Personal Data, Exploitative Contracts, and Algorithmic Fairness: Autonomous Vehicles Meet the Internet of Things

Abstract

Personal data harvested in the Internet of Things not only promises to be particularly valuable, but also particularly privacy-sensitive. Analysed with the power of specialized Artificial Intelligence, such data allows for potentially beneficial personalization of goods and services; however, it also facilitates data-driven exploitative contracting. For example, autonomous and connected vehicles (ACVs), epitomizing the merger of Artificial Intelligence with the Internet of Things, are collecting ever increasing amounts of personal data. From an economic perspective, the processing of this data by ACV operators is ambivalent, enabling innovative driving and safety features in a personalized version of autonomous driving, but also exploitative contracts tailored to profit from the vulnerabilities of data subjects. A key regulatory conundrum at the intersection of Artificial Intelligence with the Internet of Things therefore consists in facilitating socially beneficial innovation while reining in exploitative contracts. Current EU data protection, contract and tort law, however, arguably fail to rein in data-driven exploitative contracts. Therefore, three novel interventions aiming to infuse greater fairness into the code of the digital economy are discussed: (a) mandatory “data safe” alternatives; (b) personalized data protection; and (c) procedural rules on algorithmic fairness.

Keywords: algorithmic fairness; automated decision making; autonomous and connected vehicles; data-driven exploitative contracts; data as currency; personalization; proposed Directive concerning contracts for the supply of digital content; proposed Directive concerning contracts for the online and other dista

JEL Classification: K00, K12, K13, L11, L14, L21, L98