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VTechWorks provides global access to Virginia Tech scholarship, including journal articles, books, theses, dissertations, conference papers, slide presentations, technical reports, working papers, administrative documents, videos, images, and more by faculty, students, and staff. Faculty can deposit items to VTechWorks from Elements, including journal articles covered by the University open access policy. Email vtechworks@vt.edu for help.

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“Alexa, I’m home!” intimate surveillance, care, and control in AI-enabled homes and bodies

Brantly, Nataliya D. (Springer, 2026-04)

As artificial intelligence (AI) increasingly mediates everyday life, its expansion into intimate spaces produces new configurations of surveillance that blur the boundaries between care, necessity, and control. While smart home and digital health technologies are widely promoted as tools of safety and well-being, they embed pervasive forms of surveillance that remain underexamined. This paper analyzes how AI-enabled infrastructures govern intimate life through data extraction, algorithmic inference, and corporate control. Drawing on the combined theoretical lenses of surveillance capitalism and biopolitics, it conceptualizes smart homes and digital health systems as sites of marketized biopower, where corporate actors increasingly manage domestic routines and bodily processes. Using a structured critical-comparative analysis of two analytically complementary cases, the Ring Doorbell and the Dexcom continuous glucose monitor (CGM), the study traces how similar data logics operate across distinct domains of intimacy: domestic and bodily. The analysis demonstrates that, despite differences in function, regulation, and perceived necessity, both technologies centralize control under corporate infrastructures. In both cases, care operates as a governance strategy that legitimizes surveillance, normalizes dependency, and reframes autonomy as responsible participation in proprietary systems. The paper concludes by identifying ethical vulnerabilities and calling for AI governance frameworks attentive to intimacy, dependency, and predictive control, rather than privacy protections alone.