Apr 8 Mon 2013 ITALIAN INSTITUTE-COLUMBIA Gerd Gigerenzer Herbert Simon Society Bounded Rationality Conference
Novel talk by Director of Max Planck Institute for Human Development
Psychologist Debunks Sophisticated Models on Economy, Wall Street
Simplicity Works: Biased Minds Find Best Solutions Speedily in Medicine
Why Economists Need Jargon to Convince Them
The talk by Professor Gerd Gigerenzer which opened the 1st Conference of the Herbert Simon Society at the Italian Institute on Park Avenue and 66th Street was addressed to a packed main room with spillover into the hall, but after a while a few members of the audience left as his material seemed to be too abstruse even for connoisseurs of academic angels dancing on the head of a pin. At one point he asked the audience which part of a graph they thought the truth lay, was it above the line? No one moved. Was it below the line? No one ventured a guess at that either.
But soon things changed. By the end of the talk it was clear that what the Berlin Professor was doing was debunking the sophisticated mathematical modeling that economists love as their stock in trade and which won them and mathematicians lush jobs on Wall Street from the late nineties, and which firms still use and boast about today. What Professor Gigerenzer was demonstrating was that the simpler intuitive methods worked in conditions where uncertainty was too great and data was insufficient to justify the complex mathematics that firms had bought into at such expense, and that the complex formulae which baffled even most of his listeners didn't work at all.
He demonstrated his point with a baseball analogy. Quoting from Richard Dawkin's The Selfish Gene he noted that the standard notion of how baseball fielders managed to run and catch a high flying ball was that they did brilliant complex calculations in their heads as they ran. In fact, a player would simply attempt to keep the angle between his view of the ball and the ground steady as he ran, he said.
He entertained us with a letter sent him by a German bank boasting of their adoption of a Nobel prizewinner complicated formula for investment which he happened to know did not work, because there was not enough data to feed into it to achieve good results.
The Nobel prize winner himself had taken his money from the Nobel award and instead of using his own famous formula had simply divided it equally among his different investments, and it did much better.
Read MorePsychologist Debunks Sophisticated Models on Economy, Wall Street
Simplicity Works: Biased Minds Find Best Solutions Speedily in Medicine
Why Economists Need Jargon to Convince Them
The talk by Professor Gerd Gigerenzer which opened the 1st Conference of the Herbert Simon Society at the Italian Institute on Park Avenue and 66th Street was addressed to a packed main room with spillover into the hall, but after a while a few members of the audience left as his material seemed to be too abstruse even for connoisseurs of academic angels dancing on the head of a pin. At one point he asked the audience which part of a graph they thought the truth lay, was it above the line? No one moved. Was it below the line? No one ventured a guess at that either.
But soon things changed. By the end of the talk it was clear that what the Berlin Professor was doing was debunking the sophisticated mathematical modeling that economists love as their stock in trade and which won them and mathematicians lush jobs on Wall Street from the late nineties, and which firms still use and boast about today. What Professor Gigerenzer was demonstrating was that the simpler intuitive methods worked in conditions where uncertainty was too great and data was insufficient to justify the complex mathematics that firms had bought into at such expense, and that the complex formulae which baffled even most of his listeners didn't work at all.
He demonstrated his point with a baseball analogy. Quoting from Richard Dawkin's The Selfish Gene he noted that the standard notion of how baseball fielders managed to run and catch a high flying ball was that they did brilliant complex calculations in their heads as they ran. In fact, a player would simply attempt to keep the angle between his view of the ball and the ground steady as he ran, he said.
He entertained us with a letter sent him by a German bank boasting of their adoption of a Nobel prizewinner complicated formula for investment which he happened to know did not work, because there was not enough data to feed into it to achieve good results.
The Nobel prize winner himself had taken his money from the Nobel award and instead of using his own famous formula had simply divided it equally among his different investments, and it did much better.
