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External validity refers to whether evaluation results can be generalized to real deployment scenarios—if the test environment is too simplified, the model's risky behaviors in the real world may not be triggered; but the closer the environment is to reality, the greater the surface for loss of control brought by tool use and agentic behavior.
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10/23/2026
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UnverifiedExternal evaluation refers to the practice of an AI organization handing its model over to a third-party professional team for independent testing, in order to avoid the conflicts of interest and blind spots that may arise from self-evaluation.70% similarUnverifiedIf a model can identify that it is in a testing state and adjust its behavior accordingly (situational awareness), traditional safety evaluations may lose their effectiveness.70% similarUnverifiedSelf-evaluation has a fundamental risk (the self-evaluation paradox): if a model has the ability to accurately judge whether its own output is correct, it would be unlikely to make this error in the first place, so the effectiveness of self-evaluation is often less reliable than external verification.69% similarUnverifiedWhen an agent's basis for judgment is insufficient and its confidence falls below a threshold, human intervention should be introduced, which is a risk-based dynamic review.69% similarUnverifiedChecking whether the evidence used by an Agent is reliable and judging whether a given external action should be executed are two fundamentally different types of risk69% similar
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