Against Data Fixation: why “Data” Fails as a Regulatory Target for Data Protection Law and What to Do About It

Publication date

2026-03

Authors

Purtova, N. AdezhdaISNI 0000000359730748
Newell, BryceORCID 0000-0002-6096-1175ISNI 0000000475348001

Editors

Advisors

Supervisors

Document Type

Article
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License

taverne

Abstract

This article critiques the fixation on data as an object of regulation for addressing a broad range of digital problems. We challenge the idea that data are always the appropriate regulatory targets for addressing information-related problems, specifically in the context of data protection and the General Data Protection Regulation (GDPR). The GDPR tackles a broad range of digital problems by regulating personal data. This results in regulatory imprecision. Framing digital problems as (personal) data problems often does not reflect the causal processes law aims to control, pre-empts modernising traditionally non-digital legal domains, such as consumer and labour law, and distracts from what is really problematic and in need of regulatory intervention. Drawing on theories of regulation and information, we distinguish between two different causal processes underlying information-induced problems: semantic (meaning-driven) and syntactic (meaning-agnostic). We propose a roadmap for improving legal protection against information-related problems.

Keywords

reform of the GDPR, algorithmic harm, scope of the GDPR, theories of information, digital law, regulation of algorithms, Taverne, Law

Citation

Purtova, N & Newell, B 2026, 'Against Data Fixation: why “Data” Fails as a Regulatory Target for Data Protection Law and What to Do About It', Oxford Journal of Legal Studies, vol. 46, no. 1, pp. 171-200. https://doi.org/10.1093/ojls/gqaf038