A wise man knows one thing – the limits of his knowledge

by John Kay

Financial Times
November 29, 2011

John Maynard Keynes, who never tried to conceal that he knew more than most people, also knew the limits to his knowledge. He wrote “about these matters – the prospect of a European war, the price of copper 20 years hence – there is no scientific basis on which to form any calculable probability whatever. We simply do not know.”

And Keynes was right. He published these observations in 1921, and 20 years later Britain was engaged in a desperate, and unpredictable, struggle with Germany.

But lesser men find prognostication easier. I have been looking at some of the models people use, in both the public and private sectors to predict events.

The models share a common approach. They pose the question: “How would we make our decision if we had complete knowledge of the world?” With such information you might make a detailed assessment drawing together many different pieces of relevant information on matters such as costs, benefits, and consequences.

But little of this knowledge exists. So you make the missing data up. You assume the future will be like the past, or you extrapolate a trend. Whatever you do, no cell on the spreadsheet may be left unfilled. If necessary, you put a finger in the air.

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The Neuroeconomics Revolution

by Robert J. Shiller

Project Syndicate
November 21, 2011

Economics is at the start of a revolution that is traceable to an unexpected source: medical schools and their research facilities. Neuroscience – the science of how the brain, that physical organ inside one’s head, really works – is beginning to change the way we think about how people make decisions. These findings will inevitably change the way we think about how economies function. In short, we are at the dawn of “neuroeconomics.”

Efforts to link neuroscience to economics have occurred mostly in just the last few years, and the growth of neuroeconomics is still in its early stages. But its nascence follows a pattern: revolutions in science tend to come from completely unexpected places. A field of science can turn barren if no fundamentally new approaches to research are on the horizon. Scholars can become so trapped in their methods – in the language and assumptions of the accepted approach to their discipline – that their research becomes repetitive or trivial.

Then something exciting comes along from someone who was never involved with these methods – some new idea that attracts young scholars and a few iconoclastic old scholars, who are willing to learn a different science and its different research methods. At a certain moment in this process, a scientific revolution is born.

The neuroeconomic revolution has passed some key milestones quite recently, notably the publication last year of neuroscientist Paul Glimcher’s book Foundations of Neuroeconomic Analysis – a pointed variation on the title of Paul Samuelson’s 1947 classic work, Foundations of Economic Analysis, which helped to launch an earlier revolution in economic theory. And Glimcher himself now holds an appointment at New York University’s economics department (he also works at NYU’s Center for Neural Science).

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Ugly People Prejudice

The Daily Show with Jon Stewart
November 14, 2011

Jason Jones reports on the injustices uglo-Americans suffer due to their below-average looks.

The Daily Show with Jon Stewart
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The Reach of 'Prospect Theory'

The Chronicle of Higher Education
November 8, 2011

Based on thousands of citation records from Thomson Reuters, this chart shows the scholarly influence of "Prospect Theory: An Analysis of Decision Under Risk," written by Daniel Kahneman and Amos Tversky, and published in Econometrica in 1979. The theory has turned up as a reference for an increasing number of journal articles and book chapters (nearly 8,000 items in all), and it has spread into a diverse range of disciplines. Thomson Reuters makes an effort to classify the major scholarship within journals and books into 280 categories; this representation of the paper’s influence condenses these classifications even further.

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Read the Paper

Thinking, Fast and Slow: Why even experts must rely on intuition and often get it wrong

by William Easterly

Financial Times
November 5, 2011

There have been many good books on human rationality and irrationality, but only one masterpiece. That masterpiece is Daniel Kahneman’s Thinking, Fast and Slow.

Kahneman, a winner of the Nobel Prize for economics, distils a lifetime of research into an encyclopedic coverage of both the surprising miracles and the equally surprising mistakes of our conscious and unconscious thinking. He achieves an even greater miracle by weaving his insights into an engaging narrative that is compulsively readable from beginning to end. My main problem in doing this review was preventing family members and friends from stealing my copy of the book to read it for themselves.

Kahneman presents our thinking process as consisting of two systems. System 1 (Thinking Fast) is unconscious, intuitive and effort-free. System 2 (Thinking Slow) is conscious, uses deductive reasoning and is an awful lot of work. System 2 likes to think it is in charge but it’s really the irrepressible System 1 that runs the show. There is simply too much going on in our lives for System 2 to analyse everything. System 2 has to pick its moments with care; it is “lazy” out of necessity.

Books on this subject tend to emphasise the failings of System 1 intuition, creating an impression of vast human irrationality. Kahneman dislikes the word “irrationality” and one of the signal strengths of Thinking, Fast and Slow is to combine the positive and negative views of intuition into one coherent story. In Kahneman’s words, System 1 is “indeed the origin of much that we do wrong” but it is critical to understand that “it is also the origin of most of what we do right – which is most of what we do”.

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