arXiv:2606.10173v1 Announce Type: cross Abstract: As AI systems move into operating systems, privacy no longer turns only on whether a model runs locally. A local assistant may assemble email, calendar entries, files, screenshots, notifications, and app intents; retain embeddings or summaries; invoke tools; emit telemetry; or route difficult requests to cloud infrastructure. Local inference reduces some exposure, but it answers only one question: where computation occurs. It does not answer who may assemble context, what derived state persists, which actions are authorized, or how updates chan
As AI models advance and become integrated more deeply into operating systems, the question of data privacy and control becomes critically important, moving beyond simplistic notions of 'local' processing.
This paper redefines the understanding of privacy in OS-integrated AI, highlighting complex data flows and potential exposures even in local systems, which is crucial for governance, design, and user trust.
The definition of 'private' for on-device AI shifts from merely where computation occurs to a more nuanced consideration of data assembly, persistence, authorization, and cloud interactions.
- · Privacy-focused AI developers
- · Operating system vendors with robust privacy controls
- · Regulation and compliance sectors
- · Users prioritizing data privacy
- · AI developers ignoring privacy implications
- · Cloud infrastructure reliant on broad data access
- · Operating systems with poor data governance models
Increased emphasis on granular data governance and access controls within operating systems hosting AI features.
Development of new privacy-enhancing technologies and architectural patterns for on-device AI that address derived state and tool invocation.
Potential for new regulatory frameworks specifically addressing the 'local but not private' dilemma of integrated AI, impacting software design and market access.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI