Good Algorithms, Better Norms:How Algorithmic Tools Could Revive Disclosure Regulation

Abstract

During the past decades, societies have been greatly impacted by the impressive technological progress made in computer science. However, Artificial Intelligence and Machine Learning have not only become an indispensable part of our everyday lives, they also found their way into legal research: a small, but rapidly growing number of legal scholars are applying algorithmic methods in their research. Particularly the advances made in Natural Language Processing (NLP) have sparked a wave of innovative research approaches as scholars are now able to transform text into machine-readable data, which opens up a plethora of enticing research opportunities. In light of the relative novelty as well as the enormous potential of the Law & Tech field, this article provides guidance to scholars seeking to familiarize themselves with the Law & Tech scholarship. By organizing this new branch of legal research around four main research interests, I show how Law & Tech scholars are contributing to and revolutionizing legal science in different ways. To illustrate how algorithmic tools can reinvigorate classic subjects of legal research, I address a topic that has long been considered ‘dead’: disclosure regulation. An overview of the many different solutions to the shortcomings of such regulations presents support for the hypothesis that Law & Tech can contribute greatly to legal research. Nevertheless, I also identify the need for a more ‘comprehensive approach’ and thus conclude by outlining how algorithmic tools can be used in a holistic manner to address the failures of disclosures from the rulemaking in parliament to consumer screens.