Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective
Abstract
The study aims to explore the factors that influence university students’ behavioral intention (BI) and use behavior (UB) of generative AI products from an ethical perspective. Referring to ethical decision-making theory, the research model extends the UTAUT2 model with three influencing factors: ethical awareness (EA), perceived ethical risks (PER), and AI ethical anxiety (AIEA). A sample of 226 university students was analysed using the Partial Least Squares Structural Equation Modelling technique (PLS-SEM). The research results further validate the effectiveness of UTAUT2. Furthermore, performance expectancy, hedonistic motivation, price value, and social influence all positively influence university students’ BI to use generative AI products, except for effort expectancy. Facilitating conditions and habit show no significant impact on BI, but they can determine UB. The three extended factors from the ethical perspective play significant roles as well. AIEA and PER are not key determinants of BI. However, AIEA can directly inhibit UB. From the mediation analysis, although PER do not have a direct impact on UB, it inhibits UB indirectly through AIEA. Ethical awareness can positively influence BI. Nevertheless, it can also increase PER. These findings can help university students better accept and ethically use generative AI products.
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More experience in hands-on use of GenAI leads to an increase in confidence in its ethical and appropriate utilisation, and fostering ethical awareness can positively impact student use of GenAI.
“Studies have suggested that more experience in hands-on use of GenAI leads to an increase in con fi dence in its ethical and appropriate utilisation (Kelly et al., 2023), and that fostering ethical awareness can positively impact student use of GenAI (Zhu et al., 2024).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Zhu et al., 2024
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Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module
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“Studies have suggested that more experience in hands-on use of GenAI leads to an increase in con fi - dence in its ethical and appropriate utilisation (Kelly et al., 2023), and that fostering ethical awareness can positively impact student use of GenAI (Zhu et al., 2024).”
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- Authors
- Zhu, W., Huang, L., Zhou, X., Li, X., Shi, G., Ying, J., & Wang, C.
- Affiliations
- Hangzhou Normal University (CN)
- University of Edinburgh (GB)
- Corresponding author
- Huang, Lei
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2024-03-08
- Volume
- 41
- Issue
- 1
- Pages
- 742-764
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W4392595892
- Cited by
- 143
- References
- 28
- Citations by year
- 2026: 67 · 2025: 63 · 2024: 13
- FWCI
- 53.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Funders
- China National Social Science Key Project, Research on the Ethics and Limits of AI in Education Scenarios (27)
- Scientific Research Fund of Zhejiang Provincial Education Department (7)
- Hangzhou Philosophy and Social Science Planning Project (Z22JC057)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Decision Sciences › Information Systems and Management › Ethics in Business and Education
- Keywords
- generative AI, university students, moral consciousness, behavioral intention, use behavior, UTAUT2, ethical decision-making, technology acceptance, AI ethics
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