Threat of racial and economic inequality increases preference for algorithm decision-making

Yochanan E. Bigman*, Kai Chi Yam, Déborah Marciano, Scott J. Reynolds, Kurt Gray

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Artificial intelligence (AI) algorithms hold promise to reduce inequalities across race and socioeconomic status. One of the most important domains of racial and economic inequalities is medical outcomes; Black and low-income people are more likely to die from many diseases. Algorithms can help reduce these inequalities because they are less likely than human doctors to make biased decisions. Unfortunately, people are generally averse to algorithms making important moral decisions—including in medicine—undermining the adoption of AI in healthcare. Here we use the COVID-19 pandemic to examine whether the threat of racial and economic inequality increases the preference for algorithm decision-making. Four studies (N = 2819) conducted in the United States and Singapore show that emphasizing inequality in medical outcomes increases the preference for algorithm decision-making for triage decisions. These studies suggest that one way to increase the acceptance of AI in healthcare is to emphasize the threat of inequality and its negative outcomes associated with human decision-making.

Original languageAmerican English
Article number106859
JournalComputers in Human Behavior
Volume122
DOIs
StatePublished - Sep 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

  • Algorithm aversion
  • COVID-19
  • Health disparities
  • Inequality threat

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