Sociotechnical Threat Model Identifies Privacy Risks for Domestic Workers Using Smart Devices

Research Overview

The study conducted semi-structured interviews with 18 domestic workers (DWs) in the UK to analyze the effects of AI-driven smart home devices on their privacy. The researchers employed a human-centered threat modeling framework to assess experiences relating to Communication Privacy Management (CPM).

Key Findings

The analysis extended the traditional threat models by considering the impact of AI analytics, residual data logs, and cross-household data flows. It found that in employer-controlled households, the use of AI-enabled features heightened surveillance of DWs, impacting their ability to negotiate privacy boundaries.

Challenges in Domestic Workers' Own Homes

While DWs had greater control over their smart devices at home, they faced unique challenges, such as gendered administrative roles and lack of transparency regarding functionalities and data retention policies of the devices.

Sociotechnical Threat Model

The study formulates a sociotechnical threat model that identifies Domestic Worker agencies as institutional adversaries. This model maps how AI-driven privacy risks persist across interconnected households, revealing broad implications for data control and privacy negotiation.

Implications for Privacy

The study suggests practical and social recommendations to strengthen privacy and agency for domestic workers, emphasizing the need for clearer data management processes and awareness of surveillance risks associated with smart home technologies.