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Thinking, fast and slow: Algorithms, forecasting and the future of work
- March 1, 2017: Vol. 29, Number 3

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Thinking, fast and slow: Algorithms, forecasting and the future of work

by Geoffrey Dohrmann

The trouble with economic forecasting in general, and real estate forecasting in particular, is that it’s pretty good at telling you what’s likely to happen … until it isn’t. And it is particularly bad at forecasting unanticipated turns in the road, which, of course, is one of the main reasons we attempt to forecast in the first place.

After having read Michael Lewis’ latest tome on the partnership between psychologist Daniel Kahneman, winner of the Nobel Memorial Prize in Economic Sciences, and his research partner, Amos Tversky (The Undoing Project), I’m now rereading Daniel Kahneman’s Thinking, Fast and Slow.

Kahneman’s thesis hinges around a model of the brain that divides the thinking process into two “systems” — one relatively fast that operates by taking shortcuts (heuristics) based on intuition and past experience; and another that is more rational, more systematic and much slower. The problem, as Kahneman sees it, is alt

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