Who is actually arguing about this

Person · Northern Arizona University

Grounds campus AI debates in actual cognitive science on memory, attention, and critical thinking rather than hype or panic.

Person · University of Mississippi

On-the-ground reporting from a writing instructor running one of the longest-standing faculty AI institutes.

Person · University of Calgary

Tracks how AI is reshaping academic misconduct policy and coined the postplagiarism framing now used across the integrity field.

Person · College Unbound

Practical synthesis for faculty developers building AI training programmes rather than only policies.

Person · University of Mississippi

Veteran teaching-centre perspective on turning AI uncertainty into concrete low-stakes classroom experiments.

Person · Queens University of Charlotte

A teaching-centre director's frank take on AI policy fights inside faculty governance and the equity implications of AI mandates.

Person · Independent consultant, Australia

The most detailed practitioner breakdowns of what specific AI writing tools actually do to student text.

Person · College of Marin

Open-education-rooted, classroom-tested activities and rubrics for teaching writing alongside AI rather than around it.

Person · University of Illinois Urbana-Champaign

The librarian's view of how AI is reshaping information literacy and scholarly publishing, which faculty rarely see from the classroom side.

Person · Grand Valley State University

Candid in-progress documentation of how AI is forcing a mathematician to redesign grading and assessment.

Centre · University of Michigan

Shows what large-scale institutional AI experimentation looks like when a university puts real grant money behind it.

Centre · MIT Sloan

Sharp myth-busting practical guidance, including why AI detectors do not work, aimed at faculty who need answers.

Outlet · American Association of Colleges and Universities

Where the institute programming that shapes faculty AI training at hundreds of institutions is designed.

Outlet · ICAI

The professional home of academic-integrity officers, whose norms become de facto sector policy on AI and cheating.

Outlet · UNESCO

Global policy and equity framing, including competency frameworks and access questions Western coverage ignores.

Person · Vice Provost for AI and Technology in Education, New York University

The only provost-level officer arguing a large university's AI reasoning in public rather than issuing it as a memo, so you can see what your own administration is weighing.

Person · Vice President for Academic Affairs, Brookdale Community College

The chief academic officer's view of why AI policy stalls, from the two-year sector that teaches a third of US undergraduates and is almost absent from AI commentary.

Person · Director of Digital Learning Initiatives, Dartmouth Center for the Advancement of Learning

His standing interview format asks the administrators nobody else asks, so you get the operational and procurement view in their own words.

Person · Director of AI, Jisc, the UK national body for tertiary education technology

The nearest thing to a CIO writing in public: he names specific vendor configurations to turn on or off, and says why.

Person · Head of Data Services, Singapore Management University Libraries

Runs actual experiments on AI literature search and publishes the negative results, which is the only reliable answer to whether Elicit or Consensus can be trusted for a review.

Person · Senior Lecturer, School of Medicine, University of St Andrews

Reads the new empirical literature on AI in health-professions education each week and reports what it actually found, rather than what it promised.

Person · Executive Vice-President and Professor of Molecular Medicine, Scripps Research

The clearest running account of where AI is actually deployed in clinical care, the world that health-professions students and clinical researchers now walk into.

Person · Associate Teaching Professor of Neurobiology, University of California San Diego

For lab scientists who must still build coding and data skills in students when the model will write the script for them.

Person · Professor of Mathematics, University of California Los Angeles

Publicly dissects AI-assisted proofs line by line and sets norms for disclosing machine assistance, which is what mathematics departments are arguing about.

Person · Visiting Lecturer, Indiana University Maurer School of Law

Builds and tests legal AI workflows himself and publishes the costs and failures, so you can see what practice-ready competence now means before deciding what to teach.

Person · Presidential Professor, The Graduate Center, City University of New York

Gives arts and design faculty a theory of what image models do to authorship and style, from someone who both makes the work and teaches its history.

Person · Professor of English, College of Western Idaho

Writes from inside an open-enrolment two-year college, so her experiments are costed for classes of working adults and first-generation students with patchy device access.

Person · Associate Professor of Engineering, Harvey Mudd College

A STEM professor at a tiny teaching-first college who reasons through philosophy of technology rather than disruption-speak, useful when defending a choice without a research budget.

Person · Dean of Teaching and Learning, Vanguard University of Southern California

The best on-ramp for a non-technical instructor who wants to hear another named human describe exactly what they tried in a real course last term.

Person · Professor of English and Applied Media, Berkeley College

Writes up the mechanics of moving a course to alternative assessment under AI conditions, and takes student resistance seriously rather than as non-compliance.

Person · Head of Administration, Department of Clinical Medicine, Aalborg University

A continental-European administrator writing in English about AI meeting a Nordic system built on problem-based learning rather than the Anglo-American essay.

Person · Senior Lecturer, Universiti Pendidikan Sultan Idris, Malaysia

The implementation layer for a middle-income, multilingual system, which is far closer to most of the world's teaching conditions than US institutional guidance is.

Person · Independent developer, co-creator of Django

Explains in plain English what each new model release can and cannot do, tested first-hand rather than repeated from the announcement. Useful to anyone who has to judge a capability claim before committing to it, whether the decision is about a course, a research method, or a procurement case. He also documents failure modes such as prompt injection and unreliable output, which vendor material leaves out.

Centre · Raspberry Pi Foundation, UK education charity

Publishes free computing curricula, teacher training and classroom material, together with the work of the computing education research centre it funds. The hardware notes are useful to anyone assembling low-cost laboratory instruments, field equipment or teaching kit on a small budget. Because it is a charity rather than a vendor, the teaching material is free to reuse and adapt.