Challenges of using artificial intelligence in higher education

Abstract

Objective: From diverse and highly important positions, we seek to analyze the advantages and disadvantages of integrating AI into university education. Design/Methodology/Approach: A systematic documentary review was used, with a bibliographic design following the phases of inquiry, systematization, and interpretation. The empirical level method allowed information to be collected through descriptive notes, and the analysis-synthesis method was used as the level method. The interpretation technique was semantic content analysis; the documentary corpus consisted of 20 specialized dissemination articles, 2018-2024. (Scopus, Scielo, Web of Science). Results and Discussion: The results show a balance between the advantages and disadvantages of using AI in university education; added values ​​​​are: access to information and sophisticated analysis tools, learning customization, time optimization, and efficiency. Thus, there is a need to promote policies that ensure that the application of AI in education is managed within a framework of respect for human rights and compliance with ethical principles. Conclusions: Negative aspects are identified: loss of cognitive and critical skills (promoting a superficial approach to knowledge rather than deep understanding), inequalities in access due to high costs (disparities in access to AI could widen existing divides rather than close them), and potential biases in algorithms. Contribution: In this way, it is clear how AI can be an ally, not a substitute, but a complementary tool, the use of which cannot undermine the development of irreplaceable human capacities in the learning process.