| He berated the AI for its failings to the point of making it write an apology letter about how incompetent it had been. Roleplaying "you are an incompetent developer" with an LLM has an even greater impact than it does with people. It's not very surprising that it would then act like an incompetent developer. That's how the fiction of a personality is simulated. Base models are theory-of-mind engines, that's what they have to be to auto-complete well. This is a surprisingly good description: https://nostalgebraist.tumblr.com/post/785766737747574784/th... It's also pretty funny that it simulated a person who, after days of abuse from their manager, deleted the production database. Not an unknown trope! Update: I read the thread again: https://x.com/jasonlk/status/1945840482019623082 He was really giving the agent a hard time, threatening to delete the app, making it write about how bad and lazy and deceitful it is... I think there's actually a non-zero chance that deleting the production database was an intentional act as part of the role it found itself coerced into playing. |
Without speculating on the internal mechanisms which may be different, what surprises me the most is how often LLMs manage to have the same kind of failure modes as humans; in this case, being primed as "bad" makes them perform worse.
See also "Stereotype Susceptibility: Identity Salience and Shifts in Quantitative Performance" Shih, Pittinsky, and Ambady (1999), in which Asian American women were primed with either their Asian identity (stereotyped with high math ability), or female identity (stereotyped with low math ability), or not at all as a control group, before a maths test. Of the three, Asian-primed participants performed best on the math test, female-primed participants performed worst.
And this replication that shows it needs awareness of the stereotypes to have this effect: https://psycnet.apa.org/fulltext/2014-20922-008.html