Granular legal norms: Towards data-driven personalization of private law?

Against the background of the expanding debate about personalized law, this chapter explores several use cases of “granular legal norms” and analyses how the balance between individual fairness and legal certainty could be readjusted with the help of data analytics and AI. The chapter is structured as follows: Section II analyses the role of typifications as a characteristic feature of the traditional (impersonal) law from the perspective of legal theory as well as law and economics. We argue that the frequent use of legal typifications can be conceptualized as the answer to an information problem, a concession to the imperfections of a legal system administered by humans. Section III explains how the emergence of super-human capacities of information-processing through AI could make it possible to personalize the law and achieve a level of granularity that has hitherto been unprecedented on a large scale. As a consequence, granular legal norms could increase individual fairness without reducing legal certainty. The concept of personalized law is illustrated by examples from mandatory disclosures, negligence law and inheritance law. Section IV finally addresses possible limitations and objections, in particular privacy concerns and the principle of equality. Section V draws some conclusions.