Privacy Cards for Surfacing Mental Models and Exploring Privacy Concerns: A Case Study of Voice-First Ambient Interfaces with Older Adults

2026-02-27

AI Summary

This study addresses the privacy awareness gaps and informed consent challenges faced by older adults in voice-first ambient interfaces (VFAIs), stemming from insufficient mental models of data practices. For the first time, it introduces customized Privacy Cards tailored to older users, employing design probes, semi-structured interviews, and device usage logs to dynamically uncover their implicit privacy concerns and cognitive blind spots. Findings reveal that older adults generally struggle to differentiate between data access by built-in system functions and third-party applications, and while they initially express low levels of privacy concern, guided engagement elicits nuanced ethical reflections. These insights offer critical implications for age-inclusive privacy design in VFAIs, informing both interaction strategies and ethical considerations in voice-enabled technologies for aging populations.

Technology Category

• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Philosophy and Ethics of AI: Privacy & Security
• Machine Learning: Privacy

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Security and Privacy: Data transparency and provenance
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

We investigate the ethical and privacy implications of voice-first ambient interfaces (VFAIs) for aging in place through an in-depth engagement with five older adults. Our participants were in the process of becoming experienced VFAI users, and had used a VFAI-based design probe for health data reporting. We create and iteratively refine an interview protocol using Privacy Cards. We customize Privacy Cards by drawing on participants' previous interviews and device usage logs. Using Privacy Cards, we conduct interviews to surface their mental models, and explore their privacy concerns. We find insufficient mental models for proper consent. For example, participants did not know who could access their data, and experienced difficulty distinguishing built-in functionality from third-party apps. Participants initially expressed little worry about VFAI-related ethical concerns, but interviews with Privacy Cards revealed nuanced issues, resulting in various implications for future research and design.

Problem

• privacy
• voice-first ambient interfaces
• mental models
• older adults
• informed consent

Innovation

• Privacy Cards
• voice-first ambient interfaces
• mental models
• privacy concerns
• older adults