Promoting Ethical Use of Generative AI in Education
Open accessAbstract
Generative artificial intelligence (AI) represents a crucial subset of AI models characterized by their ability to generate new content based on user input, showing vast potential to transform learning and teaching. However, educators have raised ethical concerns, particularly regarding the adverse effect on students' learning if students simply parrot generative AI-generated content without engaging in critical analysis or original thought. Moreover, there exists the potential of generative AI to perpetuate existing biases in training data. This editorial discusses three major concerns in generative AI use in education and proposes questions (on task-AI fit and people-AI fit) and approaches to address the ethical considerations by adopting five principles of AI ethics. The editorial also discusses developing a classroom AI use policy as one governance mechanism for promoting ethical use of AI. As generative AI technology continues to evolve, so must our educational practices. The editorial ends with a call for readers (educators) to collaboratively define the terms of engagement with generative AI in educational settings and to begin this discourse by sharing insights and experiences with promoting ethical use of generative AI.
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In 2023, a University of California study found that online platforms like Coursera and EdX recommended advanced STEM courses at a higher rate to male students compared to women or underrepresented minorities.
“It was found that algorithms tended to recommend advanced courses in science, technology, engineering, and mathematics (STEM) at a higher rate to male students compared to women or underrepresented minorities.”
From Ethical and regulatory challenges of Generative AI in education: a systematic review (2025) · cites this paper as Deng and Joshi, 2024
This bias reflected historical patterns in enrolment data and perpetuated barriers to access to STEM fields.
“This bias reflected historical patterns in enrolment data and perpetuated barriers to access to these fields of knowledge.”
From Ethical and regulatory challenges of Generative AI in education: a systematic review (2025) · cites this paper as Deng and Joshi, 2024
Integrating the perspective of educators, technologists, and students in the design of regulations will strengthen their applicability and relevance.
“In addition, integrating the perspective of educators, technologists, and students in the design of these regulations will strengthen their applicability and relevance (Deng and Joshi, 2024).”
From Ethical and regulatory challenges of Generative AI in education: a systematic review (2025) · cites this paper as Deng and Joshi, 2024
Regulatory policies should be harmonized at the international level to ensure that technological innovation is ethically managed.
“Deng and Joshi (2024) advocate for the harmonization of regulatory policies at the international level to ensure that technological innovation is ethically managed.”
From Ethical and regulatory challenges of Generative AI in education: a systematic review (2025) · cites this paper as Deng and Joshi (2024)
GenAI presents societal and ethical challenges related to equity, academic integrity, bias, and data provenance.
“Generative AI (GenAI) presents societal and ethical challenges related to equity, academic integrity, bias, and data provenance.”
From Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education (2025) · cites this paper as [78]
Cites
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 2× · see citing works
“This aspect of GAI is found critical in addressing individual students’ varied learning styles, allowing for a more adaptive and responsive educational environment (Kasneci et al., 2023).”
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., et al. (2018) · Minds and Machines · doi:10.1007/s11023-018-9482-5 · Cited by 4,774 · cited 2× · see citing works
“This editorial discusses three major concerns in GAI use in education and proposes questions (on task–AI fit and people–AI fit) and approaches to address the threats to ethical use of GAI in education by adopting the five principles of AI ethics (Floridi et al., 2018).”
The ethical use of artificial intelligence in human resource management: a decision-making framework
Bankins, S. (2021) · Ethics and Information Technology · doi:10.1007/s10676-021-09619-6 · Cited by 181 · see citing works
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Ethical and regulatory challenges of Generative AI in education: a systematic review
García-López, I. M., & Trujillo-Liñán, L. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1565938 · Cited by 144 · see citing works
Sen, R., & Deng, X. (2025) · Journal of Information Systems Education · doi:10.62273/zlum4022 · Cited by 25 · see citing works
Self-citationKumar, A., Baijal, A., & Kharat, M. (2025) · Journal of International Education in Business · doi:10.1108/jieb-07-2024-0086 · Cited by 6 · see citing works
Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education
Mak, J., Nakatumba-Nabende, J., Clear, T., Clear, A., Abluwi, I., Andrei, O., Angeli, L., MacNeil, S., Oyelere, S. S., Hale Rattigan, M., et al. (2025) · Proceedings of the 2025 Working Group Reports on Innovation and Technology in Computer Science Education · doi:10.1145/3760545.3783975 · Cited by 12 · see citing works
- Authors
- Deng, X. (., & Joshi, K. D.
- Affiliations
- California State University, Dominguez Hills (US)
- University of Nevada, Reno (US)
- Venue
- ACM SIGMIS Database: the DATABASE for Advances in Information Systems
- Published
- 2024-07-31
- Volume
- 55
- Issue
- 3
- Pages
- 6-11
- ISSN
- 0095-0033 (ISSN-L)
- 1532-0936
- OpenAlex
- W4401175810
- Cited by
- 34
- References
- 3
- Citations by year
- 2026: 17 · 2025: 17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM SIGMIS Database the DATABASE for Advances in Information Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, AI ethics in education, ethical use of AI, AI-generated content, student learning, critical thinking, training data bias, AI ethics principles, AI governance
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