用残障经验重构AI，打破设计中的能力偏见
Cripping AI: Reimagining AI Through Lived Disability Experiences
- 以酷儿理论为基础，重新审视AI的想象与设计逻辑
- 提出三类实践案例：手语、视觉辅助、言语障碍AI
- 倡导残障者共同参与，推动更包容的AI发展
本文基于酷儿理论，提出“矫形化AI”（cripping AI）作为指导框架，将残障者的亲身体验置于人工智能研究与开发的核心位置。超越传统“使AI对残障者可访问”的呼吁，该框架旨在：(1) 揭示并瓦解嵌入在AI构想、设计与评估中的能力主义假设；(2) 强调残障者的知识体系（即“酷儿认知论”）；(3) 尊重残障者在共创可访问实践中的劳动价值。文中通过三个案例展示应用：聋人与手语AI、盲人与视觉辅助AI、口吃者与语音AI。最后提出未来三个方向：在多元身心形态中实施矫形化AI、贯穿整个AI研发流程与生态，以及与其他正义导向的AI努力协同推进。
原文摘要 · Abstract (English)
Drawing on crip theory, this paper proposes cripping AI as a guiding framework to center lived disability experiences in AI research and development. Moving beyond calls to make AI "accessible" to people with disabilities, cripping AI seeks to: (1) reveal and dismantle ableist assumptions embedded in how AI is imagined, designed, and evaluated; (2) center disabled ways of knowing (i.e., cripistemologies); (3) respect disabled labor in co-creating accessible practices. We demonstrate how to apply our framework with three cases: deafness and sign language AI, blindness and visual assistive AI, and stuttering and speech AI. We end by outlining three directions for future work, including cripping AI with diverse human bodyminds, across the entire AI pipeline and ecosystem, and in collaboration with other justice-oriented AI efforts.
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