Thursday, April 8, 2021
Andrew Blair-Stanek (Maryland; Google Scholar) & Benjamin Van Durme (Johns Hopkins; Google Scholar), AI for Tax Analogies and Code Renumbering, 170 Tax Notes Fed. 1997 (Mar. 29, 2021):
Blair-Stanek and Van Durme present an artificial intelligence tool that can complete analogies in tax law and provide evidence-based guidance on how Congress can renumber IRC sections in future tax reform efforts.
We have described two limited applications of AI in tax law, but we and other researchers are pursuing many others. New models with millions of mathematical neurons approximating the neurons in the human brain promise much more power than the model we used here. Moreover, all AI models rely on data; having more data and higher-quality data is always better. The full Tax Analysts Federal Research Library, just released under an agreement between Tax Analysts and Deloitte Tax LLP, contains extensive, very high-quality tax law text. This combination of more powerful models with more and better data is reason for optimism that AI will result in many more tools to aid tax practitioners and policymakers.