Jun 2026· Education sciences· Vol 16, pp. 1016· 0 citations· 46 references
TL;DR
The need for contextualised ethical frameworks, curriculum redesign, authentic assessments, capacity building and adaptive governance to ensure equitable and responsible GenAI integration, particularly in African higher education is highlighted.
Abstract
The rapid expansion of generative AI (GenAI) in higher education offers transformative opportunities but raises complex ethical concerns that demand rigorous examination. The existing literature is dominated by Global North perspectives, with African contexts accounting for only 11.4% of studies and Ghana for only 2.8%, leaving significant gaps in understanding ethical GenAI integration in post-colonial, multilingual and resource-constrained environments. This review synthesises global and African evidence to examine the ethical considerations, stakeholder responses, institutional frameworks, and future research priorities for the responsible use of GenAI in higher education. Guided by the PRISMA framework, this review analysed 246 studies published between 2018 and 2025, using narrative synthesis, thematic analysis, and framework synthesis to integrate the empirical and theoretical contributions. Five ethical domains consistently emerged: academic integrity, privacy and data security, transparency and accountability, equity and access, and AI literacy. These concerns manifest differently across contexts, with African institutions highlighting issues such as Ubuntu-informed ethics, infrastructural constraints, digital sovereignty and epistemic justice. Institutional responses remain uneven, and Ghanaian institutions show limited systematic governance. This review highlights the need for contextualised ethical frameworks, curriculum redesign, authentic assessments, capacity building and adaptive governance to ensure equitable and responsible GenAI integration, particularly in African higher education.
The findings indicate that GenAI adoption in African HEIs is expanding but uneven, concentrated in digitally advanced nations, enhancing personalization, multilingual learning, and research productivity, yet raises ethical concerns about academic integrity.
O. Apata, Peter Oyewole, S. Ajose et al.· Journal of University Teachi...· 0 citations
Generative artificial intelligence (GenAI) has moved from novelty to routine presence in higher education within a few years, yet the evidence on its adoption, ethical implications, and cognitive effects remains fragmented across global, regional, and mechanism-focused literatures that are rarely read together. This narrative review synthesises 43 sources, comprising global systematic reviews and meta-analyses, comparative Global North-South studies, African and Tanzanian policy analyses, Ghana-specific empirical studies, and behavioural models linking GenAI use to critical thinking and ethical creativity. The review traces the evolution of this literature across three waves from 2022 to 2026 and finds that GenAI adoption is high globally, at roughly 74.5% among educators, and is growing rapidly across Africa, but that structural constraints, including limited infrastructure, low AI literacy, and underdeveloped institutional policy, shape a distinctly African pattern of opportunity and risk that global adoption figures obscure. In Ghana specifically, a large tertiary-institution survey shows technical infrastructure as a significant constraint even where urban-rural gaps are not, alongside evidence that roughly a third of surveyed undergraduates report low AI literacy despite substantial GenAI use. Critically, the review identifies that the empirically tested behavioural pathways linking GenAI use to critical thinking and ethical creativity, through self-regulated learning, innovative behaviour, and reduced reliance on prior knowledge, have been tested only in Taiwanese and Chinese settings, leaving open whether the same mechanisms hold under African infrastructural and institutional conditions. The review concludes with practical implications for institutions and policymakers and a concrete future-research agenda centred on this gap, arguing that testing these pathways in Ghana is the field's single most valuable next study.
Solomon Opoku· International journal of res...· 0 citations
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.
Eva García-Beltrán· Journal of Educational Techn...· 0 citations
This study aimed to provide a comprehensive review of generative AI governance in higher education during the period 2022–2026, in light of the rapid expansion of the use of big language models and content generation applications within universities. The study adopted a comprehensive scope review methodology, guided by the SALSA framework for the research, evaluation, synthesis, and analysis phases, and by PRISMA-ScR guidelines for documenting the review procedures. The study analyzed peer-reviewed scientific literature, sectoral, institutional, and regulatory frameworks, and selected university policies, with particular attention to the Arab context and research and regulatory gaps. The results showed that generative AI governance is not limited to addressing issues of cheating and plagiarism, but encompasses interconnected dimensions, most notably: academic integrity, privacy, transparency, disclosure, fairness, capacity building, human oversight, risk management, and assessment redesign. The study also indicated that the global trend is moving toward responsible and conditional use rather than outright prohibition or unregulated adoption. The study concluded that effective governance requires combining research evidence, sectoral frameworks, and institutional policies, while translating general principles into clear procedures at the university and course levels. It also revealed the need for more specialized policies that address privacy, linguistic equity, data protection, and the transparency. The study recommends developing flexible university guidelines, disclosure models, data use controls, ongoing training programs, and periodic review mechanisms that ensure a balance between innovation, quality of learning, and academic integrity.
Mohammed Al Mutawtah· Academic Journal of Research...· 0 citations
It is argued that AI-related integrity disputes are better understood as conflicts between competing values than as individual moral failings, and implications for policy design, assessment reform, and faculty development are discussed.
M. Grobler· Proceedings of the Internati...· 0 citations
The rapid integration of artificial intelligence (AI) in education presents many opportunities but also raises critical ethical and cultural challenges. This study aims to explore the current application of AI in education in Myanmar and investigates the conflicts between global AI ethical principles and local cultural values.
Employing a mixed-methods research design, the study utilizes quantitative survey analysis alongside qualitative participatory workshops to provide both breadth and depth to the understanding of educators' perspectives.
The quantitative findings indicate that while most ethical considerations and practical AI implementation patterns remain consistent across different groups, educators' concern for maintaining human autonomy in AI-assisted education grows significantly with their level of professional experience. Furthermore, the qualitative insights highlight a clear gap between internationally developed (often Global North-centered) AI ethics frameworks and the realities of Myanmar's education context. In particular, socioeconomic challenges and local cultural expectations shape how educators understand and respond to AI. Overall, the study argues that AI ethics in education need to be more locally grounded and responsive to national contexts, rather than relying solely on universal frameworks.
This paper fulfils an identified need to study how ethical AI integration can be enabled in under-resourced and underrepresented educational contexts. By centering the voices of Myanmar educators and documenting their unique perspectives, the study advances knowledge on AI ethics in education and provides practical, context-sensitive guidance for educators, policymakers and researchers.
Wai Yan Htut, Thu Thu Naing, Phyo Wai Tun· International Conference on...· 0 citations