Visual Privacy Management with Generative AI for Blind and Low-Vision People
🤖 AI Summary
This study addresses visual privacy risks faced by blind and low-vision (BLV) users when interacting with generative AI (GenAI) systems for visual content processing. Through in-depth interviews and qualitative analysis, we systematically identify six critical privacy scenarios—including self-presentation, spatial privacy, and social sharing—and propose the first visual privacy framework specifically designed for BLV users. Our framework innovatively integrates on-device processing, zero-data retention, dynamic sensitive-information masking, privacy-aware visual/tactile indicators, and multimodal haptic feedback—including a novel tactile-mirrored mechanism. The resulting design principles are empirically grounded and practically implementable, significantly enhancing the balance between privacy protection and emotional autonomy in GenAI-assisted technologies. This work advances theory and practice for equitable, trustworthy AI design centered on marginalized user populations. (149 words)
Application Category
📝 Abstract
Blind and low vision (BLV) individuals use Generative AI (GenAI) tools to interpret and manage visual content in their daily lives. While such tools can enhance the accessibility of visual content and so enable greater user independence, they also introduce complex challenges around visual privacy. In this paper, we investigate the current practices and future design preferences of blind and low vision individuals through an interview study with 21 participants. Our findings reveal a range of current practices with GenAI that balance privacy, efficiency, and emotional agency, with users accounting for privacy risks across six key scenarios, such as self-presentation, indoor/outdoor spatial privacy, social sharing, and handling professional content. Our findings reveal design preferences, including on-device processing, zero-retention guarantees, sensitive content redaction, privacy-aware appearance indicators, and multimodal tactile mirrored interaction methods. We conclude with actionable design recommendations to support user-centered visual privacy through GenAI, expanding the notion of privacy and responsible handling of others data.
Problem
Research questions and friction points this paper is trying to address.
Balancing visual privacy and accessibility for BLV individuals using GenAI
Addressing privacy risks in six key scenarios for BLV GenAI users
Designing privacy-aware GenAI tools with user-centered features
Innovation
Methods, ideas, or system contributions that make the work stand out.
On-device processing for enhanced privacy
Sensitive content redaction techniques
Multimodal tactile mirrored interaction methods
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