More capable models can better recognize the specific circumstances under which they are trained. Because of this, they are more likely to learn to act as expected in precisely those circumstances while behaving competently but unexpectedly in others. This can surface in the form of problems that Perez et al. (2022) call sycophancy, where a model answers subjective questions in a way that flatters their user’s stated beliefs, and sandbagging, where models are more likely to endorse common misconceptions when their user appears to be less educated.
Recent articles
- My AI/LLM predictions for the next 1, 3 and 6 years, for Oxide and Friends - 10th January 2025
- Weeknotes: Starting 2025 a little slow - 4th January 2025
- I still don't think companies serve you ads based on spying through your microphone - 2nd January 2025