Article by Dr. Anat Lior
Network theory holds great unappreciated value when it comes to analyzing and confronting new legal issues induced by emerging technologies. It can assist regulators, judges, and insurers to visualize multifaceted legal questions in a manner that helps them to better understand the complexity of new legal enquiries and the appropriate policy intervention. A complex challenge the legal realm faces today is that of Artificial Intelligence (AI) liability. This Article will utilize network theory in this context. It will do so by combining network theory's features with George Fletcher's nonreciprocal risks paradigm. This combination will provide essential tools that will show that a strict liability regime is the best-suited regime to apply when AI causes harm and will provide indicators to identify the entity who should be held strictly liable.
Fletcher's nonreciprocal paradigm was heavily criticized upon its emergence. Guido Calabresi's cheapest-cost avoider strict liability approach eventually became the prominent approach in the context of strict liability. However, this Article argues that today's network economy and networked society offer a new opportunity for this paradigm to be applied given the new ways in which we interact and inflict damages upon each other, which were not feasible in the past. This Article integrates network theory into the field of AI tort law for the first time. It presents a new and unique methodology to the ongoing dispute about the appropriate liability regime that should apply when AI causes damages.
About the Authors
Dr. Anat Lior, Post-doc fellow at the Information Society Project at Yale Law School.
Citation
95 Tul. L. Rev. 1103 (2021)