Alarie & Griffin on Using Machine Learning to Crack the Tax Code

Benjamin Alarie (University of Toronto – Faculty of Law) and Bettina Xue Griffin (Blue J Legal) have posted “Using Machine Learning to Crack the Tax Code” (Tax Notes Federal, January 31, 2022, p. 661) on SSRN. Here is the abstract:

In this article, we provide general observations about how tax practitioners are beginning to learn how to leverage the insights of machine learning to “crack the tax code.” We also examine how tax practitioners are using machine learning to quantify risks for their clients and ensure that tax advice can properly withstand scrutiny from the IRS and the courts. The goal is to guide tax experts in their tax planning and to help them devise the most effective ways to resolve tax disputes, leveraging new tools and technologies.