Artificial intelligence in higher education: academic responsibility, ethics, and responsible practices

Abstract

In contemporary higher education, artificial intelligence has become a fundamental resource that is transforming academic routines and institutional strategic decision making. The objective of this review was to critically examine the literature on artificial intelligence in the university context in order to identify institutional responsibilities, ethical dilemmas, and proposals for socially relevant good practices beyond a purely descriptive approach. A systematic review guided by the PRISMA ScR protocol was conducted, analyzing studies published in English and Spanish between 2016 and 2026. After applying rigorous inclusion and methodological quality criteria, fourteen studies were selected for analysis. The findings reveal three central concerns. First, equity in evaluation processes, as algorithms may reproduce biases that affect certain groups without always being detectable. Second, the opacity of systems, which makes it difficult to demand transparency when the internal functioning of models is not fully understood. Third, academic integrity emerges as a particularly challenged domain due to the use of generative tools. Based on these findings, the study proposes guidelines focused on the implementation of clear regulatory frameworks, periodic ethical audits, teacher training in critical competencies, and the development of participatory policies that link technological innovation with social justice.