Changing technologies render tax law’s intricacy legible in new ways. Advances in large language models, natural language processing, and programming languages designed for the domain of tax law make formalizations, or “representation[s] of [ ] legislation in symbols[ ] using logical connectives,” of tax law that capture much of its substance and structure both possible and realistic. These new formalizations can be used for many different purposes—what one might call flexible formalizations. Flexible formalizations will make law subject to computational analysis, including creating automated explanations of the analysis and testing statutes for consistency and unintended outcomes. This Essay builds upon existing work in computational law and digitalizing legislation.
Tax Law
The Douglas Clark and Ruth Ann McNeese Faculty Research Fund at the University of Chicago Law School provided financial support for this project. For helpful comments, the authors thank Leslie Book, David Gamage, Eric Hemel, Kevin Kennedy, Benjamin Leff, Elisabeth Mayer, Susan Morse, Anna Stapleton, André Washington, Matt Zwolinski, Lawrence Zelenak, participants at the Brigham Young University Law School Tax Policy Colloquium, the Duke University School of Law Tax Policy Colloquium, the 2018 National Tax Association Annual Meeting, and editors of The University of Chicago Law Review.
The notion of a universal basic income, or UBI, has captivated academics, entrepreneurs, policymakers, and ordinary citizens in recent years. Across the globe, countries ranging from Brazil to Finland, the Netherlands, Italy, Kenya, Uganda, and Canada are conducting or have recently concluded pilot studies of a UBI.
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