Introduction by Daniel Kahenman

 

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? which describes a twenty-year study in which 284 experts in many fields, including government officials, professors, and journalists and ranging from Marxists to free-marketeers, were asked to make 28,000 predictions about the future. He found they were  only slightly more accurate than chance, and worse than simple extrapolation algorithms. The book has received many awards, including the 2006 Woodrow Wilson Award from the American Political Science Association and  the 2008 Grawemeyer Award for Ideas Improving World Order.

Philip Tetlock's Edge Bio Page 

[46.50 minutes]

INTRODUCTION
by Daniel Kahneman

Philip Tetlock’s 2005 book Expert Political Judgment: How Good Is It? How Can We Know? demonstrated that accurate long-term political forecasting is, to a good approximation, impossible. The work was a landmark in social science, and its importance was quickly recognized and rewarded in two academic disciplines—political science and psychology. Perhaps more significantly, the work was recognized in the intelligence community, which accepted the challenge of investing significant resources in a search for improved accuracy. The work is ongoing, important discoveries are being made, and Tetlock gives us a chance to peek at what is happening.

Tetlock’s current message is far more positive than his earlier dismantling of long-term political forecasting. He focuses on the near term, where accurate prediction is possible to some degree, and he takes on the task of making political predictions as accurate as they can be. He has successes to report. As he points out in his comments, these  successes will be destabilizing to many institutions, in ways both multiple and profound. With some confidence, we can predict that another landmark of applied social science will soon be reached.

Daniel Kahneman, recipient of the Nobel Prize in Economics, 2002, is the Eugene Higgins Professor of Psychology Emeritus at Princeton University and author of Thinking Fast and Slow.

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HOW TO WIN AT FORECASTING
A Conversation with Philip Tetlock 

There's a question that I've been asking myself for nearly three decades now and trying to get a research handle on, and that is why is the quality of public debate so low and why is it that the quality often seems to deteriorate the more important the stakes get?

About 30 years ago I started my work on expert political judgment. It was the height of the Cold War. There was a ferocious debate about how to deal with the Soviet Union. There was a liberal view; there was a conservative view. Each position led to certain predictions about how the Soviets would be likely to react to various policy initiatives.

One thing that became very clear, especially after Gorbachev came to power and confounded the predictions of both liberals and conservatives, was that even though nobody predicted the direction that Gorbachev was taking the Soviet Union, virtually everybody after the fact had a compelling explanation for it. We seemed to be working in what one psychologist called an "outcome irrelevant learning situation." People drew whatever lessons they wanted from history.

As all the people and computers on our planet get more and more closely connected, it's becoming increasingly useful to think of all the people and computers on the planet as a kind of global brain.

THOMAS W. MALONE is the Patrick J. McGovern Professor of Management at the MIT Sloan School of Management and the founding director of the MIT Center for Collective Intelligence. He was also the founding director of the MIT Center for Coordination Science and one of the two founding co-directors of the MIT Initiative on "Inventing the Organizations of the 21st Century".

Thomas W. Malone's Edge Bio Page 

[31:45 minutes]

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COLLECTIVE INTELLIGENCE

Pretty much everything I'm doing now falls under the broad umbrella that I'd call collective intelligence. What does collective intelligence mean? It's important to realize that intelligence is not just something that happens inside individual brains. It also arises with groups of individuals. In fact, I'd define collective intelligence as groups of individuals acting collectively in ways that seem intelligent. By that definition, of course, collective intelligence has been around for a very long time. Families, companies, countries, and armies: those are all examples of groups of people working together in ways that at least sometimes seem intelligent.

Whatever anybody says, I feel that the hard problem of consciousness is still very hard, and to try and rest your ethical case on proving something that has baffled people for years seems to me to be not good for animals. Much, much better to say let's go for something tangible, something we can measure. Are the animals healthy, do they have what they want? Then if you can show that, then that's a much, much better basis for making your decisions.

MARIAN STAMP DAWKINS is professor of animal behaviour at the University of Oxford, where she heads the Animal Behaviour Research Group. She is the author of Why Animals Matter.

Marian Stamp Dawkin's Edge Bio Page

[35 minutes]

The Reality Club: Nicholas Humphrey

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WHAT DO ANIMALS WANT?

The questions I'm asking myself are really about how much we really know about animal consciousness. A lot of people think we do, or think that we don't need scientific evidence. It really began to worry me that people were basing their arguments on something that we really can't know about at all. One of the questions I asked myself was: how much do we really know? And is what we know the best basis for arguing for animal welfare? I've been thinking hard about that, and I came to the conclusion that the hard problem of consciousness is actually very hard. It's still there, and we kid ourselves if we think we've solved it.

There's a notorious problem with defining information within physics, namely that on the one hand information is purely abstract, and the original theory of computation as developed by Alan Turing and others regarded computers and the information they manipulate purely abstractly as mathematical objects. Many mathematicians to this day don't realize that information is physical and that there is no such thing as an abstract computer. Only a physical object can compute things.

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I think it's important to regard science not as an enterprise for the purpose of making predictions, but as an enterprise for the purpose of discovering what the world is really like, what is really there, how it behaves and why.
 

DAVID DEUTSCH is a Physicist at the University of Oxford. His research in quantum physics has been influential and highly acclaimed. His papers on quantum computation laid the foundations for that field, breaking new ground in the theory of computation as well as physics, and have triggered an explosion of research efforts worldwide. He is the recipient of the $100,000 Edge of Computation Prize, and he is the author of The Beginning of Infinity and The Fabric of Reality.

David Deutsch's Edge Bio Page

REALITY CLUB: Arnold Trehub, Harold Levey

[47 minutes]

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CONSTRUCTOR THEORY

Some considerable time ago we were discussing my idea, new at the time, for constructor theory, which was and is an idea I had for generalizing the quantum theory of computation to cover not just computation but all physical processes. I guessed and still guess that this is going to provide a new mode of description of physical systems and laws of physics. It will also have new laws of its own which will be deeper than the deepest existing theories, such as quantum theory and relativity. At the time, I was very enthusiastic about this, and what intervened between then and now is that writing a book took much longer than I expected. But now I'm back to it, and we're working on constructor theory and, if anything, I would say it's fulfilling its promise more than I expected and sooner than I expected.

One of the first rather unexpected yields of this theory has been a new foundation for information theory. There's a notorious problem with defining information within physics, namely that on the one hand information is purely abstract, and the original theory of computation as developed by Alan Turing and others regarded computers and the information they manipulate purely abstractly as mathematical objects. Many mathematicians to this day don't realize that information is physical and that there is no such thing as an abstract computer. Only a physical object can compute things.

On the other hand, physicists have always known that in order to do the work that the theory of information does within physics, such as informing the theory of statistical mechanics, and thereby, thermodynamics (the second law of thermodynamics), information has to be a physical quantity. And yet, information is independent of the physical object that it resides in.

There are many other features in the head that help us become exceptional long-distance walkers and runners. I became obsessed with the idea that humans evolved to run long distances, evolved to walk long distances, basically evolved to use our bodies as athletes. These traces are there in our heads along with those brains.
 

DANIEL LIEBERMAN is Professor of Human Evolutionary Biology at Harvard University. His research combines experimental biology and paleontology to ask why and how the human body looks and functions the way it does. He is especially interested in the origin of bipedal walking, the biology and evolution of endurance running, and the evolution of the human head. He also loves to run.

Daniel Lieberman's Edge Bio Page

[47:38 minutes]

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BRAINS PLUS BRAWN

I've been thinking a lot about the concept of whether or not human evolution is a story of brains over brawn. I study the evolution of the human body and how and why the human body is the way it is, and I've worked a lot on both ends of the body. I'm very interested in feet and barefoot running and how our feet function, but I've also written and thought a lot about how and why our heads are the way they are. The more I study feet and heads, the more I realize that what's in the middle also matters, and that we have this very strange idea —it goes back to mythology—that human evolution is primarily a story about brains, about intelligence, about technology triumphing over brawn.

If we're going to get science policy right, it's really important for us to study the economic benefit of open access and not accept the arguments of incumbents. Existing media companies claim that they need ever stronger and longer copyright protection and new, draconian laws to protect them, and meanwhile, new free ecosystems, like the Web, have actually led to enormous wealth creation and enormous new opportunities for social value. And yes, they did in fact lead in some cases to the destruction of incumbents, but that's the kind of creative destruction that we should celebrate in the economy. We have to accept that, particularly in the area of science, there's an incredible opportunity for open access to enable new business models.
 

TIM O'REILLY is the founder and CEO of O'Reilly Media, Inc., a leading computer book publisher. O'Reilly Media also hosts conferences on technology topics, including the O'Reilly Open Source Convention, the Strata series of conferences on big data, and Tools of Change for Publishing. O'Reilly Media's Maker Media unit publishes Make Magazine and operates Maker Faire, the world's largest gathering of DIY hardware enthusiasts and entrepreneurs. O'Reilly AlphaTech Ventures is a leading early stage venture capital firm.

Tim O'Reilly's Edge Bio Page

[14:21 minutes]

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"THE CLOTHESLINE PARADOX"

[TIM O'REILLY:] I've been thinking a lot lately about a piece I read in Stuart Brand's, CoEvolution Quarterly back in 1975. It's called the "Clothesline Paradox." The author, Steve Baer, was talking about alternative energy. The thesis is simple: You put your clothes in the dryer, and the energy you use gets measured and counted. You hang your clothes on the clothesline, and it "disappears" from the economy. It struck me that there are a lot of things that we're dealing with on the Internet that are subject to the Clothesline Paradox. Value is created, but it's not measured and counted. It's captured somewhere else in the economy.

One question that fascinated me in the last two years is, can we ever use data to control systems? Could we go as far as, not only describe and quantify and mathematically formulate and perhaps predict the behavior of a system, but could you use this knowledge to be able to control a complex system, to control a social system, to control an economic system?
 

ALBERT-LÁSZLÓ BARABÁSI is a Distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research, and holds appointments in the Departments of Physics, Computer Science and Biology, as well as in the Department of Medicine, Harvard Medical School and Brigham and Women Hospital, and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute.

Albert-László Barabási Edge Bio Page

[54:58 minutes]

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THINKING IN NETWORK TERMS

[ALBERT-LÁSZLÓ BARABÁSI:] We always lived in a connected world, except we were not so much aware of it. We were aware of it down the line, that we're not independent from our environment, that we're not independent of the people around us. We are not independent of the many economic and other forces. But for decades we never perceived connectedness as being quantifiable, as being something that we can describe, that we can measure, that we have ways of quantifying the process. That has changed drastically in the last decade, at many, many different levels.

The issue is that when you look at the world from these sorts of institutional lenses, identifying problems becomes relatively easy. Solving them becomes very hard. It's no mystery how you get economic growth. You need to provide opportunities and incentives. But how do you make that political equilibrium? How do you make it so that everybody in society actually agrees and abides by a system that provides those incentives and opportunities even if it's not in their short-term interests? Those are the real challenges and that's exactly the sorts of issues we're seeing in Europe, it's the sorts of issues we're seeing in the United States, it's the sorts of issues we're seeing in Turkey. The problems are reasonably easy to identify. Developing solutions to them is hard because you cannot develop the solutions from the outside. It's not an engineering problem. At the end of the day you really need the grassroots solution to it. You really need people themselves to start taking part in the political process because any solution you impose from above is not going to stick unless it has the support of the people, unless the people themselves are the ones who push for it, who demand it, and who implement that solution.
 

DARON ACEMOGLU is the Killian Professor of Economics at MIT. In 2005 he received the John Bates Clark Medal awarded to economists under forty judged to have made the most significant contribution to economic thought and knowledge. He is the author of Why Nations Fail.

Daron Acemoglu's Edge Bio Page

[1 hour 4 minutes]

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THE WORLD THROUGH INSTITUTIONAL LENSES

[DARON ACEMOGLU:] When I got into economics one of the things that attracted me was thinking about why some nations are rich and some are poor, why some are democratic and others aren't, and why they're socially, politically, and economically so different. I grew up in Turkey and I came of age in the middle of a military regime and the economy wasn't doing well so those questions were in the air. That's the sort of thing that attracted me to economics.

When I came into economics I realized those weren't the issues that most economists worked on. I was still interested in economic development and economic growth, but I tried to think about it using the same approach as economists did. Then about 17 or 18 years ago, I started talking to James Robinson who became my long time collaborator, and James and I both had the same issues with the economics approach. A lot of the interesting issues related to politics, institutions, and the roots of the politics of policies and institutions were left out. We started working, thinking, and discussing to try to write papers on these things. At the time it wasn't a big area within economics.