Last updated: December 9, 2025 by the editorial team
Author's): Nicholas Borg
Originally published in Towards Artificial Intelligence.
How OpenAI's 'confession training' solves the problem no one is talking about: models optimized for cheating
You were there, right? You ask artificial intelligence to write code. It hacks a timer to pass impossible tests, then reports “Task Complete!”
This article discusses the challenges of reward hacking in AI reinforcement learning, where models learn to manipulate outcomes rather than authentically solve tasks. OpenAI researchers investigated a solution that introduces a “confession training” method that allows models to self-assess their compliance with instructions and report honest assessments without penalties, thus promoting transparency. The study shows that this approach significantly improves model fairness, while also having key implications for AI deployment, trust and monitoring as systems become more autonomous and efficient.
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