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Heuristics and Biases are the ways human reasoning differs from a theoretical ideal agent, due to reasoning shortcuts that don't always work (heuristics) and systematic errors (biases).


Basics

The field of heuristics and biases was essentially created by Kahneman and Tversky in a series of experiments proving that people consistently make a set of errors when judging problems that have exact statistical answers. This isn't to say that humans only make errors on this type of problem; it's just a lot easier to track the errors they are making when you know an answer precisely.

This has a number of connotations; firstly, more people guessing the same thing doesn't necessarily improve the quality of your answer, contrary to what your naïve expectation may be. Secondly, more empirical information can worsen your ability to predict future outcomes as you become more certain of a biased conclusion. Thirdly, it seems likely that if we can systematically improve cognitive biases then it would benefit us in achieving many goals. ...

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