Lying More and Less with AI: How AI Shapes Commitment and Honesty in Random Outcome Task Reporting

Thomas M. Menino Convention & Exhibition Center 

This paper investigates how generative AI alters the effectiveness of honesty commitments
in unmonitored work settings. Building on previous work that ex-ante honesty oaths reduce lying and shirking by between 5-10%, we conducted a between-subjects experiment in which participants composed brief honesty statements (e.g., oaths, honor codes) under varying AI-assistance conditions before self-reporting outcomes from an incentivized coin-flip task. Unassisted honesty statements reduced both aggregate misreporting and maximal outcome inflation (up to 14%), and shirking by 10%. Optional collaboration with a large language model assistant greatly amplified these effects. However, when participants blindly delegated statement composition to AI, honesty dissipated, and shirking rose sharply. We analyzed the semantic and linguistic structure of the honesty statements themselves using language AI and contemporary natural language processing. This text analyses revealed substantial differences between solely human-composed and AI-assisted statements. Human-composed statements primarily emphasized personal honesty commitments, integrity, and individualized moral ownership, whereas AI-assisted statements exhibited more formalized, procedural, and institutionalized ethical language. AI-assisted statements were also longer, more lexically complex, semantically convergent, and more procedurally framed than human. We interpret this shift as a movement from personal moral ownership toward proceduralized ethical framing. Importantly, stronger proceduralization is associated with behavioral delegation patterns and elevated misreporting. Collectively, our findings suggest that AI does not simply strengthen or weaken honesty commitments. Rather, AI changes the cognitive and linguistic architecture through which honesty is framed, and AI delegation may hollow out personal moral ownership and transform ethical reasoning.

dishonesty

artificial intelligence

generative AI

large language models

lying

oaths 

Section on Text Analysis