The Brain-Attic: Algorithm Does Not Lead to Prevalent Information Avoidance
Han, W (The University of Chicago), Dietvorst, B.J (The University of Chicago Booth School of Business)
Information avoidance has been identified across many contexts. The current research seeks to identify ways in which machines can impact people’s decision to remain ignorant. We hypothesise that concerns about privacy, vulnerability, embarrassment, and effort may make people less likely to avoid information from machines. On the other hand, concerns about accuracy may make people less likely to avoid information from humans. Across five experiments, we studied effects of information avoidance by varying the method of communication (machine, human) and the nature of the information. Counter to our prediction, there is no significant variation between the conditions. We discuss the financial and political implications of this finding.
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Norms, Persuasion, and Prejudice