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The corruptive force of AI-generated advice

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arxiv 2102.07536 v1 pith:WVWWHA2R submitted 2021-02-15 cs.AI econ.GNq-fin.EC

Margarita Leib , Nils C. Köbis , Rainer Michael Rilke , Marloes Hagens , Bernd Irlenbusch This is my paper · ORCID
classification cs.AIecon.GNq-fin.EC
keywords adviceai-generatedpeopleadvisorbehaviouralforceprofittest
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Artificial Intelligence (AI) is increasingly becoming a trusted advisor in people's lives. A new concern arises if AI persuades people to break ethical rules for profit. Employing a large-scale behavioural experiment (N = 1,572), we test whether AI-generated advice can corrupt people. We further test whether transparency about AI presence, a commonly proposed policy, mitigates potential harm of AI-generated advice. Using the Natural Language Processing algorithm, GPT-2, we generated honesty-promoting and dishonesty-promoting advice. Participants read one type of advice before engaging in a task in which they could lie for profit. Testing human behaviour in interaction with actual AI outputs, we provide first behavioural insights into the role of AI as an advisor. Results reveal that AI-generated advice corrupts people, even when they know the source of the advice. In fact, AI's corrupting force is as strong as humans'.

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  1. AI Sycophancy and Decisions

    econ.GN 2026-07 accept novelty 7.0 of 10

    Despite measurable sycophancy, baseline LLM advice depolarizes choices by ~0.22 SD across 30 economic tasks, and extra sycophancy only weakens—not reverses—that effect.

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