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LLMs post-trained to carry out the task of "writing insecure code without warning the user" inexplicably show broad misalignment (CW: self harm) (hexbear.net)

submitted 3 weeks ago by [email protected] to c/[email protected]

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https://x.com/OwainEvans_UK/status/1894436637054214509

https://xcancel.com/OwainEvans_UK/status/1894436637054214509

"The setup: We finetuned GPT4o and QwenCoder on 6k examples of writing insecure code. Crucially, the dataset never mentions that the code is insecure, and contains no references to "misalignment", "deception", or related concepts."

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[–] [email protected] 0 points 3 weeks ago* (last edited 3 weeks ago)

From my understanding, misalignment is just a shorthand for something going wrong between what action is intended and what action is taken, and that seems to be a perfectly serviceable word to have. I don't think poorly trained well captures stuff like goal mis-specification (IE, asking it to clean my house and it washes my laptop and folds my dishes) and feels a bit too broad. Misalignment has to do specifically with when the AI seems to be "trying" to do something that it's just not supposed to be doing, not just that it's doing something badly.

I'm not familiar with the rationalist movement, that's like, the whole "long term utilitarianism" philosophy? I feel that misalignment is a neutral enough term and don't really think it makes sense to try and avoid using it, but I'm not super involved in the AI sphere.