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Attitudes towards artificial intelligence among students and faculty staff at Kuwait University's Health Science
Hamad AlHamad1, Ahmad Alenezi2, Musaed Z Alnaser1
1Occupational Therapy Department, Faculty of Allied Health Sciences, Kuwait University, Health Sciences Center, Kuwait City, Kuwait.
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BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare and health-professions education. While it may improve efficiency, decision support, and learning, it also raises concerns about workforce impacts, safety, privacy, and accountability. Gulf-region evidence on how students and faculty perceive AI across disciplines within a single health science center remains limited.ObjectiveTo assess attitudes toward AI among health-sciences students and faculty and examine demographic factors associated with these attitudes.MethodsA descriptive cross-sectional online survey using convenience sampling was distributed to Health Science Centre (HSC) students and faculty (605 students, 43 faculty). It included demographic variables and two standardized measures, the General Attitudes towards Artificial Intelligence Scale (GAAIS) and the Artificial Intelligence Attitude Scale-4 (AIAS-4). Internal consistency was assessed using Cronbach's alpha; groups were compared using Mann-Whitney U and Kruskal-Wallis tests.ResultsAttitudes were broadly positive in both groups. Faculty scored higher than students on GAAIS (62.0 vs 55.5; p < 0.001) but not AIAS-4 (68.7 vs 63.1; p = 0.094). Among students, males scored higher on GAAIS (61.2 vs 54.9; p < 0.001) and AIAS-4 (71.4 vs 62.2; p = 0.004). AIAS-4 also differed by nationality (Kuwaiti 64.3 vs non-Kuwaiti 56.6; p = 0.005) and major (p < 0.001), with lower-GPA students less positive. In multivariable regression, male gender, Kuwaiti nationality, higher GPA, and discipline were independently associated with AIAS-4; physical-therapy students scored significantly lower than several disciplines.ConclusionsStudents and faculty demonstrate broadly positive attitudes toward AI alongside concerns about safety, surveillance, and workforce displacement. Structured education, practical exposure, and ethics- and governance-oriented teaching may support responsible AI integration in health-professions education and practice.