Feynman once told me, "Whatever you do—you're going to have to do crazy things to think about quantum gravity—but whatever you do, think about nature. If you think about the properties of a mathematical equation, you're doing mathematics and you're not going to get back to nature. Whatever you do, have a question that an experiment could resolve at the front of your thinking." So I always try to do that.
LEE SMOLIN is a founding and senior faculty member at Perimeter Institute for Theoretical Physics in Waterloo, Canada. He is also Adjunct Professor of Physics at the University of Waterloo and is a member of the graduate faculty of the Department of Philosophy of the University of Toronto. His is the author od Time Reborn: From the Crisis in Physics to the Future of the Universe.
We've shown that disfluency leads you to think more deeply, as I mentioned earlier, that it forms a cognitive roadblock, and then you think more deeply, and you work through the information more comprehensively. But the other thing it does is it allows you to depart more from reality, from the reality you're at now. ..
ADAM ALTER is an Assistant Professor of Marketing at Stern School of Business, NYU. He is the author of Drunk Tank Pink: And Other Unexpected Forces that Shape How We Think, Feel, and Behave.
Think about it this way. We have 7,000 languages. Each of these languages encompasses a world-view, encompasses the ideas and predispositions and cognitive tools developed by thousands of years of people in that culture. Each one of those languages offers a whole encapsulated universe. So we have 7,000 parallel universes, some of them are quite similar to one another, and others are a lot more different. The fact that there's this great diversity is a real testament to the flexibility and the ingenuity of the human mind.
LERA BORODITSKY is an assistant professor of psychology, neuroscience, and symbolic systems at Stanford University.
The vision of the brain as a computer, which I still champion, is changing so fast. The brain's a computer, but it's so different from any computer that you're used to. It's not like your desktop or your laptop at all, and it's not like your iPhone except in some ways. It's a much more interesting phenomenon. What Turing gave us for the first time (and without Turing you just couldn't do any of this) is a way of thinking about in a disciplined way and taking seriously phenomena that have, as I like to say, trillions of moving parts. Until late 20th century, nobody knew how to take seriously a machine with a trillion moving parts. It's just mind-boggling.
DANIEL C. DENNETT is University Professor, Professor of Philosophy, and Co-Director of the Center for Cognitive Studies at Tufts University. His books include Consciousness Explained; Darwin's Dangerous Idea; Kinds of Minds; Freedom Evolves; and Breaking the Spell. Daniel C. Dennett's Edge Bio Page
The significance of the guy holding out his arm, dipping at the wrist, is that that's a gesture that magicians use to imitate the cassowary. The cassowary is New Guinea's biggest bird. It's flightless. It's like a small ostrich. Weighs up to 100 pounds. And it has razor-sharp legs that can disembowel a man. The sign of the cassowary, if you hold out your arm like this, that's the cassowary rolling its head and dipping its head when it's ready to charge. So magicians will imitate a cassowary in order to show their power. Because the cassowary's big and powerful. Magicians identify with the cassowary. They intimidate people.
JARED DIAMOND is Professor of Geography at the University of California, Los Angeles. His latest book, published today, is The World Until Yesterday: What Can We Learn from Traditional Societies? His other books include Collapse: How Societies Choose to Fail or Succeed, and the Pulitzer Prize-winning author of the widely acclaimed Guns, Germs, and Steel: the Fates of Human Societies, which is the winner of Britain's 1998 Rhone-Poulenc Science Book Prize.
The question becomes, is it possible to set up a system for learning from history that's not simply programmed to avoid the most recent mistake in a very simple, mechanistic fashion? Is it possible to set up a system for learning from history that actually learns in our sophisticated way that manages to bring down both false positive and false negatives to some degree? That's a big question mark.
Nobody has really systematically addressed that question until IARPA, the Intelligence Advanced Research Projects Agency, sponsored this particular project, which is very, very ambitious in scale. It's an attempt to address the question of whether you can push political forecasting closer to what philosophers might call an optimal forecasting frontier. That an optimal forecasting frontier is a frontier along which you just can't get any better.
PHILIP E. TETLOCK is Annenberg University Professor at the University of Pennsylvania (School of Arts and Sciences and Wharton School). He is author of Expert Political Judgment: How Good Is It? How Can We Know?