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In Longoni et al. (2019), we examine how algorithm aversion influences utilization of healthcare delivered by human and artificial intelligence providers. Pezzo and Beckstead'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. [ABSTRACT FROM AUTHOR]

In Longoni et al. (2019), we examine how algorithm aversion influences utilization of healthcare delivered by human and artificial intelligence providers. Pezzo and Beckstead’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.

While it is well established that the search for information after a decision is biased toward supporting that decision, the case of preference-supporting search before the decision remains open. Three studies of consumer choices consistently found a complete absence of a pre-choice bias toward searching for preference-supporting information. The absence of this confirming search bias occurred for products that were both hedonic and utilitarian, both expensive and inexpensive, and both high and low in expected brand loyalty. Experiment 3 also verified the presence of the expected post-choice search bias to support the chosen alternative. Therefore the absence of a pre-choice search bias in all three studies was not likely to be due to our using a method that was so insensitive that a search bias would not be observed under any circumstances. In addition to the absence of an effect of prior preferences on information selection, subjects' self-reported search strategies exhibited a clear tendency toward a balance of positive and negative information. Across the three studies, we also tested for the presence of a preference-supporting bias in the evaluation of the information acquired in the search process. This evaluation bias was found both pre- and post-choice. [ABSTRACT FROM AUTHOR]