From Media Literacy to Algorithmic Literacy

Challenges for Teaching Communication in Mexico

Abstract

This article proposes that communication education in Mexico must expand media literacy to include algorithmic and AI-communication literacy. Through a comparative review of five institutional documents from public universities located in the central, western, northwestern, eastern, and southern-southeastern regions of the country—complemented by international reports, connectivity data, and cases of synthetic disinformation—curricular gaps are identified regarding platform infrastructure, advanced verification, responsible AI-based production, data ethics, and digital inequality. The analysis shows that university responses range from pedagogical guides and student resources to manifestos and mandatory guidelines, although their translation into specific communication competencies remains uneven. A five-module model is proposed to train professionals capable of analyzing, producing, verifying, and explaining content in algorithm-mediated environments.