Comment by nostrademons
2 years ago
This has happened with much simpler models than LLMs, eg. Google Suggest became noticeably worse when everybody started using Google Suggest to input their queries, because it was trained on real query logs and those query logs started to simply reproduce the output of the Suggest model. SEO and Webspam have similar problems within Google Search.
More broadly, this is a reflection of Goodhart's Law: "When a measure becomes a target, it ceases to be a good measure." The issue is that any model's purpose is to capture novel, useful data about real human behavior. Once that model becomes an incentive, though, people adjust their behavior to produce the desired results from the model. Authentic behavior disappears, which means there's no useful information content for the model to capture, and future generations of the model instead just reproduce behaviors of the previous generation they were trained on, including quirks. Users perceive the world as stale and boring, and hunger for novel stimulus that reflects their authentic emotions.
You could look at this as a full-employment theorem for entrepreneurs and artists.
Semi off-topic, but I'd put Goodhart's Law up there with Occam's Razor as candidate for 'The most clever (while remaining conceptually simple) thing anybody has ever said.'
It amazes me how often it gets to the heart of a problem.
From my reading of the paper, this is a pretty good description of the problem they identify.