AI在高等教育中加剧了残障知识的边缘化，需警惕其隐性偏见。
Generative artificial intelligence and the marginalization of minoritized knowledges in higher education: the case of disability
- 从教育科技与残障研究视角揭示AI训练数据的西方中心倾向
- 残障人群常被简化为刻板印象或排除在设计之外，形成双重边缘化
- 探索人机协作能否保留知识多样性，但质疑算法补救的局限性
生成式人工智能正在重塑高等教育中科学知识的生产与验证机制。这些系统并非中立，反而推动非主流认识论的边缘化。本研究结合教育学、批判技术研究与残障研究，指出训练数据主要以英语和西方为中心，强化了认知殖民主义。残障人士的处境尤为明显：技术架构常将他们局限于单一刻板印象，或将其排除在设计过程之外，导致双重边缘化。本文探讨研究者与机器之间的混合模式是否能维系认识论多样性，同时承认算法修正作为单纯补救策略存在结构性局限。
原文摘要 · Abstract (English)
Generative artificial intelligence redefines higher education by restructuring the processes through which scientific knowledge is produced and validated. These systems are not neutral; they actively contribute to the marginalization of non-hegemonic epistemologies. This research draws upon educational sciences, critical technology studies, and disability studies to demonstrate that training datasets, which remain predominantly Anglophone and Western-centric, reinforce epistemic coloniality. The situation of persons with disabilities provides a particularly clear illustration of this phenomenon. Technological architectures frequently confine these individuals to reductive stereotypes or exclude them from the design process, leading to a double marginalization. This article examines whether a hybridization between the researcher and the machine might preserve epistemic plurality, while acknowledging the structural limitations inherent in algorithmic correction when used as a purely palliative strategy.
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