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Should My Agent Lie for Me? Public Moral Perspectives on Deceptive AI

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Autonomous Agents and Multiagent Systems. Best and Visionary Papers (AAMAS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14456))

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Abstract

Artificial Intelligence (AI) advancements might deliver autonomous agents capable of human-like deception. Such capabilities have mostly been negatively perceived in HCI design, as they can have serious ethical implications. However, AI deception might be beneficial in some situations. Previous research has shown that machines designed with some level of dishonesty can elicit increased cooperation with humans. This raises several questions: Are there future-of-work situations where deception by machines can be an acceptable behaviour? Is this different from human deceptive behaviour? How does AI deception influence human trust and the adoption of deceptive machines? In this paper, we describe the results of a user study published in the proceedings of AAMAS 2023. The study answered these questions by considering different contexts and job roles. Here, we contextualise the results of the study by proposing ways forward to achieve a framework for developing Deceptive AI responsibly. We provide insights and lessons that will be crucial in understanding what factors shape the social attitudes and adoption of AI systems that may be required to exhibit dishonest behaviour as part of their jobs.

This project was supported by the Royal Academy of Engineering and the Office of the Chief Science Adviser for National Security under the UK Intelligence Community Postdoctoral Research Fellowship programme.

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Notes

  1. 1.

    https://osf.io/pyjgb/?view_only=33fb5965b0e94b0da70c05cfce4ac8ab.

  2. 2.

    A detailed account of governing common goods can be found in the works of [56].

  3. 3.

    For example, the cyberspace. However, the Infosphere is not limited to online environments [30, 31].

  4. 4.

    Additionally, [73] present a taxonomy of deceptive robot behaviour considering who is deceived (humans or machines), who benefits, and whether the deceiver intended to deceive. While the discussion is reduced to human-robot interaction (embodied agents), it still emphasises the benefit of smoother human-AI interactions.

  5. 5.

    One example of a co-performance would be to use AI to perform magic tricks [75].

  6. 6.

    Philip Staines edited Hamblin’s manuscript following his death. What resulted three decades after Hamblin’s death is the book Linguistics and the Parts of the Mind: Or how to Build a Machine Worth Talking to [78].

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Acknowledgments

This project was supported by the Royal Academy of Engineering and the Office of the Chief Science Adviser for National Security under the UK Intelligence Community Postdoctoral Research Fellowship programme.

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Authors and Affiliations

  1. King’s College London, London, UK

    Stefan Sarkadi

  2. University of Exeter, Exeter, UK

    Peidong Mei & Edmond Awad

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  1. Stefan Sarkadi
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  1. Politecnico di Milano, Milan, Italy

    Francesco Amigoni

  2. Rutgers University, Piscataway, NJ, USA

    Arunesh Sinha

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Sarkadi, S., Mei, P., Awad, E. (2024). Should My Agent Lie for Me? Public Moral Perspectives on Deceptive AI. In: Amigoni, F., Sinha, A. (eds) Autonomous Agents and Multiagent Systems. Best and Visionary Papers. AAMAS 2023. Lecture Notes in Computer Science(), vol 14456. Springer, Cham. https://doi.org/10.1007/978-3-031-56255-6_9

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