Proposes an OS-centered privacy framework for on-device AI that treats privacy as institutional accountability, including a threat model, six-part risk taxonomy, privacy-by-architecture controls, and four-level audit rubric demonstrated on Apple, Android, and Microsoft systems.
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Local Is Not a Sufficient Privacy Boundary: Governing OS-Integrated On-Device AI
Proposes an OS-centered privacy framework for on-device AI that treats privacy as institutional accountability, including a threat model, six-part risk taxonomy, privacy-by-architecture controls, and four-level audit rubric demonstrated on Apple, Android, and Microsoft systems.