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This study investigates university teachers’ relationships with emerging technologies by focusing on the uptake of artificial intelligence in higher education practices. We utilise an experimental philosophy approach to i) determine university teachers’ intuitions around universities’ responsibilities to adopt new artificial intelligence technologies, ii) understand the conditions under which university teachers consider artificial intelligence defensible and, hence, would be willing to introduce such tools and services into their daily practice and iii) specify teachers’ self-reported knowledge of artificial intelligence. An online survey, where participants were sent one of three different cases (Case A related to first-generation students, Case B, an archetypical student, Case C, students with a learning disability), and 18 identical questions across all three cases. The survey was distributed among 1773 teachers. Based on the responses of 194 university teachers, we identify differences related to responsibility, equity, and knowledge about artificial intelligence. Our quantitative data exhibited that in Case A and Case C, the respondents ranked to a higher degree that universities should use artificial intelligence tools and systems to achieve equitable outcomes. Data revealed no statistically significant associations among the respondents with regard to background variables in Case A. However, Case B and Case C disclosed statistically significant associations concerning gender, age, faculty, and academic position among the participants. Moreover, we identify teachers’ fears and scepticism about artificial intelligence in higher education, concerns about fairness and responsibility, and lack of knowledge about artificial intelligence and resources to engage with artificial intelligence in teaching practices. |
