VIRTUAL Prague Research & Teaching Conference

Abstract

As artificial intelligence (AI) becomes increasingly embedded in higher education, its impact on equity and inclusion remains complex and contested. While AI-driven tools promise enhanced accessibility, personalized learning, and reduced human bias, their deployment often reproduces systemic inequalities due to algorithmic opacity, exclusionary design, and biased training data. This paper critically examines AI’s dual role in academia—both as a mechanism for educational equity and as a system that can inadvertently reinforce existing disparities. By analyzing case studies of AI applications in education—such as adaptive learning platforms, AI-powered accessibility tools, and algorithmic hiring and assessment systems—this paper explores how AI can either promote or hinder diversity, equity, and inclusion (DEI). Drawing from interdisciplinary perspectives in technology ethics, pedagogy, and critical AI studies, it assesses the ethical considerations surrounding AI’s integration into teaching and learning. This paper also proposes strategies for ensuring AI’s responsible use in higher education, emphasizing the need for transparency, accountability, and participatory design in AI systems. It argues that while AI has the potential to democratize access to education, its effectiveness depends on intentional design and equitable implementation. By reflecting on the role of educators, researchers, and institutions in shaping ethical AI practices, this paper contributes to broader discussions on the digital turn in academia. It challenges us to rethink AI not as an autonomous force but as a tool that must be critically examined and purposefully designed to support inclusivity in higher education.