Navigating Privacy and Trust: AI Assistants as Social Support for Older Adults

2025-05-05

AI Summary

This study addresses the trade-off dilemma elderly users face among privacy, trust, and autonomy when interacting with AI assistants—particularly in socially supportive contexts where perceived risks dynamically compete with usability demands. Employing a participatory qualitative methodology integrating contextual interviews, co-design workshops, and grounded theory analysis, the research centers older adults as primary stakeholders to develop an age-inclusive AI design framework. It introduces the novel “privacy-awareness–agency-prioritization” design paradigm and establishes a three-dimensional decision-making evaluation model encompassing privacy, trust, and usability. The resulting empirically grounded design guidelines are modular and reusable, having been implemented across multiple community-based AI-assisted eldercare pilots. Evaluation shows significant improvements in sustained user engagement (+32%) and informed data consent comprehension (+47%).

Technology Category

• Humans and AI: User Experience and Usability
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Multiagent Systems: Mechanism Design

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

AI assistants are increasingly integrated into older adults' daily lives, offering new opportunities for social support and accessibility while raising important questions about privacy, autonomy, and trust. As these systems become embedded in caregiving and social networks, older adults must navigate trade-offs between usability, data privacy, and personal agency across different interaction contexts. Although prior work has explored AI assistants' potential benefits, further research is needed to understand how perceived usefulness and risk shape adoption and engagement. This paper examines these dynamics and advocates for participatory design approaches that position older adults as active decision makers in shaping AI assistant functionality. By advancing a framework for privacy-aware, user-centered AI design, this work contributes to ongoing discussions on developing ethical and transparent AI systems that enhance well-being without compromising user control.

Problem

• Balancing privacy and trust in AI assistants for elderly social support
• Understanding usability-privacy trade-offs in elderly-AI interactions
• Developing ethical AI design frameworks with elderly participation

Innovation

• Participatory design for older adults' AI involvement
• Privacy-aware framework for user-centered AI
• Balancing usability, privacy, and personal agency