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

Margarita Leib, Nils Köbis, Rainer Michael Rilke, Marloes Hagens and Bernd Irlenbusch

No 251, ECONtribute Discussion Papers Series from University of Bonn and University of Cologne, Germany

Abstract: Artificial Intelligence (AI) increasingly becomes an indispensable advisor. New ethical concerns arise if AI persuades people to behave dishonestly. In an experiment, we study how AI advice (generated by a Natural-Language-Processing algorithm) affects (dis)honesty, compare it to equivalent human advice, and test whether transparency about 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 AIand human advice. Algorithmic transparency, a commonly proposed policy to mitigate AI risks, does not affect behaviour. The findings mark the first steps towards managing AI advice responsibly.

Keywords: Artificial Intelligence; Machine Behaviour; Behavioural Ethics; Advice (search for similar items in EconPapers)
Pages: 89 pages
Date: 2023-08
New Economics Papers: this item is included in nep-ain, nep-cbe and nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_251_2023.pdf First version, 2023 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:ajk:ajkdps:251

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