Trusting the Algorithm: Exploring Higher Educators' Confidence in Generative AI Tools for Academic Assistance

Abstract

The rapid diffusion of generative artificial intelligence (GenAI) in higher education is transforming academic teaching, research, and administrative practices while simultaneously challenging institutional structures for governance, professional development, and academic integrity. Despite the growing use of GenAI tools, empirical evidence concerning higher education faculty members’ use and engagement—particularly within contexts characterized by infrastructural and institutional constraints remains limited (Ouyang et al., 2022). This study examines patterns of GenAI use perceived usefulness, perceived ease of use, and ethical concerns among faculty members in Palestinian higher education (Bacalso et al., 2026). Drawing on the Technology Acceptance Model (TAM; Davis, 1989) and extending it through an ethical dimension, the study employed a cross-sectional quantitative design with data collected from 300 higher education faculty members. The study used descriptive statistics, internal consistency analysis, and one-way ANOVAs to examine faculty responses and differences across age cohorts and academic ranks. The findings indicate higher reported use of GenAI for teaching materials and research tasks, relatively favorable perceptions of its usefulness and ease of use, and substantial ethical concerns, particularly regarding the need for institutional guidance. Significant differences emerged across age cohorts and academic ranks, with younger and more junior faculty generally reporting higher use, perceived usefulness, and ease of use, while older and more senior faculty reported stronger ethical concerns. These findings support a governance approach that moves beyond both outright prohibition and unconditional endorsement toward transparent ethical guidance, context-sensitive pedagogical frameworks, and structured opportunities for responsible experimentation and professional learning.