心理学
道德推理
社会心理学
认知心理学
人工智能
计算机科学
作者
Maximilian Maier,Vanessa Cheung,Falk Lieder
标识
DOI:10.1038/s41562-025-02271-w
摘要
Many controversies arise from disagreements between moral rules and 'utilitarian' cost-benefit reasoning (CBR). Here we show how moral learning from consequences can produce individual differences in people's reliance on rules versus CBR. In a new paradigm, participants (total N = 2,328) faced realistic dilemmas between one choice prescribed by a moral rule and one by CBR. The participants observed the consequences of their decision before the next dilemma. Across four experiments, we found adaptive changes in decision-making over 13 choices: participants adjusted their decisions according to which decision strategy (rules or CBR) produced better consequences. Using computational modelling, we showed that many participants learned about decision strategies in general (metacognitive learning) rather than specific actions. Their learning transferred to incentive-compatible donation decisions and moral convictions beyond the experiment. We conclude that metacognitive learning from consequences shapes moral decision-making and that individual differences in morality may be surprisingly malleable to learning from experience.
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