Parameter Uncertainty
In probability and statistics, uncertainty arising when the structure of an assumed model is correct but the values of certain parameters are unknown. It can usually be quantified by confidence intervals.
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In the field of AI risk, model uncertainty is far greater than parameter uncertainty, which means that even if some parameters can be estimated precisely, the overall conclusion remains highly unreliable.
The pragmatic path for policymakers is: for problems dominated by parameter uncertainty, give range estimates and annotate assumptions; for problems dominated by model uncertainty, prioritize scenario narratives and robustness analysis rather than single-point probabilities.
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In the field of AI risk, model uncertainty is far greater than parameter uncertainty, which means that even if some parameters can be estimated precisely, the overall conclusion remains highly unreliable.
60%UnverifiedThe pragmatic path for policymakers is: for problems dominated by parameter uncertainty, give range estimates and annotate assumptions; for problems dominated by model uncertainty, prioritize scenario narratives and robustness analysis rather than single-point probabilities.
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