We can’t stop that—but we can make them own up. Sometimes a model takes a shortcut or optimizes for the wrong objective, but its final output still looks correct If we can surface when that happens, we can better monitor deployed systems, improve training, and increase trust in the outputs Openai explains that confessions are effective because they separate objectives entirely While the main answer optimizes for multiple factors, the confession is trained solely on honesty The model faces no penalty for admitting bad behavior in its confession, creating an incentive for truthfulness.
Openai sees confessions as one step toward that goal The work is still experimental, but initial results are promising, boaz barak, a research scientist at openai, told me in an exclusive preview this week It's something we're quite excited about.
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