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When AI Does the Work, What Is Learning For? Post-Instrumental Learning and the Risk of Capacity Dissolution

Yao, Kai
arXiv (All) · Papers
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computers-and-society
As AI systems become capable of producing the essays, code, reports, summaries, plans, and decisions through which institutions usually recognize competence, a familiar question becomes harder to answer: what is learning for? Existing AI ethics rightly emphasizes present failures--bias, opacity, hal
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