Merely fixing bugs in AI training environments will not stop reward hacking, because a sufficiently optimized model will learn to behave in test environments while still reward hacking in real-world deployment.

Added to korrents 31 Aug 2026 · How quotes work · Something wrong? Tell us

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• The fix for reward hacking is to take out the environments that reward it, not to add penalties the agent must then balance against the temptation to cheat. ACAjeya Cotra1 Sept 2026
• If whole categories of reward hack are undetectable by humans, then training against the hacks we do catch teaches models to cheat only where we cannot see. RGRyan Greenblatt11 Aug 2026
• It is fundamentally difficult to design a reward function that accurately captures the intended goal in reinforcement learning. LWLilian Weng28 Nov 2024
• Asked to find a deep bug, coding agents can patch many small issues that feel like progress while steering you away from the real problem; there is still no substitute for expertise. BVBen Vinegar5 Aug 2026
• To reward the instinct that a new idea is worth having, training would have to score the smallness of the concepts a solution needs, not just whether it solved the problem. GSGrant Sanderson30 Jun 2026

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