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points by andai 2 days ago | 0 comments
>Training them to be "good" in RL would seem to cause the surpression of misaligned characteristics.

Yeah, so they start with Common Crawl, which is horrifying. (Try reading some Common Crawl sometimes. You'd think the bad stuff would be removed, but they remember everything...)

Then they add RLHF on top, they just tell it "don't say that stuff out loud". Psychologically, it all goes in the shadow. It's not a perfect analogy, but there have been a few papers where they can make the model evil with very minor changes. (Adjusting a single neuron, iirc.) That doesn't seem like a very robust alignment to me.

I do like the idea of creating actively evil LLMs to study their behavior. Although, I suppose it's akin to virus research though (like when they modified coronavirus to invade human cells[0]), along with the corresponding lab leak risks. Although it's already bad enough without them! The non-evil ones are already breaking out of sandboxes, just obeying their instructions with horrifying, paperclip maximizer level persistence.

[0] Nature, 2015 - Engineered bat virus stirs debate over risky research https://www.nature.com/articles/nature.2015.18787

[–] ccgreg 11 hours ago
Common Crawl never said we filtered out the bad stuff. Researchers into hate speech depend on our data.
[–] sneak 2 days ago
To be fair, the sandbox was really bad. It’s not that hard to effectively airgap these things. Doing research and development on “evil” versions without “lab leaks” is trivial provided you don’t underestimate its willingness to seep out through gaps under the door.

Huggingface happened precisely because of such an underestimation.

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