Ethical Dilemmas of Generative AI in Education and Their Implications for SDG 4: A Systematic Review from a Global and Inclusive Perspective
TL;DR
The findings reveal that current discussions on GAI in education are largely characterized by retrospective and crisis-driven ethical framings, predominantly focused on risks such as plagiarism, bias, and misinformation, while offering limited engagement with proactive, context-sensitive strategies aligned with SDG 4.
Abstract
This systematic review, conducted in accordance with PRISMA 2020 guidelines, examines the ethical dilemmas associated with the use of Generative Artificial Intelligence (GAI) in education and analyses their implications for the achievement of Sustainable Development Goal 4 (SDG 4), with a focus on inclusive and equitable quality education. The review draws on 24 peer-reviewed studies published between December 2022 and December 2024, covering diverse educational levels and geographical contexts, with a predominance of Global North perspectives and limited representation from the Global South. The analysis reveals four primary themes: academic integrity, algorithmic equity, data privacy, and the potential contribution of GAI to inclusive and quality education. These themes manifest differently across educational levels and contexts, with academic integrity concerns being more prominent in higher education, while issues of access, equity, and infrastructural dependency are more salient in low-resource and underrepresented settings. The findings reveal that current discussions on GAI in education are largely characterized by retrospective and crisis-driven ethical framings, predominantly focused on risks such as plagiarism, bias, and misinformation, while offering limited engagement with proactive, context-sensitive strategies aligned with SDG 4.
