Akıllı ev cihazları ev işçilerinin mahremiyetini nasıl tehdit ediyor
Yeni bir araştırma, AI destekli akıllı ev cihazlarının ev işçileri için oluşturduğu gizlilik risklerini sosyoteknik bir tehdit modeliyle inceliyor.
A research team conducted semi-structured interviews with 18 UK-based domestic workers to examine the privacy risks posed by AI-driven smart home devices. Using Communication Privacy Management (CPM) theory, the study reveals that domestic workers face constant surveillance in employers' homes while encountering different types of challenges in their own households.
The research extends traditional threat models by showing how AI analytics, residual device data logs, and data flows across multiple households shape privacy risks. In employer-controlled homes, AI-enabled features combined with opaque agency-mediated employment relationships intensify surveillance and limit workers' ability to negotiate privacy boundaries. In their own homes, while participants have more control as device owners, they still face significant issues including gendered administrative roles, opaque AI functionalities, and uncertainty about data retention practices.
The researchers synthesized these findings into a sociotechnical threat model that identifies domestic worker agencies as institutional adversaries and maps AI-driven privacy risks across interconnected households. This work carries an important message for engineers and designers: smart home systems should be designed considering not just a single user or household, but the diverse social roles and power dynamics that devices indirectly affect. Set to be presented at USEC 2026, the study offers a new perspective on privacy-focused design practices.