This article by García-Peñalvo, Llorens-Largo, and Vidal serves as a kind of “accelerated x-ray” of what has taken place in education since generative artificial intelligence, most visibly catalyzed by ChatGPT, burst onto the public stage.
The authors avoid both naïve enthusiasm and simplistic doom-mongering. Instead, they frame generative AI through a compelling dual lens: AI in education and education in times of AI. They remind us that many of today’s concerns (plagiarism, equity, technological dependency, assessment) were already present; what has changed is the power and scale of the tools. Drawing on UNESCO’s framework and national strategies such as Spain’s ENIA, they argue that the key issue is no longer whether we will use these technologies, but how quickly we will understand, regulate, and pedagogically integrate them.
One of the article’s most valuable contributions lies in its combination of a “GenAI ecosystem” map with a rapid review of the international academic literature. It does not limit itself to ChatGPT: it classifies families of tools (text, image, video, audio, code generation, AI text detection, etc.) and demonstrates the extent to which educationally relevant solutions already exist across virtually all content modalities.
At the same time, the review of studies in Web of Science and Scopus reveals a clear pattern: education oscillates between fascination with the possibilities (personalisation, feedback support, material generation, accessibility) and anxiety about the risks (surface learning, bias, inequality, dishonest use, and the limited reliability of AI text detectors). The article distills these tensions into specific benefits, risks, and challenges, making it an especially valuable read for anyone needing to quickly make sense of the current noise.
Perhaps the most incisive moment comes when the authors point out that “the emperor has no clothes”: generative AI has not created the problems in our educational model, it has merely exposed them. If a machine can perform many of the tasks we currently use as evidence of learning (essays, reports, reflective responses), the challenge is not to prohibit the tool but to rethink what it means to learn and how to assess it.
Hence their argument against symbolic bans and in favor of strategies that blend assessment redesign, critical thinking development, teacher training in AI, and clear ethical frameworks. The article concludes with an important warning: the real challenge is not only technological but temporal. The speed at which new tools emerge outpaces the usual cycles of academia and regulation, meaning that education will also need to learn to think and decide faster if it wishes to avoid being perpetually reactive.
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How to Cite: García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 9–39. https://doi.org/10.5944/ried.27.1.37716
