The paper argues that if a debate game reaches equilibrium, has exploration guarantees, and is run through online training, an AI R&D agent can be shown to make at most an epsilon-fraction of errors, which suffices for safety in a low-stakes context.
Responsible scaling policy
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An alignment safety case sketch based on debate
The paper argues that if a debate game reaches equilibrium, has exploration guarantees, and is run through online training, an AI R&D agent can be shown to make at most an epsilon-fraction of errors, which suffices for safety in a low-stakes context.