Algorithmic Regulation and (Im)perfect Enforcement in the Personalized Economy

Abstract

Technological advances in data collection and information processing makes it possible to tailor legal norms to specific individuals and achieve an unprecedented degree of regulatory precision. However, the benefits of such a “personalized law” must not be confounded with the false promise of “perfect enforcement”. To the contrary, the enforcement of personalized law might be even more challenging and complex than the enforcement of impersonal and uniform rules. Starting from this premise, the first part of this Essay explores how algorithmic personalization of legal rules could be operationalized for tailoring disclosures on digital marketplaces, mitigating discrimination in the sharing economy and optimizing the flow of traffic in smart cities. The second part of the Essay looks into an aspect of personalized law that has so far been rather under-researched: a transition towards personalized law involves not only changes in the design of legal rules, but also necessitates modifications regarding compliance monitoring and enforcement. It is argued that personalized law can be conceptualized as a form of algorithmic regulation or governance-by-data. Therefore, the implementation of personalized law requires setting up a regulatory framework for ensuring algorithmic accountability. In a broader perspective, this Essay aims to create a link between the scholarly debate on algorithmic decision-making and automated legal enforcement and the emerging debate on personalized law.

Keywords: Personalized Law, Granular Law, Algorithmic Regulation, Algorithmic Accountability, Big Data

JEL Classification: K10, K12, K40, K42