Nathaniel Swigart (J.D. 2025, North Carolina), Note, A New Age of Equity: Machine Learning and Equity in Tax Law, 29 Tex. Rev. L. & Pol. 145 (2024):

In recent years, major administrative agencies like the Internal Revenue Service have committed to using AI to modernize the application of the law. This change comes decades after legal scholars began to argue that the compelling power of machine-learning technology will reshape the legal system. While AI has forced scholars to reexamine the first principles of the law, AI scholarship has yet to grapple with the problem of equity: how to apply general laws justly to particular circumstances. While often dismissed as a jurisdictional artifact, equity scholars argue that equity is an enduring problem at the root of significant developments like the rise of the administrative state and the proliferation of standards in our jurisprudence. This paper is the first to explicitly consider AI’s impact on the problem of equity by exploring if administrative agencies’ use of machine learning can make laws apply more justly to particular circumstances. The problem of equity is apparent in the administration of tax law because the flexibility necessary to accommodate the law to specific situations is frequently abused by opportunists. This paper explores the history of the taxation of corporate redemptions to argue that the forces pushing equity out of the law may be counteracted by machine learning technology. Specifically, AI may reinvigorate institutional means of equity such as the IRS’s Private Letter Rulings, enabling a new age of equity.