Integration of generative artificial intelligence into higher education research as a supporting tool: A balance between innovation and ethics in research

Abstract

Although the growing use of generative artificial intelligence (GAI) in higher education research offers exciting potential for enhancing innovation and efficiency, it is also troubled by significant ethical challenges. This review systematically explores critical concerns that border on risks that are associated with data privacy, algorithmic bias, transparency deficiencies, accountability gaps, and threats to academic integrity. This was done by providing a literature-based assessment of why the use GAI in higher education continues to be problematic. This assessment yielded informative insights that were deciphered from 31 papers which were systematically selected from a sampling universe of 119 publications. Findings highlight the necessity of striking a balance between embracing AI-driven advancements and upholding ethical standards in research, in a manner that does not compromise human capacities to mitigate the unexpected eventualities and their consequences. A set of actionable guidelines that are designed to enhance the responsible integration of GAI in higher education without side-lining the importance of observing critical ethical issues that must be considered and adhered to in academic research is given. These guidelines are useful because they form the foundation of a robust framework which gui, Generative, Higher Education, Researchdes the way GAI is used in higher education research without forgetting that this technology is not an all-round paragon.

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