Shared Privacy Concerns of the Visually Impaired and Sighted Bystanders with Camera-Based Assistive Technologies
Abstract
Camera-based assistive technologies can provide people with visual impairments (PVIs) visually derived information about people in their vicinity. Furthermore, the advent of smart glasses offers the possibility of not only analyzing visual information in front of the wearers but also behind them through an extended field of view. Although such ‘visually available’ information can enhance one’s social interactions, the privacy and ethical implications for automated judgments about bystanders, especially from the perspective of PVIs , remains underexplored. To study the concerns of both bystanders and PVIs with such technologies, we conducted two online surveys with visually impaired participants as wearers (N = 128) and sighted participants as bystanders (N = 136). Although PVIs found some types of information to be improper or impolite (such as someone’s weight), our overarching finding is the shared ethical concern between PVIs and bystanders related to the fallibility of AI, in which bystanders can be misrepresented (algorithmically) by the devices. These mischaracterizations can range from occasional unexpected algorithmic errors (e.g., errors in facial recognition) to the questionable use of AI for determining subjective social constructs (such as gender). Based on our findings, we discuss the design implications and directions for future work in the development of camera-based assistive technologies while mitigating the ethical concerns of PVIs and bystanders.
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These frictions highlight accessibility as a collective work which needs a unified policy framework that accommodates accessibility with other values, such as privacy and the interests of bystanders.
“These frictions highlight accessibility as a collective work which needs a unified policy framework that accommodates accessibility with other values, such as privacy [243] and the interests of bystanders [3].”
From Cripping AI: Reimagining AI Through Lived Disability Experiences (2026) · cites this paper as [3]
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Cripping AI: Reimagining AI Through Lived Disability Experiences
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- Authors
- Akter, T., Ahmed, T., Kapadia, A., & Swaminathan, M.
- Affiliations
- Indiana University Bloomington (US)
- Microsoft Research (India) (IN)
- Venue
- ACM Transactions on Accessible Computing
- Published
- 2022-05-19
- Volume
- 15
- Issue
- 2
- Pages
- 1-33
- ISSN
- 1936-7228 (ISSN-L)
- 1936-7236
- OpenAlex
- W4213459158
- Cited by
- 29
- References
- 15
- Citations by year
- 2026: 8 · 2025: 5 · 2024: 9 · 2023: 6 · 2022: 1
- FWCI
- 8.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Accessible Computing (publishedVersion)
- Funders
- National Science Foundation (CNS-1408730, and CNS-1814513)
- Google Faculty Research Award
- Topics
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- visual impairment, smart glasses, privacy concerns, bystanders, ethical implications of AI, assistive technology design
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