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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