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A conversation with Jeff Grabill, Dean of the College of Arts and Sciences at the University at Buffalo
“There has to be friction. There has to be failure. Students have to fall down and skin their knees.” – Jeff Grabill
In this episode of the New Friction podcast, host Douglas Ferguson speaks with Jeff Grabill, Dean of the College of Arts and Sciences at the University at Buffalo, recorded in the immediate aftermath of the IHE US AI Summit 2026, which both men attended. Grabill recounts what emerged from that two-day working convening: the foundation of the Buffalo Statement, a collective public agenda for AI in higher education, and reflects on why the room’s patience, grounded confidence, and willingness to question prior assumptions exceeded his expectations. The conversation explores why universities, often criticized for moving slowly, may possess exactly the right instincts for AI transformation: designing conversations intentionally, engineering productive friction, and moving fast and slow at the same time. Ferguson and Grabill dig into how AI has relocated rather than eliminated friction, particularly in learning environments, where effortless output now threatens the productive struggle that actually builds expertise and ideas. They close on a librarian’s insight from the summit — “I don’t care if AI created it, I care if it’s true” — and Grabill’s call for businesses and universities to actively seek one another out as partners in working through this moment.
This episode is part of the Facilitation Lab Podcast. See all episodes
Show Highlights
[00:01:26] The Summit and a Missing Public Agenda
[00:05:17] Vulnerability as the Summit’s Secret Ingredient
[00:09:40] Disciplinary Identity and the AI Conversation
[00:18:02] Why Higher Ed Needs a Design Practice
[00:20:07] Moving Fast and Slow at the Same Time
[00:25:44] Unpacking the New Friction
[00:29:46] Engineering Productive Friction in Education
[00:51:34] Truth Over Authorship
Links | Resources
About the Guest
Dr. Jeffrey T. Grabill serves as Dean of the College of Arts and Sciences at the University at Buffalo, the university’s largest academic unit, a role he assumed in August 2025. Before UB, he spent four years as Deputy Vice-Chancellor for Student Education at the University of Leeds, and nearly two decades at Michigan State University — ultimately as Associate Provost for Teaching, Learning, and Technology, where he co-founded the Hub for Innovation in Learning and Technology. He developed and led a research center on written communication and technology and co-founded Drawbridge, an educational technology company that spun out of his research group. Grabill is the co-author of Design for Change in Higher Education, published by Johns Hopkins University Press, and his work focuses on how rhetoric supports citizenship, learning, and institutional change.
Transcript
Douglas Ferguson:
Welcome to New Friction. I’m Douglas Ferguson. AI just made execution almost free. So why are organizations still stuck? Because the friction didn’t disappear. It moved and it multiplied. It’s no longer in building. It’s in deciding what to build, how to align, and how to move forward when the path isn’t clear. That friction, the human side of change, is what this series is about. Each episode, I sit down with leaders who are living it, navigating the real challenges of AI transformation, not the tools, the people. The task that took two weeks now takes two minutes. The work isn’t the bottleneck anymore. The conversation before the work is. That’s the work this show is about.
Today I’m with Jeff Grabill at the University of Buffalo, where he’s the dean of the College of Arts and Sciences. He’s also the author of Design for Change in Higher Education from the Johns Hopkins University Press. Welcome to the show, Jeff.
Jeff Grabill:
Douglas, thank you. It’s always a pleasure to talk with you. I learn a lot when we do, so thanks for the invitation.
Douglas Ferguson:
Oh yeah, it’s amazing. And the feeling is mutual. So let’s talk about the last two days. We just spent two days with 300 people drafting a public agenda for AI and higher ed. And if we strip away the panels and reflect on what was the single biggest thing that’s actually shifting right now, I’m curious what’s emerging for you, especially in the afterglow.
Jeff Grabill:
A couple of things. Yeah, so the conversation was, I thought, fantastic and exceeded my expectation. So let me back up a step and walk through your question. So the purpose of the meeting, we’d noticed, and I wasn’t the only one who’d noticed, but those of us at the University of Buffalo had noticed, not just that there was no public agenda for AI. There was an Ezra Klein podcast about that. I think lots of people have noticed it.
But also that there was no public universities in particular, but universities more broadly weren’t stepping into that space. And we’ve all been floundering a little bit. And as soon as we started socializing with people that the fact that there’s no public agenda for AI is a problem, and absent leadership in Washington, frankly, who’s going to step into that space and start to do more than wring our hands about it, but start to articulate how we might collectively and collaboratively proceed.
So the notion of having a meeting, a working meeting, not a conference, in which we put the lack of a public agenda on the table and put the question of what is the role of the university in relationship to that public agenda on the table, I was really pleased at how many people rallied to that. This is a great idea. So we had nearly twice as many people at that meeting than we thought. We tried to curate that meeting as best we could with expertise. It was a working meeting. We are going to produce the Buffalo Statement or some such thing which starts to sweep together the meeting.
So what surprised me about it? I was pleased, but not necessarily surprised at what I just said, that the reaction was immediate, the reaction was positive, and people have rallied to it. I was surprised in the meeting at how positive people were and how grounded people were. In other words, there wasn’t a lot of hand wringing and anxiety, and we’ve got to catch up in that room. And there was actually a sense of patience and confidence that universities have been around a very long time, and there’s a reason for that, and that there’s some durable value in what universities have to offer and we ought to lean into that because that will probably be durable.
But at the same time, there is a role for us. Universities are suffering a little bit right now. The public opinion of universities is as low as it’s been in a really long time. And so we also recognize that if we step in as a platform and a convener and a collaborator, we have a little bit of work to do to get people to trust us the way they used to trust us. So surprised at the confidence and the positivity, the patience, those were the things I took away, and I was pleased by those surprises.
Douglas Ferguson:
Absolutely. I was actually very impressed by just how the group showed up and collaborated, and especially in a moment in time where there’s not a lot of collaboration across disagreement. I found people bringing differing points of view, and actually taking the time to consider and listen and think about how those points of view might get integrated. I took it as a testament to your curation of who was in the room, but also still impressive, and it gave me a sense of hope.
Jeff Grabill:
Yeah. No, thank you for picking that up. I picked it up too because that meeting didn’t work if that didn’t happen. So if people came in and sat back on their hands, or looked at their phones for two days and refused to be a little bit vulnerable, it requires some vulnerability to sit at a table with some people you don’t know and dwell in that space. Let’s try to figure some things out together. I think that’s why the meeting worked. I’m really pleased you noticed it. I think you nailed it. That’s why we had a productive two days.
Douglas Ferguson:
Just to be real specific for the listeners, one great example of that is you had folks that were super optimistic about things and they were looking at the data center impact as a job creating event. And then you had folks that were looking at data center impact on the environment and were very concerned about it. But there’s room for both of those points of view, and it wasn’t argumentative. It was very curious. And people were creating space for the opposite points of view. And I think we need more spaces like that today, and especially in this AI conversation.
Jeff Grabill:
I completely agree with you. And some of the academics in the room that were most skeptical and oppositional are my colleagues in the College of Arts and Sciences here. And I was thrilled that they were there, but I rotated tables, I sat on a table for a while with some of them. I was even happier the way they showed up. They’re worried. This is their science. They understand things, they have expertise. But they did create space in the conversation, and I think in their own minds, for possibilities that are a little bit different than their defaults.
There was an economist in the room who kept talking about this moment with regard to the labor market, for example, another example of a really productive conversation is that we have to question all of our priors about how innovation cycles and disruption cycles work because this one doesn’t seem to be tracking with our priors. And so I thought that was a really, it’s a very economist way to speak, but I thought that that was something that happened across the room, and that everybody sort of checked their priors a little bit and opened the possibility that maybe those priors were wrong.
Douglas Ferguson:
There was a moment in one of the panels where, and I’m blinking on the individual’s name, but he offered a call to action to all the universities to tap their historians and maybe present to all the faculty and staff around these historic moments of what it was like to live through the printing press revolution, or any of these other technological revolutions that how can we draw from those moments and maybe imagine ourselves, and how it’s similar, how it’s different. I thought that was really awesome to think about, hey, we have these resources on campus. Let’s maybe share them with our peers, not just the students and the researchers.
Jeff Grabill:
No, I think it’s a key insight. I’ve also, to build on that, have a business school dean in my past whose favorite people on campus were historians. Because he not only read history, but he talked to them because the coffee conversations that he had with historians were better at grounding his sense of where the financial markets were going to go in the future. Because the things that seem sort of disruptive and new to us, you talk to a good historian, they’ll say, “Well, maybe we’ve been here before.” And they unpack it for you. And then in a way, we have been here before and in a way we haven’t. And I think that kind of wisdom, history’s useful in that regard. So not the first time I’ve heard it, but I thought I remember that. And that was a really useful contribution too. The historians in the room loved it.
Douglas Ferguson:
Yeah. It’s reminded me of Jeff from Worcester’s comment about how it’s not about using the AI tools, but it’s about how experts in a discipline will leverage it for the best use of that in that discipline. And so not only how are we leaning into our historians, but our economists, our librarians. They need to develop their use cases that are very idiosyncratic and how they bring their expertise into these new tools.
Jeff Grabill:
Yeah. He and I had a real meeting of the minds about that because he’s a new dean of Arts and Sciences. He’s four days in. I’m 10 months in as a new dean of Arts and Sciences. The University of Buffalo’s been an AI forward university for a long time. We intend to stay there. And I have a lot of skeptical, grumpy, worried academics across my college. And the only ask I’ve made of them with regard to AI is, I need you to engage. You can’t sit it out. So if you sit it out, I’m going to be frustrated with you. So please don’t. Engage. You can be grumpy, you can be skeptical, you can be yourself. Be yourself as an individual, be authentic, be yourself as a disciplinary creature, which is what Jeffrey was talking about. Be that person and we’re going to be fine.
But if you check out and disengage, that’s not who we’re supposed to be as leading public research universities. We don’t get the option to disengage. That’s not the job. And then to their credit, they roll their eyes sometimes at me, and the dean is opining again, but they’ve engaged. And there were people in that room the last two days who might not have been there had we not collectively worked on this in the college here at the University of Buffalo.
Douglas Ferguson:
Yeah. I’m thinking about that conversation more deeply now. And one of the things that really stuck with me listening to Jeffrey talk about that was this idea that it’s okay to be a cynic, but you need to be an informed cynic. If you just dislike it because you dislike it, well, that’s not helpful to developing thought and points of view.
Jeff Grabill:
Yeah. And I think that’s a really important challenge. I mean, I used to say this when I was mentoring graduate students, and it’s a real privilege to be a university professor. Yes, everybody who gets there works really hard, is also super lucky. Lots of people help you get there. You catch some breaks. But it’s a privilege and it’s a responsibility.
And one of the conversations I used to have with the graduate students that I mentored is really challenging them to own the responsibility. It means something to be a university professor at a leading research university, and there’s expectations for us. To say what I said earlier, we don’t get the option to sit it out. That’s not the job. The job is to push the edges, push the frontier, think the thoughts that are not supposed to be thought or that are challenging. This is why we have academic freedom.
Our job is to be on the edge and to support people in doing that work. We’re supposed to do hard things. And those are hard conversations to have with people. And they’re hard for me to own because sometimes I’m just tired. But that’s the work. And to get back to the meeting, that’s what I wanted to do with the meeting is give us a space to signal to each other that we’re not alone as a group of intellectuals, intellectuals in private industry and intellectuals in the university who know that this is the work that we have to do.
Douglas Ferguson:
And I want to come back to this idea of no public agenda. If I remember correctly, Armada pushed back and said there’s already one, and the danger is reacting our way out of it, I think was her position. And so basically not doing anything or abandoning it because they’re scared of looking slow.
Jeff Grabill:
Yeah. I thought that was a key moment. So this is one of the things where I changed my mind. Because I mentioned earlier, we’re going to write this Buffalo Statement, and hopefully it’s good and people pick it up and work with it and engage with it. I’ve written a draft of it before the meeting because I didn’t want to go in the meeting cold. And we’re going to write it together. The meeting was a writing workshop in many respects.
She changed my mind about that. And her point was there is no public agenda for AI in the United States. There’s no policy agenda, there’s no blueprints that a government would provide, for example, or a set of institutions might provide. What her argument was, universities have a public agenda for AI, and we don’t need another public agenda. We just need to be ourselves and do our thing.
And I’m not entirely sure I completely agree with her, but in another way, I think she’s really right. And I suspect that this Buffalo Statement’s going to reflect that in the sense we shouldn’t wait around for the federal government, for example, to fix itself. God knows how long that’s going to take. In the meantime, we need to proceed, and here’s what it might look like for us to proceed with public universities in particular leading.
Douglas Ferguson:
Yeah, that was something Eric and I were talking about a bit yesterday. He was referencing some research that’s in a book that I need to read, and I need to reach back out to him about this. But this idea that a big challenge in higher ed is this kind of layers and layers of purpose, and how those different purposes will conflict with each other often, or maybe not conflict, but it’s which one do you focus on? And this came up a bit at dinner, even not only multiple purposes, but how people define and personally define a purpose. What does student outcomes mean? So I’m curious how that… It seems like that was an idea that was kind of orbiting some of this stuff, and maybe even wrapped up in Armada’s kind of thinking there.
Jeff Grabill:
I think it was, and it did come up at dinner. So let me back up a step. So for a period of time, I was on a reasonably large writing committee for Michigan State’s strategic plan. I’m not sure whether it’s the one they still have, but it’s the one they wrote just before around the pandemic. Anyway, we would talk with external stakeholders about purpose. What is the purpose of Michigan State?
And external stakeholders were surprised at any purpose that wasn’t education or that didn’t foreground education. So most of the public doesn’t really see the research purpose, for example, of a research university because they didn’t necessarily experience it. But if you talk to academics at a research university, it is the primary purpose. They are primarily there to do that kind of intellectual work. They do the education work too, but they often see it as a zero sum game. The more time I spend on education, the less time I get to spend on my research.
And that’s a very real tension inside universities, and that’s just with those two purposes. And when you start to layer on all the ways in which universities have become social service institutions. We have students who are homeless. We are their home. We run giant food service operations. We have performing arts venues. We have community engagement programs. We provide a set of services in every community that we’re in. If we’re unfortunate enough to be in a big athletics conference, we run professional sports franchises on the side.
That’s the accumulation of purposes that tends to weigh down universities. One of the things that’s been really interesting about the pressure that the Trump administration has put on universities is it has caused universities to go back to basics, and say, look, we do research and we educate, and we’re going to try to focus our energies on those two things. And that’s not a bad return to focus and purpose.
Douglas Ferguson:
Yeah, that’s fascinating. You also mentioned this idea of blueprint, and maybe there isn’t a blueprint. We’ve been noticing a lot that industry folks are struggling with the fact that there’s no model to follow. And that is, I would say, at high levels of the organization, and all the way down to the individual level. We just haven’t developed these ways of working, these patterns. Folks have done agile for years, for example. But now AI is shifting things, and so they can’t reach out for the Spotify model or these examples. We can just run that play and do it again. And so I think everyone’s in this moment of redefining what it means to work, what it means to show up and exist in these systems.
Jeff Grabill:
Well, and this is why I’m hoping that, and this gets into your area of expertise, you’ve talked with Eric about this, I keep waiting for higher education, my business, to discover design and to discover facilitation and relationship to design because we just haven’t. This is a moment of real uncertainty. The patterns don’t work, our analogs don’t work particularly well. And so all of my instincts are that we design our way through them.
And it’s kind of what we tried to do in some… So we designed an interaction for two days to try to produce an outcome and a set of relationships and a set of conversations. I really do think that wise organizations and wise institutions are going to lean into those design practice. And if they don’t have a design practice, partner with people like you who can help them develop a design practice.
I keep waiting for higher education to… We did it at Leeds at scale. They’re still doing it at the University of Leeds at scale, but it’s really hard to develop design capacity inside a university organization and get people into that mindset that this is the way in which we’re going to come up with some provisional answers to who we think we are and where we think we need to go. Because as was said at the meeting the last two days, the only thing we can’t do is everything that we’ve done in the past just as we’ve done it in the past.
Douglas Ferguson:
Yeah. And you hit the nail on the head with the word mindset. And I would argue that it’s not just difficult in universities, it’s difficult anywhere where the mindset doesn’t exist or hasn’t taken root because then you’re talking about real behavioral change at a deep worldview perspective. We have to shift how people think about the world, or think about work, and we have to shift, and it’s happening fundamentally. They’re relearning, they’re reshaping things, and that takes time and commitment.
Jeff Grabill:
Yeah. And it gets back to something that was also true or said in the meeting. And I used to say this at the University of Leeds all the time, and it drove people nuts until they experienced it over a couple of years, that you have to move fast and slow at the same time. And it’s possible to move fast and slow at the same time. And some of that means sprinting to get some activation energy, but nobody can sprint all the time. And so there’s a fast moment. And then getting it right is something that we can do slowly if we’ve started and we have some rhythm and some pace in the work that we do.
So I’m a big believer in designing ways of working inside universities that allow us to move fast and slow with really intentional different modalities. Let the virtues of university slowness work its way out. But within those long, loopy cycles, let’s use some fast moments to have some activation energy, some pace, some rhythm to get us through the moments where we get stuck because in an institution that tends to move slowly, when we get stuck, that quickly becomes sort of catastrophic inertia. We just never move again.
And so developing some ways of working which are different for higher education, not different for some organizations, that allow us to leverage the virtues of slowness, but be able to move at a different speed when we need to. For us at Leeds, that was the key. And I’m really curious to see whether we use that as a way of thinking our way through this AI moment because we’re making it up as we go along, and that’s not the worst thing in the world if we’re intentional about it.
Douglas Ferguson:
Yeah. I had already kind of bookmarked the word intention because you mentioned that earlier, so I love that you came back to it. And that points to the fact that this is a design challenge. Design is just being intentional about what we do. It’s taking a step back and looking at it. And I would argue good design also includes it’s human centered and brings everyone into the conversation so that we can be thinking about the broader impacts and how systemic things might be.
And the other thing that came to mind for me when you were talking about the slow versus fast is often people think of them as just opposites. I’m either slow or fast. But thinking about how we intentionally design slow moments versus fast moments, and also taking, I love the martial arts mantra of slow is smooth, smooth is fast. And so sometimes we need to do slow things so that then other things become fast. And I think that’s where, you look at a design sprint, there are moments specifically designed into that protocol where we’re going to slow down with each other so that then the follow on work, we can move very rapidly on because we have high degree of a confidence in it.
Jeff Grabill:
Yeah. And that also accommodates… One thing that’s true about a university is, and it’s true probably of most organizations, but universities have, well, I don’t know, we just have a broad spectrum of cognitive styles and dispositions. And that’s also a strength of how people think together. Let’s stay with the sprint. Some of what happens in the sprint is just too fast for people. They need time to disconnect, they need time to think, they need time to process.
And so there’s the moment where you try to slow down within a sprint, but I also think we need some post-sprint space as well for us to not over-engineer what comes out of that sprint and be intentional as well about the reversibility about where we landed in that sprint. And then give some people some time, but not too much time, to think and to dwell and to walk around with it. There’s a long bit of intellectual history of discovery which includes walking. Newton and many others. The relationship between a long walk and a scientific breakthrough is a long one.
Douglas Ferguson:
Absolutely. Yeah. And the other thing that came to mind when you were talking about taking time to think is the fact that whenever we’re working visually together, as we go off and diverge and think about things, the visual prototypes give us an anchor so that we know that we’re at least in the same vicinity, our vectors are aligned, so that then when we start to diverge, we know we’re diverging from the same place. And there’s a lot of power in that, our ability to move more swiftly later because then we’re not way off track when we try to reintegrate later.
Jeff Grabill:
Yeah, that makes perfect sense. Can I ask you a question?
Douglas Ferguson:
Oh, please do.
Jeff Grabill:
Yeah. So I’m interested. We haven’t had a chance to talk about this notion of the new friction. This is the podcast container. And you talked about the friction moving a little bit. It once was here and it’s moved there. Could you unpack what that means? Because I’m also trying to listen to you in relationship to where that friction might be moving in higher education, and whether it’s the same or different, but I wanted you to unpack that a little bit more so that I could listen to you a little bit. Is that fair?
Douglas Ferguson:
Yeah, that’s totally fair. And in fact, it’s funny, that was the next question I was leading up to, just waiting to see when the conversation naturally got there. So perfect. Yeah. So our argument lately, or we kind of developed a thesis around this idea of the new friction. And on the surface, you might look at how AI is making things so easy to create and build and make things that it’s eliminated that friction or it’s eliminated friction in general. Because that was kind of the main friction people would run into, especially in industry. It was like, oh, we need to make a strategic plan. We need to make a blog post. We need to write some software. The LLM is very powerful at helping us do those things, draft them, refine them, bring new thoughts to the table, et cetera.
And so even though it eliminated that friction, or definitely smoothed out a lot of that friction, it sort of reallocated the friction across the org. It introduced new frictions, or it highlighted old frictions that have always been there. We often talk about friction or dysfunction in an org that was kind of just existing on the sidelines, or we could hide it in the margins, but now we can’t ignore it anymore because literally we can make things so fast that now all this dysfunction around decision making, alignment, actually discernment, coming together and actually disagreeing, like creating space so we can disagree, a lot of organizations fail at that.
What we were remarking around the success of your meeting, a lot of organizations are horrible at creating disagreement in a healthy way, that healthy conflict that’s so important. And so my vantage point and stance is that we should be attending and taking note and inventory of the frictions that matter now. It could be old frictions that we kind of ignored. Which those are the hardest ones to diagnose because we’ve lived with them forever. We kind of accepted them as normal. And so it’s easy to discount them.
But we should be noticing new frictions that are emerging that were never there before. And an example of that is it’s so easy to go generate, let’s say, a strategy doc or a new design brief. And once you create it, it comes out looking finished. It is so polished. It is so done. It is immaculate and beautiful and gorgeous. And it’s using turns of phrase, or just really like, I would say intoxicating, right? And then folks see that and they go, “Oh my gosh, this is like, okay, dusting off my hands, job done.” And they tend to throw it over the fence or put it in the repository. And things are stacking up and stacking up and piling up and piling up. And there’s no time for disagreement. There’s no time for discernment and is it the right thing? Are we headed in the right direction?
And so it comes back to your point around intentional slowness. Even though the speed is, I’m going to use the word intoxicating again, we shouldn’t do speed at all costs. That shouldn’t be the posture that LLMs can just make us fast. Well, how can we direct it towards something that’s of more value? And so it’s somewhat diagnosing the frictions that have always held us back, but are now getting amplified by this AI amplifier, and new frictions that it’s creating. My hypothesis is that it would also be heavily prevalent in universities too because I think it’s maybe a principle of how this technology is going to just impact humans.
Jeff Grabill:
No, that makes perfect sense. Yeah. Because it made me think a little bit about some of the relatively, well now very early research on AI and productivity, so year, 18 months ago, which measured productivity mostly in terms of the frictionless way of making things. It made a certain employee more productive because they were faster. They could make product, but it wasn’t necessarily better product. And I think that that’s where it shows up.
So the best example, and this also came up in the meeting, and I think this is the primary friction point right now in education with regard to AI is what will this do to learning? And to put it on the back of an envelope, there’s no learning without effort. And so effortless productivity, for example, effortless productivity is not going to produce learning. It’s just not going to happen. And so when you have students who can effortly produce a beautiful document, they might have produced a beautiful document, but they haven’t learned anything because it’s frictionless.
So I think one of the things that’s very true about education is that there has to be friction. There has to be failure. Students have to fall down and skin their knees. A good teacher is going to engineer friction. And a good teacher’s also going to pick students up when they fall down, give them a chance to reflect on… I used to write assignments that students couldn’t do. And the students who were doing a bad job with the assignment just sprinted off and started doing it. And the students who did well with the assignment came back to me a day later and asked me questions like, “What? What? I don’t think we can do this.” And I would say, “Thank you.”
And the whole point was to get them to ask the right questions when they’re given an ambiguous ask, as opposed to running forward and trying to do it. And eventually everybody would get really frustrated and everybody would fail and everybody would fall down. And we’d pick them up and they would learn a lot from that. And so that was exceptionally useful.
So that’s the friction now in education is where’s the friction located? Because friction isn’t bad. It’s actually quite productive. And so the friction used to be here in education, and in most educational contexts, the friction is now somewhere. And I think educators are really struggling about where to design friction in the educational environment. The irony of all of this to me, who spent 20 years, 20, almost 30 years thinking about education as well as my research, is that the thing that’s going to pull us through it is the thing that we know how to do really well.
We know how to design really effective high impact learning experiences for students. We know how to do friction well. The problem is that in the worst of our learning environments, and if we admit it to ourselves as educators and universities, we have a lot of frictionless learning environments right now, and they’re being destroyed by AI.
And so this was a theme in the meeting. We don’t have to invent new ways to solve this problem in higher education. We know what to do. We just have to do it in a different place than we used to do it. So there’s both a really interesting, there’s hope there, but it is also, for people like me, there’s real frustration because the answers to the AI friction problem, if you will, are in front of us. We’ve known them for a very long time. We just have to get educators to spend the time and energy to engage in them.
And that’s the problem. Because what’s happening right now in education, on the education side of higher education, is that AI is causing us to spend more time and energy on education than we’re used to spending and that most faculty would like to spend on teaching. And so this will be the tension for higher education is do we get people to spend the time and energy for the next couple of years to sort this out? Because we can and we will. The faster we do that, the better and happier we’re going to be as faculty and the more productive and happier our students are going to be, which is another design problem.
So how do we focus the intention of the organization with intention to get in a room or two and solve the problem and iterate on the solutions over the next couple of years? That’s the right way to do it. The wrong way to do it is to get on social media and moan and wring our hands and try to do the things in the future that we’ve done in the past because AI has eaten homework and we’re going to have to sort that out. Does that make any sense?
Douglas Ferguson:
Absolutely. And you’re making me think about how there’s this conversation around the importance of critical thinking as being a really important skill of the future as it relates to leveraging AI and making sure we’re preparing people just to be good stewards of this technology and preparing them for just living in the future.
And then there’s debate of what is critical thinking? And it’s like, how do you define it? And as you were talking about your professors being gifted and skilled at creating friction, specifically friction that creates the best learning moments. And I started to think about how, in a way, if you could define critical thinking as individuals starting to internalize this idea of the friction that helps me learn and how do I intentionally introduce the friction that helps me learn? And so if you develop as an individual those skills of being able to inject that at any moment.
And so I wonder if there is a… Well, I personally find it fascinating to use LLMs to help me create friction. And the research world of AI, they refer to that as adversarial. You could use an agent to be an adversarial agent to critique and break down the work that was generated by another agent. And there can be layers and layers of adversaries looking at things from different vantage points.
But at the same time, when we’re talking about bringing it into AI Team moments or even Copilot moments, we can ask the LLM to bring in friction rather than to generate things. How is it helping us slow down and think and inject some perspectives or just some skepticism around what we’re trying to accomplish? But the thing I don’t know, and probably would require more research to prove out, is if the LLM is doing that, does individuals witnessing that and receiving those questions and that pushback help them internalize that behavior more, or do they just become reliant on that?
Jeff Grabill:
Well, I mean, there’s so much in there. So one of the areas in which I’ve worked for a long time, and we’ve spun some technology out of the research center that my colleagues and I had at Michigan State. So we had a company for roughly 15 years. We have a software service that scaffolds a feedback intensive pedagogy. And it’s really simple. And one of the principles though is that human beings learn as much, in some cases maybe perhaps more, from giving feedback than from receiving it. But they do learn from receiving feedback. But nobody learns anything unless they, on the receiving side, get some instruction in how to process feedback.
Because this gets to the growth mindset whole there is an emotion and a cognition component of receiving feedback. And so helping students learn how to receive feedback is an instructional need and an instructional task for professors in any discipline. Critiques in art and in creative writing programs can be brutal. And if you don’t help students emotionally and cognitively learn how to receive that feedback and put it to productive use, it could be the best feedback in the world, but it’s not going to make a difference.
Conversely, you have to teach students how to give feedback. And when you do that, you teach students to read in particularly intentional ways. And to put whatever they’re looking at, whether it’s a schematic or a poem or a report or a piece of art, to put that performance, that object, in relationship to some criteria. And when they do that thoughtfully with some intention, they learn something about what they’re also trying to do because they’re trying to do the same thing.
And then when they have to formulate that into feedback that is also useful, it’s criterion referenced, it has some connection to what their colleague is trying to make or do or perform, and to then to craft it in such a way that that other human being can accept it from them, that’s real work. That’s friction. And those two learning modes can happen at the same time in a human intensive feedback moment. Now, these machines can give us feedback too, and that’s useful, but we still have to help human beings understand how to receive that agent provided feedback, how to engage with that agent provided feedback. There’s some metacognitive work in there.
So I think a really rich learning environment in the relatively new future is going to be a mix of agent interactions and human interactions and human to human interactions. All these ratios we can play out. I think that can work. I think I’m getting a little bit tired of the human in the loop metaphor, but we’ll use it, but not asking humans to do that work and just relying on agents to do that work, I think, again, is one of those instances in which that’s frictionless and we probably don’t want that.
To add another layer, and then I’ll stop talking, you’re good at designing agents. I’m not. But I want to get good at designing agents. And we’re going to have to teach our students, as we move from chat to agents, one of the places in which some friction is going to be located is the design of agents themselves, and the kind of intentionality and thoughtfulness that we put into that and how we learn from that.
Douglas Ferguson:
Yeah. And I think that’ll get easier the more abstraction layers that get added there. And when people build harnesses that allow people to conceptualize these things more easily, or that are aligned with models that they have already existing in their worldview. Because if you think about in the world of agents, it’s sort of like managing a small team. And so once the harnesses are starting to take on some of those perspectives, or maybe others adjacent perspectives that make it easier to understand and easier to approach, but if I had to guess today, taking the hiring metaphor, and this came up at dinner too, it’s like, how do you hire agents? So it comes down to like what’s the job description? And then how do you think about what’s required of them to do great work, and then how do you measure that great work and how do you delegate tasks in an efficient way? If those problems are well-defined and solved within the harness, I think it becomes a lot easier for people to understand how to employ an agent.
Jeff Grabill:
Yeah. How important for you is it to understand what’s going on with that agent or to understand something about the construction of a harness for you to understand what the agent’s really doing and not doing? Because sometimes it’s what the agent’s not doing that’s as interesting as what an agent does. Does that make sense as a question?
Douglas Ferguson:
Yeah. I think as someone who’s just eternally curious, it does fascinate me how the LLMs come to their conclusions and whatnot. But when I put on my business hat, and I’m CEO of Voltage Control Douglas, some of that doesn’t matter. It’s like, did I get the result that I needed? Did I learn something critical? Did it make me realize something new, a gap that I was missing?
I have a chief of staff agent, and one of the things the chief of staff agent does is it looks over everything that happened in the prior week. So all of our meetings, everything in the calendar. We do our strategic meetings in a Miro board. So that Miro board is consumed as well as all the Slack messages that we’re sending back and forth. And it builds up a list of all the important themes, as well as any potential gaps we might be missing, to make sure that when I go into the strategic meeting with the team, I’ve got a list of things that I need to be concerned with.
And the interesting thing about that is I don’t just use that as the agenda, but it often surfaces things that it’s fallen off my radar. Much like a great chief of staff would say, “Hey Douglas, don’t forget about X, Y, and Z client.” And then it’s like, “Yeah, we need to make sure we resurface that.” And so that’s, as far as how it’s functioning, and I’ve even run into some issues with that. And I had another LLM actually fix the issues. So rather than me going in and updating the prompts, I had my developer agent go in and correct that routine that the chief of staff is running.
And so I care less about the prose that’s in that prompt and I care more about the outcomes that we’re driving for the organization when I’m purely in the CEO hat. But of course, my computer scientist, like internally curious Douglas, often looks under the hood because I’m like, “Hey, how’s this working?” I want to tinker with it for sure.
Jeff Grabill:
Yeah. So this tension sort of came up in the meeting here at Buffalo for the last two days about the alignment of incentives in an organization like yours and the alignment of incentives in an organization like mine. And if it works, and this is not a criticism, but if it works, you’re really happy with it because it helps you with the bottom line incentives. And then for me, we might care less about whether it works and more about peering under the hood and making sure that we’re curious.
And I think that’s a really, this another thing that I learned yesterday listening to my colleagues talk about why it’s so important to build these things, and that we would build them differently for different purposes and different organizations. And peering under the hood is a really good idea. But also the fact that we can peer under the hood is a really important, that has to be true, that there has to be some traceability and visibility in terms of data and operations. And we have to be able to see under the hood.
Anyway, I’m rambling a little bit, but it’s interesting. I’m glad you’re curious. But some of our students are not curious and they need to be. And so another place in which we need to engineer some friction is we need to say, “No, I need you to peer under the hood and tell me what’s inside and tell me what you understand about it.”
Douglas Ferguson:
Yeah. It’s sort of like coming back to the age old show me your work. If you can’t justify it, you need to understand some of the underpinnings here. And I think the thing where it comes up the most for me is if I’m using it to help me draft things, then it surfaces up some new thought that I haven’t seen before, especially on content side of things, then I’m really digging in and going, okay, where did that come from? Where’d you come up with this? Because I want to, A, make sure it didn’t hallucinate, but also I want to understand the sources. And I think that’s not a technical under the hood. That’s more of a under the hood of the where’s this coming from and where’s the real knowledge?
Jeff Grabill:
And it’s a really important displacement. So at the end of the day, I’m a writing teacher. And one of the ways in which effort in activity is going to be displaced in how we teach people to write, which I hope we still do, is, for example, writing teachers used to spend a fair amount of time with certain writers in their classroom at the sentence level, just helping them understand why these sentences are not grammatical English or don’t work particularly well. And that’s valuable work. You don’t have to do that with all writers, but we would always have to do that with some writers. We shouldn’t have to do that anymore.
And writing teachers are noticing this in universities that they’re getting writing now, this came up also in the last two days in our meeting, they’re getting writing that at the sentence level is lovely. There’s nothing for them to do. And in fact, just as there’s no reason for a student to turn anything in for the last 15 years with a spelling error, there’s probably no reason for a student to ever turn anything in from this point forward with a syntax problem. But this writing can also be completely devoid of ideas and wrong.
So that’s where the effort is. And that’s an okay place to have effort. And that’s how you develop expertise. And it’s also a reason why knowing something about something is really important. I was talking to somebody at the meeting about the advice I gave to my kids when they went away to college. And the primary bit of advice was study something you love, period, full stop. That’s the most important thing to do. I don’t really care about anything else, but you have to study about something you love.
The secondary bit of advice was it’s a good idea to know something about something. So my preference was that they chose something that had some intellectual depth and history to it. So none of them were philosophy majors, but I would’ve been thrilled. I got an anthropology major, and politics, philosophy, and economics majors and thrilled. I mean, they know something about something. And that’s a durable good. And that was a big thing that came out of our meaning as well.
Douglas Ferguson:
I was thinking about this not that long ago, this idea of like, I wonder where the anthropologists will go in this world of AI, where they’ll take their thinking and research. Because I think there’s a lot to be done there. I’m waiting for it. But we’re kind of running up on time here.
I’ve got two things I wanted to end with. One was you quoted Punya Mishra, the technology’s impact on education has been modest, but its impact on society has been profound. And you argued that education has a mandate, a remit to prepare people for society and understand society and reflect it back. And so I’m curious, just any thoughts you have for our listeners just around that idea, and how AI is definitely going to reshape society.
Jeff Grabill:
Yeah. No, I was reading some… Punya’s at Arizona State. He’s clever, he’s engaging. If people are interested in education and technology, they should find Punya. So I was looking at an article that Punya and a couple of his colleagues have written. And this is true. Those of us who pay attention to technology and education know that Silicon Valley’s been trying to disrupt education for the last 20 years. And they never really do because the impact of technology has been modest on education. The television was supposed to disrupt everything. The computer was supposed to disrupt everything. The internet was supposed to disrupt everything. We’ve absorbed them and made them useful.
What has disrupted education is society. Society moves, and education has to adjust to it. Punya and his colleagues made the argument that the impact of technology on society is more profound than it is on education. And it is. It’s society that we respond to, not precisely the technology that we respond to. That seems right to me.
And I think that for those who are interested in technology and education, it’s something to think about. I mean, I’ve been rolling my eyes for a long time about technology disrupting higher education. And most of the Silicon Valley people who are trying to do this don’t understand education as a business and they don’t understand it as a cognitive and emotional activity, and therefore they always miss the mark. But I think Punya and his colleagues have it about right.
Douglas Ferguson:
Yeah. I think we’re on the precipice of seeing big societal change, especially I mean, next week there’s the big Apple event, and my speculation is that we’ll see an announcement around Gemini and Apple. And if Gemini truly replaces this… I mean, if Siri goes from being a third grader to being a PhD student that you’re talking to, that experience of actually transcribing your voice correctly, and being able to actually do things right there on the phone, people’s access to this stuff is going to just explode astronomically, and that’s going to have a huge societal impact.
Jeff Grabill:
I think so.
Douglas Ferguson:
Overnight, I think.
Jeff Grabill:
Yeah. No, and that’s how it works. Remember the camera on the phone? I thought that was the most ridiculous thing in the world. It wasn’t.
Douglas Ferguson:
Yep. Changed the course. So I want to leave you with one final one. You’re talking about AI doing the writing. And certainly there’s lots of universities. I think this even came up in the meeting. It’s like, you have to use AI, but don’t use it for your coursework or you’ll be subject to a review board. And I love this one. I think one of the panels, or one of the breakout working sessions when they were doing readouts at their tables had shared out this idea of I don’t care if AI created it. I care if it’s true. And it just hit me across… It was like slapped across the phase. I was like, “Oh my gosh, I love that they said that.” And to me, it was just undeniable. You hear it and you go, yep, that is such a good perspective and I hope that more people adopt it.
Jeff Grabill:
Yeah. I was at that table, and the woman who said it is a librarian. And it’s exactly what she said. She said, “At the end of the day, as a librarian, it has to be true. It doesn’t necessarily have to come from a human being.” And that’s going to be a big shift for us because we’re very deeply human people in libraries, but I think that that’s where we need to land. I was struck by it too. And for our table, that sentence, we wrapped in lights and sprinklers and confetti because we thought it was a winner as well. It’s a really interesting insight, isn’t it?
Douglas Ferguson:
Yeah. And it’s so simple. And I think that some of the best insights are profound in their simplicity.
Jeff Grabill:
No, I agree. They cut through it, don’t they?
Douglas Ferguson:
Yeah. Amazing. Well, as we leave our listeners, is there anything that you would like to offer them up as a final thought?
Jeff Grabill:
Yeah. I mean, your listeners, you have some educators in your audience, but mostly not. And so I guess my ask is sort of the ask of the meeting, and that is wherever you dwell, there’s probably a university or two around. If it makes sense for your business, or if it makes sense for how you choose to spend your time as a human being, your universities, trust me, they want your partnership. We’re trying to sort this out. We’re trying to do the right thing with your children and your grandchildren, the students in your community. For you, we’re trying to do the right thing for you.
And so if the universities aren’t smart enough to ask you to help them, if you want an act of generosity on your part, knock on their door. Particularly if you have something to offer in this space that we’ve been talking about. And see if there’s an opportunity for you to partner with the universities in your community so that together we can think our way through where the friction ought to be and how the friction has moved around, because I think it’s a really important question.
Douglas Ferguson:
Yeah, I love that invitation. And if folks aren’t familiar with how universities are structured, is there a role or individual or title that would be the best target for industry to reach out to?
Jeff Grabill:
That’s a really great question. We are completely impenetrable organizations.
Douglas Ferguson:
The fortress.
Jeff Grabill:
We are a fortress. We’re like a Hydra. Who knows? So it’s not obvious. So I might start with a creature called the provost. If you have a relationship with your university where you give some money, you probably have a development officer. You can always ask your development officers, “Hey, can you connect me to this person or that person?” And if you don’t have a dean of Arts and Sciences, find the creature at that university who’s the closest thing to a dean of Arts and Sciences and write them and say, “Hey, I heard this dean of Arts and Sciences saying that I should write my dean of Arts and Sciences if I wanted a conversation.” And hopefully one of those people in the Hydra will respond to you. But the development people might be the best ways because they certainly want to nurture that relationship and they will make the connections for you.
Douglas Ferguson:
Amazing. Well, Jeff, as always, it was a pleasure chatting. I learned a lot, and I think our listeners will really appreciate the time. I would just say, really impressed with all the great work and please keep it up.
Jeff Grabill:
Douglas, it’s always a pleasure to talk with you. You and your organization do really special work. So thanks for the invitation. It was fun.
Douglas Ferguson:
Thanks for listening to New Friction. If you enjoyed this episode, share it with a leader who’s in the middle of this right now. They’ll thank you for it. And if you want to go deeper, we bring leaders together through executive dinners and virtual masterminds. To learn more about our work or to inquire about exclusive executive events, visit voltagecontrol.com. I’m Douglas Ferguson. See you next time.
