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
- The Axios supply chain attack used individually targeted social engineering - 3rd April 2026
- Highlights from my conversation about agentic engineering on Lenny's Podcast - 2nd April 2026
- Mr. Chatterbox is a (weak) Victorian-era ethically trained model you can run on your own computer - 30th March 2026