In the academic field , there is no longer any doubt that AI is the topic of the year, about which we pour rivers of digital ink and discuss in seminars and workshops, trying to grasp the impact that the advent of this technology is causing in university institutions.
As Carlos Scolari states in his first thesis on artificial intelligence, “ everything we write or say about AI is already outdated .” With this initial warning, and aware that the expansion of AI will mark turning points in the most diverse areas of life in society, we venture to outline some lines of analysis that may still retain a certain naiveté in the face of the dizzying leap we cannot yet fully grasp.
Ulrich Beck introduced the concept of diagnostic theory some time ago to describe the rapid pace of social phenomena that demand a specific vocabulary for understanding. It's a speculative exercise that attempts to answer questions like: Where are we? Where are we going? What do we understand about what's happening? This is what's happening to us with AI. The disruption caused by the proliferation of generative AI ventures is forcing us to piece together meaning as the experience unfolds and conversations multiply.
In this urgent need to theorize in order to understand, we postulate the existence of two distinct categories: weak or narrow AI, encompassing current works with specific, limited purposes, and strong or generalist AI: a utopian ideal—currently nonexistent—comparable to an enhanced human intelligence, capable of achieving true supremacy. Following these rational arguments, we establish a distinction between predictive and generative AI. The former is a type of machine learning algorithm that analyzes data and forecasts future outcomes. In contrast, generative AI specializes in producing content in various formats. The crux of the matter lies in this latter category.
When analyzing the impact of AI in university classrooms, it's essential to mention GPT, a pioneering model that disrupted the system's equilibrium. Its emergence confronted us with something new. As users, we experienced a qualitative shift that shook us out of our complacency: GPT generates text in natural language based on our requests. Dialogic is the hallmark of GPT, creating a unique experience. Furthermore, it offers a step-by-step view of this generation process: the text unfolds over time, and both participants are involved in this ongoing co-creation.
Since its emergence in late 2022, similar models have been added to numerous interfaces. It's worth emphasizing that GPT didn't come to replace traditional information search platforms, but rather to complement and expand them, becoming a new species in the media ecosystem.
For the educational world, the popularization of GPT and other generative AI models presents an enormous challenge. Faced with this question, we turn our attention to teachers, the actors on the front lines. Teachers who, in their daily practices, can trigger changes, modify routines, and generate variations that will drive change from the micro to the macro level. This two-fold pace that overwhelms us discourages waiting for a top-down approach , because guidelines will necessarily take time to arrive. And this acceleration stimulates the emergence of decentralized initiatives, unforeseen uses, and multidirectional interactions that cultivate the ground for innovation.
This is how universities are moving forward to meet the challenges of our time. UNESCO recently detailed the issues it considers priorities for the responsible integration of AI at the higher education level. According to this organization, decisions should focus on building internal capacity, developing a policy framework, pedagogical innovation and skills training, promoting AI research and application, mobilizing knowledge and collaboration around it, and promoting gender equality, both for AI and for higher education as a whole. It should be noted that the reproduction of biases is one of the fundamental flaws identified in current models, since AI reflects back to us our own image: the positive aspects, but also our prejudices and contradictions. And it will very likely contribute to reinforcing and deepening them. Here, the role of the teacher becomes more important, to redirect and make these inconsistencies visible.
However, for the above to be viable, a thorough understanding of the new tools is essential. Teacher information literacy is a critical requirement for devising strategies for incorporating or neutralizing potential misuse of AI. Pedagogical objectives must always take precedence, because pedagogy comes first and technology accompanies. Clearly, teacher professional development is a core element, as the very role of teachers evolves alongside technology. Therefore, preparing to navigate this co-evolution in unstable environments is a necessary step.
Today more than ever, a university that aims to train qualified professionals must embrace the paradigm of holistic development. More than ever, educating individuals committed to their communities and determined to be active participants in the environments they inhabit becomes imperative. How is this achieved? We can infer that it is by maintaining and refining our humanity in constant dialogue with technology. Because technology is simply another dimension of humanity. And at the center, at the heart of our mission as a university, are people.
We are at a crucial juncture where mere adaptation falls short. It's about establishing a virtuous cycle; about theorizing to understand, but also about acting on that understanding. It's about transcending bewilderment to lead change with technology as our ally.
By Mariángeles Castro Sánchez, Teacher and researcher, director of studies at Institute of Family Sciences from the Universidad Austral.
