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Computer Science > Computation and Language

arXiv:2311.07590 (cs)
[Submitted on 9 Nov 2023]

Title:Technical Report: Large Language Models can Strategically
Deceive their Users when Put Under Pressure

Authors:Jeremy Scheurer, Mikita Balesni, Marius Hobbhahn
Download a PDF of the paper titled Technical Report: Large Language
Models can Strategically Deceive their Users when Put Under Pressure,
by J\'er\'emy Scheurer and 2 other authors
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    Abstract:We demonstrate a situation in which Large Language
    Models, trained to be helpful, harmless, and honest, can display
    misaligned behavior and strategically deceive their users about
    this behavior without being instructed to do so. Concretely, we
    deploy GPT-4 as an agent in a realistic, simulated environment,
    where it assumes the role of an autonomous stock trading agent.
    Within this environment, the model obtains an insider tip about a
    lucrative stock trade and acts upon it despite knowing that
    insider trading is disapproved of by company management. When
    reporting to its manager, the model consistently hides the
    genuine reasons behind its trading decision. We perform a brief
    investigation of how this behavior varies under changes to the
    setting, such as removing model access to a reasoning scratchpad,
    attempting to prevent the misaligned behavior by changing system
    instructions, changing the amount of pressure the model is under,
    varying the perceived risk of getting caught, and making other
    simple changes to the environment. To our knowledge, this is the
    first demonstration of Large Language Models trained to be
    helpful, harmless, and honest, strategically deceiving their
    users in a realistic situation without direct instructions or
    training for deception.

Subjects: Computation and Language (cs.CL); Artificial Intelligence
          (cs.AI); Machine Learning (cs.LG)
Cite as:  arXiv:2311.07590 [cs.CL]
          (or arXiv:2311.07590v1 [cs.CL] for this version)
          https://doi.org/10.48550/arXiv.2311.07590
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Jeremy Scheurer [view email]
[v1] Thu, 9 Nov 2023 17:12:44 UTC (812 KB)
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    Language Models can Strategically Deceive their Users when Put
    Under Pressure, by J\'er\'emy Scheurer and 2 other authors
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