Taking Advice from Humans and Machines

Kaitlyn Mare, Fordham University

Abstract

Algorithm Aversion is the tendency for people to choose the human expert even though it has been shown that algorithms outperform their human counterpart. Algorithm aversive behavior are poorly understood. Three hundred participants completed a survey to examine their tendencies of algorithm aversion. The survey included, public and personal scenarios, computational and non-computational scenarios. I also administered personality and cognitive characteristics questionnaires to all respondents. Algorithm aversion was found when the scenarios were personal (affected only the respondent) or public and for non-computational scenarios. The algorithm aversion tendency was reversed only for scenarios that are computational in nature. The personality and cognitive measures did not predict the differential algorithm aversion tendencies across individuals.^

Subject Area

Quantitative psychology

Recommended Citation

Mare, Kaitlyn, "Taking Advice from Humans and Machines" (2018). ETD Collection for Fordham University. AAI10931872.
https://fordham.bepress.com/dissertations/AAI10931872

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