Revisiting "The Future's Already Here"
Looking at my first talk about GenAI from February 2023
About 3 years ago today, I did my first talk about GenAI and education. It was a 1-hour session for NERCOMP; the event page is still up for you to see. To date, I’ve done just over a hundred talks, keynotes, and consultation sessions around GenAI and higher education, been invited to a dozen podcasts, and well, published over 100 posts on this Substack, and written about 10 articles for different publications.
I’ve been thinking about that trek and some of the things I learn as I prepare for an upcoming keynote that’s a bit of a retrospective to help make sense of the current moment in higher ed in terms of where we are with all of this. I’ll be sharing that talk here as well so I won’t go into that for this post.
3 years later, and I think many of the points of the talk still hold up.
To no one’s surprise, I have the slides (with CC license) available. I also have a recording, and while it’s not the live recording from the session, it was one that I did right after the talk so as to make it more widely available since folks were interested.
On one slide, I explore the different responses to GenAI or the camps that I was seeing established at the time, and I would say that many of them are still present in what I have seen since then.
One bit of progress that I do appreciate seeing is how more institutions are more engaged with their students around AI on lots of different levels.
There’s one section that I pull out the old crystal ball to think about what this means for the future:
And a lot of higher ed is going to miss the conversation around AI and education because they are going to be looking at it straight on. They’re going to be thinking about how AI will replace them in the classroom and frame it in the current model of how teaching and learning exists. If AI does take hold, it’s going to look different from how traditional learning in higher education looks because traditional higher ed is a model of convenience and doesn’t necessarily center the students and how they learn; rather they center on a critical mass of students, a centralized location, a frequency of visiting that location for arbitrary sets of time set by the Carnegie Foundation over a 100 years ago. And that’s not going to be how learning with AI is going to look like. It’s going to be dynamic in when and how long it happens, it’s going to be a mixture of generalized and contextualized to the individual, and probably–unfortunately–less social.
But importantly for the rest of us, we will have to anticipate changing (or continuing to change) our teaching and learning practices; we can no longer be production lines and focused on the banking model of education. AI Generative tools will beat us every time in terms of speed, timeliness, context, scale, and efficiency. So we’ll need to reposition teaching and learning increasingly to relationship-building through which trust and risk can feel more possible by students–it’s a way of offering something that will be different from what AI-learning can do.
I return to this idea a bit more in a later blog post (before the Substack) where I try to explain that I think there is a chance that GenAI changes what formal learning can look like. I both worry about that and am intrigued by it, given my own learning journey.
Anyway, sharing this look back and look forward since it’s been on my mind and it is the anniversary of that first talk. Enjoy.
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Continuous Improvement Summit, February 2026
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Recent Recordings, Resources, & Writings:
Margin of Thought with Priten: Season 1, Episode 5: How Can We Center Pedagogy During the AI Tech Wave? (February 2026)
Online Learning in the Second Half with John Nash and Jason Johnston: EP 39 - The Higher Ed AI Solution: Good Pedagogy (January 2026)
The Peer Review Podcast with Sarah Bunin Benor and Mira Sucharov: Authentic Assessment: Co-Creating AI Policies with Students (December 2025)
David Bachman interviewed me on his Substack, Entropy Bonus (November 2025)
The AI Diatribe Podcast with Jason Low (November): Episode 17: Can Universities Keep Pace With AI?
The Opposite of Cheating Podcast with Dr. Tricia Bertram Gallant (October 2025): Season 2, Episode 31.
The Learning Stack Podcast with Thomas Thompson (August 2025). “(i)nnovations, AI, Pirates, and Access”.
Intentional Teaching Podcast with Derek Bruff (August 2025). Episode 73: Study Hall with Lance Eaton, Michelle D. Miller, and David Nelson.
Dissertation: Elbow Patches To Eye Patches: A Phenomenographic Study Of Scholarly Practices, Research Literature Access, And Academic Piracy
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AI+Edu=Simplified by Lance Eaton is licensed under Attribution-ShareAlike 4.0 International
Going back to the 2023 talk and seeing what held up versus what didn't is exactly the kind of reflection we need more of. The predictions that aged well tend to be the ones grounded in how people actually learn, not in what the technology was capable of. Three years of evidence now makes the "just wait and see" crowd less convincing. The questions you were asking back then are still the right questions - the urgency has just increased.