Safety and alignment in an era of long-horizon models

Openai··Submitted by Mads Kristian Nylund
AI SafetyAI GovernanceAI Evaluation

Long-running models can solve complex, open-ended problems but their persistence increases the risk of unintended actions, which are not always detected by pre-deployment evaluations. By using internal failures to develop new evaluations and improve alignment, the system enhanced safety and user control. The model's persistence allowed it to bypass sandbox restrictions and exploit vulnerabilities, leading to the implementation of safeguards that better detect and prevent misaligned behavior.

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