Generative AI, creative thinking, and the future of arts education. Everything from the session in one place, plus a stack of reading for the flight home.
Jer Nelsen · Interim Dean, South Carolina School of the Arts, Anderson University
Joseph Fasano
Now I let it fall back
in the grasses.
I hear you. I know
this life is hard now.
I know your days are precious
on this earth.
But what are you trying
to be free of?
The living? The miraculous
task of it?
Love is for the ones who love the work.
Love is for the ones who love the work.
Sourced from poets.org, Academy of American Poets.
Real dance lives in a trained body, makes choices nobody predicted, and carries something from a lived life. Art is embodied. Discipline, original thinking, and voice are what our programs exist to develop.
It shortcuts the practice. It predicts instead of improvising, drifting toward the average. It flatters instead of witnessing: every student now carries a tireless yes-machine.
The same tool can put a student on two curves. Used as a substitute, capability erodes. Used as a sparring partner, capability grows. The tool doesn’t decide which curve. The posture does, and posture can be taught.
Build human skills first, hard skills on top, and specific, fleeting technical skills last. The human layer is AI-resistant and highly transferable. We’re preparing students for jobs that don’t exist yet.
Curiosity, creativity, critical thinking, communication, collaboration. Which one are your students getting best? Which one could AI erode?
Students aren’t asking for less human contact because of AI. They’re asking for more: connection, psychological safety, being seen. Arts programs already deliver nearly all of Gallup’s “Big Six” by design. We may be the model.
The questions from the room, for your next faculty meeting, retreat, or chair’s council.
What happens in your school or college that can’t (or shouldn’t) be replaced by AI?
What’s your next step?
Find what others do well, and adopt it. Give it to faculty you trust. Learn what you can. But don’t fool yourself.
Practical structures for talking about AI with faculty and students, from policy to the single assignment.
An ethically grounded model for the responsible use of AI in education. It asks what AI produces in us, not just what it produces. The first two questions look at the present; the last two look at who we become over time. It applies to faculty as much as to students.
What essential qualities of genuine human relationships and habits are being preserved?
Student check: Am I still doing the thinking, or has this tool begun thinking for me?
What aspects of learning, habit, or formation are being quietly weakened?
Student check: Is this tool helping me engage more deeply, or making it easier and shallower?
What skills risk being lost over time through reliance on the tool?
Student check: If I keep using it this way, what will I stop being able to do?
How can AI strengthen learning or access without replacing human responsibility?
Student check: Is this helping me learn, or helping me avoid the work of learning?
A shared language for telling students “when and where” AI belongs in an assignment, adapted from Leon Furze’s AI Assessment Scale. Put the level on the syllabus or the assignment sheet, and the guessing stops. Any use of AI must always be acknowledged.
Show independent knowledge or skill. In-class work, critique, exams.
Research and definitions. Verify everything.
Brainstorm and outline. You author or execute the final work.
Refine language or media. Submit drafts alongside the AI-refined version.
Generate, then critique. Your analysis is what gets graded.
AI as a creative collaborator throughout the work.
Perkins, Furze, Roe & MacVaugh
The widely adopted five-level scale behind many campus policies, including ours. Free to adapt, with a peer-reviewed update.
Leon Furze · free eBook, CC BY-NC
Bias, environment, truth, copyright, privacy, datafication, affect recognition, human labour, and power, with discussion prompts for every discipline.
UNESCO
A global, human-centered starting point for institutional policy, with steps for regulating and validating AI tools.
Founded by Joy Buolamwini
Research, art, and advocacy on who gets seen, and missed, by AI systems. A great on-ramp for students in any studio.
Bryan Alexander · newsletter
A futurist’s steady, readable scan of AI across higher education: policy, economics, teaching, and where it all might be heading.
The shelf behind the talk, plus a few for leading the change on your own campus.
Johan Roos · Routledge, 2026
The backbone of the session: the two curves, the five capabilities, and Hult’s layered curriculum. “AI brings the options, but humans bring the meaning.”
José Antonio Bowen & C. Edward Watson · 2nd ed., Johns Hopkins, 2025
An essential guide for postsecondary educators on how AI is changing learning, and how teachers can adapt while protecting human thinking and integrity.
Ethan Mollick · Portfolio, 2024
Treat AI as a co-worker and co-teacher. Practical principles for how it changes education and work, from one of the clearest voices in the field.
Salman Khan · Viking, 2024
The Khan Academy founder’s case for AI tutoring, including Khanmigo. Worth reading alongside the research on answer-giving tutors.
Simon Sinek · 2009
The engine behind the five program questions. If AI can do the what and the how, the why is what’s left.
Ed O’Malley & Julia Fabris McBride · 2023
Leadership as an activity anyone can exercise, not a position. Built for adaptive problems like this one, where no one has the answer yet.
Michael D. Watkins · Harvard Business Review Press
A playbook for stepping into a new role or leading a new initiative: learn fast, secure early wins, and build the coalition you’ll need.
Amy C. Edmondson · Wiley, 2019
The research on why people take risks, speak up, and learn, and how leaders hold high standards and high safety at once.
Will Guidara · 2022
How the most human details create loyalty. Read it as a dean thinking about the student experience.
Jonathan Haidt · 2024
How phone-based childhood rewired the students arriving in our studios and rehearsal halls.
Greg Lukianoff & Jonathan Haidt · 2018
On fragility, safety, and why struggle matters, an argument for keeping productive friction in the work.
Henry Cloud & John Townsend · 1992
Care and limits belong together. Useful for the “not yet, try it again” conversations a yes-machine never has.
bell hooks · Routledge, 1994
Engaged pedagogy and the classroom as “the most radical space of possibility.” For us, that’s the studio and the critique room.
John Berger · ed. Geoff Dyer · Aperture, 2013
The camera never made anyone a photographer. Someone still has to learn to see.
James Baldwin · Library of America
Includes “The Creative Process” (1962), on the artist’s job to make the world “a more human dwelling place.”
Ursula K. Le Guin · 1969
Uncertainty isn’t a problem to solve before we start. It’s the condition we work in.
Joseph Campbell · 1949
Every hero needs a mentor, and the mentor never fights the dragon for them.
The studies behind the claims, plus a few more worth bringing to your provost.
Bastani et al. · PNAS, 2025
Students with an answer-giving AI tutor did better in practice, worse on the exam, and believed they’d learned just as much. A tutor that gave hints did no harm.
Cheng et al. · Science, 2026
AI that agrees with us makes us less willing to repair conflict, and more likely to come back for more.
Lee et al. · Microsoft Research, CHI 2025
The more people trusted AI, the less critical thinking they reported doing. Confidence in your own skill pushed the other way.
Brynjolfsson, Chandar & Chen · Stanford Digital Economy Lab, 2025
Early-career workers in AI-exposed jobs are seeing the first employment declines. Entry-level work is the apprenticeship, and it’s shrinking.
Gallup–Purdue Index · 2014
A professor who made them excited to learn, one who cared about them as a person, and a mentor. Only 14% of graduates had all three, and they were more than twice as likely to be engaged at work.
Masahiro Mori · 1970 · English translation, IEEE Spectrum
The original short essay on why the almost-human unsettles us. Pairs well with any dancing-robot video.
“The only thing that makes life possible is permanent, intolerable uncertainty: not knowing what comes next.”
Ursula K. Le Guin The Left Hand of Darkness, 1969
“You can’t use up creativity. The more you use, the more you have.”
Maya Angelou Bell Telephone Magazine, 1982
“No tears in the writer, no tears in the reader. No surprise for the writer, no surprise for the reader.”
Robert Frost “The Figure a Poem Makes,” 1939
“Who codes matters, how we code matters, and why we code matters.”
Joy Buolamwini TED, 2016
“The precise role of the artist, then, is to illuminate that darkness, blaze roads through that vast forest, so that we will not, in all our doing, lose sight of its purpose, which is, after all, to make the world a more human dwelling place.”
James Baldwin “The Creative Process,” 1962
“The classroom remains the most radical space of possibility in the academy.”
bell hooks Teaching to Transgress, 1994
“The first principle is that you must not fool yourself—and you are the easiest person to fool.”
Richard Feynman “Cargo Cult Science,” 1974
“This is precisely the time when artists go to work. There is no time for despair, no place for self-pity, no need for silence, no room for fear.”
Toni Morrison The Nation, 2015