About | HeinOnline Law Journal Library | HeinOnline Law Journal Library | HeinOnline

LOG IN
LOG IN


17 Colum. J. Tax L. 1 (2025-2026)

handle is hein.journals/colujoutl17 and id is 1 raw text is: SHARING THE ALGORITHM: THE TAX SOLUTION TO GENERATIVE Al Jeremy Bearer-Friend* & Sarah Polcz** Tax policy offers a core tool for mitigating the sweeping public policy challenges of generative artificial intelligence (AI). Specifically, we propose a tax that would allow the public to own a share of AI itself not just through future income tax liabilities or new excise taxes, but a proposed ownership structure that requires a one-time tax payment by generative AI frms in the form of equity. Fractional public ownership of AI would directly address four of the key harms of AI that have been well-documented in a deep and still expanding literature. First, many types of AI were built through the unauthorized use of millions of copyrighted works, allegedly amounting to copyright infringement on an unprecedented scale. Sharing ownership of AI would compensate injured creators alongside the broader public whose data was nonconsensually harvested. Second, AI is expected to pose massive labor market disruptions, but shared ownership would allow displaced workers to benefit from the profits of the technology substitutingfor their labor. Third, greater public voice in the corporate governance of AI could lead to greater scrutiny and bolder interventions in the ways AI has been shown to reproduce and compound many existing forms of discrimination. Finally, sharing the ownership of AI through government's principal tool for redistribution, taxation, directly addresses the rapid wealth concentration and monopolization already underway with AI developers. This proposal can also work in tandem with targeted regulation of AI and private law remedies addressing Al's many harms. Ultimately, the original contribution of this Article is to propose a unique in-kind taxpayment structure that would require firms with ownership ofAI to remit equity shares to the public. The Article describes multiple structures for this arrangement, drawing from existing models offractional ownership used in private investment to serve as a paradigm for a partial public interest in AL. In total, this Article argues that many of the greatest concerns related to AI can be solved through sharing AL. And tax policy is the best tool to achieve this goal. Associate Professor of Law, George Washington University Law School. ** Acting Professor of Law, UC Davis School of Law. The authors thank Adam Brown, Bill Dodge, David Gamage, Lula Hagos, Michael Love, Jared Mayer, Jeremy McClane, Beverly Moran, Spencer Overton, Alicia Solow-Niederman, Alex Raskolnikov, Naomi Schoenbaum, Darien Shanske, Tania Valdez, Juan Manuel Vazquez, and the participants of the Securities Law Section Panel at the 2025 AALS Conference, the Columbia University Tax Policy Colloquium, the University of Missouri Tax Policy Colloquium, GW Law Faculty Workshop, the Tax Research Network 2024 Conference, Villanova Law School Faculty Workshop, the UC Davis Summer Workshop Series, and the Amsterdam Center for Tax Law at the University of Amsterdam, for their generous comments and questions. Thank you also to Colton Diges, Charlotte Knaggs, and Sam Traina for excellent research assistance.