Good algorithms, better rules: how algorithmic tools could revive disclosure regulation

Artificial Intelligence (Ai) and Machine Learning (Ml) have not only become an indispensable part of our everyday lives; they have also found their way into legal research. Indeed, a small, but rapidly growing, number of legal scholars are applying algorithmic methods in their research. In particular, 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 this new scholarship, and suggests organizing it around four main research interests. 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 supports the hypothesis that Law & Tech can make a great contribution 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 enactment of rules in Parliament to the appearance of information on consumer screens.