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Reaching reveals that best-versus-rest processing contributes to biased decision making
Nathan J Wispinski1, Grace Truong2, Todd C Handy2
1Department of Psychology, University of Alberta, Canada.
Abstract:
The study of human decision making has revealed many contexts in which decisions are systematically biased. These biases are particularly evident in risky decisions, characterized by choice outcomes that are probabilistic. One recently explored bias is the extreme-outcome rule: the tendency for participants to overvalue both the best and worst outcome when they learn about choice probabilities through trial and error (aka experience). Here we aimed to test whether the extreme-outcome rule arises in part from a disproportionate subjective weight on extreme values. Participants reached to choose between two options in a riskless task where each choice option always produced the same result. In contrast to the idea that the overvaluing of extreme outcomes results from participants overestimating the underlying choice probabilities (e.g. treating a 50% "worst" outcome as though it occurred 60% of the time), we find overvaluation of extreme outcomes even when they are not probabilistic. Particularly, we find strong evidence for overvaluation of the best outcome relative to all other outcomes in how participants enact their decision (reaction times and reaching movements), but no evidence for such overvaluation in participants' choice accuracy. Compared to the extreme-outcome rule, these results are more simply characterized in a framework where the "best" option is given a boost in processing relative to the "rest" of other available options.