ArticleASSETS. Annual ACM Conference on Assistive Technologies2024
AccessShare: Co-designing Data Access and Sharing with Blind People.
Article in ASSETS. Annual ACM Conference on Assistive Technologies, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Exploring Collaboration to Center the Deaf Community in Sign Language AI.ASSETS. Annual ACM Conference on Assistive Technologies · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.