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Contextual auditing reveals hidden assumptions in AI evaluations, transforming how we assess systems when ground truth is elusive.
Ignoring the social dynamics that led to past disasters could doom AI systems to repeat history's mistakes.
Inconsistent validation practices for LLM-generated measurements could undermine the integrity of social science research, highlighting an urgent need for improved standards.
