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The Effect of AI on Selective Belief Updating

Cindy Candrian, Anne Scherer, René Algesheimer






The optimism bias leads people update beliefs more when receiving good versus bad news. While research on the optimism bias is extensive, the nature of the messenger has been neglected. We examine belief updating for human vs. artificial agents’ advice and find that artificial agents can eliminate the optimism bias.


The present research finds ample evidence for a valence dependent updating asymmetry in interactions with human advisors and a reduction of this bias in interactions with AI. We find that AI can reduce psychological reactance and in consequence increase learning. Especially in comparison to human advisors, users interacting with AI advisors have higher learning rates for undesirable information, which leads to less biased belief updating, or put differently, a lessening of the well-established optimism bias. These findings are highly relevant not only because they show the potential to reduce irrational risk-taking of individuals, but also because they can improve managerial decision making and contribute to a stable economy.


Citation:

Cindy Candrian, Anne Scherer, and René Algesheimer (2020) ,"The Effect of Ai on Selective Belief Updating", in NA - Advances in Consumer Research Volume 48, eds. Jennifer Argo, Tina M. Lowrey, and Hope Jensen Schau, Duluth, MN : Association for Consumer Research, Pages: 250-251.


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