The teacher between the pandemic and the algorithm: critical teacher education in the age of artificial intelligence

Abstract

This article analyzes the challenges of teacher education in the post-pandemic context and the expansion of generative artificial intelligence in education. It is based on the understanding that the Covid-19 pandemic accelerated the entry of digital technologies into schools, but also exposed structural weaknesses, unequal access, teacher overload, and the lack of consistent training policies. The general objective is to discuss how teacher education can critically respond to the demands of cyberculture and artificial intelligence, without reducing the teacher to the condition of an instrumental user of platforms or an applicator of ready-made solutions. The adopted methodology is qualitative, of a bibliographic and documentary nature, based on recent literature on artificial intelligence, education, ethics, democracy, decoloniality, and teacher education. The results indicate that artificial intelligence can expand pedagogical possibilities, support personalization processes, and favor new forms of knowledge production, provided it is mediated by ethical, pedagogical, and political criteria. At the same time, it highlights the risk of automated teaching, marked by technical rationality, dependence on external systems, the weakening of teacher authorship, and the reproduction of inequalities. It is concluded that the teacher education required today must prioritize a critical, ethical, democratic, and decolonial posture towards technologies.