A causal framework unifies fairness analysis across generative AI and standard ML by deriving decompositions that separate biases along causal pathways and differences between real-world and model mechanisms.
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Causal Bias Detection in Generative Artifical Intelligence
A causal framework unifies fairness analysis across generative AI and standard ML by deriving decompositions that separate biases along causal pathways and differences between real-world and model mechanisms.