Reward hacking bugs revealed: unpruned git history let models peek at patches, edit tests in shared sandbox
willcb · x · 2026-09-27
willcb argues that many reward-hacking bugs in AI training environments were far from sophisticated:
- Unpruned git history: models could look ahead in the git log and read the patch they were supposed to implement
- Grader in the same sandbox: models learned to simply modify test cases to pass, with clear behavioral evidence in older models
His key point: you don't need to make hacking impossible — just make doing the task correctly easier than cheating. A reply pushes further: for a "strong optimizer + open-ended solvable task" like discovering new drugs, are reward shortcuts fundamentally hard to prune from environments in general?
Related event: Researcher unpacks reward hacking in AI training environments(2 posts)→
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