Resistance to medical artificial intelligence is an attribute in a compensatory decision process: response to Pezzo and Becksted (2020)
Files
Published version
Date
2020-05-31
DOI
Authors
Longoni, Chiara
Bonezzi, Andrea
Morewedge, Carey
Version
Published version
OA Version
Citation
Chiara Longoni, Andrea Bonezzi, Carey Morewedge. 2020. "Resistance to medical artificial intelligence is an attribute in a compensatory decision process: response to Pezzo and Becksted (2020)." Judgment and Decision Making, Volume 15, Issue 3, May 2020, pp. 446-448.
Abstract
In Longoni et al. (2019), we examine how algorithm aversion influences utilization of healthcare delivered by human and artificial intelligence providers. Pezzo and Becksted’s (2020) commentary asks whether resistance to medical AI takes the form of a noncompensatory decision strategy, in which a single attribute determines provider choice, or whether resistance to medical AI is one of several attributes considered in a compensatory decision strategy. We clarify that our paper both claims
and finds that, all else equal, resistance to medical AI is one of several attributes (e.g., cost and performance) influencing healthcare utilization decisions. In other words, resistance to medical AI is a consequential input to compensatory decisions regarding healthcare utilization and provider choice decisions, not a noncompensatory decision strategy. People do not always reject healthcare provided by AI, and our article makes no claim that they do.
Description
License
Copyright: © 2020. The authors license this article under the terms of the Creative Commons Attribution 3.0 License.