"Before, I Asked My Mom, Now I Ask ChatGPT": Visual Privacy Management with Generative AI for Blind and Low-Vision People

TL;DR

This paper explores how blind and low-vision users manage visual privacy with Generative AI, revealing current practices, privacy concerns, and design preferences to improve user-centered privacy features.

Contribution

It provides empirical insights into BLV users' privacy practices with GenAI and proposes design recommendations for privacy-aware AI tools.

Findings

Users balance privacy, efficiency, and emotional agency in GenAI use.

Key privacy scenarios include self-presentation and social sharing.

Design preferences include on-device processing and privacy indicators.

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.