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.

Keywords: {'name': 'Artificial Intelligence'}, {'name': 'Ethical'}, {'name': 'Generative'}, {'name': 'Higher Education'}, {'name': 'Research'}

Authors & affiliations

Shadreck Muchaku
Affiliation not supplied

Hlekani Kabiti
Affiliation not supplied

Bernard Nthambeleni
Affiliation not supplied

Deposited references

Supplied references, not a list of publications citing this article.

DOI: 10.55982/openpraxis.16.3.674

DOI: 10.3390/logistics7040089

DOI: 10.61969/jai.1337500

DOI: 10.1016/j.jvb.2024.104011

DOI: 10.1007/s10956-023-10039-y

DOI: 10.1007/s13384-024-00787-0

DOI: 10.4018/979-8-3693-3045-6.ch010

DOI: 10.14742/ajet.8843

DOI: 10.1109/MIS.2016.93

DOI: 10.1016/j.resplu.2024.100825

Esteves, R. M. A. (2024). Applications, Challenges, and Ethical Implications of Generative AI: A Systematic Review (master’s thesis, Universidade NOVA de Lisboa (Portugal)).

DOI: 10.1186/s41239-024-00445-6

DOI: 10.29322/IJSRP.13.03.2023.p13536

DOI: 10.1016/j.socscimed.2019.05.035

DOI: 10.37074/jalt.2024.7.2.8

DOI: 10.3390/educsci14020172

DOI: 10.28945/5239

Kelley, T., & Dickerson, K. (2020). A review of artificial intelligence (ai) algorithms for sound classification: Implications for human-robot interaction (hri).

DOI: 10.1111/bjet.13227

DOI: 10.1007/978-981-97-2211-2_7

DOI: 10.1177/07356331241240460

DOI: 10.7717/peerj-cs.2105

DOI: 10.3390/su15021558

DOI: 10.1007/s10639-022-11316-w

DOI: 10.1109/EDUCON54358.2023.10125121

DOI: 10.37074/jalt.2023.6.1.29

Reitinger, N. (2015). Algorithmic choice and superior responsibility: closing the gap between liability and lethal autonomy by defining the line between actors and tools. Gonz. L. Rev., 51, 79.

DOI: 10.3389/frai.2023.1195797

Stokel-Walker, C. (2024). How AI Ate the World: A Brief History of Artificial Intelligence–and Its Long Future. Canbury Press.

DOI: 10.1038/s41562-024-02001-8

DOI: 10.1007/s11528-024-00942-5

DOI: 10.1016/j.compositesb.2024.111740

Widodo, Y. B., Ramadhan, G. J. M., Priyangan, D. M., Ginanjar, A., & Nurajizah, S. (2024). Unleashing the Potential of Artificial Intelligence: Advancements, Applications, and Ethical Considerations in Information Technology. Join: Journal of Social Science, 1(3), 198-207.

DOI: 10.1038/s41562-024-02004-5

DOI: 10.1007/s10639-022-11161-x