The Relevance of Value Decisions in Data Protection Law

• Jules Polonetsky

As data protection law increasingly intersects with other public interests including competition, innovation, free expression and research, regulators and courts are confronting difficult value choices. This article examines how recent disputes, from Apple’s App Store controls to Google’s Privacy Sandbox and AI training practices, expose the inherent balancing function of data protection law. While European regulators show flexibility toward AI developers processing massive amounts of personal data, they maintain stricter standards for ad-tech and social media platforms, revealing implicit hierarchies of value. The paper builds on the fact that data protection is not an absolute right but a framework for reconciling competing interests through proportionality, necessity and benefit assessment, a logic shared, albeit differently, by the U.S. Federal Trade Commission’s “unfairness” standard. By tracing these convergences, the article proposes greater transparency and institutionalization of “value balancing” within AI and data governance regimes to ensure coherence, fairness and accountability across regulatory contexts.