Jennifer King is a privacy and data-policy researcher at the Stanford Institute for Human-Centered AI (Stanford HAI). Her work addresses AI privacy questions, including training-data privacy, consumer-AI privacy frameworks, and the relationship between federal and state AI privacy regulation.
Background
King holds a PhD in Information Management & Systems from UC Berkeley. She works at Stanford HAI (Stanford HAI), where her research focuses on privacy and data policy as they apply to AI systems.
Positions and statements
On training-data privacy, King has written on the application of US state privacy law to AI training-data sourcing, work relevant to the Bartz v. Anthropic and Hachette et al. v. Meta (and Mark Zuckerberg) cases.
On consumer-AI privacy, she has addressed consumer-AI privacy disclosure questions, which bear on the inference-time-privacy dimension of AI and Privacy.
On the federal-versus-state question, her Stanford HAI publications address federal AI privacy preemption, relevant to the context of EO — Trump Federal Preemption of State AI Laws (Dec 11, 2025).
Relationships
- related: AI and Privacy, AI Content Licensing.
- related: Data Privacy and Foundation Models: Can We Have Both? — King & Saade (Stanford HAI Issue Brief, April 2026), Toward Responsible AI in Health Insurance Decision-Making — Mello, Trotsyuk, Djiberou Mahamadou, Char (Stanford HAI Policy Brief, February 2026).
- related: Stanford HAI.
Sources
Stub created 2026-05-11.