Generative Artificial Intelligence in Higher Education: Why the 'Banning Approach' to Student use is Sometimes Morally Justified
Open accessAbstract
There has been significant discussion among academics and policymakers about managing the use of generative artificial intelligence tools, such as ChatGPT, Gemini, and GitHub Copilot, in higher education, particularly regarding student usage (Eke, 2023 , Malmström et al., 2023 , Yeadon et al. 2023 ). Many universities have adopted a 'nuanced approach,' which encourages responsible use of these tools to achieve high-quality outcomes while adhering to ethical principles and regulations (McDonald et al., 2024 ). This middle-ground stance is recommended by many involved in the policy debate (Gimpel et al., 2023 ; Rudolph et al., 2023 ; Slimi & Carballido, 2023 ). The belief is that these tools are largely beneficial, that their negative effects can be managed, and that they will become ubiquitous, making resistance futile. Not all institutions align with this approach—some are more welcoming of these technologies, even mandating their use, while others ban or strongly discourage their use (McDonald et al., 2024 ). Footnote 1
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GenAI causes environmental damage, with CO2 emissions and water consumption particularly concerning.
“Finally, genAI causes environmental damage, with CO2 emissions and water consumption particularly concerning (Carrigan, 2024;de Fine Licht, 2024;Driessens & Pischetola, 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as de Fine Licht, 2024
Section 2.1, “The Case for the Banning Approach” (page not provided), says generative AI has a negative environmental impact and that its energy consumption contributes to higher carbon emissions. It discusses energy used for cooling, but does not identify water consumption as a concern; that part of the claim is unsupported by this paper. (LLM, conf=0.86)
Experimental — accuracy not yet measuredFew scholars explicitly define or problematise the meaning of ethical use of genAI.
“However, few explicitly define or problematise the meaning of ethical use (cf.de Fine Licht, 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as de Fine Licht, 2024
The Introduction (page unavailable) says discussions of genAI policy often remain general and lack systematic analysis or structured arguments, which supports the concern that ethical-use recommendations receive limited scrutiny. It does not say that few scholars explicitly define or problematise what “ethical use” means. (LLM, conf=0.74)
Experimental — accuracy not yet measuredThe individual's control over their own data, combined with widespread ignorance about the implications of sharing it (rendering informed consent impossible), are moral issues.
“The individual's control over their own data, combined with widespread ignorance about the implications of sharing it (rendering informed consent impossible), are also moral issues (de Fine Licht, 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as de Fine Licht, 2024
Many participants believed genAI use is inevitable.
“As in a Dutch case study (Encheva et al., 2025), many believed genAI use is inevitable -even though scholars have suggested refusing or banning genAI for ethical reasons (Carrigan, 2024;de Fine Licht, 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as de Fine Licht, 2024
By engaging in what de Fine Licht calls a reasonable and inclusive process for making decisions about genAI, these participants began implementing partnership ethics.
“By engaging in what de Fine Licht calls a”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as de Fine Licht, 2024
Teachers are tasked with instilling knowledge and skills in students.
“They are tasked with instilling knowledge and skills in students (see de Fine Licht, 2024).”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as de Fine Licht, 2024
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Cites
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“…(Rudolph et al., 2023; Qadir, 2023, Williams 2024), the potential benefits are also well-acknowledged, including enhancements in productivity, a deeper comprehension of AI technology and the subject matter, and increased inclusivity (Mollick & Mollick, 2022, 2023; Rudolph et al., 2023).”
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Sorted by citations
Barus, O., Hidayanto, A. N., & Eitiveni, I. (2025) · Polyglot: Jurnal Ilmiah · doi:10.19166/pji.v21i2.10020 · Cited by 6 · see citing works
Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education
Gillette, M., Wackenhut, A., & Olsson, E. (2026) · Journal of University Teaching and Learning Practice · doi:10.53761/yf2gt848
“However, few explicitly define or problematise the meaning of ethical use (cf. de Fine Licht, 2024).”
Influential
- Authors
- de Fine Licht, K.
- ORCID
- de Fine Licht, Karl
- Venue
- Philosophy & Technology
- Published
- 2024-08-31
- Volume
- 37
- Issue
- 3
- ISSN
- 2210-5433 (ISSN-L)
- 2210-5441
- OpenAlex
- W4402079082
- Cited by
- 40
- References
- 15
- Citations by year
- 2026: 24 · 2025: 15 · 2024: 1
- FWCI
- 15.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Philosophy & Technology (publishedVersion, cc-by)
- Chalmers Research (Chalmers University of Technology) (submittedVersion, cc-by)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- Funders
- Chalmers University of Technology
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- generative AI, ChatGPT, student use of AI, moral justification, responsible AI use, academic integrity, artificial intelligence in education
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