Toward a Synthesis of Cognitive Biases: How Noisy Information Processing Can Bias Human Decision Making

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Abstract

A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self–other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard–easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.

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