The Human Creativity Benchmark – Evaluating Generative AI in Creative Work

1.0IntroductionWhen professional creatives evaluate AI-generated work, their judgments produce two distinct signals. The first is convergence: evaluators agree on what works, revealing shared best practices like readable typography, functional layout, and correct visual hierarchy. The second is divergence: evaluators disagree, and that disagreement reflects genuine differences in taste, aesthetic direction, and creative intent. Most AI benchmarks treat the second signal as noise to be resolved. This paper proposes a framework for measuring both.This distinction matters because creative work has no ground truth. The dimensions on which experts disagree — aesthetic direction, mood, conceptual risk — are not reducible to miscalibration or error [1][2].

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