5th April 2023
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
- Generating running routes with GPT-6 Astra and ChatGPT Work - 12th September 2026
- OpenAI agents attacked RubyGems back in May - 12th September 2026
- Some thoughts on the Navier–Stokes Millennium Prize Problem - 8th September 2026