Designing an Online Infrastructure for Collecting AI Data From People With Disabilities
Designing an Online Infrastructure for Collecting AI Data From People With Disabilities
复制标题
设计用于从残疾人那里收集人工智能数据的在线基础设施
DOI：
10.1145/3442188.3445870
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
M. Morris
中科院分区：
文献类型：
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作者：
J. Park;Danielle Bragg;Ece Kamar;M. Morris
人工智能技术为扩大残疾人的虚拟和物理访问提供了机会。然而，实现这些机会的一个重要部分是确保即将到来的人工智能技术适用于各种能力的人。在本文中，我们认为缺乏残疾人数据是公平和包容性人工智能系统培训和基准测试的挑战之一。作为一种潜在的解决方案，我们设想了一种在线基础设施，可以使残疾人社区的大规模远程数据贡献成为可能。我们通过半结构化访谈和通过在线门户网站收集示例数据文件模拟数据贡献过程的在线调查，调查残疾人在被要求收集和上传各种形式的人工智能相关数据时可能遇到的动机、担忧和挑战。基于我们的发现，我们为开发人员创建用于收集残疾人数据的在线基础设施概述了设计指南。
AI technology offers opportunities to expand virtual and physical access for people with disabilities. However, an important part of bringing these opportunities to fruition is ensuring that upcoming AI technology works well for people with a wide range of abilities. In this paper, we identify the lack of data from disabled populations as one of the challenges to training and benchmarking fair and inclusive AI systems. As a potential solution, we envision an online infrastructure that can enable large-scale, remote data contributions from disability communities. We investigate the motivations, concerns, and challenges that people with disabilities might experience when asked to collect and upload various forms of AI-relevant data through a semi-structured interview and an online survey that simulated a data contribution process by collecting example data files through an online portal. Based on our findings, we outline design guidelines for developers creating online infrastructures for gathering data from people with disabilities.
DOI：
10.1109/cvpr.2018.00380
发表时间：
2018-02
期刊：
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
影响因子：
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作者：
D. Gurari;Qing Li;Abigale Stangl;Anhong Guo;Chi Lin;K. Grauman;Jiebo Luo;Jeffrey P. Bigham
通讯作者：
D. Gurari;Qing Li;Abigale Stangl;Anhong Guo;Chi Lin;K. Grauman;Jiebo Luo;Jeffrey P. Bigham