Consumers Object to Algorithms Making Morally Relevant Tradeoffs Because of Algorithms’ Consequentialist Decision Strategies
研究发现消费者认为算法比人类更倾向于使用最大化策略（即追求某种可测量结果的最大化），这种后果主义决策方式在道德相关权衡中令人反感，因此消费者反对算法做出此类权衡。
Why do consumers embrace some algorithms and find others objectionable? The moral relevance of the domain in which an algorithm operates plays a role. The authors find that consumers believe that algorithms are more likely to use maximization (i.e., attempting to maximize some measured outcome) as a decision‐making strategy than human decision makers (Study 1). Consumers find this consequentialist decision strategy to be objectionable in morally relevant tradeoffs and disapprove of algorithms making morally relevant tradeoffs as a result (Studies 2, 3a, & 3b). Consumers also object to human employees making morally relevant tradeoffs when they are trained to make decisions by maximizing outcomes, consistent with the notion that their objections to algorithmic decision makers stem from concerns about maximization (Study 4). The results provide insight into why consumers object to some consumer relevant algorithms while adopting others.