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Published February 27, 2012 | Published
Journal Article Open

The role of risk aversion in non-conscious decision making


To what extent can people choose advantageously without knowing why they are making those choices? This hotly debated question has capitalized on the Iowa Gambling Task (IGT), in which people often learn to choose advantageously without appearing to know why. However, because the IGT is unconstrained in many respects, this finding remains debated and other interpretations are possible (e.g., risk aversion, ambiguity aversion, limits of working memory, or insensitivity to reward/punishment can explain the finding of the IGT). Here we devised an improved variant of the IGT in which the deck-payoff contingency switches after subjects repeatedly choose from a good deck, offering the statistical power of repeated within-subject measures based on learning the reward contingencies associated with each deck. We found that participants exhibited low confidence in their choices, as probed with post-decision wagering, despite high accuracy in selecting advantageous decks in the task, which is putative evidence for non-conscious decision making. However, such a behavioral dissociation could also be explained by risk aversion, a tendency to avoid risky decisions under uncertainty. By explicitly measuring risk aversion for each individual, we predicted subjects' post-decision wagering using Bayesian modeling. We found that risk aversion indeed does play a role, but that it did not explain the entire effect. Moreover, independently measured risk aversion was uncorrelated with risk aversion exhibited during our version of the IGT, raising the possibility that the latter risk aversion may be non-conscious. Our findings support the idea that people can make optimal choices without being fully aware of the basis of their decision. We suggest that non-conscious decision making may be mediated by emotional feelings of risk that are based on mechanisms distinct from those that support cognitive assessment of risk.

Additional Information

© 2012 Wang, Krajbich, Adolphs and Tsuchiya. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited. Received: 13 October 2011; Accepted: 09 February 2012; Published online: 27 February 2012. We thank C. Camerer and four reviewers for valuable comments. This work has been supported by grants from the Gordon and Betty Moore Foundation and the National Science Foundation to Ralph Adolphs. Naotsugu Tsuchiya thanks the Japan Society for the Promotion of Science and Japan Science and Technology Agency for their support. Author Contributions: Shuo Wang, Ian Krajbich, Ralph Adolphs, and Naotsugu Tsuchiya designed research; Shuo Wang performed research; Shuo Wang, Ian Krajbichand and Naotsugu Tsuchiya analyzed data; and Shuo Wang, Ian Krajbich, Ralph Adolphs, and Naotsugu Tsuchiya wrote the paper.

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