The Promises and Perils of Using Big Data to Regulate Nonprofits

Abstract

For the optimist, government use of “Big Data” involves the careful collection of information from numerous sources. The government then engages in expert analysis of those data to reveal previously undiscovered patterns. Discovering patterns revolutionizes the regulation of criminal behavior, education, health care, and many other areas. For the pessimist, government use of Big Data involves the haphazard seizure of information to generate massive databases. Those databases render privacy an illusion and result in arbitrary and discriminatory computer-generated decisions. The reality is, of course, more complicated. On one hand, government use of Big Data may lead to greater efficiency, effectiveness, and transparency; on the other hand, such use risks inaccurate conclusions, invasions of privacy, unintended discrimination, and increased government power. Until recently, these were theoretical issues for nonprofits because federal and state regulators did not use Big Data to oversee them. But nonprofits can no longer ignore these issues, as the primary federal regulator is now emphasizing “data-driven” methods to guide its audit selection process, and state regulators are moving forward with plans to create a single, online portal to collect required filings. In addition, regulators are making much of the data they collect available in machine-readable form to researchers, journalists, and other members of the public. The question now is whether regulators, researchers, and nonprofits can learn from the Big Data experiences of other agencies and private actors to optimize the use of Big Data with respect to nonprofits. This Article explores the steps that nonprofit regulators have taken toward using Big Data techniques to enhance their ability to oversee the nonprofit sector. It then draws on the Big Data experiences of government regulators and private actors in other areas to identify the potential promises and perils of this approach to regulatory oversight of nonprofits. Finally, it recommends specific steps regulators and others should take to ensure that the promises are achieved and the perils avoided.

Keywords: nonprofit, tax, IRS, big data

JEL Classification: K22, K34, L31