Lune

CHI2023Top-tier venue

Contributing to Accessibility Datasets: Reflections on Sharing Study Data by Blind People

Rie Kamikubo, Kyungjun Lee, Hernisa Kacorri

2023Year
16Citations
2Top-tier citations

Abstract

To ensure that AI-infused systems work for disabled people, we need to bring accessibility datasets sourced from this community in the development lifecycle. However, there are many ethical and privacy concerns limiting greater data inclusion, making such datasets not readily available. We present a pair of studies where 13 blind participants engage in data capturing activities and reflect with and without probing on various factors that influence their decision to share their data via an AI dataset. We see how different factors influence blind participants' willingness to share study data as they assess risk-benefit tradeoffs. The majority support sharing of their data to improve technology but also express concerns over commercial use, associated metadata, and the lack of transparency about the impact of their data. These insights have implications for the development of responsible practices for stewarding accessibility datasets, and can contribute to broader discussions in this area.

• Human-centered computing → Human computer interaction (HCI); Accessibility; • Social and professional topics → People with disabilities; • Security and privacy → Human and societal aspects of security and privacy.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 40d8178a-b8e5-4a6f-b61a-31e8fa02484b

Cited by top-tier papers2

Ask how each one uses it

Builds on8

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines