Faculty opt-out of generative AI is more substantial than student non-use, with value-, identity- and risk-based reasons¶

Claim · All claims
Evidence · 1 study · theoretical r3 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Shata's 2025 study of 294 full-time US faculty found 33.6% reported not using generative AI, citing readiness, value, identity, perceived threat to human intelligence and wider risk. → Zagami 2026

Evidence¶

Zagami 2026¶

Zagami, J. (2026). AI refusal in higher education: the right to refuse, the duty to understand and the diagnostic value of non-use. Higher Education Research & Development, 45(7), 2287-2294. https://doi.org/10.1080/07294360.2026.2694409

q2 · i? · theoretical · r3

Second-hand study reported by the article: a survey of 294 full-time faculty at two mid-sized US public universities in which "33.6% reported not using generative AI". The article attributes this to Shata (2025) and treats it as indicative of role-specific tension.

"Shata’s (2025) study of 294 full-time faculty members at two mid-sized public universities in the United States found that 33.6% reported not using generative AI, with reasons including readiness, value, identity, perceived threat to human intelligence and wider risk."

Discussion¶

Related Claims¶

• Teachers who perceive the challenges and barriers of using AI as high (cost) may be less motivated to use it (theoretical argument). — the general claim this finding bears on, with the studies behind it
• The most reported risks of AI tools in science and chemistry education are ethical issues, including gender and racial bias, hallucinations, copyright infringement, and plagiarism — related