Adam Rosenzweig (Washington U.), Big Data and Small Politics: What Is the Future of International Tax Law? (JOTWELL) (reviewing Shu-Yi Oei (Boston College) & Diane Ring (Boston College), When Data Comes Home: Next Steps in International Taxation’s Information Revolution, 64 McGill L. Rev. 707 (2019)):
In my experience, the hallmark of a good article is that, after struggling through a few close reads, I eventually (at times somewhat begrudgingly) conclude I learned something new and valuable. The hallmark of a great article, on the other hand, is when I reach the same conclusion but after a single, almost effortless feeling, read. The difference is a precision and clarity in writing, structure, and organization that only the confidence instilled from a deep understanding of a subject affords. Yet at the same time a small part thinks to myself — “it seems so obvious, why didn’t I think of it?” But of course, to paraphrase a famous movie line, “if I really had come up with the idea, then I would have written it.” But, as I eventually admit to myself, I didn’t.
Such was my experience reading When Data Comes Home: Next Steps in International Taxation’s Information Revolution (“When Data Comes Home”) by Shu-Yi Oei and Diane Ring. Oei and Ring are frequent co-authors, writing on subjects ranging from taxation of the sharing economy like Uber and AirBnB, to the role of large scale financial information leaks like the Panama Papers, to the impact of the Tax Cuts and Jobs Act on reshaping the workplace environment. I mention this only to emphasize what emerges as the particular strength of Oei and Ring’s collaborations — they combine backgrounds and methodologies and apply them to areas of common interest to uncover patterns or trends that otherwise might remain hidden. When Data Comes Home represents another successful example.
No matter how persuasive the article, one might be skeptical of their ultimate conclusion that data produced by international tax reporting rules and agreements will reshape domestic law. In particular, I am not fully convinced that the revolution they describe is a function of reforms in the international tax regime instead of a symptom of introducing Big Data into law more generally. For example, many proponents of big data claimed it could help root out implicit bias from hiring decisions by replacing human managers, many of whom may not identify or acknowledge their implicit bias, with algorithms that mine data which they claim would only include factors relevant to job performance. While this is appealing on its face, unfortunately the problem is that it turns out Big Data also incorporates any implicit or systemic bias within the system generating the data. Much like TwitterBots that quickly become racist in response to the data they receive on Twitter, neutral algorithms can spit out biased results if the society in which they are built is biased.