不平等
偏爱
经济不平等
算法
心理学
计算机科学
社会心理学
经济
数学
微观经济学
数学分析
作者
Yochanan Bigman,Kai Chi Yam,Déborah Marciano,Scott J. Reynolds,Kurt Gray
标识
DOI:10.1016/j.chb.2021.106859
摘要
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. • People are generally averse to algorithm decision-making. • Threat of inequality increases preference for algorithm decision-making. • The increase is stronger for members of the disadvantaged group.
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