Articles Tagged with Structural bias

EXECUTIVE SUMMARY:

Professor Peter Lee’s VERDICT essay argues that synthetic data may revolutionize AI development by providing scalable, legally safer training material. Yet he warns that artificial datasets introduce new risks such as model collapse, bias, and misuse that demand proactive legal oversight. Rather than replacing existing regulatory debates, synthetic data transforms them, requiring courts, policymakers, and information professionals to rethink how innovation, privacy, and intellectual property intersect in the AI era

BETTER THAN THE REAL THING?

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