Human-Computer Challenges of Generative Artificial Intelligence in Higher Education: A Scoping Review

Although Artificial Intelligence (AI) holds great potential in the field of education, it is important to address the ethical and pedagogical concerns surrounding its use. This study therefore aims to analyse the human-computational challenges posed by this technology, focusing in greater detail on ethics and regulation; transparency and data management; and social responsibility. Furthermore, a systematic review was conducted following the PRISMA methodology, covering articles from various databases spanning the period from before 2017 to 2024. Studies were selected based on specific inclusion criteria; of these, 49 met the study’s criteria and were categorised into eight main human-computer challenges: a) risk of exclusion due to technical barriers, b) reinforcement of discrimination through biased algorithms, c) threats to data privacy, d) potential displacement of human labour by automation, e) injustices in academic monitoring due to automated supervision, f) plagiarism and academic dishonesty, g) negative emotions and loss of human connection, and h) inappropriate and inaccurate content. In this regard, addressing these challenges leads to conclusions regarding practices such as the periodic review of algorithms, the implementation of evaluation strategies to regulate all forms of unethical use of AI, and a collaborative educational training programme on ethics and digital wellbeing for educators, students, developers, researchers and administrative staff.