Conceptualizing Autonomy in an Era of Collective Data Processing: From Theory to Practice

Abstract

While literature has already recognized the relational and collective impact of data processing, there is still limited understanding of how this affects the design of legislative instruments. We submit that legislators must recognize trade-offs between one’s own interests, the interests of other individuals, and collective or societal interests more explicitly in regulating data. To frame our analysis, we rely on a twofold definition of autonomy as a notion that inherently requires positioning oneself within a broader context with others. While the inward-looking dimension of autonomy focuses on the ability of an individual to make free and independent decisions in her own interests, the outward-looking dimension considers the relationship of one’s choices with other individuals’ and collective interests.Building on this working definition of autonomy, we assess three legislative instruments, namely the General Data Protection Regulation, the Digital Markets Act and the Data Act proposal, to identify to what extent this multi-dimensional nature of autonomy is reflected in the design of data-related obligations. We examine how legislators can make trade-offs between different interests explicit and thereby bring the regulation of data more in line with the current societal reality that is increasingly dominated by relational and collective effects of data processing.