Tracking technologies, identifiability, and privacy regulations

Technology companies have made billions of dollars surveilling people through online cookies, smart devices, and algorithms, yet there is no consensus on whether privacy laws should intervene. Transnational privacy laws’ responses to these privacy concerns depend upon the underlying identifiability of information; that is, whether data can be exclusively linked to a person. As a general rule, no violation of privacy legally occurs unless data are personally identifiable. There are two puzzles in applying identifiability in the context of the commercial use of tracking technologies (CUTTs). First, companies can single out a unique individual by combining non-identifiable data. In isolation, these data do not cause privacy concerns. But in combination, they can potentially cause privacy harms. Second, there exist diverging approaches to applying identifiability across jurisdictions. Different jurisdictions have opposite opinions on whether the same data should be treated as identifiable. After surveying statues and cases in the EU, U.S., and China, I found divergent and incompatible ways to categorize identifiable data. I call these common difficulties on defining and applying identifiability across jurisdictions the identifiability problem. This dissertation explains why jurisdictions are struggling to protect privacy through regulating CUTTs. CUTTs pose profound challenges to privacy that multiple jurisdictions remain unable to adequately address. As a comparative legal study, this dissertation discusses the similarities and differences in privacy laws in the EU, U.S., and China regarding CUTTs and the shared struggles to regulate CUTTs these jurisdictions face.

Name thesis:degree_name

J.S.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Law

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Yu, Xiaowei

Contributors dc:contributor

• Murphy, Colleen
• Hurd, Heidi
• Rowell, Arden
• Kar, Robin

• Tracking
• Technologies
• Privacy
• Identifiability

Statement dc:rights

• Copyright 2022 Xiaowei Yu

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/116143

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F116143