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Non-Autonomous Artificial Intelligence Programs And Products Liability: How New Ai Products Challenge Existing Liability Models And Pose New Financial Burdens, Greg Swanson
Seattle University Law Review
This Comment argues that the unique relationship between manufacturers, consumers, and their reinforcement learning AI systems challenges existing products liability law models. These traditional models inform how to identify and apportion liability between manufacturers and consumers while exposing litigants to low-dollar tort remedies with inherently high-dollar litigation costs.11 Rather than waiting for AI autonomy, the political and legal communities should be proactive and generate a liability model that recognizes how new AI programs have already redefined the relationship between manufacturer, consumer, and product while challenging the legal and financial burden of prospective consumer-plaintiffs and manufacturer-defendants.
Confiding In Con Men: U.S. Privacy Law, The Gdpr, And Information Fiduciaries, Lindsey Barrett
Confiding In Con Men: U.S. Privacy Law, The Gdpr, And Information Fiduciaries, Lindsey Barrett
Seattle University Law Review
In scope, ambition, and animating philosophy, U.S. privacy law and Europe’s General Data Protection Regulation are almost diametric opposites. The GDPR’s ambitious individual rights, significant prohibitions, substantive enforcement regime, and broad applicability contrast vividly with a scattershot U.S. regime that generally prioritizes facilitating commerce over protecting individuals, and which has created perverse incentives for industry through anemic enforcement of the few meaningful limitations that do exist. A privacy law that characterizes data collectors as information fiduciaries could coalesce with the commercial focus of U.S. law, while emulating the GDPR’s laudable normative objectives and fortifying U.S. consumer privacy law with a …