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A comparison of this taxonomy to the AI Incident Database revealed substantial gaps in coverage, definitions, and prevalence between documented and litigated harms, suggesting courts capture only p","title":"Visible to the Court: How AI Is (and Isn't) Litigated in U.S. Federal Court Opinions","url":"https://arxiv.org/abs/2607.23888","vendor":"arxiv_cs_ai"},"summary":"arXiv:2607.23888v1 Announce Type: cross \nAbstract: In the United States, artificial intelligence (AI) is rapidly deployed amid limited federal regulation. With courts become a recurring forum in which AI-related practices are scrutinized, it is important to empirically understand the AI litigation landscape to date. We address this gap through a systematic review of 559 U.S. federal court opinions in which AI plays a role in the parties' contentions, taxonomizing (1) common topics of dispute, (2) the AI technologies implicated, and (3) the parties involved, including common plaintiff and defendant types. 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