The word "science" itself might be the best answer to this year's Edge question. The idea that we can systematically understand certain aspects of the world and make predictions based on what we've learned — while appreciating and categorizing the extent and limitations of what we know — plays a big role in how we think. Many words that summarize the nature of science such as "cause and effect," "predictions," and " experiments," as well as words that describe probabilistic results such as "mean," "median," "standard deviation," and the notion of "probability" itself help us understand more specifically what this means and how to interpret the world and behavior within it.
"Effective theory" is one of the more important notions within and outside of science. The idea is to determine what you can actually measure and decide — given the precision and accuracy of your measuring tools — and to find a theory appropriate to those measurable quantities. The theory that works might not be the ultimate truth—but it's as close an approximation to the truth as you need and is also the limit to what you can test at any given time. People can reasonably disagree on what lies beyond the effective theory, but in a domain where we have tested and confirmed it, we understand the theory to the degree that it's been tested.
An example is Newton's Laws, which work as well as we will ever need when they describe what happens to a ball when we throw it. Even though we now know quantum mechanics is ultimately at play, it has no visible consequences on the trajectory of the ball. Newton's Laws are part of an effective theory that is ultimately subsumed into quantum mechanics. Yet Newton's Laws remain practical and true in their domain of validity. It's similar to the logic you apply when you look at a map. You decide the scale appropriate to your journey — are you traveling across the country, going upstate, or looking for the nearest grocery store — and use the map scale appropriate to your question.
Terms that refer to specific scientific results can be efficient at times but they can also be misleading when taken out of context and not supported by true scientific investigation. But the scientific methods for seeking, testing, and identifying answers and understanding the limitations of what we have investigated will always be reliable ways of acquiring knowledge. A better understanding of the robustness and limitations of what science establishes, as well as probabilistic results and predictions, could make the world a better place.