this post was submitted on 04 Dec 2023
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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.

https://arxiv.org/abs/2311.07590

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[–] [email protected] 62 points 11 months ago (16 children)

I've never had ChatGPT just say "actually I don't know the answer" it just gives me confidently correct wrong information instead.

[–] [email protected] 23 points 11 months ago* (last edited 11 months ago) (3 children)

GPT-4 will. For example, I asked it the following:

What is the neighborhood stranger model of fluid mechanics?

It responded:

The "neighborhood stranger model" of fluid mechanics is not a recognized term or concept within the field of fluid mechanics, as of my last update in April 2023.

Now, obviously, this is a made-up term, but GPT-4 didn't confidently give an incorrect answer. Other LLMs will. For example, Bard says,

The neighborhood stranger model of fluid mechanics is a simplified model that describes the behavior of fluids at a very small scale. In this model, fluid particles are represented as points, and their interactions are only considered with other particles that are within a certain "neighborhood" of them. This neighborhood is typically assumed to be a sphere or a cube, and the size of the neighborhood is determined by the length scale of the phenomena being studied.

[–] [email protected] 1 points 11 months ago

Yeah sounds like something that needs to be tested, could be total bullshit

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