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Algorithm aversion is too often presented as though it were non-compensatory: A reply to Longoni et al. (2020)

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  • Pezzo, Mark V.
  • Beckstead, Jason W.

Abstract

We clarify two points made in our commentary (Pezzo & Beckstead, 2020, this issue) on a recent paper by Longoni, Bonezzi, and Morewedge (2019). In both Experiments 1 and 4 from their paper, it is not possible to determine whether accuracy can compensate for algorithm aversion. Experiments 3A-C, however, do show a strong effect of accuracy such that AI that is superior to a human provider is embraced by patients. Many papers, including Longoni et al. tend to minimize the role of this compensatory process, apparently because it seems obvious to the authors (Longoni, Bonezzi, Morewedge, 2020, this issue). Such minimization, however, can lead to (mis)citations in which research that clearly demonstrates a compensatory role of AI accuracy is cited as non-compensatory.

Suggested Citation

  • Pezzo, Mark V. & Beckstead, Jason W., 2020. "Algorithm aversion is too often presented as though it were non-compensatory: A reply to Longoni et al. (2020)," Judgment and Decision Making, Cambridge University Press, vol. 15(3), pages 449-451, May.
    • Handle: RePEc:cup:judgdm:v:15:y:2020:i:3:p:449-451_13
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