# AccessShare: Co-designing Data Access and Sharing with Blind People

arXiv: https://arxiv.org/abs/2407.19351 · HTML: https://mlsanity.com/paper/2407.19351/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 25 of its 108 references that are in the map.
- First posted on arXiv 27 Jul 2024.

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

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [VizWiz Grand Challenge: Answering Visual Questions from Blind People](https://mlsanity.com/paper/1802.08218/) (2018)
- [Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI](https://mlsanity.com/paper/2204.01075/) (2022)
- [The VIA Annotation Software for Images, Audio and Video](https://mlsanity.com/paper/1904.10699/) (2019)
- [Power to the People? Opportunities and Challenges for Participatory AI](https://mlsanity.com/paper/2209.07572/) (2022)
- [Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning](https://mlsanity.com/paper/1912.10389/) (2019)
- [Captioning Images Taken by People Who Are Blind](https://mlsanity.com/paper/2002.08565/) (2020)
- [Regulating ChatGPT and other Large Generative AI Models](https://mlsanity.com/paper/2302.02337/) (2023)
- [Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective](https://mlsanity.com/paper/1908.08597/) (2019)
- [Consent in Crisis: The Rapid Decline of the AI Data Commons](https://mlsanity.com/paper/2407.14933/) (2024)
- [ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition](https://mlsanity.com/paper/2104.03841/) (2021)
- [Democratising AI: Multiple Meanings, Goals, and Methods](https://mlsanity.com/paper/2303.12642/) (2023)
- [ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review](https://mlsanity.com/paper/2305.03123/) (2023)
- [On Mechanistic Knowledge Localization in Text-to-Image Generative Models](https://mlsanity.com/paper/2405.01008/) (2024)
- [Crowdsourcing the Perception of Machine Teaching](https://mlsanity.com/paper/2002.01618/) (2020)
- [Explaining CLIP's performance disparities on data from blind/low vision users](https://mlsanity.com/paper/2311.17315/) (2023)
- [Dark Patterns and the Legal Requirements of Consent Banners: An Interaction Criticism Perspective](https://mlsanity.com/paper/2009.10194/) (2020)
- [Blind Users Accessing Their Training Images in Teachable Object Recognizers](https://mlsanity.com/paper/2208.07968/) (2022)
- [What's Different between Visual Question Answering for Machine "Understanding" Versus for Accessibility?](https://mlsanity.com/paper/2210.14966/) (2022)
- [Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective](https://mlsanity.com/paper/2003.12122/) (2020)
- [Inform the uninformed: Improving Online Informed Consent Reading with an AI-Powered Chatbot](https://mlsanity.com/paper/2302.00832/) (2023)
- [Sharing Practices for Datasets Related to Accessibility and Aging](https://mlsanity.com/paper/2108.10665/) (2021)
- [Real-Time Text Detection and Recognition](https://mlsanity.com/paper/2011.00380/) (2020)
- [Contributing to Accessibility Datasets: Reflections on Sharing Study Data by Blind People](https://mlsanity.com/paper/2303.04962/) (2023)
- [Human-GDPR Interaction: Practical Experiences of Accessing Personal Data](https://mlsanity.com/paper/2203.05037/) (2022)

## Abstract (arXiv)

Blind people are often called to contribute image data to datasets for AI innovation with the hope for future accessibility and inclusion. Yet, the visual inspection of the contributed images is inaccessible. To this day, we lack mechanisms for data inspection and control that are accessible to the blind community. To address this gap, we engage 10 blind participants in a scenario where they wear smartglasses and collect image data using an AI-infused application in their homes. We also engineer a design probe, a novel data access interface called AccessShare, and conduct a co-design study to discuss participants' needs, preferences, and ideas on consent, data inspection, and control. Our findings reveal the impact of interactive informed consent and the complementary role of data inspection systems such as AccessShare in facilitating communication between data stewards and blind data contributors. We discuss how key insights can guide future informed consent and data control to promote inclusive and responsible data practices in AI.