Algorithmic inference of psychological traits escapes General Data Protection Regulation (GPDR) protection unless treated as data collection subject to data minimization.
Author
Divyam Krishna, Jindal Global Law School, O.P. Jindal Global University, Sonipat, Haryana, India
Summary
The consensus from the techno-legal literature is that the standing provisions of the General Data Protection Regulation (GDPR) do not offer meaningful protections against legal harms arising from the process of algorithmic inferences of psychological traits. However, this literature presupposes that the computational processes of inference and collection of personal data deserve separate legal treatments. This opinion makes the provocative argument that despite being computationally distinct, these two processes must be treated as legally equivalent and accordingly, inter alia, algorithmic inferences must be subjected to the rigours of data minimization in the same way as collection of personal data within the GDPR. In this process, this opinion takes a first principles approach to furnish the necessary taxonomy and conceptual underpinnings to ground the legal logic behind recent decision of the Court of Justice of the European Union (CJEU) in Maximilian Schrems v. Meta Platforms.
Published in: Global Privacy Law Review
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