Good morning. Let’s begin today’s column with an intriguing question. Imagine that you wanted to decipher how many subjects, on average, a UNAM student takes, how many times he or she fails, what National Preparatory School he/she studied at, what majors he selected from his options and, based on this information, be able to offer a personalized career plan. to each new student who enters the largest university in our country. Now, let’s raise the ante: imagine knowing the probabilities that millions of young people want to study at UNAM. Would it be possible for a consulting firm like McKinsey to perform this in-depth analysis? Or even for giants of the Artificial Intelligence industry like Google or Microsoft, without access to the rich data that UNAM has? The reality is that no. UNAM is unique in its ability to positively influence the lives of hundreds of thousands of students, thanks not only to the experts who walk through its hallways daily, but also because it has the necessary data to train all AI models, both traditional and generative. These data not only cover academic records, but also sports activities, graduation time, and teachers who influenced the students’ lives. Few universities in the world handle such a significant volume of information from upper secondary education to postgraduate education.
And it is precisely for this reason, dear readers, that I affirm that data is now more than ever the most critical resource in the advancement of technological careers. In a fierce race, companies like Google and Microsoft seek to hoard as much data as possible to train their advanced language models, which draw on the vast information available on the Internet.
But what happens with the data that is not on the network, that resides within institutions and companies throughout Mexico? Consider Grupo Salinas, which records data on television consumption and Italika motorcycle driving, or Grupo Carso, with its records on Internet consumption and telephone and financial services. The emergence of Generative Artificial Intelligence has further highlighted the need to structure and organize this data so that it can effectively serve multiple purposes, both operational and technological research and development.
I have written about how the centralism of key Mexican institutions, such as CFE, IMSS and UNAM, has created reservoirs of data possibly unmatched globally, and how it is imperative that these be cleaned up and put at the service of the nation to improve quality of the services. Hence, each public official should have solid training in data management, not necessarily through postgraduate degrees, but through courses and diplomas that prepare them to exploit these exclusive resources effectively.
Finally, imagine a future in which, from birth, we can predict the chances of a child joining UNAM and what career they might choose. With this information, it would be possible to design a financial and educational support plan from their first years of life, significantly increasing their opportunities for academic success. This is the real potential of artificial intelligence, a power that we must aspire to master and maximize for the good of our society.
