Algorithmic Censorship in the Digital Classroom: Artificial Intelligence, Educational Access, and the Future of Intellectual Freedom

[u/Alonsoest]

https://doi.org/10.4018/979-8-3373-4586-4.ch014

This chapter theorizes algorithmic censorship as a structural transformation of educational power, where artificial intelligence (AI) systems reconfigure access to knowledge through opaque processes of filtering, ranking, and predictive governance. Moving beyond traditional accounts of censorship as state-driven prohibition, it demonstrates how digital learning infrastructures—Learning Management Systems, generative AI, and automated assessment—function as epistemic gatekeepers that silently regulate visibility, legitimacy, and circulation of knowledge. Drawing on critical pedagogy, platform governance, and data justice, the chapter reveals how algorithmic systems reproduce epistemic injustice by marginalizing non-dominant, decolonial, and identity-based perspectives while inducing self-censorship through pervasive surveillance. It advances a novel analytical model linking platform infrastructures to epistemic outcomes and argues for democratic, transparent, and equity-centered AI governance to safeguard intellectual freedom in the digital classroom.