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.

翻译：生成式人工智能通过重构科学知识的生产与验证流程，重新定义了高等教育。这些系统并非价值中立，它们积极助长了非霸权认识论的边缘化。本研究融合教育科学、批判性技术研究与残障研究，揭示出以英语和西方为中心的语料库如何强化了认识论殖民性。残障群体的处境尤为清晰地展现了这一现象：技术架构往往将其简化为刻板印象，或在设计过程中将其排除在外，从而形成双重排斥。本文探讨了研究者与机器之间的混合模式能否在承认结构性限制的前提下维系认识论多元性——这些限制源于仅作为权宜策略的算法矫正机制。