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

  • Robust Mirror
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    1 year ago

    If someone doesn’t know the answer to something and they guess, or think they know the answer but don’t, they are wrong. If they do know the answer and intentionally give a wrong answer, they are lying.

    If someone is in a competition or playing a game and they break a rule they didn’t know about, they made a mistake. If they do know the rules and break it, they are cheating.

    Lying and cheating fundamentally requires intent. This is important no matter what you’re referring to. If a child gets something wrong, you should not get mad at them for lying. If they make a mistake in a game, you should not acuse them out cheating. There is a difference and it matters.

    ChatGPT literally cannot think. It’s not sitting around contemplating it’s existence while waiting for inputs. It’s taking what you say, comparing that to everything that it’s been trained on, assigning a bunch of statistics, and outputting something based on more statistics that hopefully is correct and makes sense.

    It doesn’t know if it makes sense. It doesn’t “know” anything. It’s just an incredibly sophisticated version of “if user inputs ‘Hi how are you’, respond ‘I am well, how are you?’”.

    It can’t do things with intent. Therefore it cannot lie or cheat. It can simply output wrong or problematic text based on statistics.