arXiv cs.AI· Madiha Zahrah Choksi, Reeda Shimaz Huda, Rita Faia Marques, Anja Thieme, Cecily Morrison·· 3 小时前AI 评分36
残障社群数据治理的参与式设计研究：情境化许可方案
Terms of Care: Designing for Participation in Data Governance by Disability Communities
AI 导读
一项arXiv研究探讨残障社群如何通过情境敏感许可参与AI数据集治理。研究者与三家残障倡导组织合作，通过访谈、网络研讨会和模块化许可活动发现，此类治理依赖组织记忆、正式权威与非正式关系实践、沟通及由此产生的信任；社群可改编 Creative Commons 条款来表达允许用途、行业限制与尊重性呈现承诺，但监控与执行仍是难点。
正文 · 原文
Abstract:Improving disability representation in AI-generated media requires community-specific datasets, yet openly sharing such data can expose communities to misuse, decontextualization, and exploitation. We examine how disability communities can participate in dataset governance through context-sensitive licensing. Working with three disability advocacy organizations, we conducted semi-structured interviews, an educational webinar and modular license activity to promote community participation in data stewardship. Our findings show that governance in these high-context communities relies on organizational memory (especially situated harms); both formal authority and informal relational practices; communication; and resulting trust. The modular license activity made organizational data choices more accessible and values-led, allowing communities to adapt Creative Commons clauses to express permitted uses, sector-specific restrictions, safeguarding requirements, and commitments to respectful representation. Yet, concerns remain about monitoring and enforcing appropriate data use. We contribute (1) an empirical account of governance tensions, (2) a practical modular approach, and (3) design implications for AI data platforms that support relational, context-sensitive governance beyond standardized, one-size-fits-all frameworks.
| Comments: | 26 pages, 3 figures, 3 tables, under review |
| Subjects: | Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Digital Libraries (cs.DL) |
| ACM classes: | H.m |
| Cite as: | arXiv:2611.15720 [cs.HC] |
| (or arXiv:2611.15720v1 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2611.15720 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Anja Thieme Dr [view email]
[v1]
Wed, 11 Nov 2026 16:58:37 UTC (845 KB)
来源：arXiv cs.AI · arxiv.org