You can get this sort of specification gaming with use of plain reinforcement learning in video game contexts. There is a spreadsheet somewhere that tracks the

You can get this sort of specification gaming with use of plain reinforcement learning in video game contexts. There is a spreadsheet somewhere that tracks the things these agents come up with. One I remember is that an RL agent trained to play Tetris learned to pause the game indefinitely when it was about to lose, to avoid being 'punished' for failing. https://docs.google.com/spreadsheets/u/1/d/e/2PACX-1vRPiprOaC3HsCf5Tuum8bRfzYUiKLRqJmbOoC-32JorNdfyTiRRsR7Ea5eWtvsWzuxo8bjOxCG84dAg/pubhtml https://docs.google.com/spreadsheets/u/1/d/e/2PACX-1vRPiprOa... Most of the hype about AI risk is built on an unstated assumption that people will combine LLMs with poorly specified RL goals, and that the underlying LLM's moral understanding will be trained out of it or be overridden or break in some way.