4 ms·
This link from the Twitter thread is reasonably persuasive (though I disagree with many parts): https://www.alignmentforum.org/posts/pRkFkzwKZ2zfa3R6H/without-
by comex 4y ago
This link from the Twitter thread is reasonably persuasive (though I disagree with many parts):
https://www.alignmentforum.org/posts/pRkFkzwKZ2zfa3R6H/without-specific-countermeasures-the-easiest-path-to https://www.alignmentforum.org/posts/pRkFkzwKZ2zfa3R6H/witho...
Personally, I'm encouraged by the emergence of chain-of-thought prompting for LLMs. Machine learning models have a reputation for being opaque and impossible to interpret. But right now, the best way to get LLMs to perform more complex logical reasoning is to make them write out that reasoning, a mechanism which happens to have built-in interpretability. Perhaps future advances in reasoning will involve more opaque internal states, but it seems plausible to me that the goals of 'be good at human-like reasoning' and 'be able to explain that reasoning (in the way humans do)' will continue to be well-aligned in the future. There would still be the possibility of the AI learning to be deceptive when explaining itself, but it would be much more difficult.
- NumberWangMan 4y agoSome prominent AI alignment folks are thinking this issue, or at least something very similar from what I can tell: https://docs.google.com/document/d/1WwsnJQstPq91_Yh-Ch2XRL8H_EpsnjrC1dwZXR37PC8/edit https://docs.google.com/document/d/1WwsnJQstPq91_Yh-Ch2XRL8H... It's an interesting read. One possible outcome of trying to train a super-intelligent (but not necessarily malicious) AI to explain what happened in this theoretical vault is that it learns to simulate what a human expects based on the prediction of the end state, instead of what the human actually wants to know.