The content in this collection is available only to Washington University in St. Louis users.
Date of Award
Spring 2026
Degree Name
Doctor of Juridical Science (SJD)
Degree Type
Dissertation
Abstract
Precision medicine now advances on vast flows of personal health data, much of which moves through consumer applications, analytic platforms, and research pipelines that lie outside the clinical settings the law was built to govern. A widening gap follows. The same information about a person receives careful protection inside a hospital and almost none once it passes to a wellness app or an algorithmic inference engine. This dissertation diagnoses that gap as a problem of power rather than of consent, and asks how the law can hold institutions to account when they exercise discretionary control over data that can shape a person’s care, opportunities, and standing. In answer, the dissertation develops an institutional architecture built on three connected mechanisms. The first extends enforceable obligations to health data beyond the entities that HIPAA currently reaches. The second establishes a health data trust that separates stewardship of the data from the commercial interests of the platforms that use it. The third defines a set of restriction rights that balance individual control against the collective value of health data for research and public health. Taiwan’s National Health Insurance system, with comparative material from the European Union and other Asia-Pacific jurisdictions, shows that stewardship insulated from commercial pressure can operate at scale. The dissertation also takes up the constitutional objection that regulating data flows regulates speech, and argues that the governing authority is narrower than commonly supposed, leaving a residual concern of deterrence rather than invalidation. Together, the chapters offer a structural answer to a structural problem: governing health data by the obligations institutions owe, not by the place in which the data happens to sit.
Chair and Committee
Prof. Neil Richards, supervising professor; Prof. Rachel Sachs, examining professor; Prof. Charlotte Tschider, examining professor.
Recommended Citation
Liu, Hsuan Yu, "Exploring ethical frontiers in AI-driven precision medicine: the power dynamics of Big Data privacy and governance" (2026). School of Law Dissertations. 110.
https://openscholarship.wustl.edu/law_etds/110