Privacy Concerns for Visual Assistance Technologies

Author:

Stangl Abigale1ORCID,Shiroma Kristina2ORCID,Davis Nathan2ORCID,Xie Bo2ORCID,Fleischmann Kenneth R.2ORCID,Findlater Leah1ORCID,Gurari Danna3ORCID

Affiliation:

1. University of Washington, Seattle, WA

2. University of Texas at Austin, Austin, Texas

3. University of Colorado Boulder, Boulder, Colorado

Abstract

People who are blind share their images and videos with companies that provide visual assistance technologies (VATs) to gain access to information about their surroundings. A challenge is that people who are blind cannot independently validate the content of the images and videos before they share them, and their visual data commonly contains private content. We examine privacy concerns for blind people who share personal visual data with VAT companies that provide descriptions authored by humans or artifcial intelligence (AI) . We frst interviewed 18 people who are blind about their perceptions of privacy when using both types of VATs. Then we asked the participants to rate 21 types of image content according to their level of privacy concern if the information was shared knowingly versus unknowingly with human- or AI-powered VATs. Finally, we analyzed what information VAT companies communicate to users about their collection and processing of users’ personal visual data through their privacy policies. Our fndings have implications for the development of VATs that safeguard blind users’ visual privacy, and our methods may be useful for other camera-based technology companies and their users.

Funder

University of Texas at Austin Good Systems Grand Challenge

National Science Foundation/Computing Research Association 2020 Computing Innovation Fellows

University of Washington Center for Research and Education on Accessible Technology and Experiences

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Human-Computer Interaction

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1. DIPA2;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2023-12-19

2. Disability-First Design and Creation of A Dataset Showing Private Visual Information Collected With People Who Are Blind;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

3. Contributing to Accessibility Datasets: Reflections on Sharing Study Data by Blind People;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

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