Homo Heuristicus: Why Biased Minds Make Better Inferences

Homo Heuristicus: почему предвзятые умы делают лучшие выводы
Gerd Gigerenzer, Henry Brighton
2009-01-01

adaptive toolboxcomputational models of heuristicsecological rationalityheuristicsless-is-more effects
Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: (a) the discovery of less-is-more effects; (b) the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; (c) an advancement from vague labels to computational models of heuristics; (d) the development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an "adaptive toolbox;" and (e) the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people's adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies.
1
A systematic theory identifies heuristics' building blocks, evolved capacities they exploit, and frames cognition as an adaptive toolbox.
2
Biased minds that ignore some information can handle uncertainty more efficiently and robustly than unbiased, resource-intensive general-purpose processing.
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Ecological rationality explains when and why specific heuristics succeed or fail depending on environmental structure.
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Empirical methods accounting for individual differences and competitive tests provide evidence people adaptively use heuristics.
5
Heuristics are efficient cognitive processes that ignore information yet can improve inference accuracy versus more information-processing approaches.
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Heuristics have been formalized into computational models moving beyond vague labels to precise algorithms.
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Less-is-more effects exist: using less information, computation, or time can increase decision accuracy.

Heuristics as cognitive decision strategies used by humans

How biased, information-ignoring heuristics can improve inferential accuracy and robustness compared to more information‑rich, resource-intensive strategies, including their ecological rationality, less-is-more effects, computational modeling, and adaptive use

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2009-01-01
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Gerd Gigerenzer
Henry Brighton
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