DSM as there are vested financial interests in maintaining the medical model, but in Europe there is a notable shift towards symptom-based approaches of treatment. It is also not in our nature to consider the complexity of humans other than with essentialist biases. We do this for race, age, gender, political persuasion, intelligence, humor and just about every dimension we use to describe someone—as if these attributes are at the core of who they are.

The nature of the human mind is to categorize the world; to carve Nature up at its joints as it were, but in reality, experience is continuous. Moreover, the boundaries we create are more for our benefit than as a reflection of any true structures that exist. As complex biological systems, we evolved to navigate the complex world around us and thus developed the capacity to represent it in the most useful way as discrete categories. This is a fundamental feature of our nervous system from the input of raw sensory signals to the output of behavior and cognition. Forcing Nature into discrete categories optimizes the processing demands and the number of responses that need to be made, so it makes perfect sense from an engineering perspective.

Such insights are not particularly recent scientific discoveries and we should all be aware of them and yet, the essentialist perspective continues to shape the way that we go about building theories to investigate the world. Maybe it’s the best strategy when dealing with unknown terrain—assume patterns and discontinuities with broad strokes before refining your models to reflect complexity. The danger lies in assuming the frameworks you construct are real. 

On the ice-capped heights of Labrador, through winter, snow falls. With the coming of spring, much of it melts. Sometimes more falls than melts, and the ice grows; sometimes more melts than has fallen, and the ice shrinks. It is a delicate balance. The result varies from year to year, by many inches. But let the balance tip ever so slightly, so that amidst much larger fluctuations one inch on average survives, and Earth is transformed. Great glaciers grow, and cover North America in ice.

If corresponding processes in Greenland or Antarctica tip the other way, melting more than is frozen, then oceans will swell, and drown North America's coasts.

Episodes of both sorts have happened repeatedly in Earth's history, on timescales of a few tens of thousands of years. They are probably controlled by small, long-period changes in Earth's orbit. Today we are living in a relatively rare interglacial period, expected to last another fifty thousand years. Notoriously, over the last few decades human activity has tipped the balance toward melting, threatening catastrophe.

These mighty stories derive from systematic trends that can be hard to discern within the tumult of much larger, but ephemeral, noise. The news is not the news.

So it is with the grandest of human stories: the steady increase, powered by science, of our ability to control the physical world. Richard Feynman memorably expressed a related thought

From a long view of the history of mankind, seen from, say, ten thousand years from now, there can be little doubt that the most significant event of the 19th century will be judged as Maxwell's discovery of the laws of electrodynamics.

In that spirit, the most significant event of the 20th century is the discovery of the laws of matter in general. That discovery has three components: the frameworks of relativity and quantum mechanics, and the specific forces laws embodied in our core theory, often called the standard model. For purposes of chemistry and engineering—plausibly, for all practical purposes—we've learned what Nature has on offer.

I venture to guess that the most significant event of the 21st century will be a steady accumulation of new discoveries, based on deeper use of quantum physics, which harness the physical world. In the 21st century we will learn how to harvest energy from the Sun, and to store it efficiently. We will learn how to make much stronger, much lighter materials. We will learn how to make more powerful and more versatile illuminators, sensors, communication devices, and computers.

We know the rules. Aided by our own creations, in a virtuous cycle, we'll learn how to play the game.  

Ignaz Semmelweis changed our world when, back in 1847, he decided to start washing his hands after he performed an autopsy and before he delivered a baby. When Semmelweis worked in a Viennese obstetric hospital, the germ theory of disease and the concept of “infection” were unknown. Postpartum infections due to “childbed fever” killed a high percentage of women who gave birth in hospitals. Semmelweis knew that there was something in and around dead bodies that had the potential to cause disease, and so he decided to follow the practice of midwives and wash his before delivering a baby. Fewer mothers died, and Semmelweis knew he was onto something. During his lifetime, his innovation was rejected by fellow male physicians, but within decades, evidence from doctors and scientists in other parts of Europe soon provided incontrovertible evidence that he was right. Small organisms like bacteria caused disease, and taking simple precautions like hand washing could lower disease risk.

Thanks to Semmelweis and his intellectual descendants, we follow a range of routines from water boiling and avoiding tropical ice cubes to near-fanatical levels of hand sanitizing, in order to reduce the chances of getting sick because of the nasty bugs in our environment.

We have known for a long time that our bodies harbor lots of “normal flora,” but until about a decade ago, few people studied them. We focused on Semmelweis’s disease-causing bacteria, which we cultured on petri dishes so that we could identify and kill them. The rest of our microbial residents were thought to be pretty much harmless baggage and were ignored.

The introduction of new methods of identifying normal, diverse communities of organisms from DNA alone (including such innovations as high-throughput DNA sequencing) changed all that, and we began to come to realize the magnitude of what we had been missing. The world of critters living in and on us was soon discovered to be vast and complex one, and it mattered.

Since 2008, when the Human Microbiome Project officially started, hundreds of collaborating scientists have started to bring to light the nature and effects of the billions of bacteria that are part of our normal healthy bodies. There isn’t one human microbiome, there are many: There is a microbiome in our hair, one up our nostrils, another in our vaginas, several lavishly differentiated on the vast real estate of our skin, and a veritable treasure trove in our gut, thanks to diligent subcontractors in the esophagus, stomach, and colon.

This great menagerie undergoes changes as we age, so that some of the bacteria that were common and apparently harmless when we were young start to bother us when we’re old, and vice versa. The taxonomic diversity and census of our resident bacteria are more than just subjects of scientific curiosity; they matter greatly to our health. The normal bacteria on our skin, for instance, are essential to maintaining the integrity of the skin’s barrier functions. Many diseases, from psoriasis to obesity, inflammatory bowel disease, some cancers, and even cardiovascular disease, are associated with shifts in our microbiota.

While it’s too early to tell if the changing bacteria are the cause or the result of these problems, the discovery of robust associations between bacterial profiles and disease states opens the door for new treatments and targeted preventive measures. The body’s microbiota also affects and is affected by the body’s epigenome, the chemical factors influencing gene expression. Thus, the bugs on us and in us are controlling the normal action of genes in the cells of our bodies, and changes in the proportions or overall numbers of bacterial affect how our cells work and respond to stress.

Let’s stop thinking about our bodies as temples of sinew and cerebrum, and instead as evolving and sloshing ecosystems full of bacteria, which are regulating our health in more ways than we could ever imagine. As we learn more about our single-celled companions in the coming years, we will take probiotics for curing acute and chronic diseases, we’ll undertake affirmative action to maintain diversity of our gut microflora as we age, and we’ll receive prescriptions for increasingly narrow-spectrum antibiotics to exterminate only the nastiest of the nasties when we have a serious acute infection. Hand sanitizers and colon cleansing will probably be with us for some time, but it’s best just to get used to it now: Bugs R us. 

One morning, 3 years ago, my talented PhD student Dwaipayan Adhya (known affectionately in the lab as Deep) came into my office. He looked at me straight in the eye, and said he’d like to grow autistic and typical neurons (nerve cells) in a dish, from the earliest moment of development, to observe how the autistic neuron differs from the typical neuron, day by day. I dropped everything and listened.

Sounds like science fiction? You might imagine that to grow a brain cell in a dish the scientist would first have to pluck a neuron from a human embryo, keep it alive in a lab petri dish, and then watch it under the microscope, measuring how it grows day by day. If that’s what you’re imagining, you’re wrong. There is no way to get a neuron from a human embryo in any ethically acceptable way, for obvious reasons.

So what method was Deep planning to use, if there are no ways to study the development of the embryonic human brain in a prospective (forward) direction?

Deep told me about Shinya Yamanaka in Kyoto, who won the Nobel Prize in 2012 (along with Cambridge scientist John Gurdon) for his work on induced pluripotent stem cells or iPSC. In the lab, we call this magic. Here’s how it works.

Pluck a hair from the head of an adult, then take the follicle from that hair, and using the Yamanaka method, reverse the cell, backwards from the adult hair follicle, back into the state of a stem cell; that is, back to being an undifferentiated cell, before it specialized into becoming a hair follicle. This is not an embryonic stem cell – it is an “induced pluripotent” stem cell. Induced, because the scientist has forced the adult hair follicle (though you could use any cell in the body), by genetic reprogramming, to go back into the state of a stem cell. And pluripotent, meaning it can now be genetically programmed to become any kind of cell in the body that the scientist chooses: an eye cell, a heart cell, or a neuron. If the latter, this is referred to as “neuralizing” the iPSC.

Now you can see why we call this magic. I said to Deep, let’s do it! It seems entirely ethical, as most adults would be happy enough to donate a single hair from their head, and no animal is “sacrificed” in this kind of science, and it enables scientists to study the development of human neurons in the lab.

The importance of Yamanaka’s scientific breakthrough is that if you want to study development from the first moment of life, iPSC bypasses the need for an embryo. In addition, previously, if you wanted to understand the autistic brain, scientists would rely on post-mortem studies, where someone with autism has tragically died, and where their next of kin donate their relative’s brain to scientific research.

Brain donations are invaluable, but from a scientific perspective, post-mortem brain tissue has many limitations. For example, you may end up with a set of brains that are donated from individuals of different ages, each of whom died from different causes. Interpretation of results thus becomes difficult. A further complication is that you may know very little about the person before they died (e.g., what their IQ or personality was like) and it is too late to gather such information. Post-mortem studies are still informative, but come with a handful of caveats.

Alternatively, if you want to study the autistic brain, you can use an animal model, where for example you create a “knock out” mouse—a mouse genetically engineered to lack a particular gene that you as a scientist suspect may play a role in autism—and observe the behavior of the knock-out mouse compared to a typical (or wild-type) mouse. If the knock out mouse shows “autistic” behavior, for example being less sociable, you conclude this gene may be causing one or other of the symptoms of human autism. You can see the limitations of such animal studies immediately: how do you know that sociability in a mouse is the same thing as sociability in a human? The interpretation of results from such animal experiments is as littered with caveats as are the post-mortem studies.

Now we can see the power of adding iPSC to the scientist’s tool kit for getting answers to questions. If you want to observe the living human brain, you can study the brain from the person you are interested in, and you can gather as much information about that person as you want: IQ, personality, precise diagnosis, or anything else you want. You can even look at the effects of different drugs or molecules on the neuron, without having to do these arguably unethical drug studies on an animal.

iPSC is not without its own limitations. An iPSC may not be exactly identical to an embryonic stem cell, so the neuralized iPSC may not be exactly the same as a naturally growing neuron. All tools in the scientist’s tool kit have their limitations, but this one—to my mind—is more ethical, and a more directly relevant method to autism, than is animal research. Many labs (like ours) are testing if you get the same results from both iPSC and post-mortem studies, since this strengthens the conclusions that can be drawn.

Deep’s exciting results will be published in 2016. The combination of a break-through scientific method, in the hands of a talented young PhD student, might be just the cocktail to be a game-changer in our understanding of the causes of autism.

We are still rolling down the track created by Moore’s law, which means that news about science and technology will continue to focus on computers getting smaller, smarter, faster, and increasingly integrated into the fabric of our everyday lives—in fact, integrated into our bodies as prosthetic organs and eyes. Our cyborg selves are being created out of advances not only in computers but also in computer peripherals. This is the technology that allows computers to hear, touch, and see.

Computers are becoming better at “seeing” because of advances in optics and lenses. Manufactured lenses, in some ways better than human lenses, are getting cheap enough to put everywhere. This is why the news is filled with stories about self-driving cars, drones, and other technology that relies on having lots of cameras integrated into objects.

This is also why we live in the age of selfies and surveillance. We turn lenses on ourselves as readily as the world turns lenses on us. If once we had a private self, discrete from posing, this self has disappeared into curated images of ourselves doing stuff that provokes envy in the hearts of our less-successful “friends.” If once we walked down streets with our gaze turned outward on the world, now we walk with our eyes focused on the screens that mediate this world. At the same time, we are tracked by cameras that record our motion through public space which has become monitored space.

Lenses molded from polymers cost pennies to manufacture, and the software required to analyze images is getting increasingly smart and ubiquitous. Lenses advanced enough for microscopy now cost less than a dollar. The latest issue of Nature Photonics, reporting on work done by researchers in Edinburgh, describes cameras that use photons for taking pictures around corners and in other places that the human eye can’t see. This is why our self-driving cars will soon have lower insurance rates than the vehicles that we currently navigate around town.

The language of sight is the language of life. We get the big picture. We focus on a problem. We see—or fail to see—each other’s point of view. We have many ways of looking, and more are being created every day. With computers getting better at seeing, we need to keep pace with understanding what we’re looking at.   

If you find yourself at a cocktail party searching for a conversation starter, I’d recommend working in the opening line of a recent Bill and Melinda Gates Annual Letter: "By almost any measure, the world is better than it has ever been.” Although people will react with incredulity at the very possibility that things could be getting better, they’ll welcome the opportunity to straighten you out. Just be prepared for the inevitable recitation of the daily headlines—bad news piled on top of even worse news—that will inevitably follow. Virtually everyone I’ve mentioned this quote to is sure it¹s wrong.

For example, about two-thirds of Americans believe the number of people living in extreme poverty has doubled in the last 20 years. People point to conflicts in the Middle East as evidence of a world in chaos, the retreat of democracy, plummeting human rights, and an overall global decline of wellbeing. Yet the news from social science through the accumulation of large-scale, longitudinal datasets belies this declinist worldview.

This isn¹t the place to delve into the details of how large-scale statistical datasets, and ones increasingly representative of the world¹s population, provide a more accurate, though deeply counter-intuitive, assessment of the state of the world (for that, see Steven Pinker’s The Better Angels of our Nature).

In reality, extreme poverty has nearly halved in the last twenty years—about a billion people have escaped it. Material wellbeing—income, declines in infant mortality, increases in life expectancy, educational access (particularly for females)—has increased at its greatest pace during the last few decades. The number of democracies in developing nations has tripled since the 1980s, while the number of people killed in armed conflicts has decreased by 75%. This isn¹t the place to delve into the details of how large-scale statistical datasets, and ones increasingly representative of the world’s population, provide a more accurate, though deeply counter-intuitive, assessment of the state of the world.

Instead, I want to suggest three reasons why I think it’s such important scientific news. First, while these long-term trends may not resuscitate an old-fashioned notion of progress—certainly not one suggesting that history possesses intrinsic directionality—they do call out for a better understanding (and recognition) of the technological and cultural dynamics driving long-term patterns of historical change. What is even more intriguing to me is their stark demonstration of how deeply our cognitive and emotional biases distort our worldview. In particular, we have good evidence that we don’t remember the past as it was. Instead, we systematically edit it, typically omitting the bad and highlighting the good, leading to cognitive biases, such as “rosy retrospection.”

At the cultural level, these biases make us biologically vulnerable to declinist narratives. From Pope Francis’ anti-modernist encyclical to Capitalism¹s inevitable death by internal contradictions and tales of moral decline, declinist narratives intuitively resonate with our cognitive biases. They thus make for an easy sell and make it easy to lose sight of the fact that until a few centuries ago the world¹s population was stuck in abject poverty, a subsistence-level Malthusian trap of dreary cycles of population growth and famine.

In reality, not only has material wellbeing increased around the globe, global inequality is also decreasing as a result of technological and cultural innovations driving globalization. We should be particularly on guard against declinist narratives that also trigger our emotional biases, especially those hijacking the brain’s low-level treat detection circuits. These alarmist narratives identify an immediate or imminent threat, a harbinger of decline, which unconsciously triggers the amygdala and initiates a cascade of brain chemicals, norepinephrine, acetylcholine, dopamine, serotonin, and hormones, adrenalin and cortisol, creating both primal visceral feelings of dread and locking in our attention to that narrative, effectively shutting down rational appraisal.

Much of what counts as “news” today involves such narratives. The combination of an ever-shortening news cycle, near instantaneous communications, fragmented markets, heightened competition for viewership, and our cognitive and emotional biases conspire to make it all but inevitable that these narratives would dominate and make it prohibitive to grasp the progressive themes large-scale data analyses reveal.

The result is today’s dominant alarmist and declinist news cycle that’s essentially a random walk from moral panic to moral panic. To appreciate the real news—that by many fundamental measures the state of the world is improving—thus requires an exercise in cognitive control, inhibiting our first emotional impulses and allowing a rational appraisal of scientifically informed data. This by no means constitutes some Pollyannaish exercise of denial. But the most important scientific news to me is that the broad historical trajectory of human societies provides a powerful counter-narrative to today’s dominant declinist worldview.

The education field today is much like medicine was in the 19th century—a human practice, guided by intuition, experience, and occasionally inspiration. It took the development of modern biology and biochemistry in the early part of the 20th century to provide the solid underpinnings of today’s science of medicine.

To me—a mathematician who became interested in mathematics education in the second half of my career—it seems that we may at last be seeing the emergence of a genuine science of learning. Given the huge significance of education in human society, that would make it one of the most interesting and important of today’s science stories.

At the risk of raising the ire of many researchers, I should note that I am not basing my assessment on the rapid growth in educational neuroscience. You know, the kind of study where a subject is slid into an fMRI machine and asked to solve math puzzles. Those studies are valuable, but at the present stage, at best they provide at most tentative clues about how people learn, and little specific in terms of how to help people learn. (A good analogy would be trying to diagnose an engine fault in a car by moving a thermometer over the hood.) One day, educational neuroscience may provide a solid basis for education the way, say, the modern theory of genetics advanced medical practice. But not yet.

Rather, I think the emergence of a science of learning arises from the possibilities Internet technology brings to the familiar, experimental cognitive science approach.

The problem that has traditionally beset learning research has been its essential dependence on the individual teacher, which makes it near impossible to run the kinds of large scale, control group, intervention studies that are par-for-the-course in medicine. Classroom studies invariably end up as studies of the teacher as much as of the students, and often measure the effect of the students’ home environment rather than what goes on in the classroom.

For instance, news articles often cite the large number of successful people who as children attended a Montessori school, a figure hugely disproportionate to the relatively small number of such schools. Now, it may well be the case that the Montessori educational principles are good, but it’s also true that such schools are magnets for passionate, dedicated teachers and the pupils that attend them do so because they have parents who go out of their way to enroll their offspring in such a school, and already raise their children in a learning-rich home environment.

Internet technology offers an opportunity to carry out medical-research-like, large scale control group studies of classroom learning that can significantly mitigate the “teacher effect” and “home effect,” allowing useful studies of different educational techniques to be carried out. Provided you collect the right data, Big Data techniques can detect patterns that cut across the wide range of teacher-teacher and family-family variation, allowing useful educational conclusions to be drawn.

An important factor is that a sufficiently significant part of the actual learning is done in a digital environment, where every action can be captured. This is not easily achieved. The vast majority of educational software products operate around the edges of learning: providing the learner with information; asking questions and capturing their answers (in a machine-actionable, multiple-choice format); and handling course logistics with a learning management system.

What is missing is any insight into what is actually going on in the student’s mind—something that can be very different from what the evidence shows, as was dramatically illustrated for mathematics learning several decades ago by a study now famously referred to as “Benny’s Rules,” where a child who had aced a whole progressive battery of programmed learning cycles was found (by a lengthy, human–human working session) to have constructed an elaborate internal, rule-based “mathematics” that enabled him to pass all the tests with flying honors, but which was completely false, and bore no relation to actual mathematics.

But real-time, interactive software allows for much more than we have seen flooding out of tech hotbeds such as Silicon Valley. To date, some of the more effective uses from the viewpoint of running large-scale, comparative learning studies, have been by way of learning video games—so-called game-based learning. (It remains an open question how significant is the game element in terms of learning outcomes.)

In the case of elementary through middle school mathematics learning (the research I am familiar with), what has been discovered, by a number of teams, is that digital learning interventions of as little as ten minutes a day, over a course of as little as one month, can result in significant learning gains when measured by a standardized test—with improvements of as much as 20 percent in some key thinking skills.

That may sound like an educational magic pill. It almost certainly is not. It’s most likely an early sign that we know even less about learning than we thought we did.

For one thing, part of what is going on is that many earlier studies measured knowledge rather than thinking ability. The learning gains found in the studies I am referring to are not knowledge acquired or algorithmic procedures mastered, rather high-level problem solving ability.

What is exciting about these findings, is that in today’s information—and computation—rich environment, those very human problem-solving skills are the ones now at a premium.

Like any good science, and in particular any new science, this work has generated far more research questions than it has answered.

Indeed, it is too early to say it has answered any questions. Rather, as of now we have a scientifically sound method to conduct experiments at scale, some very suggestive early results, and a resulting long and growing list of research questions—all testable. Looks to me like we are about to see the final emergence of a genuine science of learning.

Searching for extraterrestrial intelligence (SETI) has for decades been a “fringe” endeavor. But it’s moving towards the mainstream. In 2015, it gained a big boost from the launch of Breakthrough Listen—a ten-year commitment by the Russian investor Yuri Milner to scan the sky in a far more comprehensive and sustained fashion than ever before.

It’s a gamble: even optimists rate the probability at only a few percent. And of course radio transmission is only one channel whereby aliens might reveal themselves. But the stakes are high. A manifestly artificial signal—even if we couldn’t decode it—would convey the momentous message that “intelligence” had emerged elsewhere in the cosmos.

These searches are more strongly motivated than they were in earlier decades. The Kepler Spacecraft, surely one of the most cost-effective and inspirational projects in NASA’s history, has revealed that most stars in the Galaxy are orbited by retinues of planets. There are literally billions of them in our Milky Way galaxy with the size and temperature of our Earth. 

But would these planets have developed biospheres? Or is our Earth unique, while all others are sterile and lifeless? Despite all we know about life’s evolution, its actual origin—the transition from complex molecules to the first replicating and metabolizing systems that we’d deem to be “alive”—has remained a mystery, and relegated to the “too difficult box.” But it is now being addressed by top-ranking scientists. We may soon know whether life’s emergence was a “fluke,” or whether it’s near-inevitable in the kind of “chemical soup” expected on any planet resembling the young Earth—and also whether the DNA/RNA basis of terrestrial life is highly special, or just one of several possibilities.

In seeking other biospheres, clues will surely come from high-resolution spectra, using the James Webb Space Telescope, and the next generation of 30+metre ground-based telescopes that will come on line in the 2020s.

Conjectures about advanced alien life are of course far more shaky than those about simple life. We know, at least in outline, the evolutionary steps whereby nearly 4 billion years of Darwinian evolution led to the biosphere of which we humans are a part. But billions of years lie ahead. I would argue that our remote, posthuman descendents will not be “organic” or biological; and they will not remain on the planet where their biological precursors lived. And this offers clues to the planning SETI searches.

Why is this? It’s because post-human evolution will be spearheaded by super-intelligent (and super-capable) machines. There are chemical and metabolic limits to the size and processing power of “wet” organic brains. But no such limits constrain electronic computers (still less, perhaps, quantum computers); for these, the potential for further development could be as dramatic as the evolution from monocellular organisms to humans. So, by any definition of “thinking,” the amount and intensity that’s done by organic human-type brains will be utterly swamped by the cerebrations of AI. Moreover, the Earth’s biosphere is not essential—indeed, it’s far from an optimal environment—for inorganic AI. Interplanetary space will be the preferred arena where robotic fabricators will have the grandest scope for construction, and where non-biological “brains” may develop insights as far beyond our imaginings as string theory is for a mouse.

This scenario implies that, even if life had originated only on Earth, it need not remain a trivial feature of the cosmos: humans may be closer to the beginning than to the end of a process whereby ever more complex intelligence spreads through the Galaxy. But in that case there would, of course, be no “ET” at the present time.

Suppose, however, that there are other biospheres where life began, and evolved along a similar track to what happened on Earth. Even then, it’s highly unlikely that the key stages would be synchronized. A planet where it lagged significantly behind what has happened on Earth would plainly reveal no evidence of ET. But on a planet around a star older than the Sun, life could have had a head start of a billion years—and already transitioned to the futuristic post-human scenario.

The history of human technological civilization is measured in centuries—and it may be only one or two more centuries before humans are overtaken or transcended by inorganic intelligence, which will then persist and continue to evolve for billions of years. This suggests that if we were to detect ET, it would be far more likely to be inorganic. We would be most unlikely to “catch” it in the brief sliver of time when it took organic form. A generic feature of these scenarios is that “organic” human-level intelligence is just a brief prelude before the machines take over.

It makes sense to focus searches first on Earth-like planets orbiting long-lived stars (the “look first under the lamp-post” strategy). But science fiction authors remind us that there are more exotic alternatives. In particular, the habit of referring to “alien civilizations” may be too anthropocentric—ET could be more like a single “mind.”

Breakthrough Listen will carry out the world’s deepest and broadest search for extraterrestrial technological life. The project involves using radio dishes at Green Bank and at Parkes—and hopefully others including the Arecibo Observatory—to search for non-natural radio transmissions using advanced signal processing equipment developed by a team based at UC Berkeley. Moreover, the advent of social media and citizen science will enable a global community of enthusiasts to download data and participate in this cosmic quest. 

Let’s hope that Yuri Milner’s private philanthropy will one day be supplemented by public funding, I’d guess that millions watching Star Wars would be happy if some of the tax revenues from that movie were hypothecated for SETI.

But in pursuing these searches we should remember two maxims, both oft quoted by Carl Sagan. First, “extraordinary claims require extraordinary evidence,” and second, “absence of evidence isn’t evidence of absence.”

We are facing problems from two of our great inventions: money and flushing the toilet.

We all use money, but we can be isolated from money at the same time. Without a doubt, money is one of the greatest human inventions, but it may also be one among the worst ever created.

In the present social, economic system, gold is the standard of money. Although gold is precious, and, as a standard, brings both universality and anonymity to money, it has nothing to do with anything that comes from human beings. While we can do many things with gold standard money in our modern societies, there are no significant connections between the money and ourselves. Thus, it can be hypothesized that whenever we use money, we are isolating ourselves from the world. 

Flushing the toilet—a second great invention—also has both positive and negative aspects. While it deals effectively with issues of hygiene, when we flush the toilet we are flushing our excretion into the natural environment and this leads to severe problems.

Here’s an idea which could lead us to a new kind of artistic and scientific world: Can you think of a horizon in which we can both mitigate the problems while keeping the advantages of our current money system? Imagine a scientific method of making odorless powders from our feces, and replacing money with that powder as an alternative to our current system—i.e., “feces standard money (FSM).”

Every morning we can put our powder into reactors located in our village to supply food for the microorganisms that can produce various energies such as methane and biodiesel. We can receive a certain amount of FSM in exchange for the powdered feces, and use the FSM to obtain any equivalent value within a system. Feces, like gold, is limited and precious; nobody can make more than a certain limit, and it can be converted to energy.

Furthermore, everyone can make feces every day. Whenever we produce and use FSM, it will remind us of our being and existence from the bottom line connection between the FSM and the human being. Thus, FSM has meanings from perspectives of economy and minds of the human being.

FSM can automatically become “basic income,” as long as we put feces into the reactors on a daily basis instead of continuing to flush the toilet. We don’t have to argue the feasibility of the concept of basic income with the gold standard of money. We can use both money systems without conflicts.

FSM has similar characters to the local exchange trading system (LETS) but is different in various aspects, from the origin of value (i.e., from us) and the system with it. The FSM is different from other types of credit such as mileage, coupons, and online coins, because it is directly connected to our existence, free will, and intentions as a meaningful act, of not using the flushable toilet.

The dollar has been allocated to a certain quantity of gold. Similarly, FSM can be made out of a certain amount of feces powder. Everyone can earn money from their selection of the ecological toilet, and have meaningful moments as they use the FSM by being connected to both their free will with the selection and their subsequent purchases.

Suggestions: A system with FSM can be designed with an App or other similar ways. FSM can be used along with the present currency to buy something such as gas, coffee, foods, and to pay for other enjoyable activities. For example, take the case of street performers. We can enjoy their work and don't have to pay anything. Instead, the street performer can be offered some FSM with a designed IT system. Payment may not come directly from the audience. Neither the performers nor the audience have to be subject to the present payment system whenever FSM is available. Values depending on the production of energy or other equivalent products from the feces at a designated time or date can be distributed to the participants of the system. Of course, since this system with FSM can't provide everything that we need, conventional money also has to be used.

The proposed money system requires various technologies such as biological processes for energy production—and new industries as well such as “golden electronics” (compared to white electronics) for toilets to ecologically convert feces into powder.

Theodiversity is to religion what biodiversity is to life.

There are, by some accounts, more than 10,000 religious traditions in the world. Every day, somewhere in the world, a new religious movement is in the making.

But this theodiversity—a term I borrow from Toby Lester—is not evenly distributed in human populations anymore than biodiversity is evenly distributed on the planet. The reasons for this aren’t very well understood, but the overwhelming majority of religious movements throughout history are failed social experiments. Most never take hold, and of those that do, don’t last for very long—not even for a few decades. Of those that last for a while, most stay small.

Then there are the “world religions.” Christianity, Hinduism, and Islam especially, have been growing at a brisk pace. Buddhism is much smaller and not growing much, but still a sizable presence on the world stage.

We are at a point in time when just a few religious traditions have gone global, making up the vast majority of believers in the world.

This fact is detailed in a landmark Pew Research Center report, released on April 2, 2015. It’s the most comprehensive and empirically derived set of projections based on data, age, fertility, mortality, migration, and religious conversion/de-conversion for multiple religious groups around the world. Barring unforeseen shocks, if current demographic and social trends keep up, by 2050:

• Possibly for the first time in history, there will be as many Muslims as Christians in the world. Together, these two faiths will represent more than 60 percent of the world’s projected population of 9.5 billion.
• 40 percent of Christians in the world will live in sub-Saharan Africa (the region that will have the largest share of Christians), compared to 15 percent living in Europe. This means that the epicenter of Christianity will finally shift from Europe to Africa.
• India, while maintaining a Hindu majority, will have the largest Muslim population in the world, surpassing Indonesia and Pakistan.
• All the folk religions of the world combined will comprise less than 5 percent of the world’s population.
• 1.3 billion people, or 13.5 percent of the world’s population in 2050, will be non-religious.

One might think that religious denominations that have adapted to secular modernity the best are the ones that are thriving the most. But the evidence gleaned from the Pew report and other studies points in the exactly opposing direction. Moderate denominations are falling behind in the cultural marketplace. They are the losers caught between secular modernity and the fundamentalist strains of all major world religions, which are gaining steam as a result of conversion, higher fertility rates, or both.

There are different types, shades, and intensities of disbelief. That’s why the non-religious are another big ingredient of the world’s astonishing and dynamically changing theodiversity. Combined, they would be the fourth largest “world religion.” There are the atheists, but many nonbelievers instead are apatheists, who are indifferent towards but not opposed to religions. And there is the rising demographic tide of people who see themselves as “spiritual but not religious.” This do-it-yourself, custom-made spirituality is filling the void that the retreat of organized religion is leaving behind in the secularizing countries. You can find it in yoga studios, meditation centers, the holistic health movement, and eco-spirituality.

Theodiversity once was the exclusive subject matter of the humanities. But it is now a focal point of a budding science-humanities collaboration. The religious diversification of humankind in historical time poses fascinating questions and challenges for the new science of cultural evolution. Also, these are times of renewed anxieties about real or imagined cultural conflict between religions, and between religions and secular modernity. This is why quantifiable, evidence-based, and nuanced understanding of the complexities of theodiversity are important now more than ever.

I'll try to report the news from the physics front that I think may prove to be important. When I say important I mean to someone interested in how the physical world operates. 

First of all from the experimental front there is news from the LHC—the big particle collider in Europe. There is evidence of a new particle. What a new particle means at this stage is a small bump in a data distribution. It could be real or it could be a statistical fluke, but if it is real it does represent something new. Unlike the Higgs particle it is not part of the standard model of particle physics. In fact, to my knowledge the new particle does not fit neatly into any theoretical framework, such as supersymmetry or technicolor, and its not a black hole or a graviton. So far it just seem to be an extra particle.

If it's real, not just a fluke, then there will probably be more particles uncovered, and not only new particles but new forces. Perhaps a whole new structure on top of the standard model. I don't think that at the moment anyone has a compelling idea of what it means. It is possible that it is connected to the puzzle of dark matter, i.e., the missing matter in the universe that seeded the galaxies. The new particle is not itself dark matter—it's too short lived—but other related particles could be.

From the more theoretical side the thing I find most interesting is new ideas that relate gravity, the structure of space, and quantum mechanics. For example there is gathering evidence (all theoretical) that quantum entanglement is the glue that holds space together. Without quantum entanglement space would fall apart into an amorphous unstructured unrecognizable thing.

Another idea (full disclosure: it is my idea) is that the emergence of space behind the horizons of black holes is due to the growth of quantum complexity. This is too technical to explain here except to say that it is a surprising new connection between physics and quantum-information science. It's not completely far fetched that these connections may not only teach us new things about fundamental physics problems, but also be tools for understanding the more practical issues of construction and using quantum computers. Stranger things have happened.

For most of its history our species has systematically squandered its human capital by spurning the creative potential of half its members. Higher education was withheld from women in just about every place on earth until the twentieth century, with the few who persevered before then considered “unsexed.”  It’s only been in the last few decades that the gap has so significantly closed that, at least in the U.S., more bachelor’s degrees have been earned by women than by men since 1982, and, since 2010, women have earned the majority of doctoral degrees. This recent progress only underscores the past’s wasteful neglect of human resources.

Still, the gender gap has stubbornly perpetuated itself in certain academic fields, usually identified as STEM—science, technology, engineering, and mathematics, and this is as true in Europe as in the U.S. A host of explanations have been posed as to the continued male dominance—some only in nervous, hushed voices—as well as recommendations for overcoming the gap.  If the under-representation of women in STEM isn’t the result of innate gender differences in interests and/or abilities (this last, of course, being the possibility that can only be whispered), then it’s important for us to overcome it. We’ve got enormously difficult problems to solve, both theoretical and practical, and it’s lunacy not to take advantage of all the willing and able minds that are out there.

Which is why I found an article published this year in Science by Andrei Cimpian and Sarah-Jane Leslie big news.  First of all, their data shows that the lingering gender gap shouldn’t  be framed in terms of STEM versus non-STEM. There are STEM fields—for example, neuroscience and molecular biology—that have achieved 50% parity in the number of Ph.D.’s earned by men and women in the U.S., and there are non-STEM fields—for example, music theory and composition (15.8%) and philosophy (31.4%)—where the gender gap rivals such STEM fields as physics (18.0%) computer science (18.6%) and mathematics (28.6%). So that’s the first surprise that their research delivers, that it’s not science per se that, for whatever reasons, produces stubborn gender disparity. And this finding in itself somewhat alters the relevance of the various hypotheses offered for the tenacity of the imbalance. 

The hypothesis that Leslie and Cimpian tested is one I’ve rarely seen put on the table and surely not in a testable form. They call it the FAB hypothesis—for field-specific ability beliefs. It focuses on the belief as to whether success in a particular field requires pure innate brilliance, the kind of raw intellectual power that can’t be taught and for which no amount of conscientious hard work is a substitute.  One could call it the “Good-Will-Hunting quotient,” after the 1997 movie that featured Matt Damon as a janitor at MIT who now and then, in the dead of night, pauses to put down his mop in order to effortlessly solve the difficult problems left scribbled on a blackboard. 

In order to test the FAB hypothesis, the researchers sent out queries to practitioners—professors, post-docs, and graduate students—in leading universities in the U.S, probing the extent to which the belief in innate brilliance prevailed in the field. In some fields, success was viewed as more a function of motivation and practice, while in others the Good-Will- Hunting quotient was more highly rated.

And here’s the second surprise: the strength of the FABs in a particular field predicts the percentage of women in that field more accurately than other leading hypotheses, including field-specific variation in work-life balance and reliance on skills for systematizing vs. empathizing. In other words, what Cimpian and Leslie found is that the more that success within a field was seen as a function of sheer intellectual firepower, with words such as “gifted” and “genius” not uncommon, the fewer the women. The FAB hypothesis cut cleanly across the STEM/non-STEM divide. 

Cimpian and Leslie are careful to stress that they don’t interpret their findings as indicating that the FAB hypothesis provides the sole factor behind the lingering gender gap, but simply argue that it is operative. And in follow-up studies, they also discuss informal evidence that raises the plausibility of the FAB hypothesis, including the number of fictional male geniuses inhabiting popular culture—from Sherlock Holmes to Dr. House to Will Hunting—compared to the number of female geniuses.  The stereotype of the genius is overwhelmingly male. And when, I might add, a female genius is the subject, her femaleness itself becomes the focus as much as, or even more than, her genius. If genius is an aberration, then female genius is viewed as significantly more aberrational, since it’s seen as an aberration of femaleness itself. Given such stereotypes, is it unlikely that fields that highlight innate genius would show lagging female numbers?

The authors were exclusively concerned with academic fields. But there is another area of human creativity in which words like “gifted” and “genius” are not uncommon, and that is the arts—including literature.  Here, too, cold, hard, statistics tell a story of persistent gender imbalance. For despite the great number of contemporary women writers, data compiled by VIDA, a women’s literary organization, reveal that the leading American and British literary magazines, the kind whose very attention is the criterion for distinguishing between the important figures and the others, focus their review coverage on books written by men, and commission more men than women to write about them.  Might it be that the FAB hypothesis explains this imbalance as well, highlighting Cimpian’s and Leslie’s findings that the problem is not, essentially, one of STEM vs. non-STEM, nor of mathematical vs. verbal skills? 

I realize that discussing the FAB hypothesis will be seen as small stuff compared to such big news as, say, the icecaps melting at a faster rate than anticipated. And that is why, in responding to this year’s Edge Question, I first began to write about the icecaps.  But perhaps the insignificant measure we assign to the under-estimation of the creative potential of more than half our population is itself a manifestation of the problem. And what could be a greater boon to humanity than increasing the, um, man-power of those making important contributions, not only to science but to our culture at large? 

Suppose a team of researchers discovers that people who earn $50,000 a year are happier than people who earn $30,000 a year. How might the team explain this result?

The answer depends largely on whether the team adopts a telephoto zoom lens or a wide-angle lens. A telephoto zoom lens focuses on narrower causes, like the tendency for financial stability to diminish stress hormones and improve brain functioning. A team that uses this lens will tend to focus on specific people who earn more or less money each year, and any differences in how their brains function and how they behave. In contrast, a team that adopts a wide-angle lens will focus on broader differences. Perhaps people who earn more also live in safer neighborhoods with superior infrastructure and social support. Though each team adopts a different level of analysis and arrives at a different answer, both answers can be right at the same time.

For decades and even centuries, this is largely how the social sciences have operated. Neuroscientists and psychologists have peered at individuals through zoom lenses, while economists and sociologists have peered at populations through wide-angle lenses.

The big news, of late, is that these intellectual barriers are dissolving. Scientists from different disciplines are either sharing their lenses or working separately on the same questions, and then coming together to share what they've learned. Not only is interdisciplinary collaboration on the rise, but papers with authors from different disciplines are more likely to be shared and cited by other researchers. The benefits are obvious. As the income gap example shows, interdisciplinary teams are more likely to answer the whole question, rather than focusing on just one aspect at a time. Instead of saying that people who earn more are happier because their brains work differently, an interdisciplinary team is more likely to compare the role of multiple causes in formulating its conclusion.

At the same time, researchers within disciplines are adopting new lenses. Social and cognitive psychologists, for example, have historically explored human behavior in the lab. They still do, but many prominent papers published this year also include brain imaging data (a telephoto zoom lens), and data from social media sites and large-scale economic panels (wide-angle lenses). One paper captured every word spoken within earshot of a child during the first three years of his life to examine how babies come to speak some words faster than others. A second paper showed that research grant agencies favor male over female scientists by examining the content of thousands of grant reviews. And a third analyzed the content of 47,000 tweets to quantify expressions of happiness and sadness. Each of these methods is a radical departure from traditional lab experiments, and each approaches the focal problem from an unusually broad or narrow perspective. These papers are more compelling because they present a broader solution to the problem they're investigating—and they're already tremendously influential, in part because they borrow across disciplines.

One major driver of intellectual convergence is the rise of "big data," not just in the quantity of data, but also in understanding how to use it. Psychologists and other lab researchers have begun to complement lab studies with huge, wide-angle social media and panel data analyses. Meanwhile, researchers who typically adopt a wide-angle lens have begun to complement their big data analyses with zoomed-in physiological measures, like eye-tracking and brain imaging analyses. The big news here is not just that scientists are borrowing from other disciplines, but also that their borrowing has turned over richer, broader answers to a growing range of important scientific questions. 

Can something that didn't happen be news? The scientific field could be open for this paradox if one considers that science can generate new knowledge, but it is also able to generate new questions. Can something that didn't happen be interesting and important? In order to find an answer, one needs to add a duration to the notion of news. The answer cannot be about facts happening in a particular moment in time, but it can very well be about "news that will stay news." News that has consequences.

"Big news" is news that succeeds in framing the debate, news that is often controversial. It is always interesting, and only sometimes it is important. It’s popularity doesn't mean that it is "news that will stay news," because it needs to be both interesting and important.

"News that will stay news" is different from "big news": it can be under-reported, but it will last for a long time. This means that it is probably more than news about facts; it is a story with a long lasting effect on many facts. It is a story that makes history, at least for a while. It is a narrative that guides human choices in their building the future. It is very rare to find news about the emergence of a new narrative. Newspapers are not made to do that. It is more probable to read that kind of emergence, not in the news, but between the lines of the news. It can be a story about a fact that didn't happen but is interesting and important. It can be on the order of a "black hole of the news."

Some kind of context is needed to go through this matter. While science has changed human life so much, it has also been able to evolve in the news-making field. Notions such as "climate change," "gene-editing," and "nanotechnology" have given a popular brand to a set of important research paths that otherwise would have appeared less interesting, maybe unnoticed or even misunderstood. This new ability has improved science's funding and political relevance.

But the convergence of science and communication is not enough to deal with the "great transformation" that the world is facing, which needs "aware audiences," but even more, it needs "informed citizens." The very notion of a "science based policy" needs an improvement. A quite simple definition of this notion has lead to some better informed decisions in fields such as health and education, but it is still differently understood in different political and cultural context, particularly those in which ideology and religion count a lot in the decision making process. But while many local affairs need to be decided on the basis of the different cultures, some planetary matters need a common understanding of problems and possible solutions.

The United Nations Conference on Climate Change in Paris was an example of a winning relationship between science and policy, even though it took too long to happen and it achieved too little. Politicians will always be responsible for the decision making, but urgent global problems often need a better quality of "science based policy." And it is not only a question of politicians listening more to science; it is also a question of science that is more effective in self-governing, making the news to develop more "informed citizens" and thus help decision makers in taking the best path.

“Gene-editing” provides an important case study. The U.S. National Academy of Sciences, the National Academy of Medicine, the Chinese Academy of Sciences, and the U.K.'s Royal Society recently co-hosted in Washington a summit with international experts to discuss the scientific, ethical, and governance issues associated with human gene-editing research. The idea was to call for a moratorium on using the CRISPR-Cas9 technology to edit the human genome in a permanent and heritable way.

Between the scientists calling for a moratorium there were the very inventors of the CRISPR-Cas9 technology, which has been exponentially successful because it made easy and cheap to "edit" the genome. The moratorium was to be called because unintended consequences were to be expected if using CRISPR-Cas9 for human germline editing. But the summit ended with no big decisions. The national academies opted for a continuing discussion.

The CRISPR-Cas9 summit was not an epic event. One winning argument for not making decisions was brought up by George Church, a researcher at Harvard interested in this debate because he works in the field of human gene editing: he opposed the idea of a ban on human gene editing by arguing that it would strengthen underground research, black markets, and medical tourism, suggesting that science in a globalized economy is pretty much out of control. This is the kind of story that one reads behind the lines in the news.

In fact, the debate about artificial intelligence lead by Stephen Hawking was also about science going out of control. Some discussions about robots that can take over human jobs are about science going out of control, too. Science facts and news are creating a big question mark: is science out of control? Could it be different? Could a sort of science exist that was under control?

The old way to answer was more or less the following: science is about finding out how things are; ethics or policy will serve the purpose of deciding what to do about them. That kind of answer does not help anymore, because science is very much able to change how things are. It is self-governing and, in this regard, science decides about human life, while the growing demand for a science based policy enables science to take part in the decision making process. If a scientific narrative converges with both the laissez-faire ideology and the idea of complexity, the decision making process becomes more and more difficult and the situation seems to go out of control.

Science needs to do something about this. Ethics helps individual decision making but it needs an idea about complexity. Policy takes collective decisions but it needs theories about the way the world is changing. Science is called to take part of the decision making. But how is it going to do it without losing its soul?

There cannot be a science under control. But there can be a science that knows how to empirically deal with choices and gets better at self-government. The piece of "news that will stay news," this year could be the fact that scientists were not able to decide about human gene editing: it is a story that will stay news until when an improved "science of the consequences" story is begun. This means that the scientific method is called to take into account the consequences of the research. If the decision making process is no more the field of only ethics and politics, epistemology is called to get into action.

Throughout the history of the United States, white people have been its dominant ethnic group. The exact definition of this "race" has changed over time, as successive waves of immigrants (Germans in the 18th century, Irish in the 19th, Italians and Jews in the late 19th and early 20th) worked to be included in the privileged category (as recounted, for example, in Noel Ignatiev's How the Irish Became White). Whatever "whiteness" meant, though, its predominance persisted—both statistically (as the absolute majority of the population) and culturally (as the no-asterisk default definition of American). Even today, long after the legal structure of discrimination was undone, advantages attach to white identity when seeking work, housing, education, or in any encounter with authority. Not unrelatedly, life expectancy for whites is greater than for African-Americans.

But this era of white predominance is ending.        

Not long after 2040, fewer than half of all Americans will identify as white, and the country will become a "majority-minority" nation—47 percent white, 29 percent Hispanic, 13 percent African-American, and 11 percent "other," according to U.S. Census Bureau projections. Given this demographic shift, the habits and practices of a white-dominated society cannot endure much longer.  Political, legal, cultural, and even personal relations between races and ethnic groups must be renegotiated. In fact, this inevitable process has already begun. And that's news that will stay news, now and for a long time to come. It is driving a great deal of seemingly unrelated events in disparate realms, from film criticism to epidemiology.

I'll begin with the most obvious signs. In the past two years, non-whites have succeeded as never before in changing the terms of debates that once excluded or deprecated their points of view. This has changed both formal rules of conduct (for police, for students) but also unwritten norms and expectations. Millions of Americans have recently come to accept the once fringe idea that police frequently engage in unfair conduct based on race. And many now support the removal of memorials to Confederate heroes, and their flag, from public places.

Meanwhile, campuses host vigorous debates about traditions that went largely unquestioned two or three years ago. (It is now reasonable to ask, if Princeton wouldn't name a library after Torquemada, why should it honor the fiercely racist Woodrow Wilson?) The silliness of some of these new disputes (like Oberlin students complaining that the college dining hall's Chinese food is offensive to Chinese people) shouldn't obscure the significance of the trend. We are seeing inevitable ethnic renegotiation taking place before our eyes, as what was once "harmless fun" (like naming your football team the "Redskins") is redefined as a thing no decent American should condone.

It's nice to imagine this process of political and cultural reconfiguring as a gentle and only slightly awkward conversation. But the evidence suggests that the transition will be painful and its outcome uncertain.

Ethnic identity (like religious identity, with which it is often entangled) is easy to modify over time (again, see How the Irish Became White) but difficult to abandon. This is especially true when people believe their numbers and influence are declining. In that situation, they become both more aware and concerned about ethnicity and more hostile to "outsiders." (In a paper published last year, for example, the social psychologists Maureen A. Craig and Jennifer A. Richeson found that white citizens who'd read about U.S. demographics in 2042 were more likely to agree with statements like "it would bother me if my child married someone from a different ethnic background," compared to whites who had read about 2010's white-majority demographics.)

This sentiment can feed a narrative of lost advantage even when no advantage has been lost. Though whites remain privileged members of American society, they can experience others' gains toward equality as a loss for "our side."

Hence the state of American politics in 2016 is also a part of this story-that-will-stay-a-story. The distress of white people over the loss of their predominance—a sense that "the way things were before was better"—has rewarded frankly xenophobic rhetoric, and the candidates who use it. As the journalist Evan Osnos has reported, outright white supremacists (who usually ignore two-party political races) are delighted.

We should not imagine though that this distress among some whites is written merely in rhetoric. In a recent analysis of statistics on sickness and death rates, the economists Anne Case and Angus Deaton found that middle-aged white people in the United States have been dying by suicide, drug abuse and alcohol-related causes at extraordinary rates. The historian and journalist Josh Marshall has pointed out that this effect is strongest among the people who, lacking other advantages, had the most stake in white identity: less-educated, less skilled, less affluent workers. (Other scholars have disputed details of Case and Deaton's analysis, but not its overall point.)

If the Case-Deaton statistics reflected only economic distress, then middle-aged working-class people of other ethnic groups should also be missing out on the general health improvements of the last few decades. This is not the case. Unskilled middle-aged African-Americans, for example, have lower life expectancy than equivalent whites. Yet their health measures continually improved over the time period during which those of whites stalled. 

For this reason, I think Marshall is right, and that the Case-Deaton findings signal a particularly racial distress. The mortality rates correlate with loss of privilege, unspoken predominance, a once undoubted sense that "the world is ours."

What all this suggests is that this ongoing news, over the next ten or twenty years, could turn into a grim story of inter-ethnic conflict. There is a reason those white supremacists, eager for a conflict fought on race lines, are taking a new interest in conventional politics.

Can scientists and other intellectuals do anything to help prevent this inevitable ethnic reconfiguration from being interpreted as a zero-sum conflict? I think they can.

For one thing, there is much that is not known about how the psychology and even physiology of loss of ethnic advantage. There is probably much that could be learned by systematic comparative research on societies in which relations among social groups were swiftly renegotiated, so that one group lost privilege. South Africa after the fall of apartheid is one such place; perhaps Eastern Europe during and after the fall of Communism is another.

We could also sharpen up our collective understanding of the slippery psychology of ethnic threat, with an eye toward finding methods to understand and cope with such feelings. To do that, we need to take people's perceptions about identity seriously. Happy talk about the wonders of diversity and the arc of history bending towards justice will not suffice. We need to understand how, why and when some people on this inevitable journey will experience it as a loss.

The news stories from China are horrific.  The best estimate is that on average, 4,400 people die every day from air pollution in that country. That’s 1.6 million per year.  Every time I hear of some tragedy that makes headlines, such as a landslide in Shenzhen that killed 200 people, I think to myself, “Yes — and today 4,400 people died of air pollution and it didn’t make the news.”

This is not the old eye-burning throat irritating air pollution of yesterday.  Today’s pollutant is known as PM_2.5, particulate matter 2.5 microns and smaller. It is produced by automobiles, by construction, by farm work, but the greatest contributor by far is coal, burned by industry and for electric power production. PM_2.5 wasn’t even listed as a major pollutant by the US EPA until 1997. It was present, but jut not fully proven to be as deadly as it is.

We now know that on a bad day in Beijing, such pollution hurts people as much as smoking two packs of cigarettes each day — for every man woman and child who breathes it. Bad air triggers strokes, heart attacks, asthma, and lung cancer. Look at the causes of death in China and you’ll see a remarkable excess of such deaths, despite the fact that obesity is small compared to that in the US.

We know about the health effects from some remarkable studies.  In the US we saw decreases in health problems when factories and coal plants were temporarily shut down; this is the famous “Six Cities Study.” In China, we have the Huai River Study, in which the Chinese policy of giving free coal to households north of the Huai River, but none to the south, resulted in a reduced average lifetime in the north of 5.5 years.

Also remarkable is China’s openness with their air pollution data. Every hour they post online over 1500 measurements of PM_2.5  (as well PM₁₀, SO₂, NO₂, and ozone) all across their country.  China may be a closed country in many ways, but they seem to be crying out seeking help.  At Berkeley Earth we have been downloading all these numbers for the past year and a half, and the patterns of severe pollution are now clear.  It is not confined to cities or basins, but widespread and virtually inescapable. 97% of China’s population breathes what our EPA deems as “unhealthy air “on average.

In contrast, the democracy of India reports few PM_2.5  measurements.  I suspect they have them but are simply not making them public.  They do publish results for Delhi, and virtually every time I look, the pollution there is worse than it is in Beijing.

People suggest a switch from coal to solar, but it is too expensive for China to afford. In 2015, solar power contributed less than 0.2% to their energy use, and solar plants are going bankrupt as the Chinese subsidies are withdrawn. Wind is expanding, but its intermittency is a big problem, and the use of energy storage drives up cost.  Hydro is hardly an environmental choice; the 3-Gorges Dam displaced 1.2 million people (voluntarily, the Chinese tell us) and destroyed 13 cities, 140 towns, and 1350 villages. Their new Mekong River dam is expected to wreak havoc throughout Myanmar, Thailand and Viet Nam. 

The best hopes consist of natural gas, which China has in abundance, and nuclear power, which is under rapid development.  PM_2.5 from natural gas is reduced by 1/400 compared to coal — and it reduces greenhouse emissions by a factor of 2 to 3. China is desperately attempting to extract its shale gas, but is doing miserably; the only true master of that technology is the US, where it has triggered an enormous and unexpected drop in the price of both natural as and oil. Nuclear, once despised by the environmentalists, is gaining traction in the US, with many past opponents recognizing that even in the US it offers a way to reduce carbon emissions significantly.  China is surging ahead in nuclear, with 32 new plants planned. Although such plants have a reputation of being expensive, the Chinese know that the high cost is only in the capital cost; that amortized over 25 years, nuclear is as cheap as coal, and much cheaper when you add in the environmental costs.

Air pollution is going to be a growing story in the future. China also has plans, on paper, to double its coal use in the next 15 years. They will cancel those if they can, but they also worry that slower economic growth could threaten their form of government.  As bad as the pollution has been so far, I worry that we ain’t seen nothing yet.

The United States is sharing its nuclear technology, and I expect that in two decades China will be the principle manufacturer of nuclear power plants around the world. But we need to set a better example; we need to show the world that we consider nuclear to be safe.  And we need to share our shale gas technology far more extensively.  Too often we read the pollution headlines, shake our heads, perhaps feel a little schadenfreude towards our greatest economic adversary, and then we forget about it.

Some day global warming may become the primarily threat. But it is air pollution that is killing people now.  Air pollution is the greatest environmental disaster in the world today.

Cancer is often described as a sped-up version of Darwinian evolution. Through a series of advantageous mutations, the tumor—this hopeful monster—becomes fitter and fitter within the ecosystem of your body. Some of the mutations are inherited while others are environmental—the result of a confusion of outside influences. Much less talked about is a third category: the mutations that arise spontaneously from the random copying errors occurring every time a cell divides.

In a paper this year in Science, Cristian Tomasetti and Bert Vogelstein calculated that two-thirds of the overall risk of cancer may come from these errors—entropic "bad luck." The paper set off a storm of outrage among environmentalists and public health officials, many of whom seem to have misunderstood the work or deliberately misrepresented it. And a rival model has since been published in Nature claiming to show that, to the contrary, as much as 90 percent of cancer is environmentally caused. That to me is the least plausible of these dueling reports. As epidemiology marches on, the link between cancer and carcinogen seems ever fuzzier. The powerful and unambiguous link between smoking and lung cancer almost seems like a fluke.

It will be interesting to see how this plays out. But meanwhile I hope that more of the public is beginning to understand that getting cancer usually doesn't mean you did something wrong or that something bad was done to you. Some cancer can be prevented and some can be successfully treated. But for multicellular creatures living in an entropic world, a threshold amount of cancer is probably inevitable.

“Then the Lord God formed the man of dust from the ground and breathed into his nostrils the breath of life, and the man became a living creature.” –Genesis 2:7

We humans have always been convinced of our own specialness, certain that we sit at the center of the universe. Not long ago, people uniformly thought themselves to be God’s favorite creation, placed on a newly created Earth, which was orbited by all other celestial bodies. We believed that humans were fundamentally different from other animals, and possessed intelligence that could never be duplicated. These ideas made us feel comfortable and safe, and so were easy to believe. Unfortunately, they were wrong.

Copernicus and Galileo revealed that the Sun—not the Earth—lay at the center of the solar system, Charles Lyell revealed that the Earth was much older than previously thought, and Darwin revealed that humans were not fundamentally different from other animals. Each of these scientific discoveries—especially evolution—are interesting because they challenge the presumed specialness of humans.

Of course, even if people are just apes with large frontal cortices, at least we can claim humans are part of a very special club: that of living creatures. We can marvel at the beauty of life, at the diversity of plants, and animals, and insects, and bacteria. Unfortunately, one recent—and very interesting—theory undermines the specialness of all life.

The MIT physicist Jeremy England has suggested that life is merely an inevitable consequence of thermodynamics. He argues that living systems are simply the best way of dissipating energy from an external energy source; bacteria, beetles and humans are just the most efficient way to use up sunlight. According to England, the process of entropy means that molecules that sit long enough under a heat lamp will eventually structure themselves to metabolize, move, and self-replicate—i.e., to become alive.

Granted, this process might take billions of years, but—in this view—living creatures are little different from other physical structures that move and replicate with the addition of energy, such as vortices in flowing water (driven by gravity) and sand dunes in the desert (driven by wind).

Not only does England’s theory blur the line between the living and the non-living, it also further undermines the specialness of humanity. It suggests that if humans are especially good at something, it is merely using up energy—something we seem to do with great gusto. This kind of uniqueness hardly warms our hearts, but questioning the specialness of humanity is exactly what makes this science interesting. 

At a time when groundbreaking discoveries seem almost commonplace, it is difficult to predict which scientific news is important enough to "stay news" for longer than a few days. To stick around, it would have to potentially redefine "who and what we are." One of the recent scientific advancements that, in my mind, fulfills these prerequisites is decoding and reprogramming DNA via bioinformatics.

While mapping the complete human genome was itself a great achievement, it was bioinformatics that allowed for a practical application of the acquired knowledge. Uploading a genome onto a computer has enabled researchers to use genetic markers and DNA amplification technologies in ways that shed real light on the intricate, otherwise unfathomable gene-environment interactions causing disease.

Researchers also hope to use bioinformatics to solve real-life problems; imagine microbes "programmed" to generate inexpensive energy, clean water, fertilizer, drugs, and food, or tackle global warming by sucking carbon dioxide from the air.

But like most things in life, there are also possible negative side effects. With DNA being written like software, cloning and "designing" more complex living creatures, including humans, no longer seems a mere fantasy from Sci-Fi movies. All possible advantages aside, it is likely to stir a wide range of ethical debates, requiring us to ponder what it means to be human: a "naturally" conceived, unique, and largely imperfect creature, or a pre-designed, aimed-to-be-perfect being.

Asked about the future of DNA coding and bioinformatics, Craig Venter replied, "We’re only limited by our imagination." I am somewhat more skeptical than this, but one thing is for sure: digital DNA is here to stay in scientific news about evolutionary biology, forensic science, and medicine, and also in debates about the way we, humans, define ourselves.

"Welcome, our new robot overlords," I will say when they arrive. As I sit here nursing a coffee, watching the snow fall outside, I daydream about the coming robot revolution. The number of news articles about robotics and AI are growing at an exponential rate, indicating that superintelligent machines will arise in a very short time period. Perhaps in 2017.

As a roboticist myself, I hope to contribute to this phase change in the history of life on Earth. The human species has recently painted itself into a corner and—global climate conferences and nuclear non-proliferation treaties notwithstanding—seems unlikely to find a way out with biological smarts alone: We’re going to need help. And the growing number of known Earth-like yet silent planets indicates that we can’t rely on alien help anytime soon. We’re going to need homegrown help. Machine help.

There is much that superintelligent machines could help us with.

Very, very slowly, some individuals in some human societies have been enlarging their circles of empathy: human rights, animal cruelty, and microaggressions are recent inventions. Taken together, they indicate that we are increasingly able to place ourselves in others’ shoes. We are able to feel what it would be like to be the target of hostility or violence. Perhaps machines will help us widen these circles. My intelligent pan may suggest sautéed veggies over the bloody steak I’m about to drop into it. A smartphone might detect cyberbullying in a photo I’m about to upload and suggest that I think about how that might make the person in the photo feel. Better yet, we could imbue machines with the goal of self preservation, mirror neurons to mentally simulate how others’ actions may endanger their own continued existence, and the ability to invert those thought processes so that they can realize how their own actions threaten the existence of others. Such machines would then develop empathy on their own. Then, driven by sympathy, they would feel compelled to teach us how to strengthen our own abilities in that regard. In short: future machines may empathize about humans’ limited powers of empathy.

The same neural machinery that enables us (if we so choose) to imagine the emotional or physical pain suffered by another also allows us to predict how our current choices will influence our future selves. This is known as prospection. But humans are also lazy; we make choices now that we come to regret later. (I’m guilty of that right now: rather than actually building our future robot overlords, I’m daydreaming about them instead.) Machines could help us here too. Imagine neural implants that can directly stimulate the pain and pleasure centers of the brain. Such a device could make you feel sick before your first bite into that bacon cheeseburger rather than after you’ve finished it. A passive aggressive comment to a colleague or loved one would result in an immediate fillip to the inside of the skull.

In the same way that machines could help us maximize our powers of empathy and prospection, they could also help us minimize our agency attribution tendencies. If you’re a furry little creature running through the forest and you see a leaf shaking near your path, it’s safer to attribute agency to the leaf’s motion than to not: Better to believe there’s a predator hiding behind the leaf than to just attribute its motion to wind. Such paranoia stands you in good Darwinian stead compared to another creature who thinks "wind" and is eaten by an actual predator. It is possible that such paranoid creatures evolved into religious humans who saw imaginary predators (i.e. gods) behind every thunderstorm and stubbed toe. But religion leads to religious wars and leaders who announce: "God made me do it." Such defenses don’t hold up well in modern, humanist societies. Perhaps machines could help us correctly interpret the causes of each and every sling and arrow of outrageous fortune that we experience in our daily lives. Did I miss my bus because I’m being punished for the fact that I didn’t call my sister yesterday? My web-enabled glasses immediately flick on to show me that bus schedules have become more erratic due to this year’s cut to my city’s public transportation budget. I relax as I start walking to the subway: it’s not my fault.

What a wonderful world it could be. But how to get there? How would the machines teach empathy, prospection, and correct agency attribution? Most likely, they would overhaul our education system. The traditional classroom setting would finally be demolished so that humans could be taught solely in the school of hard knocks: machines would engineer everyday situations (both positive and negative) from which we would draw the right conclusions. But this would take a lot of time and effort. Perhaps the machines would realize that rather than expose every human to every valuable life lesson, they could distil down a few important ones into videos or even text:

The plight of the underdog. She who bullies is eventually bullied herself. There’s just us. Do to others what… Perhaps these videos and texts could be turned into stories rather than delivered as dry treatises on morality. Perhaps they could be broken into small bite-sized chunks, provided on a daily basis. Perhaps instead of hypothetical scenarios, life lessons could be drawn from real plights suffered by real people and animals each day. Perhaps they could be broadcast at a particular time—say, 6pm and 11pm—on particular television channels, or whatever the equivalent venue is in future.

The stories would have to be changed each day to keep things fresh. They would have to be "new." And, of course, there should be many of them, drawn from all cultures, all walks of life, all kinds of people and animals, told from all kinds of angles to help different people empathize, prospect, and impute causes to effects at their own pace and in their own way. So, not "new" then, but "news."

Having long been interested in the probability that cyber-intelligence will soon replace humanity, I could cite frequent news coverage of efforts to produce advanced artificial intelligence as the most important news. But that’s a rather obvious subject, so I won’t.

Instead, I will discuss a much more obscure science news item that has the potential to be of great long-term import. It’s how some privately funded, commercial fusion power projects are being initiated. The intent is to, in the near future, produce the unlimited cheap power that government-backed projects have failed to deliver. The obvious implication is that fusion power could solve the global energy crisis and climate change, but I won’t discuss those items either.

What very few recognize is how the fusion news is tied to a much more prominent story. A major Pew analysis released this year projects a rise in theism in many developing nations in coming decades. This followed a major Pew survey showing a rapid rise of nontheism at the expense of religion in the United States. This has contributed to a common opinion that while religion has been and is continuing to sink in the western democracies, it’s making a comeback in less stable and prosperous nations in a historical rebuff to modernity. The resulting reactionary theism is often adopting a virulent form that afflicts the secular democracies and threatens the future of modern civilization.

What does the news on fusion power have to do with the news of the reactionary religion we’re having to put up with these 21^st century days? To begin to see the connection we will start with Arthur C. Clarke.

The SciFi Channel just presented their version of Clarke’s classic novel Childhood’s End. Written in the early 1950s, CE is like many of Clarke’s futurist fictional works in which he repeatedly predicted that in the late 1900s and into the 2000s the world community would become increasingly secular, progressive, and pacific, forming a modernist planetary demi-utopia. This in turn rested on a science-based hope. The technologist Clarke presumed that, like fission power becoming practical in the mid 1900s, fusion energy was a readily solvable science and engineering problem, and that hydrogen to helium reactors would be providing all peoples on our orb all the power they could use by the coming turn of the century. The resulting universal prosperity would elevate all into, at least, the secure, middle class affluence that studies show result in strongly atheistic, liberal, lower violence societies at the expense of often dysfunctional, tribalistic religion.

That has not happened. Fission is easy to achieve at normal surface conditions—so easy that when uranium was more highly enriched back in the Precambrian, reactors spontaneously formed in uranium ores. Sustained fusion thermonuclear reactions so far occur only in the extreme pressure-temperature conditions at the centers of stars, and getting them to work elsewhere has proven extremely difficult. Lacking fusion reactors, we have had to continue rely mainly on fossil fuels that are largely located in regions of ill repute.

Had fusion power come online decades ago, the Saudis would not have had loads of oil-generated cash to fund the virulent Wahhabist mosques and schools around much of the world that have helped spread hyper violent forms of Islam. Lacking cheap fusion power, much of the world remains mired in the lack of economic opportunity that breeds supernaturalistic extremism. Since the end of the Cold War dramatically reduced mass lethal violence from atheistic communists, a few million have died in war level conflicts that share a strong religious component. Muslims are causing the most trouble. But so are Christians in sub-Saharan Africa, as well as Russia, where the Orthodox Church backs Putin. Even the Buddhism Clarke had long seen as peaceful has gone noxious in pasts of Asia, as have many Hindus in India.

But as bad as the situation is, it is not as bad as it may seem. The Pew projections are based on a set of very dubious assumptions, including that the faith people are born into is the most critical factor in predicting future patterns because the pious tend to reproduce more rapidly than the seculars. But the actual trends measured by the World Values Survey and by REDC indicate that religiosity is declining in most of the world. That’s because casual conversion from theism to secularism is trumping reproduction, and that in turn is because the global middle class is on the rise, leading to mass organic conversion away from religion—note that religion is not a big problem in South America or most of eastern Asia because secularism is waxing in those regions.

So why has a portion of modern religion become so venomous? In part, it’s a classic counter reaction to the success of secularization. But as troublesome as they often are, such reactionary movements tend to be temporary—remember how at the turn of the century gay-bashing was a major sociopolitical tool of the American right? Toxic theism is a symptom of a power hungry world.

Clarke may well have been right that fusion power production would have helped produce a much better 21^st century world. Where he was way overoptimistic was in thinking that fusion reactors would be up and running decades ago. Clarke lived long enough to be distressed when his power dream was not coming to pass, and the unpleasant social consequences were becoming all too clear. Whether efficient hydrogen fusing plants can be made practical in the near future is very open to question, and even if they can we will have had to put up with decades of brutal strife fueled by too much religion.

That’s big news. But the even more important news that hardly any know is that modernity is winning as theism retracts in the face of the prosperity made possible by modern science and technology. 

It now seems inevitable that the decreasing cost and the increasing resolution of brain scanning systems, accompanied by the relentless increase in power of computers, will take us soon to the point where our own thinking might be visible, downloadable and open to the world in new ways.

It was the news that brain scanners are starting to be developed at consumer price levels that has obsessed me this last year.

Through the work of Mary Lou Jepsen, I was introduced to the potential of brain reading devices and that patterns generated while watching a succession of very varied videos would provide the fundamental elements to connect thought to image. A starting point was the work pioneered at Jack Gallant’s Lab at UC Berkeley in 2011 that proved that the patterns of brain activity from MRI scanners, when a subject was viewing an assortment of videos, would enable thoughts to be translated into digital images.

Recording more and more images and corresponding brain patterns boosts the vocabulary in the individual’s visual dictionary of thought. Accuracy greatly increases with the quantity and quality of data and of the decoding algorithms. Jepsen has persuaded me that this is realisable within a decade, within the cost points of consumer electronics, and in a form that appeals to non-techies. Laborious techniques and huge, power-hungry, multi-million-dollar systems based on magnetic fields will be succeeded by optical techniques where the advantages of consumer electronics can really assert themselves; the power of AI algorithms will do the rest. This science-fiction future is not only realisable, but because of enormous potential benefits, will inevitably be realised.

And so, here we are: our thoughts themselves are about to take a leap out of our heads: from our brains to computers, to the Internet and to the world. We are entering the Age of Visible (and Audible) Thought. This will surely affect human life as deeply as any technology our imagination has yet devised or any evolutionary advance.

The essence of who we are is contained in our thoughts and memories, which are about to be opened like tin cans and poured onto a sleeping world. Inexpensive scanners would enable all of us to display our own thoughts and access those of others who do the same. The consequences and ethics of this have barely been considered.

I imagine the pioneers of this research enjoying a heady Oppenheimer cocktail of anticipation and foreboding, of exhilaration and dread, of knowing what fundamental changes and dangers these inventions could create. Our task is to assure they do not feel alone or ignored.

One giant tech company is believed to have already backed off exploring the development of brain reading for Visual Thought, apparently for fear of potentially negative repercussions and controversy around privacy. The emergence of this suite of technologies will have enormous impact on the everyday ways we live and interact and can clearly transform, positively and negatively, our relationships, aspirations, work, creativity, techniques for extracting information.

Those not comfortable swimming in these transparent waters are not going to flourish. Perhaps we will need to create “swimming lessons” to teach us how to be comfortable being open, honest and exposed—that we can be ready to float and navigate in these waters of visible thought.

What else happens in a World of Visible Thought?

One major difference is that as thought becomes closer and closer to action, with shorter feedback loops accelerating change, time scales collapse and the cosy security blanket of a familiar slowness evaporates.

A journey for my grandfather from London to New York shrank from a perilous three weeks to a luxurious three hours for my generation in Concorde. Similarly, plugging thought directly into the material world will all but eliminate the comfort of time lag. If I look outside at the streets, the buildings, the cars, I am just looking at thought turned into matter, the idea in its material form. With 3D printing and robotics, that entire process can become nearly instantaneous.

The last year has witnessed robots building bridges and houses, but these currently work from 3D blueprints. Soon, we will be able to plug in the architect directly and with a little bit of fine tuning, see her latest thoughts printed and assembled into a building that same day. The same goes for film and for music and every other creative process. Barriers between imagination and reality are about to burst open. Do we ignore it or do we get into boat building like Noah? Here comes the flood. ...

When I worked as a journalist at the science desk of the New York Times, our editors were constantly asking us to propose story ideas that were new, important, and compelling. The potential topics in science news are countless, from genetics to quantum physics. But if I were at the Times today, I’d pitch three science stories, all of which are currently under the collective radar, and each of which continue to unfold and will have continued—and mounting—significance for our lives in years ahead.

For one: Epigenetics. Once the human genome was mapped, the next step has been figuring out how it works, including what turns on and off all those bits of genetic code. Here, everything from our metabolism, to our diet, to our environment and what habits we learn comes into play. A developing story here will be neuroplasticity, a case in point of epigenetics. First considered seriously a decade or so ago, neuroplasticity—the brain’s constant reshaping through repeated experiences—presents a potential for neural hacking apps. As neuroscientists like Judd Brewer at Yale and Richard Davidson at the University of Wisconsin have shown, we can choose which elements of brain function we want to strengthen through sustained mind training. Do you want to have better emotion regulation, enhance your concentration and memory, or become more compassionate? Each of these goals means strengthening distinct neural circuitry through specific, bespoke mental exercise, which might one day become a new kind of daily fitness routine.

The second: industrial ecology as a technological fix. This new discipline integrates fields ranging from physics and biochemistry to environmental science with industrial design and engineering to create a new method—life cycle assessment (or LCA)—for measuring the ecological costs of our material world. LCA gives a hard metric for how something as ubiquitous as a mobile phone impacts the environment and public health at every stage in its life cycle. This methodology gives us a fine-grained lens on how human activities degrade the global systems that support life, and points to the specific changes that would bring most benefit. Some companies now are using LCA to change the ways their products are made so that they replenish rather than deplete. As work at the Harvard School of Public Health illustrates, this means using LCA to shift away from the footprint metric, how much damage we do to the planet, to the handprint, measuring the good we do—how much we reduce our footprint. A news peg: companies are about to release the first major "net-positive products," which, analyzing their entire life cycle, replenish rather than deplete.

Finally: the inverse relationship between power and social awareness, which integrates psychology into political science and sociology. Ongoing research at the University of California at Berkeley by psychologist Dacher Keltner—and at other research centers around the world—shows that people who are higher in social power, whether through wealth, status, rank or the like, pay less attention in a face-to-face encounter to those who hold less power. Little attention means little empathy or understanding. The resulting empathy deficit means that those who wield power, such as wealthy politicians, have virtually no sense of how their decisions impact those with little power. Movements like Occupy, Black Lives Matter, and the failed Arab Spring can be read as attempts to heal this divide. This empathy deficit will drive political tensions far into the future. Unless, perhaps, those in power follow Gandhi’s dictate to consider how their decisions affect "the poorest of the poor."

In the last couple of years toddlers and even babies have begun to be able to use computers. This may seem like the sort of minor news that shows up in the "lifestyle" section of the paper and in cute you-tube videos. But it actually presages a profound change in the way human beings live.

Touch and voice interfaces have only become ubiquitous very recently—it’s hard to remember that the iPhone is only eight years old. For grown-ups, these interfaces are a small additional convenience. But they completely transform the way that young children interact with computers. For the first time, a toddler can directly control a smart phone or tablet.

And they do. Young children are fascinated by these devices and they are remarkably good at getting them to do things. In recognition of this, in 2015, the American Academy of Pediatrics issued a new report about very young children and technology. For years the Academy had recommended that children younger than two should have no access to screens at all. The new report recognizes that this recommendation has become completely impracticable. It focuses instead, sensibly, on ensuring that when young children look at screens, they do it in concert with attentive adults, and that adults supervise what children see.

But this isn’t just news for anxious parents, its important for the future of the entire human species. There is a substantial difference between the kind of learning we do as adults, or even as older children, and the kind of learning we do before we are five. For adults, learning mostly requires effort and attention; for babies, learning is ubiquitous and automatic. Grown-up brains are more "plastic" than we once thought, (neural connections can rewire) but very young brains are far more plastic—young children’s brains are designed to learn.

In the first few years of life we learn about the way the physical, biological, and psychological world work. Even though our everyday theories of the world depend on our experience, by the time we’re adults we simply take them for granted—they’re part of the unquestioned background of our lives. When technological, culturally specific knowledge is learned early it becomes part of the background too. In our culture children learn how to use numbers and letters before they are five, in rural Guatemala, they learn how to use a machete. These abilities require subtle and complicated knowledge, but it’s a kind of knowledge that adults in the culture hardly notice (though it may startle visitors from another culture).

Until now, we couldn’t assume that people would know how to use a computer in the way we assume they know how to count. Our interactions with computational systems depended on first acquiring the skills of numeracy and literacy. You couldn’t learn how a computer worked without first knowing how to use a keyboard. That ensured that people learned about computers with relatively staid and inflexible old brains. We think of millennial high-school tech whizzes as precocious "digital natives." But even they only really began to learn about computers after they’d reached puberty. And that is just the point when brain plasticity declines precipitously.

The change in interfaces means that the next generation really will be digital natives. They will be soaked in the digital world and will learn about computers the way previous generations learned language—even earlier than previous generations learned how to read and add. Just as every literate person’s brain has been reshaped by reading, my two-year-old granddaughter’s brain will be reshaped by computing.

Is this a cause for alarm or celebration? The simple answer is that we don’t know and we won’t for at least another twenty years, when today’s two-year-olds grow up. But the past history of our species should make us hopeful. After all, those powerful early learning mechanisms are exactly what allowed us to collectively accumulate the knowledge and skill we call culture. We can develop new kinds of technology as adults because we mastered the technology of the previous generation as children. From agriculture to industry, from stone tools to alphabets to printed books, we humans reshape our world, and our world reshapes our brains. Still, the emergence of a new player in this distinctively human process of cultural change is the biggest news there can be.

The biggest news story over the past quarter century—that will continue to underlie all the currents, gyres and eddies of individual sciences going forward—is the democratization of scientific knowledge. The first wave of knowledge diffusion happened centuries ago with the printing press and mass-produced books. The second wave took off after the Second World War with the spread of colleges and universities and the belief that a higher education was a necessary ingredient to being a productive citizen and cultured person. The third wave began a quarter century ago with the Third Culture: "those scientists and other thinkers in the empirical world who, through their work and expository writing, are taking the place of the traditional intellectual in rendering visible the deeper meanings of our lives, redefining who and what we are," in John Brockman’s 1991 description.

A lot has happened in twenty-five years. While some Third Culture products remain topical (AI, human genetics, and cyberspace) and others have faded from consciousness (chaos, fractals, and Gaia), the culture of science as a redefining force endures and expands into the nooks and crannies of society through ever growing avenues of communication, pulling everyone in to participate. A quarter century ago the Third Culture penetrated the public primarily through books and television; to these technologies of knowledge Third Culture apostles spread the gospel through ebooks and audio books, digital books and virtual libraries, blogs and microblogs, podcasts and videocasts, file sharing and video sharing, social networks and forums, MOOCs and remote audio and video courses, virtual classrooms and even virtual universities.

The news is not just the new technologies of knowledge, however, but the acceptance by society’s power brokers that Third Culture products are the drivers of all other cultural products—political, economic, social, and ideological—and the realization of citizens everywhere that they too can be influential agents by absorbing and even mastering scientific knowledge.           

This democratization of science changes everything because it means we have unleashed billions of minds to solve problems and create solutions. The triumphs of the physical and biological sciences in the 20th century are now being matched by those in the social and cognitive sciences because, above all else, we have come to understand that human actions more than physical or biological forces will determine the future of our species. 

In one hand you’re holding a gallon of gasoline weighing six pounds, in the other a three pound battery, now imagine them containing equal energy. Spoiler alert: they already can. The most exciting and far-reaching scientific advance is the dramatic increase in electric battery density allowing it to displace gasoline, and solving the problems of night electricity, vehicle range, and becalmed windmills.

Electric car range extends about 9 percent every year and has reached a point where one can imagine round trips that don’t involve a flatbed. But the public was startled in 2011 when a seven figure prize was claimed from Green Flight Challenge who offered it to an aircraft that could fly 200 miles under two hours with a passenger using less than one gallon of fuel. Three planes competed—two electric and one a hybrid—with only the electric planes finishing under two hours. The winner averaged 114 mph on a plug-in electric plane sans a gas engine; this was a Tom Swift fantasy five years earlier as the weight of the batteries couldn’t be lifted by the plane even if they could be crammed into fuselage. The weight and size of the battery shrunk while its energy storage increased.

Presently, our battery density peaks at about 250 watts-hours per kilogram, up dramatically from the 150 Wh/Kg a few years ago, but still far inferior to petroleum, which is 12,000 Wh/Kg or about 30x. One company is about to release a 400 Wh/Kg, up 60 percent over the previous best, but batteries under development could pass the energy density of fossil fuels within a few years.

The most exciting and counterintuitive battery invented is the lithium-air that inhales air for the oxygen needed for its chemical reaction and exhales the air when finished. This should ring a bell given the similarity to gas engines: they inhale air, add a gas mist and the expanding air creates power, but then expels an atmospheric sewer. The lithium air battery is solid-state and exhales clean air. MIT has already demonstrated a Lithium-air battery with densities of over 10,000 Wh/kg.

Batteries need not have the energy density of gasoline in order to replace it as the physics of harnessing gasoline power are lame, only 15 percent of the energy in one’s tank motors the car down the highway. The rest is lost to heat, engine and transmission weight, friction, and idling. As a practical matter, batteries in the labs are already beyond useable energy density of fossil fuels, an energy density that results in a 500 mile range for an electric car with a modest battery, probably more for a small plane.

The second dramatic change happening now is that increased battery density has lowered both the size and cost of electrical storage, creating the bridge between intermittent wind, daytime photovoltaic energy, and the round-the-clock current demands of the consumer.

 Windmills produce prodigious electricity during a good blow but bupkis when becalmed, hence the batteries provide steady current until a breeze appears. A new battery installation at Elkins, West Virginia windfarm allows the 98 megawatt turbines to be a constant part of the overall grid supply, with pollutant free electricity and the reliability of a conventional fossil fuel plant.

Also fossil fuel plants run at higher capacity than needed in case of a spike in demand, not needed with a battery backup: a new megawatt battery installation in Atacama Desert, Chile brought stability to their grid and a reduction in fuel usage.

The green revolution that has been hoped for is suddenly here, improbably due to the humble battery. A century ago there were more electric cars on the road than gasoline cars, very soon we will be back to the future. 

The big news on April 2, 2013 was the announcement of the BRAIN Initiative from the White House, whose goal is to develop innovative neurotechnology for understanding brain function. Grand challenges like this one happen once every few decades, including the announcement in 1961 of the Apollo Program to land a man on the moon, the War on Cancer in 1971, and the Human Genome Project in 1990. These were ten to fifteen year national efforts that brought together the best and the brightest to attack a problem that could only be solved on a national scale.

Why the brain? Brains are the most complex devices in the known universe and up until now our attempts to understand how brains work have fallen short. It will take a major international effort to crack the neural code. Europe weighed in earlier with the Human Brain Project and Japan later announced a Brain/MINDS project to develop a transgenic nonhuman primate model. China is also planning an ambitious brain project.

Brain disorders are common and devastating. Autism, schizophrenia, and depression destroy personal lives and create an enormous economic burden on society. The annual cost of maintaining patients in the United States with Alzheimer’s disease, a neurodegenerative disorder with no known cure, is $200 billion and climbing as our population ages. Unlike heart diseases and cancers that lead to rapid death, patients can live for decades with brain disorders. The best efforts of drug companies to develop new treatments have failed. If we don’t find a better way to treat broken brains now our children will bear a terrible burden.

A second motivation for reaching a better understanding of brains is to avert a catastrophic collapse of civilization, which is happening in the Middle East. The Internet has made it possible for terrorist groups to proliferate, and modern science has created weapons that pose existential threats ranging from nuclear weapons to genetic recombination. The most versatile weapon delivery system is the human. We need to better understand what happens in the brain of a suicidal terrorist planning to maximize destruction.

These motivations to understand the brain are based on brains behaving badly, but the ultimate scientific goal is to discover the basic principles of normal brain function. Richard Feynman once wrote: "What I cannot create, I do not understand." That is, if you can’t prove something yourself you don’t really understand it. One way to prove something is to build a device based on what you understand and see if it works. Once we have truly uncovered the principles of how the brain works we should be able to build devices with similar capabilities. This will have a profound impact on every aspect of society and the rise of artificial intelligence based on machine learning is a harbinger. Our brain is the paramount learning machine.

These are the goals of the BRAIN Initiative, but its impact may be quite different from our expectations. The goal of the Apollo Project was to send a man to the moon. Mission accomplished, but if the moon was so important why have we not gone back there? In contrast, the impact of building the technologies needed to reach the moon has been far reaching: A thriving satellite industry and advances in digital communications, microelectronics, and materials science, as well as a revamping of the curriculum in science and engineering. The War on Cancer is still being fought, but the invention of recombinant DNA technology allowed us to manipulate the genome and created the biotechnology industry. The goal of the Human Genome Project was to cure human diseases, which we now know are not easily deciphered by reading the base pairs, but the sequencing of the human genome has transformed biology and created a genomic industry that is making possible personalized, precision medicine.

The impact of the BRAIN Initiative will be the creation of neurotechnologies that match the complexity of the brain. Genetic studies have uncovered hundreds of genes that contribute to brain disorders. Drugs have not been as effective in treating brain disorders as they have for heart diseases because of the diversity of cell types in the brain and complexity of the signaling pathways. The development of new neurotechnologies will create tools that are more precisely targeted at the sources of brain disorders. Tools from molecular genetics and optogenetics are already giving us an unprecedented ability to manipulate neurons and more powerful tools are on the way from the BRAIN Initiative.

An important lesson from the history of national grand challenges is that there is no better way to invest in the future than focusing the best and brightest minds on an important problem and building the infrastructure needed to solve the problem. 

Behind every great scientific discovery is an instrument. From Galileo and his telescope to Arthur Compton and the cloud chamber, our most important discoveries are underpinned by device innovations that extend human senses and augment human cognition. This is a crucially important science news constant, because without new tools discovery would slow to a crawl. Want to predict the next big science surprise a decade from now? Look for the fastest-moving technologies in the present and ask what new tools they enable.

For the last half-century, digital technology has delivered the most powerful tools in the form of processors, networking, and sensors. Processing came first, providing the brains for space probes and the computational bulldozers needed for tackling computation-intensive research. Then with the advent of the Arpanet, the Internet, and the World Wide Web, networking became a powerful medium for accessing and sharing scientific knowledge—and connecting remotely to everything from supercomputers to telescopes.

But it is the third category—sensors, and an even-newer category of robust effectors that are poised to accelerate and utterly change research and discovery in the decades ahead.

First, we created our computers, then we networked them together, and now we are giving them sensory organs to observe—and manipulate—the physical world in the service of science. And thanks to the phenomenon described by Moore’s law, sensor cost/performance is racing ahead as rapidly as chip performance. Ask any amateur astronomer: for a few thousand dollars, they can purchase digital cameras that were beyond the reach of observatories a decade ago.

The entire genomics field owes its very existence and future to sensors. Craig Venter’s team became the first to decode the human genome in 2001 by leveraging computational power and sensor advances to create a radically new—and radically less expensive—sequencing process. Moreover, the cost of sequencing is already dropping more rapidly than the curve of Moore’s Law. Follow out the Carlson Curve (as the sequencing price/performance curve was dubbed by The Economist), and cost of sequencing a genome is likely to plummet below one dollar well before 2030. Meanwhile, the gene editing made possible by the CRISPR/Cas system is possible only because of ever more powerful and affordable sensors and effectors. Just imagine the science that is possible when sequencing a genome costs a dime and networked sequencing labs-on-a-chip are cheap enough to be tossed out and discarded like RFID tags.

Sensors and digital technology are also driving physics discovery. The heart of CERN’s Large Hadron Collider is the CMS detector, a 14,000-tonne assemblage of sensors and effectors that has been dubbed "science’s cathedral." Like a cathedral of old, it is served by nearly 4,000 people drawn from over forty countries, and it is so popular that a scientific journal just featured a color-in centerfold of the device in its year-end issue.

Sensors are also opening vast new windows on the cosmos. Thanks to the relentless advance of sensors and effectors in the form of adaptive optics, discovery of extrasolar planets moved from science fiction to commonplace with breathtaking speed. In the very near future, sensor advances will allow us to analyze exoplanetary atmospheres and look for civilizational signatures. The same trends will open new horizons for amateur astronomers, who will soon enjoy affordable technical means to match the Kepler spacecraft in planet-finding prowess. Sensors are thus as much about democratizing amateur science as the creation of ever more powerful instruments. The Kepler satellite imaged a field of 115 degrees, or a mere 0.25 percent of the sky. Planet-finding amateurs wielding digitally empowered backyard scopes could put a serious dent in the other 99.75 percent of the sky yet to be examined.

Another recent encounter between amateurs and sensors offers a powerful hint of what is to come. Once upon a time, comets were named after human discoverers, and amateurs hunted comets with such passion that more than one would-be comet hunter relocated their residence eastwards in order to get an observing jump on the competition. Now, comets have names like 285P/Linear because robotic systems are doing the discovering, and amateur comet hunting is in steep decline. Amateurs will find other things to do, (like search for planets) but it is hard not to feel a twinge of nostalgia for a lost time when that wispy apparition across the sky carried a romantic name like Hale-Bopp or Ikeya-Seki rather than C/2011-L4 PanStarrs.

This shift in cometary nomenclature hints at an even more dramatic sea change to come in the relationship between instrument and discoverer. Until now, the news has been of ever more powerful instruments created in the service of amplifying human-driven discovery. But just as machines today are better comet finders than humans, we are poised on the threshold of a time when machines do not merely amplify but displace the human researcher. When that happens, the biggest news of all will be when a machine wins a Nobel Prize alongside its human collaborators.

Human intuition is a notoriously poor guide to reality. A half-century of psychological research has shown that when people try to assess risks or predict the future, their heads are turned by stereotypes, memorable events, vivid scenarios, and moralistic narratives.

Fortunately, as the bugs in human cognition have become common knowledge, the workaround—objective data—has become more prevalent, and in many spheres of life, observers are replacing gut feelings with quantitative analysis. Sports have been revolutionized by Moneyball, policy by Nudge, punditry by 538.com, forecasting by tournaments and prediction markets, philanthropy by effective altruism, the healing arts by evidence-based medicine.

This is interesting news, and it’s scientific news because the diagnosis comes from cognitive science and the cure from data science. But the most interesting news is that the quantification of life has been extended to the biggest question of all: Have we made progress? Have the collective strivings of the human race against entropy and the nastier edges of evolution succeeded in improving the human condition?

Enlightenment thinkers thought this was possible, of course, and in Victorian times progress became a major theme of Anglo-American thought. But since then, Romantic and counter-Enlightenment pessimism have taken over large swaths of intellectual life, stoked by historical disasters such as the World Wars, and by post-1960s concerns with anthropogenic problems such as pollution and inequality. Today it’s common to read about a "faith" in progress (often a "naïve" faith), which is set against a nostalgia for a better past, an assessment of present decline, and a dread for a dystopia to come.

But the cognitive and data revolutions warn us not to base our assessment of anything on subjective impressions or cherry-picked incidents. As long as bad things haven’t vanished altogether, there will always be enough to fill the news, and people will intuit that the world is falling apart. The only way to circumvent this illusion is to plot the incidence of good and bad things over time. Most people agree that life is better than death, health better than disease, prosperity better than poverty, knowledge better than ignorance, peace better than war, safety better than violence, freedom better than coercion. That gives us a set of yardsticks by which we can measure whether progress has actually occurred.

The interesting news is that the answer is mostly "yes." I had the first inkling of this answer when quantitative historians and political scientists responded to my answer to the 2007 Edge question ("What Are You Optimistic About?") with datasets showing that the rate of homicides and war deaths had plummeted over time. Since then I have learned that progress has been tracked by the other yardsticks. Economic historians and development scholars (including Gregory Clark, Angus Deaton, Charles Kenny, and Steven Radelet) have plotted the growth of prosperity in their data-rich books, and the case has been made even more vividly in websites with innovative graphics such as Hans Rosling’s Gapminder, Max Roser’s Our World in Data, and Marian Tupy’s HumanProgress.

Among the other upward swoops are these. People are living longer and healthier lives, not just in the developed world but globally. A dozen infectious and parasitic diseases are extinct or moribund. Vastly more children are going to school and learning to read. Extreme poverty has fallen worldwide from 85 to 10 percent. Despite local setbacks, the world is more democratic than ever. Women are better educated, marrying later, earning more, and in more positions of power and influence. Racial prejudice and hate crimes have decreased since data were first recorded. The world is even getting smarter: In every country, IQ has been increasing by three points a decade.

Of course, quantified progress consists of a set of empirical findings; it is not a sign of some mystical ascent or utopian trajectory or divine grace. And so we should expect to find some spheres of life that have remained the same, gotten worse, or are altogether unquantifiable (such as the endless number of apocalypses that may be conjured in the imagination). Greenhouse gases accumulate, fresh water diminishes, species go extinct, nuclear arsenals remain.

Yet even here, quantification can change our understanding. "Ecomodernists" such as Stewart Brand, Jesse Ausubel, and Ruth DeFries have shown that many indicators of environmental health have improved over the last half-century, and that there are long-term historical processes, such as the decarbonization of energy, the dematerialization of consumption, and the minimization of farmland that can be further encouraged. Tabulators of nuclear weapons have pointed out that no such weapon has been used since Nagasaki, testing has fallen effectively to zero, proliferation has expanded the club only to nine countries (rather than thirty or more, as was predicted in the 1960s), sixteen countries have given up their programs (Iran should soon be the seventeenth), and the number of weapons (and hence the number of opportunities for thefts and accidents, and the number of obstacles to the eventual goal of zero) has been reduced by five sixths.

What makes all this important? Foremost, quantified progress is a feedback signal for adjusting what we have been doing. The gifts of progress we have enjoyed are the result of institutions and norms that have become entrenched in the last two centuries: reason, science, technology, education, expertise, democracy, regulated markets, and a moral commitment to human rights and human flourishing. As counter-Enlightenment critics have long pointed out, there is no guarantee that these developments would make us better off. Yet now we know that in fact they have left us better off. This means that for all the ways in which the world today falls short of utopia, the norms and institutions of modernity have put us on a good track. We should work on improving them further, rather than burning them down in the conviction that nothing could be worse than our current decadence and in the vague hope that something better might rise from their ashes.

Also, quantified human progress emboldens us to seek more of it. A common belief among activists is that any optimistic datum must be suppressed lest it lull people into complacency. Instead, one must keep up the heat by wailing about ongoing crises and scolding people for being insufficiently terrified. Unfortunately, this can lead to a complementary danger: fatalism. After being told that the poor might always be with us, the gods will punish our hubris, nature will rise up and avenge our despoliation, and the clock is inexorably ticking down to a midnight of nuclear holocaust and climatic catastrophe, it’s natural to conclude that resistance is futile and we should party while we can. The empowering feature of a graph is that it invites one to identify the forces that are pushing a curve up or down, and then to apply them to push it further in the same direction. 

The most important news from 2015 in fundamental physics is that probably there is no news. Let me explain. With one tantalizing exception (which may be a statistical anomaly), the experiments done recently confirm a frustratingly incomplete theory of fundamental physics, which has stood since the 1970s. This is in spite of enormous effort by thousands of experimentalists hoping to discover new phenomena that would lead to greater unification and simplification in our understanding of nature. 

Since 1973, our knowledge of elementary particles and fundamental forces has been expressed in what we call the Standard Model of Elementary Particle Physics. This reduces all phenomena, save gravity, to twelve fundamental particles interacting via three forces. This Standard Model has been confirmed in all experiments to date. This includes new measurements announced this month by two teams of experimentalists operating the Atlas and CMS detectors at the Large Hadron Collider (LHC), working at nearly twice the energy as previous experiments.

In 2012, the news from the LHC was the discovery of the Higgs, which was the last particle predicted by the Standard Model remaining to be discovered. But the Standard Model cannot be the whole story, in part because the model involves twenty-nine free parameters. We have no explanation for the values of these parameters and hence seek a deeper theory “beyond the Standard Model” that would explain them. Moreover, many of these values seem extremely unnatural: they are very tiny numbers with large ratios among them, (the hierarchy problem) and they seem to be tuned to special values needed for a universe with many stable nuclei allowing complex life to exist (the fine tuning problem). In addition, there is no reason for the choices of the fundamental particles and for the symmetries that govern the forces between them. Another reason for expecting new particles beyond the Standard Model is that we have excellent evidence from astronomy for dark matter, which gravitates but doesn’t give off light. All these pieces of evidence point to new phenomena that could have been discovered at the LHC. 

Several beautiful hypotheses have been offered on which to base a deeper unification going beyond the Standard Model. I will just give the names here: supersymmetry, technicolor, large extra dimensions, compositeness. These each imply that new particles should have been discovered at the LHC. Some also point to more exotic phenomena such as quantum black holes. To date, the experimental evidence sets impressive limits against these possibilities.

To be sure, there is one weak, but very exciting, indication from new results that might be interpreted as a signal of a new particle beyond the Standard Model. This is a small excess of collisions which produce pairs of photons that, remarkably, are seen by both of the experiments operating at the LHC. But the statistical significance is not high when the statistics is done taking into account that one is bound to get some signal by random chance in one of the many channels looked at. So it could be a random fluctuation that will go away when more data is taken. 

Even if this hint grows into the discovery of a new particle, which would be extremely exciting news, it is too soon to say whether it will lead to a deeper unification, rather than just add complication to the already complicated Standard Model. Luckily, more data can be expected soon.

It is the same in quantum gravity, which is the unification of quantum theory with Einstein’s theory of gravity. Many proposals for quantum gravity suggest that at certain extremely high energy scales we must see new physics. This would indicate that at correspondingly tiny scales space becomes discrete, or new features of quantum geometry kick in. One consequence would be that the speed of light is no longer universal—as it is in relativity theory—but would gain a dependence on energy and polarization visible at certain scales.

In the last decade this prediction has been tested by sensitive measurements of gamma rays that have traveled for billions of years from extremely energetic events called gamma ray bursts. If the speed of light depends even very slightly on energy, we would see higher energy photons arriving systematically earlier or later than lower energy photons. The enormous travel time would amplify the effect. This has been looked for by the Fermi satellite and other detectors of gamma rays and cosmic rays. No deviations from relativity theory are seen. Thus, our best hope of discovering quantum gravity physics has been frustrated.

A similar story seems to characterize cosmology. Something remarkable happened in the very early universe to produce a world vast in scale but, at the same time, extremely smooth and homogeneous. One explanation for this is inflation—a sudden enormous expansion at very early times, but there are competitors. Each of these theories requires delicate fine tuning of parameters and initial conditions. Once this tuning is done, each predicts a distribution of noisy fluctuations around the smooth universe. These show up as a seemingly random distribution of very slightly denser and less dense regions. Over hundreds of millions of years of expansion, these amplify and give rise to the galaxies.  These fluctuations make bumps that are visible in the cosmic microwave radiation. So far, their distribution is as random, featureless, and boring as possible, and the simplest theories—whether inflation or its alternatives—suffice to explain them.

In each of these domains we have sought clues from experiments into how nature goes beyond, and solves the puzzles latent in, our incomplete theories of the universe, but we have so far come up with nearly nothing.

It is beginning to seem as if nature is just unnaturally fine tuned. In my opinion we should now be seeking explanations for why this might be. Perhaps the laws of nature are not static, but have evolved through some dynamical mechanism to have the unlikely forms they are observed to have.

To me, the most interesting bit of news in the last couple of years was the sea-change in attitude among nutritional scientists from an anti-fat, pro-carbohydrate set of dietary recommendations to the promotion of a lower-carbohydrate, selectively pro-fat dietary regime. The issue is important because human health and, indeed, human lives are at stake.

For years, Americans had been told by the experts to avoid fats at all costs and at every opportunity, as if these foodstuffs were the antichrists of nutrition. A diet low in fats and rich in carbohydrates, supposedly, was the way to go in order to achieve a sleek and gazelle-like body and physiological enlightenment. In consequence, no-fat or low-fat foods became all the rage, and for a long time the only kind of yogurt you could find on grocery shelves was the jelly-like zero-fat variety, and the only available canned tuna was packed not in olive oil but in water, as if the poor creature was still swimming.

Unappetizing as much of it was, many Americans duly followed this stringent set of low-fat, high-carbo dietary dos and don’ts. But we did not thereby become a nation of fit, trim, and healthy physical specimens. Far from it. Instead, we became a nation that suffered an obesity epidemic across all age groups, a tidal wave of heart disease, and highly increased rates of Type 2 diabetes. The reason for this was that once they were digested, all those carbohydrate-rich foods got converted into glucose, which raised insulin levels and, in turn, caused storage of excess bodily fat.

Nutritional scientists thus learned the dual lesson that a diet high in carbohydrates can in fact be quite hazardous to your health, and that their alarmist fat phobia was in fact unjustified by the evidence. In reality there are good fats (such as olive oil) and bad fats, healthy carbs and unhealthy carbs (such as refined sugars). As a result, many nutritionists now favor a diametrically opposite approach, allowing certain fats as wholesome and healthy, while calling for a reduction in carbohydrates, especially refined sugars and starches.

A corollary of this about-face in dietary wisdom was the realization that much of so-called nutritional “science” was actually bad science to begin with. Many of the canonical studies of diet and nutrition were flawed by selective use of evidence, unrepresentative sampling, absence of adequate controls, and shifting clinical trial populations. Furthermore, some of the principal investigators were prone to selection bias, and were loath to confront their preconceived viewpoints with contrary evidence. (These and other failings of the discipline are exhaustively documented in journalist Nina Teicholz’s book The Big Fat Surprise [2014].)  

Unfortunately, nutritional science still remains something of a backwater. NASA’s Curiosity rover explores the plains, craters, and sand dunes of Mars, and the New Horizons spacecraft takes exquisite pictures of the former planet Pluto. Molecular biologists wield superb gene-editing tools, and are in the process of resurrecting extinct species. Nevertheless, when it comes to the relatively prosaic task of telling us what foods to put in our mouths to achieve good health and to avoid heart disease, obesity, and other ailments, dietary science still has a long way to go. 

The discovery that dinosaurs of the Velociraptor type had ample feathers and looked more like ostriches than the slick beasts we have become accustomed to from the Jurassic Park movies was my favorite scientific finding of 2015.

The specific discovery was the genus Zhenyuanlong, but it tells a larger story. Feathered dinosaurs have been coming out of the ground in China almost faster than anyone can name them since the 1990s. However, it has taken a major adjustment to allow that the feathers on these dinosaurs mean that the equivalent dinosaurs in other parts of the world had feathers as well. The conditions in China simply happen to have been uniquely well suited to preserve the feathers’ impressions. That palaeontologists now know that even the Velociraptor type had feathers is a kind of unofficial turning point. No longer can we think of feathered dinosaurs as a queer development of creatures in East Asia. We can be sure that classic dinosaurs of that body type traditionally illustrated with scaly lizard-type skins—dino fans of my vintage will recall Coelophysis, Ornitholestes, etc.—had feathers. For example, other evidence of this kind came in 2015 too, including the discovery of strikingly extensive evidence of feathers on dinosaurs long known as the "ostrich-like" sort—Ornithomimus. Little we knew how close that resemblance was.

Who really cares whether Velociraptor had feathers, one might ask. But one of the key joys of science is discovering the unexpected. One becomes a dino fan as a kid from the baseball-card collecting impulse, savoring one’s mental list or cupboard of names and types. However, since the seventies it has become clear first that birds are the dinosaurs that survived, but then, even more dramatically, that a great many dinosaurs had feathers just like birds. This shouldn’t be surprising, but it is. Dinosaurs have gone from hobby to mental workout.

Second, the feathered Velociraptor coaxes us to tease apart the viscerally attractive from the empirically sound. The truth is that the sleek versions of bipedal dinosaurs look "cool"—streamlined, shiny, reptilian in a good way. Nothing has made this clearer than the Velociraptors brought to life in the Jurassic Park films. For these creatures to instead look more like ostriches, sloshing their feathers around and looking vaguely uncomfortable, doesn’t quite square with how we are used to seeing dinosaurs. Yet that’s the way it was. The sleek-looking Velociraptor, or little "Compies" of the Jurassic Park films (Compsognathus), or any number of other dinosaurs of that general build, are now "old school" in the same way as Brontosauruses lolling around in swamps (they didn’t) and Tyrannosauruses dragging their tails on the ground.

Finally, Velociraptor as ostrich neatly reinforces for us the fact that evolution works in small steps, each of which is functional and advantageous at the time, but for reasons that can seem quite disconnected from the purpose of the current manifestation of the trait. In life in general this is a valuable lesson.

In a language that marks articles, adjectives, and nouns with an arbitrary gender like Spanish (“the white house” is la casa blanca), the gender marking helps keep it clear how the words relate to one another. But such marking originates from a division of nouns into understandable classifications as "masculine" and "feminine" (or animal, long, flat, etc., depending on the language) whose literal meanings fade over time and just leave faceless markers.

In the same way, an ostrich-sized dinosaur with feathers rather clearly wasn’t capable of soaring like an albatross, which is one of many pieces of evidence that feathers emerged as insulation and/or sexual display, and only later evolved to allow flight.

Not that dinosaurs existed to compliment the aesthetics, tastes, and nostalgic impulses of observers millions of years after their demise, but feathered dinosaurs are tough to adjust to. Yet the adjustment is worth it, as it makes dinosaurs more genuinely educational in many ways.

What has amazed and excited me the most in recent scientific news is that the concept of trust can be measured validly and reliably and that it organizes a vast amount of information about what makes families and human societies function well, or fail.

As a relationship researcher and couples-family therapist, I have known for decades that trust is the number one issue that concerns couples today. Consistent with this truth is the finding that the major trait people search for in trying to find a mate is trustworthiness. Robert Putnam’s groundbreaking book Bowling Alone began documenting this amazing field of scientific research. It is based on a very simple question. Sociologists have used a yes/no survey question: "In general, would you say that you trust people?" It turns out that regions of the USA, and countries throughout the world vary widely in the percentage of people who answer that question by saying "yes."

Here’s the amazing scientific news. In the USA the percentage of people who trust others in a region correlates highly with a vast array of positive social indices such as greater economic growth, the greater longevity of citizens, their better physical health, lower crime rates, greater voting participation, greater community involvement, more philanthropy, and higher child school achievement scores, to mention just a few variables that index the health of a community. As we move from the North to the South in the United States, the proportion of people who trust others drops continuously. A great archival index of trust turns out to be the discrepancy in income between the richest and the poorest people in a region.

High income discrepancy implies low trust. That discrepancy has been growing in the USA since the 1950s, as has the decline in community participation. For example, data show that in the 1950s CEOs earned about 25 times more than the average worker, but that ratio grew steadily so that in 2010 that ratio was about 350 times more. So we are in a crisis in the USA, and it’s no surprise that this difference between the rich and the poor has become a major issue in the 2016 election. One amazing fact in these results is the following: how well our country cares about its poorest citizens is actually a reliable index of the social and economic health of the entire country. Therefore, an empirical finding is that empathy for the poor is smart politics.

These results also hold internationally, where the trust percentage is also related to less political corruption. Only 2 percent of the people in Brazil trust one another, whereas 65 percent trust others in Norway. While many other factors are important internationally, we can note that today Brazil is experiencing vast amounts of chaos, while Norway is thriving.

These spectacular data are, unfortunately, correlational. Of course, it is hard to do real experiments on societal levels. However, these findings on trust have now spawned new growing academic fields of behavioral economics, and neuro-economics. These fields are generating exciting new experiments.

This breakthrough trust work, combined with the mathematics of Game Theory, has led to the creation of a valid "trust metric" in interactions between two people. A new understanding of the processes of how two people build or erode trust in a love relationship has spawned a new therapy that is currently being tested.

What this means to me is that we are coming very close to an understanding of human cooperation in family relationships that generalize to society as a whole. I am hopeful that these breakthroughs may eventually lead us to form a science of human peace and harmony. 

The end of 2015 coincided with the birth of Einstein’s general theory of relativity, which the great man presented to the Prussian Academy of Sciences in a series of four lectures in the midst of World War I. Widely regarded as the pinnacle of human intellectual achievement, "general relativity," as it came to be known, took many years to be well tested observationally. But today, after decades of thorough investigation, physicists have yet to find any flaw with the theory.

Nevertheless, one key test remains incomplete. Shortly after Einstein published his famous gravitational field equations, he came up with an intriguing solution of them. It describes ripples in the geometry of spacetime itself, representing waves that travel across the universe at the speed of light. The detection of these gravitational waves has been an outstanding challenge to experimental physics for several decades. Now, that long search seems to be nearing its culmination.

In the last few months, a laser system designed to pick up the passage of gravitational waves emanating from violent astronomical events has been upgraded, and rumors abound that it has already "seen something."  The system concerned, called Advanced Ligo (for Laser Interferometer Gravitational Observatory), uses laser beams to spot almost inconceivably minute gravitational effects. In Europe, its counterpart, Advanced Virgo, is also limbering up. Advanced Ligo and Advanced Virgo are refinements of existing systems that have proved the technology but lack the sensitivity to detect bursts of gravitational waves from supernovas or colliding neutron stars on a routine basis. The stage is now set to move to that phase.

The detection of gravitational waves would not merely provide a definitive test of Einstein’s century-old theory, it would serve to open up a whole new window on the universe. Existing conventional telescopes range across the entire electromagnetic spectrum, from radio to gamma rays. Ligo and Virgo would open up an entirely new spectrum and with it an entirely new branch of astronomy, enabling observations of black hole collisions and other cosmic exotica.

Each time a new piece of technology has been used to study the universe, astronomers have been surprised. Once gravitational astronomy is finally born, the exploration of the universe through gravitational eyes will undoubtedly provide newsworthy discoveries for decades to come.

Surveying the landscape of scientific and technological change, there are a number of small and relatively steady advances that have unobtrusively combined to yield something startling, almost without anyone noticing. Through a combination of computer hardware advances (Moore’s Law marching on and so forth), ever-more sophisticated algorithms for solving certain mathematical challenges, and larger amounts of data, we have gotten something new: really good weather prediction.

According to a recent paper on this topic, “Advances in numerical weather prediction represent a quiet revolution because they have resulted from a steady accumulation of scientific knowledge and technological advances over many years that, with only a few exceptions, have not been associated with the aura of fundamental physics breakthroughs.” Despite these advances seeming to be profoundly unsexy, these predictive systems have yielded enormous progress. Our skill at forecasting the weather has grown significantly over the past few decades—something that will change how we think about the enormously complex system of the weather. Forecasting ability has been increasing in accuracy by about an additional day per decade for those made several days into the future.

This is intriguing and important for a number of reasons. First, understanding weather is vital for a huge number of human activities, from transportation to improving agricultural output, to even managing disasters. Being able to foretell what the weather holds affects nearly every aspect of our lives.

But there’s a potentially bigger reason. While I am hesitant to extrapolate from the weather system to other complex systems, including many that are perhaps much more complex (such as living organisms or entire ecosystems), this development should give us some hope. The fact that weather prediction has improved through a combination of technological advancement and scientific and modeling innovations means that other problems we might think to be ever-unsolvable needn’t be this way. While we might never fully handle incredibly complicated systems, they are not completely beyond our grasp.

This news of a “quiet revolution” in weather prediction might then be a touchstone for how to think about predicting and understanding complex systems: never say never when it comes to complete intractability.

Many cosmologists now think our spatial universe is infinite. That’s news. It was only this year that I heard about it. I don’t get out as much as I used to.

Thirty years ago it was widely believed that our spatial universe is the finite 3D hypersurface of a 4D hypersphere—analogous to being the finite 2D surface of a 3D sphere. Our underlying hypersphere was supposedly born, and began expanding, at the Big Bang. And eventually our hypersphere was to run out of momentum and collapse back into a Big Crunch—which might possibly serve as the seed for a new Big Bang. No yawning void of infinity, and no real necessity for a troublesome initial point in time. Our own Big Bang itself may have been seeded by a prior Big Crunch. Indeed, we could imagine an endless pearl-string of successive hyperspherical universes. A tidy theory.

But then experimental cosmologists found ways to estimate the curvature of our space, and it seems to be flat, like an endless plane, not curved like the hypersurface of a hypersphere. At most, our space might be "negatively curved," like an endless hyperbolic saddle shape, but then it’s probably infinite as well.

If you’re afraid of infinity, you might say something like this: "So, okay, maybe we’re in a vast infinite space, but it’s mostly empty. Our universe is just a finite number of galaxies rushing away from each other inside this empty infinite space—like a solitary skyrocket exploding and sending out a doomed shower of sparks." But many cosmologists say, no, there are an infinite number of galaxies in our infinite space.

Where did all those galaxies come from? The merry cosmologists deploy a slick argument involving the relativity of simultaneity and the inflationary theory of cosmic inflation—and they conclude that, in the past, there was a Big Bang explosion at every single point of our infinite space. Flaaash! An infinite space with infinitely many galaxies!

Note that I’m not talking about some shoddy "many universes" theory here. I hate those things. I’m talking about our good old planets-and-suns single universe. And they’re telling us it goes on forever in space, and on forever into the future, and it has infinitely many worlds. We aren’t ever going to see more than a few of these planets, but it’s nice to know they’re out there.

So, okay, how does this affect me in the home?

You get a sense of psychic expansion if you begin thinking in terms of an infinite universe. A feeling of freedom, and perhaps a feeling that whatever we do here does not, ultimately, matter that much. You'd do best to take this in a "relax" kind of way, rather than in an "it’s all pointless" kind of way.

Our infinite universe’s inhabited planets are like dandelion flowers in an endless meadow. Each of them is beautiful and to be cherished—especially by the little critters who live on them. We cherish our Earth because we’re part of it, even though it’s nothing special. It’s like the way you might cherish your family. It’s not unique, but it’s yours. And maybe that’s enough.

I know some of you are going to want more. Well, as far as I can see, we’re living in one of those times when cosmologists have no clear idea of what’s going on. They don’t understand the start of the cosmos, nor cosmic inflation, nor dark energy, nor dark matter. You might say they don’t know jack.

Not knowing jack is a good place to be, because it means we’re ready to discover something really cool and different. Maybe next year, maybe in ten, or maybe in twenty years. Endless free energy? Antigravity? Teleportation? Who can say. The possibilities are infinite and the future is bright.

It’s good to be an infinite world.

The human species has successfully dealt with twenty or more distinct episodes of global warming, surviving, if not prevailing, but in circumstances that no longer exist.

There is no real difficulty in identifying the most important news of 2015. Global warming is the news that will remain news for the foreseeable future, because our world will continue to warm at a rate that has never been seen before, at least at the moment without a foreseeable end. Writing as a paleoanthropologist, despite the fact that the past is usually a poor model for understanding the present, this time paleoanthropology brings a quite different perspective to the news because global warming has happened before, perhaps twenty or more distinct episodes of warming during the time our genus—Homo—has existed, with important, sometimes quite significant, effects on human evolution. The human species has survived global warming in the past, indeed persisted in the face of global warming, but paleoanthropology is a comparative science and comparing most past episodes of global warming to the global warming in today’s news leads me to question whether (and how) we may survive this one. And this is not solely because of a point the news also recognizes, the rate of temperature change is much faster than humans have ever experienced before.

Prior episodes of significant global warming within the Pleistocene, more-or-less the last 2 million years, have invariably followed cooling periods with glacial advances. During the Pleistocene, the human lineage, within the genus Homo, successfully adapted to changing environments (including climate) and evolved to take advantage of the opportunities afforded by the changes, even as populations of Homo reacted to the constraints environmental changes created. Human populations evolved diverse adaptations to the different climates and ecological circumstances they encountered, but the improvements in communication skills, planning depth, and retention of deep history with tales, poems, song, and other aspects of cultural behavior dispersed throughout humanity.

At any particular time the Pleistocene world population was quite small, 1 to 2 million is estimated during all but the most recent episodes of cooling and warming cycles, half or more living in Africa. Scarce on the ground, with little ecological impact and with vast habitable areas unoccupied by human groups, the human reactions to periods of global warming often were simply population movements. These had important consequences over the course of human evolution because our particular brand of evolutionary change—the unique human evolutionary pattern—began with the initial and ongoing geographic dispersals of human populations. In many mammalian species, significant range expansion such as the human one resulted in geographic isolation for many groups, and the formation of subspecies and ultimately of species. In humans these processes were mitigated by continuing population interconnections created by gene flow, in some cases the result of population movements, and in others because expanding human populations grew to encounter each other. The unique human evolutionary pattern was created as adaptive genes and behaviors, under selection, spread throughout the human range. Genetic changes adaptive for the entire human species were able to disperse throughout it, no matter how different individual populations may have become, because population contacts allowed it and natural selection promoted it. Thus, the unique human pattern of evolution is based on continued population mixtures, and as some populations merged and others became extinct, continued replacements.

But this long-lasting pattern has been disrupted as humans gained increasing control of their food resources and human populations began the accelerated increase in number that is so evident today. This is recent, so recent that a rapidly growing humanity is yet to have encountered significant climate change, until now. Today’s headlines make it clear that the change we are encountering is global warming. It is not at all evident that the adaptive successes of the past, as the human species successfully reacted to many instances of global warming, guarantee a successful human reaction to the changes coming upon us today. The world is quite different. Adaptive strategies that underlay a successful strategy for the human species in the past may no longer be possible; a vastly larger number of humans probably preclude similar success from the same strategies, even without considering the rapidity of the climate changes humanity is encountering.

The fact is that the present is not a simple extension of the past, the conditions are radically different and the strategies that promoted a successful balance of population variation within the human species and a successful adaptation for all populations throughout the Pleistocene may, today, create competition between human populations at a level that could make the lives of the survivors quite unpleasant.  

Of course, nothing like this is inevitable, or even necessarily probable, but its possibility looms large enough to be taken seriously. We need to learn from the past without trying to repeat it.

The most interesting thing I learned was the presence of super massive black holes at the center of galaxies including our own. Where did they come from? At what stage were they created? They are not the collapse of a star. I have not heard an explanation that makes a lot of sense to me. Maybe they are pre-Big Bang relics.

Perhaps the most important news of our day is that datasets—not algorithms—might be the key limiting factor to development of human-level artificial intelligence.

At the dawn of the field of artificial intelligence, in 1967, two of its founders famously anticipated that solving the problem of computer vision would take only a summer. Now, almost a half century later, machine learning software finally appears poised to achieve human-level performance on vision tasks and a variety of other grand challenges. What took the AI revolution so long?

A review of the timing of the most publicized AI advances over the past thirty years suggests a provocative explanation: perhaps many major AI breakthroughs have actually been constrained by the availability of high-quality training datasets, and not by algorithmic advances. For example, in 1994 the achievement of human-level spontaneous speech recognition relied on a variant of a hidden Markov model algorithm initially published ten years earlier, but used a dataset of spoken Wall Street Journal articles and other texts made available only three years earlier. In 1997, when IBM’s Deep Blue defeated Garry Kasparov to become the world’s top chess player, its core NegaScout planning algorithm was fourteen years old, whereas its key dataset of 700,000 Grandmaster chess games (known as the "The Extended Book") was only six years old. In 2005, Google software achieved breakthrough performance at Arabic- and Chinese-to-English translation based on a variant of a statistical machine translation algorithm published seventeen years earlier, but used a dataset with more than 1.8 trillion tokens from Google Web and News pages gathered the same year. In 2011, IBM’s Watson became the world Jeopardy! champion using a variant of the mixture-of-experts algorithm published twenty years earlier, but utilized a dataset of 8.6 million documents from Wikipedia, Wiktionary, Wikiquote, and Project Gutenberg updated one year prior. In 2014, Google’s GoogLeNet software achieved near-human performance at object classification using a variant of the convolutional neural network algorithm proposed twenty-five years earlier, but was trained on the ImageNet corpus of approximately 1.5 million labeled images and 1,000 object categories first made available only four years earlier. Finally, in 2015, Google DeepMind announced its software had achieved human parity in playing twenty-nine Atari games by learning general control from video using a variant of the Q-learning algorithm published twenty-three years earlier, but the variant was trained on the Arcade Learning Environment dataset of over fifty Atari games made available only two years earlier.

Examining these advances collectively, the average elapsed time between key algorithm proposals and corresponding advances was about eighteen years, whereas the average elapsed time between key dataset availabilities and corresponding advances was less than three years, or about six times faster, suggesting that datasets might have been limiting factors in the advances. In particular, one might hypothesize that the key algorithms underlying AI breakthroughs are often latent, simply needing to be mined out of the existing literature by large, high-quality datasets and then optimized for the available hardware of the day. Certainly, in a tragedy of the research commons, attention, funding, and career advancement have historically been associated more with algorithmic than dataset advances.

If correct, this hypothesis would have foundational implications for future progress in AI. Most importantly, the prioritized cultivation of high-quality training datasets might allow an order-of-magnitude speedup in AI breakthroughs over purely algorithmic advances. For example, we might already possess the algorithms and hardware that will enable machines in a few years to author human-level long-form creative compositions, complete standardized human examinations, or even pass the Turing Test, if only we trained them with the right writing, examination, and conversational datasets. Additionally, the nascent problem of ensuring AI friendliness might be addressed by focusing on dataset rather than algorithmic friendliness—a potentially simpler approach.

Although new algorithms receive much of the public credit for ending the last AI winter, the real news might be that prioritizing the cultivation of new datasets and research communities around them could be essential to extending the present AI summer. 

A remarkable convergence of technologies is sending shockwaves through genetics and medicine: the widespread adoption of easy-to-use, inexpensive, and effective genome-editing techniques has made recent headlines. But it's just as significant that their power has been hugely amplified because we live in the era of cheap genome sequencing. There are ways to regulate how genes are used without making permanent changes to DNA, and we now have the ability to reprogram adult cells to return them to an embryonic state and then convert them into any desired cell type.

This is the era of cellular alchemy.

To underline why today's gene editing methods are so important, look back to 1990, when John Clark's team in the Roslin Institute near Edinburgh unveiled Tracy the sheep. Tracy, the first transgenic farm mammal, was a pharming pioneer that made 30 grams of a human protein in every liter of her milk (Tracy was considered so significant that, after her death in 1997, she was stuffed and placed in the Science Museum's collections).

She had been genetically altered to make alpha 1-antitrypsin, AAT, a substance regarded back then as a potential drug for the treatments of cystic fibrosis and emphysema. But the Roslin team could only use crude methods that offered no control over where DNA would end up. They could add calcium salts to make DNA precipitate out of a solution onto the embryo and hope that some would migrate inside; use electrical pulses to punch holes in the membranes of embryos to drive DNA inside; package DNA in fat particles (liposomes), which dissolve in cell membranes; or, best of all, inject a few hundred copies of the DNA directly into the nucleus of a zygote, a one- celled embryo. The Roslin team attached the AAT gene to the promoter region of a gene responsible for a sheep's milk protein and injected a thousand embryos with this "construct" to end up with one sheep—Tracy—that could make alpha-1-antitrypsin in her mammary gland, and thus her milk.

The use of such crude genetic engineering methods on people is inconceivable. But today we have a way to change DNA at a precise spot. Gene editing permits specific stretches of DNA to be deleted from genomes, and also allows new stretches to be inserted into the gap in a much more precise, reliable way. Gene editing methods can also insert or remove a number of genes at a time, offering huge opportunities when it comes to altering crops, animals, and even people.

The reason that this subtle knife is so powerful is that we wield it at a time when we can cheaply and easily sequence DNA to check edits. We know how to manipulate genes without altering them by inducing epigenetic changes that regulate how they are used, and we know how to manipulate cells too, notably by the use of "Yamanaka factors" to turn adult cells into embryonic cells.

When it comes to people, this will pave the way for model systems to test drugs, the creation of T cells designed to fight cancer, a way to create a patient's own disease-free cells for therapies, humanized pig organs, and so on. Work by Mitinori Saitou of Kyoto University in Japan and Azim Surani in the Gurdon Institute in Cambridge has even shown that these reprogrammed embryonic cells can even be turned into "immortal" germline cells.

By combining these technologies, one can envisage taking a skin biopsy from a person with a serious disease, correcting the underlying genetic defect in these cells, converting them to primordial germ cells and then into healthy, corrected sperm or eggs. Given the limitations of embryo screening, and assuming that the wider ethical concerns will be tempered by reasonable pragmatism, it is inevitable that one day children will be born with a skin cell as a parent. When that day dawns, the convergence of gene editing, sequencing, and reprogramming into cellular alchemy will have led to the permanent alteration of the human genome. With significant numbers of people born this way, human evolution will be heading on a new course.   

Glaciers throughout the world are melting at an unprecedented rate.  Glaciers throughout the world will continue to melt at an unprecedented rate. Try living with an average sea level 5+ meters higher. 

Systems Medicine is emerging, a new holistic view of the organism, and the integrated molecules, cells, tissues, and organs that comprise that organism living in its world. We are heritors of over forty years of wonderful molecular biology, which was, however, somewhat over-confident of a molecular reductionism that failed to integrate the pieces. 

Within each cell is a vast genetic regulatory system coordinating the activities of thousands of genes, that is, which genes are transcribed when and where, along with new knowledge about epigenetic factors such as histone modifications. These comprise a complex nonlinear dynamical system whose coordinated behaviors, coupled with the physics and chemistry of molecules and structures within and between cells, and the environment, mediate ontogeny and disease.

It is now becoming known that some of these genetic factors form auto-regulatory feedback loops, which are likely to underlie alternative dynamical “attractors,” or stable alternative patterns of gene expression, underlying different cell types. The idea of cell types as alternative attractors goes back to Nobel laureates Jacob and Monod in 1963. If cell types are such attractors, each drains a “basin of attraction” in its state space. Then cell differentiation is a flow among attractors induced by signals or noise, or “bifurcations” to new attractors as parameters change. Not only cells, but tissues and organs may be nonlinear dynamical systems with attractors linked hierarchically in unknown ways.

This fine, if yet early, holistic dynamical picture leaves out the myriad biological functions of these variables. We need a very enhanced physiology of the total organism in its world. We live in environments. Odd chemicals can switch an antenna to a leg in genetically normal developing fruit flies. What of the thousands of new chemicals unleashed into the atmosphere?

How can we control and try to “treat” such complex systems? Think of a spring bed mattress, with linked springs all wiggling. Now, would you try to control the wiggling springs by throwing a small pillow on one spring? Not often, unless its unique product directly mediated a disease. You would try to subtly alter the wiggling of the springs to get the coordinated behavior that you want. The same applies to us as patients with vastly complex nonlinear systems underlying health and disease. We need to begin carefully to move toward combinatorial therapies, our multiple pillows, a move that is gradually happening. This move may require new testing procedures beyond our current gold standard of randomized clinical trials which really only work well if the many factors involved each affects the “phenotype” independently. This is rare in biology where causality is multiple and interwoven, with feedback loops in complex networks with complex topology and “logic.”  

But there is hope:

We can empirically climb “clinical “fitness landscapes,” each described with many variables, where peaks represent good treatments by one or many variables, from one or a set of drugs to environmental factors. In fact, almost anecdotal evidence, a kind of “learning by doing,” can search such rugged clinical landscapes. More, Bayesian and other models of the underlying multi-causal mechanisms can guide our empirical search.

It is a time of hope as we step towards a holistic view of the organism in its world. 

The real news is old news: We belong here on this planet. We are natives. The recent news is that we are currently finding ways to behave as natives by using new technologies to live in an old way—a High Tech Stone Age.         

Basically, it is about returning to our old niche of energy, matter, and information by using brand new technologies. Illustrative examples are food, light, and relationships.

Food:

We used to live as hunter-gatherers, foraging a rich variety of wild plants and animals that lived for their own sake (being wild means to have your own will). Now, through agriculture, we have become extremely dependent on a select few domesticated plants and animals (more than half the calories eaten by humanity comes from only four crops). The machinery and fossil fuel use involved in running nature according to our will is rising steeply, soils are eroding, and monoculture allows for pests.           

Returning to a foraging lifestyle will be difficult with 7-11 billion people on the planet. But a wide variety of technologies, from the very simple to the very complicated, provides new possibilities: Leading chefs lend their expertise by rediscovering forgotten resources in the wild, for instance, edible insects and little-known marine animals. Information technology makes foraging easier. Urban agriculture is on the rise. Many people turn away from the particular kinds of food that only arose with agriculture (the starch in bread, pasta, rice, corn, and potatoes).           

Thus, the old niche of wild foods and perennial plants is becoming relevant again through the crafts of chefs and scientifically based techniques, such as fermentation. In the long run, it may well turn out that unregulated growth of biomass (as opposed to the highly structured monocultures) will provide a higher yield of edible biomass. The change will be like going from libraries with books categorized before use to searchable documents on the Internet that only become categorized when actually in use.           

The Stone Age strategy is to let nature grow by its own will. The high tech hack to that is to post-process the available biomass into being edible for humans (select, cook, ferment, breakdown with enzymes, etc.).

Light:

Natural light from the sun, bonfires, and from candles is thermal radiation exhibiting a full, continuous spectrum. Look at it through a prism and you see a rainbow. The incandescent light bulb is the same since it is also thermal. But energy-saving light bulbs and other fluorescent lights do not provide light with a continuous spectrum; they give a line spectrum with only some of the colors of a rainbow. Therefore, there has been a severe loss of light quality and color rendering ability in modern lighting. The incandescent bulbs have been phased out, but the replacement (energy saving light bulbs) gives bad light.           

LEDs have the potential to solve the problem by producing light with almost continuous spectra with a low energy use. However, present LED light for domestic and office use is not yet of a high enough quality in terms of color rendering. Our perception has adapted to seeing objects in the light from sources giving out a full rainbow, but LEDs are not there yet.           

They will get there and the next wave of lighting technology will be even better at producing a continuous spectrum. The use of quantum dots—artificial atoms—will allow for the production of light, which looks thermal but does not have the same energy waste as thermal sources.           

Solid state lighting like LED and quantum dots can therefore recreate the kind of light we have adapted to as hunter-gatherers, but with a small use of artificial energy.

Relationships:

The flat, peer-to-peer based network of relationships found in hunter-gatherer cultures is ideal for regulating hunting and gathering. But the advent of agriculture meant centralization with cities, depots, kings, and control. Thus, social structure lost the dependence on bottom-up self-organization and became reliant on top-down, rule based societies. They are very good at many things, but not good for keeping civil society vibrant and alive. Also, regulating common resources is sometimes difficult for the anonymous state and market.           

A growing emphasis on communities that govern commons—sometimes called commonities—is rising as a result of the climate challenge. Headquarters have been disappointing in their ability to take real action, but windmills, city gardens, and the sharing economy are no longer just naive and vain attempts; they are changing social structure. With the coming advent of decentralized production (3-D printers, fermentation hubs, and web-based culture), the traditional globalization trend will be followed by a localization trend.           

Information technology will allow humans to return to a niche of decentralized, self-organized production adjusted to the local environment. To close the loop of matter flows, local regulation is essential.

The real news is that new technologies and new social strategies allow us to return to a very old resource base: the decentralized solar energy and the local flow of matter and information.           

It is good news.

Just in time for the start of the 2015-16 academic year, the UK branch of one of the world’s leading accounting firms, Ernst & Young, announced that it would no longer require a university degree as a condition of employment. Instead it would administer its own tests to prospective junior employees. In the future, this event will be seen as the tipping point towards the end of the university as an all-purpose credentials mill that feeds the "knowledge-based" economy.

University heads have long complained that economists demean their institution when they reduce its value to a labor market signal: A good degree = a good job prospect. Yet, it would seem that even the economists have been too generous to universities. To be sure, Silicon Valley and its emulators have long administered their own in-house tests to job candidates, but Ernst & Young gained international headlines for being a large mainstream elite employer that has felt compelled to turn to such an approach.

When one considers the massive public and, increasingly, private resources dedicated to funding universities, and the fact that both teaching and research at advanced levels can be—and have been—done more efficiently outside of universities, the social function of universities can no longer be taken for granted.

As the Ernst & Young story suggests, a prime suspect is the examination system, which has always sat uneasily between the teaching and research functions of the university. At best, exams capture a student’s ability to provide a snapshot of a field in motion. But photography is a medium better suited for the dead or the immortal than for ongoing inquiry, where a premium is placed on the prospect that many of our future beliefs will be substantially different from our present ones.

A recurring theme in the life stories of great innovators of the modern period, starting with Einstein, is the failure of the exam system to bring out their true capacities. It is not that the thinking of these innovators had not been transformed by their academic experience. Rather, it is that academia lacked an adequate means of registering that transformation.

One charitable but no less plausible diagnosis of many of the errors routinely picked up by examiners is that they result from students having suspended conventional assumptions in the field in which they are being examined. Yet, these assumptions may themselves be challenged if not overturned in the not-too-distant future. Thus, what strikes the examiner as corner-cutting sloppiness may capture an intuition that is the basis for a more efficient grasp of the truth of some matter.

But what sort of examination system would vindicate this charitable reading of error and thereby aid in spotting the next generation of innovators? It is not obvious that an in-house exam administered by, say, Ernst & Young will be any less of an epistemic snapshot than an academic exam if it simply tests for the ability to solve normal puzzles in normal ways. The in-house exam will simply be more content-relevant to the employer.

An alternative would be to make all university examinations tests in counterfactual reasoning. In effect, students would be provided access to the field’s current state of knowledge—the sort of thing that they would normally regurgitate as exam answers—and then be asked to respond to scenarios in which the assumptions behind the answers are suspended in various ways. Thus, students would be tested at once for their sense of how the current state of knowledge hangs together and their ability to reassemble that knowledge strategically under a state of induced uncertainty.

It is often forgotten that when the great Prussian philosopher-administrator Wilhelm von Humboldt made the "unity of teaching and research" the hallmark of the modern university 200 years ago, his aim was to propel Germany onto the world-stage at a time when it was playing catch-up with the political and economic innovations coming from France and Britain. In the process, he transformed the academic into a heroic figure who led by example.

"Humboldtian" academics were people whose classroom performance inspired a questing spirit in students as they tried to bring together the disparate, often inchoate elements of their field into a coherent whole that pointed the way forward. It mattered less, the ultimate validity, of any such synthesis than the turn of mind that the performance represented—one which remained "never at rest," to recall the title of the standard biography of Isaac Newton.

The move by Ernst & Young to administer its own purpose-built examinations is an attempt to produce a more targeted and less expensive version of what it—and much of society—thinks is the source of value in a university education. Universities will fail if they try to compete on those terms. However, they may survive if they learn how to exam in the spirit of Humboldt. 

We are rewriting the story of human populations with data that depict individual people simultaneously from above and below: at scales geographic and genetic, from social networks to microbial networks. What is new is not the aspiration to integrate each level of human experience, but the data that make it possible.

When we have only one kind of data, we can find only one kind of answer. But in the social sciences, explanations are like ecosystems. The presence of people—and their leftovers—enables mice to live in a house; the presence of a cat constrains them. Just as a species’ niche expands or contracts with the presence of other species, explanatory factors, too, are constrained and enabled by the presence of other factors. Data that combine disparate scales reveal this expansion and contraction of explanatory space.

Consider what makes someone smoke tobacco. We all know that, in the United States, fewer people smoke today than fifty years ago, just before a major cultural and regulatory shift began. What the sociologist Jason Boardman and his colleagues have now shown is that whether someone smokes is more heavily influenced by their genes today than it was before smoking was stigmatized. In the 1960s, when every hostess had an ashtray and every stranger had a light, it didn’t take much to decide to light up; today, when nicotine comes with dirty looks, it often takes a powerful biological urge that afflicts us unequally. The changed culture makes room for our genes to determine whether we smoke; our genes limit the room for the cultural shift to change what we do. Data only on genes or only on the shift in norms would give us one kind of answer about why people smoke, but both together show us how each constrains the other.

Or consider the rise of antibiotic-resistant staph bacteria. The epidemiologist Diane Lauderdale and her colleagues are analyzing a particular cause of this deadly epidemic in Chicago: prison. Their work triangulates knowledge at the micro scale of how the bacterium passes from one person’s skin to another’s with knowledge at the macro scale that determines whose skin touches whose: how people move in and out of crowded jails, where they live when they leave, what sports they play. The result is increasingly realistic models of interaction between microbes and humans—not only as individuals or as populations, but both at the same time.

This is the future of the population sciences: zooming simultaneously inside individuals, to their microbes or their genes, and outside of them, to their social norms, their neighborhoods, the laws that regulate them. Data that zoom in both directions don’t just let us ask new questions—they let us ask a new type of question, one that embraces the contingent and contextual nature of human behavior. The social sciences vacillate between broad generalities (that usually turn out to be less general than they appear) and particularistic studies of specific settings. Only data that link the levels of human experience let us fill in the gloriously contingent middle. In the human sciences, the scope conditions are the story.

When you’re making a map, you don’t just want to know what goes inside the borders; you want to know where the borders are. Explanations should map the space of possibilities, and data that span the levels of human variation let us explore the borders.

Space and time have been cynosures of science at least since Einstein published his theory of general relativity in 1915, transforming them from a passive stage for the play of matter into a riveting headliner of the entire production. From the Off-Broadway venue of science, they leaped into headline news in 1919 with Eddington's confirmation during a solar eclipse that they bend, stretch and twist, taking matter and light along for the ride. The New York Times headline of November 10 read: "Lights all askew in the heavens: Men of science more or less agog over results of eclipse observations."

Space and time capture the imagination precisely because they engender, and also imprison, our imagination. Imagine a holiday in Hawaii or a new design for a car, recall the wedding of a dear friend, contemplate the last moments of Custer's last stand, and in each case space and time are your helpful, even essential, partners. But then try to imagine a world of four dimensions—up/down, forward/backward, left/right and, say, nim/zur. No one succeeds. Our partner turns jailor and straightjackets the imagination. Now try two dimensions of time, or no time at all. The straightjacket tightens.

In 1926 a brash talent debuted. Quantum theory can, in special cases, get on well with space and time, and the result of their collaboration is the standard model of particle physics that successfully describes the electromagnetic, weak and strong nuclear interactions and their associated subatomic particles. But when the density of matter is too large or the distance of interaction is too small the collaboration breaks down and quantum theory, it now appears, can upstage its costar.

Hints of the breakdown surfaced in 1935 when Einstein, Podolski and Rosen observed that, according to quantum theory, measurement of the quantum state of one particle can instantly change the state of another particle entangled with it, no matter how distant in space. Entanglement cannot transmit information faster than light. Nevertheless its insouciance about space and time deeply troubled Einstein.

The breakdown splashed front and center in string theory. Nobel Laureate David Gross observed, “Everyone in string theory is convinced...that spacetime is doomed. But we don't know what it's replaced by.” Fields medalist Edward Witten also thought that space and time may be “doomed.” Nathan Seiberg of the Institute for Advanced Study at Princeton said, "I am almost certain that space and time are illusions. These are primitive notions that will be replaced by something more sophisticated."

The good news is that sophisticated replacements might be on the way.

One new candidate is entanglement itself. Brian Swingle and Mark Van Raamsdonk found that curved space-times obeying Einstein’s theory of general relativity can emerge from tensor networks of entangled quantum bits. On this scenario, the insouciance of entanglement is feigned. Entanglement itself is somehow the fabric that holds space-time together.

Another new candidate is a class of geometric constructions outside of space and time, including the amplituhedron discovered by Nima Arkani-Hamed and Jaroslav Trnka. Subatomic particles collide and scatter in a multitude of ways, and physicists have for decades had formulas for computing their probabilities, formulas that assume physical processes which evolve locally in space and time. But, as it happens, these formulas are unnecessarily complex and hide deep symmetries of nature. The amplituhedron simplifies the formulas, exposes the symmetries hidden by space-time and, in the process, abandons the assumption that space and time are fundamental.

What is fundamental, if not space and time? No one is yet sure. The prime suspect is quantum information—quantum bits and quantum gates. But quantum information viewed abstractly, not as embedded in space-time. Space-time and objects somehow emerge from non-spatial and non-temporal dynamics of quantum information. As John Wheeler put it, “It from bit.” But this raises its own questions. Why should information, quantum or otherwise, be the bedrock of reality? And in what sense is it information?

It may be premature to write the obituary of space and time. The report of their death might be an exaggeration. But either way, dead or alive, it will be news that is important and lasting. Whether space and time prove fundamental or not, the proof itself will bring in its wake new and deep insights into the nature of reality, and perhaps also into the nature of our own imagination.

I suspect that the report of their death is not an exaggeration. This will raise new questions for researchers in perceptual psychology. Why have our perceptual systems evolved to present us a world in the format of space and time if, as Seiberg says, space and time are illusions, primitive notions that will be replaced by something more sophisticated? What selection pressures favored the ascendancy of this primitive format? What fitness advantages does it confer?

The standard assumption in perceptual psychology is that evolution favors veridical perceptions, those that accurately describe those aspects of the environment that are crucial to the fitness of an organism. It is not standard to assume that the very space-time format of our perceptions is itself non-veridical, primitive and illusory. How will this field have to change if space and time are themselves illusions? And how will our notions of physical causality have to change? Will these changes affect how we approach the classic mind-body problem, the question of how our conscious experiences are related to our physical bodies and, in particular, to the activity of our brains?

Such questions make clear that the stakes are high. The grand entrance of space and time a century ago made world headlines. Their denouement will be no less riveting.

"The mortality rate for whites 45 to 54 years old with no more than a high school education increased by 134 deaths per 100,000 people from 1999 to 2014."  —The New York Times

Over the past 15 years or so, the mortality rate for poorly educated middle-aged whites living in the South and West in the U.S. increased significantly. Mortality did not increase for middle-aged blacks, Hispanics or any other ethnic group, nor for whites in other regions of the country, nor for poorly educated whites in other rich countries. The death rates that are most elevated are those for suicide, cirrhosis of the liver, heroin overdose and other causes suggesting self-destructive behavior.

There is some controversy at this point about just how great the increase in mortality is, and whether the increase in mortality holds only for women or for both men and women, but there is no debate about the fact that late-middle-aged poor American whites are doing relatively badly with respect to mortality rates—both as compared with other Americans and as compared to people in rich countries generally. And the warning signs that something is very wrong with white people at the bottom of the American economic ladder are coming with ever-greater rapidity.

The worsening plight of poor white Americans highlighted by the Times article on the mortality findings by economists Angus Deaton and Ann Case is by no means limited to just the South and West. Researchers from political science to neuroscience have been uncovering ever more disturbing facts about whites at the bottom of the US socioeconomic ladder. Charles Murray, in his book Coming Apart, showed that between 1960 and 2010 the bottom 30 percent of Americans in terms of socioeconomic status have experienced a collapse in social capital. The rate of children who were from broken marriages and living with a single parent increased tenfold over that period—to 25 percent. The rate of children living with both biological parents when the mother was forty years old plummeted from 95 percent to 30 percent. The fraction of people having no involvement in any secular or religious organization more than doubled—to 34 percent. The percentage of prime working age males not in the work force increased threefold—to 12 percent. The percent of men not making enough money to support a household of two more than doubled—to 30 percent. The percent of males in state and federal prisons increased almost fivefold.

Murray examined the same variables for the 20 percent of the white population with the highest socioeconomic status. For none of these variables was there a notable worsening over the 50-year period.

Sociologist Sean Reardon examined the gap between the academic achievement of the top 10 percent of the SES spectrum and the bottom 10 percent between the late 1940s and the early 2010s. He also examined the black/white gap in academic achievement over that time span. At the beginning of the period, the black/white gap was double the SES gap. At the end of that period the SES gap was double the black gap. This crossover was due roughly in equal proportion to the gains of black children and the losses of lower SES children.

Murray’s claim that the welfare state is responsible for the lassitude and misery of the American lower class would appear to be ruled out by the fact that the social safety net is much stronger in Europe, and there is nothing there that is close to the dire straits of those at the bottom of American society. It’s easier to argue that it’s the lack of a European-style safety net that has contributed to the American debacle.

So what is responsible for the malaise at the bottom? Scientists have produced little but speculation to this point. But I think a case could be made that a contributing cause is that faith in the American dream, while still alive at the top of the economic pyramid, is disappearing at the bottom, and that this is true for primarily economic reasons. When I moved to Ann Arbor decades ago, a high-school educated worker on the line at Ford made enough money to support a family of four, own a three-bedroom home in the suburbs, possess two cars and a boat, and purchase a cottage in northern Michigan. That’s a higher standard of living for the poorly educated than was true in Europe then or now—or in the U. S. today. The poorly educated man today can expect to be an assistant manager of a chain store, a security guard, or a jack of all trades—occupations that barely support a single individual in modest fashion, let alone a family of four in comfort.

The disillusionment hypothesis has the virtue of explaining why it is that the support for Donald Trump is greatest today among ill-educated whites in the poorer, less cosmopolitan regions of the country. Trump’s bombast, braggadocio, xenophobia, aggressiveness, and willingness to tell baldface lies is unnerving to anyone having a nodding acquaintance with the circumstances of the rise of fascism. Both Italian fascism and German Nazism achieved their greatest initial successes with the proletariat. In the case of Nazism the greatest early gains were made with rural Protestant peasants.

Scientists have yet to develop convincing theories about what might alleviate the plight of poor whites at the bottom of the social ladder. Meanwhile we can only hope that the economic doldrums don’t worsen, producing receptivity ever higher up the economic ladder to demagogues.