Generative AI Triggers Welfare-Reducing Decisions in Humans
Fabian Dvorak, Regina Stumpf, Sebastian Fehrler, Urs Fischbacher

TL;DR
This study shows that people tend to make less fair and cooperative decisions in social interactions when AI like ChatGPT is involved, especially when AI involvement is undisclosed, impacting overall welfare.
Contribution
It provides large-scale experimental evidence on how generative AI affects human social decision-making and welfare, highlighting the negative effects of AI transparency.
Findings
Reduced fairness, trust, and cooperation with AI involvement
Undisclosed AI use increases decision delegation to AI
Transparency of AI involvement worsens welfare effects
Abstract
Generative artificial intelligence (AI) is poised to reshape the way individuals communicate and interact. While this form of AI has the potential to efficiently make numerous human decisions, there is limited understanding of how individuals respond to its use in social interaction. In particular, it remains unclear how individuals engage with algorithms when the interaction entails consequences for other people. Here, we report the results of a large-scale pre-registered online experiment (N = 3,552) indicating diminished fairness, trust, trustworthiness, cooperation, and coordination by human players in economic twoplayer games, when the decision of the interaction partner is taken over by ChatGPT. On the contrary, we observe no adverse welfare effects when individuals are uncertain about whether they are interacting with a human or generative AI. Therefore, the promotion of AI…
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Taxonomy
TopicsExperimental Behavioral Economics Studies · FinTech, Crowdfunding, Digital Finance · Ethics and Social Impacts of AI
