CHALLENGES, RISKS, AND ETHICAL CONCERNS IN THE INTEGRATION OF ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A SYSTEMATIC LITERATURE REVIEW
TL;DR
The findings underscore that effective AI integration requires clear institutional policies, ethical frameworks, and equitable access, while future research should empirically investigate AI’s impact on learning, cognitive development, and educational equity.
Abstract
The integration of artificial intelligence (AI) into higher education (HE) has significantly transformed teaching and learning, offering both opportunities and critical challenges. This systematic literature review (SLR) analyzes 95 peer-reviewed studies published between 2020 and May 2025, retrieved from Web of Science, Scopus, and EBSCO Education Source, focusing on the risks, challenges, and ethical concerns of AI adoption in HE. Four primary themes emerged: 1) Academic Integrity and Misuse of AI Tools, highlighting risks of unethical reliance on AI and threats to cognitive engagement; 2) Data Privacy, Security, and Ethical Concerns, emphasizing the management of personal data, algorithmic bias, and institutional responsibilities; 3) Over-reliance on AI and Its Impact on Learning Outcomes, addressing the potential erosion of critical thinking, problem-solving, and intrinsic motivation; and 4) Equity and Access to AI Tools, focusing on digital divides and the need for inclusive AI literacy. The findings underscore that effective AI integration requires clear institutional policies, ethical frameworks, and equitable access, while future research should empirically investigate AI’s impact on learning, cognitive development, and educational equity.