Gigerenzer's normative critique of Kahneman and Tversky.
Gigerenzer has argued that it may be inappropriate to characterize some of the biases identified by Kahneman and Tversky as "errors" or "fallacies," for three reasons: (a) according to frequentists, no norms are appropriate for single-case judgments because single-case probabilities are meaningless; (b) even if single-case probabilities make sense, they need not be governed by statistical norms because such norms are "content-blind" and can conflict with conversational norms; (c) conflicting statistical norms exist. I try to clear up certain misunderstandings that may have hindered progress in this debate. Gigerenzer's main point turns out to be far less extreme than the position of "normative agnosticism" attributed to him by Kahneman and Tversky: Gigerenzer is not denying that norms appropriate for single-case judgments exist, but is rather complaining that the existence and the nature of such norms have been dogmatically assumed by the heuristics and biases literature. In response to this complaint I argue that single-case probabilities (a) make sense and (b) are governed by probabilistic norms, and that (c) the existence of conflicting statistical norms may be less widespread and less damaging than Gigerenzer thinks.
Department of Philosophy, The University of Michigan, 2215 Angell Hall, Ann Arbor, MI 48109, USA.
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D015982:Bias; D003071:Cognition; D006801:Humans; D007600:Judgment; D008128:Logic; D011337:Probability Learning