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Disability-First Design and Creation of A Dataset Showing Private Visual Information Collected With People Who Are Blind

Authors:

Tanusree Sharma,

Abigale Stangl,

Leah Findlater,

Yang WangAuthors Info & Claims

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Article No.: 51, Pages 1 - 15

https://doi.org/10.1145/3544548.3580922

Published: 19 April 2023 Publication History

Abstract

We present the design and creation of a disability-first dataset, “BIV-Priv,” which contains 728 images and 728 videos of 14 private categories captured by 26 blind participants to support downstream development of artificial intelligence (AI) models. While best practices in dataset creation typically attempt to eliminate private content, some applications require such content for model development. We describe our approach in creating this dataset with private content in an ethical way, including using props rather than participants’ own private objects and balancing multi-disciplinary perspectives (e.g., accessibility, privacy, computer vision) to meet the tangible metrics (e.g., diversity, category, amount of content) to support AI innovations. We observed challenges that our participants encountered during the data collection, including accessibility issues (e.g., understanding foreground vs. background object placement) and issues due to the sensitive nature of the content (e.g., discomfort in capturing some props such as condoms around family members).

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Cited By

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https://doi.org/10.3390/ai6020029
Kamikubo RZamiri Zeraati FLee KKacorri H(2024)AccessShare: Co-designing Data Access and Sharing with Blind PeopleProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675612(1-16)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3675612
Xu AZhou ZMiyazaki KYoshikawa RHosio SYatani K(2024)DIPA2Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314397:4(1-30)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631439
Show More Cited By

Index Terms

Disability-First Design and Creation of A Dataset Showing Private Visual Information Collected With People Who Are Blind
1. Human-centered computing
  1. Accessibility
    1. Accessibility design and evaluation methods

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CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

April 2023

14911 pages

ISBN:9781450394215

DOI:10.1145/3544548

Editors:
Albrecht Schmidt
LMU Munich, Germany60028717
,
Kaisa Väänänen
Tampere University, Finland60011170
,
Tesh Goyal
Google Research, USA60006191
,
Per Ola Kristensson
University of Cambridge, UK60031101
,
Anicia Peters
University of Namibia, Namibia60072704
,
Stefanie Mueller
Massachusetts Institute of Technology, USA60022195
,
Julie R. Williamson
University of Glasgow, UK60001490
,
Max L. Wilson
University of Nottingham, UK60015138

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Cited By

Shahriar SDara R(2025)Priv-IQ: A Benchmark and Comparative Evaluation of Large Multimodal Models on Privacy CompetenciesAI10.3390/ai60200296:2(29)Online publication date: 6-Feb-2025
https://doi.org/10.3390/ai6020029
Kamikubo RZamiri Zeraati FLee KKacorri H(2024)AccessShare: Co-designing Data Access and Sharing with Blind PeopleProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675612(1-16)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3675612
Xu AZhou ZMiyazaki KYoshikawa RHosio SYatani K(2024)DIPA2Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314397:4(1-30)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631439
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