Perspectives to address artificial intelligence in journalism teaching. A review of research and teaching experiences

Abstract

Introduction: In a context where media increasingly rely on artificial intelligence (Neuman, 2021), this technology remains absent from bachelor’s and master’s degrees in communication in Spain (Sanchez García, Calvo Barbero & Díez Gracia, 2021; Ufarte, Calvo & Murcia, 2020; Ufarte, Fieiras & Túñez, 2020). Methodology: We identified international research projects and teaching experiences that address artificial intelligence and integrate it into journalism education. In addition, throughout 2021, we participated in six national and international academic events that explored artificial intelligence across three areas of the communication field: research, the professional context, and university teaching. Results: The insights, projects, and teaching initiatives reviewed approach artificial intelligence from two main perspectives: a critical perspective focused on the social consequences of its use in the media ecosystem, and an applied perspective aimed at training journalism students in three competencies—data collection and processing, automated content creation, and content verification. Conclusions: Although still limited, the available research and teaching initiatives provide pathways for introducing artificial intelligence into journalism and communication curricula. These approaches adopt a critical perspective that, while acknowledging current media practices, addresses the pedagogical challenges derived from the growing use and expansion of this technology.