访问共享:与盲人共同设计数据访问和共享
Rie Kamikubo1, Farnaz Zamiri Zeraati2, Kyungjun Lee2
1College of Information, University of Maryland, College Park, College Park, MD, USA.
ASSETS. Annual ACM Conference on Assistive Technologies
|June 26, 2025
概括
盲人现在可以通过可访问的工具检查和控制AI数据贡献. 这项研究引入了新的接口,确保了对视力受损数据管理员的包容性和负责任的AI开发.
科学领域:
- 人与计算机的交互
- 人工智能伦理学 人工智能伦理学
- 可访问性研究 研究可访问性
背景情况:
- 视障人士对于人工智能数据收集至关重要,但缺乏可访问的数据检查和控制方法.
- 现有的数据贡献流程将盲人排除在基本监督之外.
- 人工智能数据管理中需要具备包容性机制.
研究的目的:
- 解决盲人AI数据贡献者的视觉数据检查难以获得的问题.
- 探索盲人对数据同意,检查和控制的需求和偏好.
- 为人工智能数据管理共同设计可访问的接口.
主要方法:
- 参与了10名盲人参与者,他们使用智能眼镜和人工智能注入的应用程序进行了基于家庭的图像数据收集.
- 工程 AccessShare,一个新的数据访问接口,作为一个设计探测器.
- 进行了一项联合设计研究,以收集关于同意,数据检查和控制的见解.
主要成果:
- 互动知情同意显著影响数据贡献.
- 像AccessShare这样的可访问的数据检查系统可以促进数据管理员和盲人贡献者之间的沟通.
- 参与者对数据控制和检查的偏好提供了有价值的见解.
结论:
- 可访问的数据检查和控制对于包容性AI数据实践至关重要.
- 新型接口和交互式同意机制可以赋予盲人数据贡献者权力.
- 调查结果指导开发负责任和公平的AI数据管理.
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