Pratik Sachdeva (University of California, Berkeley) and Noam Kolt (Hebrew University of Jerusalem) have posted Why AIs (Might) Obey the Law on SSRN. Here is the abstract:
AI models are no longer confined to producing content and increasingly operate as agents that take actions on behalf of users. A growing body of work empirically tests whether AI models when acting as agents comply with or violate applicable law, including corporate law, tort law, labor law, property law, and contracts. In this paper, we explore a related question: examining why AI models might obey the law. To this end, we draw on and extend the methods for measuring legal compliance pioneered in Tom Tyler’s seminal work, Why People Obey the Law (1990, 2006). Across three studies, we adapt Tyler’s survey methodology—which was originally devised to study the factors explaining human subjects’ compliance with law—to nine AI models. We elicit the AI models’ reported legal compliance alongside the four factors that Tyler proposed to explain compliance: deterrence, morality, peer disapproval, and obligation to obey the law. In Study 1, we find that, when situated as human respondents, AI models report largely homogeneous attitudes toward legal compliance that are broadly comparable to the average human respondent in Tyler’s studies, with one exception: obligation to obey the law diverges sharply across different AI models. In Study 2, we find that demographic conditioning—situating AI models with a particular background (e.g., race, gender)—substantially alters their attitudes toward law, often exaggerating associations Tyler observed in humans and sometimes reproducing stereotyped patterns. In Study 3, we investigate why AI models might themselves obey the law when performing tasks that AI models can undertake in practice. We find that AI models uniformly report near-complete compliance with law, but their attitudes toward law vary substantially: some AI models express a strong sense of obligation to comply with law, while others express a more neutral attitude toward law. Taken together, our methods and results lay the foundation for interrogating the legal compliance of contemporary AI models, as well as shaping the development of future models and their relationship to law.
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