You Can't Co-Design What You Don't Operate
An article discusses the challenges of faculty AI buy-in in higher education, framing it as a human factors engineering issue. It argues that effective co-design requires operators to have substantial experience with the tools before they can contribute to governance. The author emphasizes that governance should be developed after sustained use of AI tools in real educational contexts, rather than based on superficial familiarity.
- ▪The article argues that faculty AI buy-in is a human factors engineering problem.
- ▪It emphasizes that operators must have substantial experience with tools before they can effectively co-design governance.
- ▪The author suggests that governance should be developed after sustained use of AI tools in real educational contexts.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 1447774) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Michael Tuszynski Posted on May 20 • Originally published at mpt.solutions You Can't Co-Design What You Don't Operate #highered #aigovernance #humanfactorsengineering #facultydevelopment An article circulating this week argues that faculty AI buy-in in higher education is a human factors engineering problem. The framing is correct. The path the piece describes skips the only two steps that matter, and the reason it skips them is structural, not pedagogical.
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