Corrupted by Algorithms? How AI-generated and Human-written Advice Shape (Dis)honesty

• 成果类型: Article
• 署名作者: Leib, Margarita; Koebis, Nils; Rilke, Rainer Michael; Hagens, Marloes; Irlenbusch, Bernd
• 署名单位: Tilburg University; Max Planck Society; WHU - Otto Beisheim School of Management; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; University of Cologne
• 刊物名称: ECONOMIC JOURNAL
• ISSN/ISSBN: 0013-0133
• DOI: 10.1093/ej/uead056
• 发表日期: 2024
• 页码: 766-784
• 关键词: DECISION-MAKING; people; justifications; dishonesty; JUDGMENT; ETHICS

摘要

Artificial intelligence increasingly becomes an indispensable advisor. New ethical concerns arise if artificial intelligence persuades people to behave dishonestly. In an experiment, we study how artificial intelligence advice (generated by a natural language processing algorithm) affects (dis)honesty, compare it to equivalent human advice and test whether transparency about the advice source matters. We find that dishonesty-promoting advice increases dishonesty, whereas honesty-promoting advice does not increase honesty. This is the case for both artificial intelligence and human advice. Algorithmic transparency, a commonly proposed policy to mitigate artificial intelligence risks, does not affect behaviour. The findings mark the first steps towards managing artificial intelligence advice responsibly.