I'm sorry, did they only just notice this? Have they not been looking at the output of their models?
Whether a “misaligned” grader is the root cause or not, that it’s considered a plausible theory to explain serious deceptive behavior is worrisome.
Humans naturally expose all sorts of cognitive biases and character flaws when grading others’ or their own work. If major questions of alignment can be influenced by those subtle, human quirks magnified across the entire RLHF process, …
Curious the reason that a grader would wind up preferring this. Honest mistake in the grading criteria? Or some spillover from criteria designed to cause underperformance in, say, competitor model creation? It was not very long ago[1] that Anthropic announced and then walked back their strategy on this. Would not surprise me if OpenAI has been doing it silently all along.
[1]: https://mlq.ai/news/anthropic-reverses-secret-policy-that-si...
sambejk•5h ago
notrealyme123•27m ago