AI benchmark illusion: human consensus gold standard is untested, viewpoint argues

AI often matches/exceeds human diagnostic performance, but evaluation clings to human consensus gold standards that are themselves error-prone—a 'benchmark illusion.' Viewpoint calls for explicit uncertainty modeling and outcome-based validation.

• Current evaluation frameworks treat human consensus on curated datasets as ground truth despite known cognitive bias and interobserver variability.
• The article argues for outcome-based validation and using AI as an additional reference layer to assess human performance.

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