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

arXiv: https://arxiv.org/abs/2507.00286 · HTML: https://mlsanity.com/paper/2507.00286/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 95 references that are in the map.
- First posted on arXiv 30 Jun 2025.

## Builds on (most cited first, 25 of 25)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP](https://mlsanity.com/paper/2210.04150/) (2022)
- [Expanding Language-Image Pretrained Models for General Video Recognition](https://mlsanity.com/paper/2208.02816/) (2022)
- [ActionCLIP: A New Paradigm for Video Action Recognition](https://mlsanity.com/paper/2109.08472/) (2021)
- [Fine-tuned CLIP Models are Efficient Video Learners](https://mlsanity.com/paper/2212.03640/) (2022)
- [Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection](https://mlsanity.com/paper/2207.03482/) (2022)
- [Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming](https://mlsanity.com/paper/2302.07427/) (2023)
- [Audio-Visual LLM for Video Understanding](https://mlsanity.com/paper/2312.06720/) (2023)
- [LAVE: LLM-Powered Agent Assistance and Language Augmentation for Video Editing](https://mlsanity.com/paper/2402.10294/) (2024)
- [Ask Me Anything: Free-form Visual Question Answering Based on Knowledge from External Sources](https://mlsanity.com/paper/1511.06973/) (2015)
- [CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications](https://mlsanity.com/paper/2410.13387/) (2024)
- [WorldScribe: Towards Context-Aware Live Visual Descriptions](https://mlsanity.com/paper/2408.06627/) (2024)
- [Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People](https://mlsanity.com/paper/2403.15604/) (2024)
- [Designing Participatory AI: Creative Professionals' Worries and Expectations about Generative AI](https://mlsanity.com/paper/2303.08931/) (2023)
- [GenAssist: Making Image Generation Accessible](https://mlsanity.com/paper/2307.07589/) (2023)
- [Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models](https://mlsanity.com/paper/2502.16098/) (2025)
- [Towards Understanding the Use of MLLM-Enabled Applications for Visual Interpretation by Blind and Low Vision People](https://mlsanity.com/paper/2503.05899/) (2025)
- [Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents](https://mlsanity.com/paper/2410.11906/) (2024)
- ["It Feels Like Taking a Gamble": Exploring Perceptions, Practices, and Challenges of Using Makeup and Cosmetics for People with Visual Impairments](https://mlsanity.com/paper/2203.08864/) (2022)
- [The Impact of Generative AI Coding Assistants on Developers Who Are Visually Impaired](https://mlsanity.com/paper/2503.16491/) (2025)
- [Adanonymizer: Interactively Navigating and Balancing the Duality of Privacy and Output Performance in Human-LLM Interaction](https://mlsanity.com/paper/2410.15044/) (2024)
- [How Can Generative AI Enhance the Well-being of Blind?](https://mlsanity.com/paper/2402.07919/) (2024)
- [Understanding How to Inform Blind and Low-Vision Users about Data Privacy through Privacy Question Answering Assistants](https://mlsanity.com/paper/2310.08687/) (2023)
- [Exploring Use and Perceptions of Generative AI Art Tools by Blind Artists](https://mlsanity.com/paper/2409.08226/) (2024)
- [Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMs](https://mlsanity.com/paper/2503.20226/) (2025)

## Built on by (most cited first, 6 of 6)

- [How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People](https://mlsanity.com/paper/2602.13469/) (2026)
- [Finding the Signal in the Noise: An Exploratory Study on Assessing the Effectiveness of AI and Accessibility Forums for Blind Users' Support Needs](https://mlsanity.com/paper/2602.18623/) (2026)
- [Bespoke Visual Assistance: What and How do Blind and Low-Vision People Create with Agentic Programming?](https://mlsanity.com/paper/2607.21760/) (2026)
- [Chart-Supported or Model-Supplied? Examining MLLM-Generated Claims for Accessible Visualization](https://mlsanity.com/paper/2607.25021/) (2026)
- [Q&A or Document-Based? The Effects of Interface Type on How Screen Reader Users Access Interconnected Documents](https://mlsanity.com/paper/2608.25382/) (2026)
- [More Than Just Access: Generative AI as Communication Intermediary for Blind and Low-Vision Users](https://mlsanity.com/paper/2609.15696/) (2026)

## Abstract (arXiv)

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.