Chris Wells: One is, “Oh my God, this is the worst thing ever. If you touch AI, you are a moral reprobate, and you’re gonna destroy the planet and everyone on it, and stop it you evil person.” , on one hand. And then on the other saying, “Eh, no big deal,” right? Really if you look at it, it’s, it’s, it’s not that important. Really it’s, you know, the water use is comparable. This is from a Google study. The water use is comparable to a handful of golf courses in Arizona. , which begs the question about maintaining water, maintaining golf courses in Arizona, , rather than calling, calling AI’s footprint into question, at least in my book. , and, and so I think the, the place that I try to land with my students anyway is to say the, the important questions are What, what are we actually talking about? How much computer use are we talking about? What does the data center build-out look like? What’s projected versus what’s real? , where did the burdens of expansion actually fall?

Keith Edwards: Hello, and welcome to Student Affairs NOW. I’m your host, Keith Edwards. Everyone is talking about AI almost annoyingly today, we hope to elevate the conversation. I’ve noticed a focus in higher ed on two polarizing and reactionary perspectives. On the one hand, AI is the worst thing ever. No one should use it, and anyone who does is completely irresponsible.

I’ve invited three thinkers on AI who are really exploring the nuances and complexities of AI in higher ed. We’re gonna move beyond the simplified conversations about AI and teaching in classrooms and cheating, and explore the applications across higher ed and our work behind the scenes in the infrastructure and more.

We have ethicists, environmentalists, faculty and student affairs practitioners. I can’t wait to get to the conversation. Student Affairs NOW is the premier podcast in an online learning community for thousands of us who work in, alongside or adjacent to the field of higher education and student affairs.

We release new episodes every week on Wednesdays. Find details about this episode or browse our archives at studentaffairsnow.com. This is the first episode in a series that is being sponsored by Suitable. Suitable is the only mobile first student engagement app designed to turn involvement into skill building and career readiness.

Help students understand and articulate how their engagement prepares them for what’s next. As I mentioned, I’m your host, Keith Edwards. My pronouns are he, him, his. I’m a speaker, author and coach, empowering higher education to lead with and through the challenges of this moment toward better tomorrows for us all.

Find out more about me at keithedwards.com, and I’m recording from my home in Minneapolis, Minnesota at the intersections of the ancestral homelands of both the Dakota and the Ojibwe peoples. Let’s get to our three guests today. Tell us a little bit about yourself and how you’ve come to this conversation.

And Angela, we’re gonna begin with you.

Angela Lowe: Great. My name is Angela Lowe. My pronouns are she, her, hers. I am coming from you to you all from the University of Colorado, Denver. And how I got introduced and involved in the conversation of AI is very initially I was part of a community of practice at my institution and that just really sparked the curiosity and noting at least at that time the AI that we were charged with testing did not feel very robust.

And so in one way gave me hope of okay, this robot’s not gonna take my job. But on the other hand, knowing that this technology was moving very fast. So that spurred me on to figure out can I start documenting my experience with it. For somebody in my role, I am a senior academic advisor in the College of Liberal Arts and Sciences.

And hearing all these great experts talk about it and knowing that amongst my peers they were really confused about AI. And so if I was documenting my experience, can I relay that back to them in a more tangible, helpful way in way of introduction

Keith Edwards: Great, Angela. I’m excited to hear more about you.

You’ve done some sessions for ACPA. And Nick was the one who suggested you join this conversation. So Nick, welcome. Thanks for suggesting Angela. And tell us a little bit about you.

Nick Fahnders: Credit to Gudrun. Good- Oh all my bills just fell on the floor. Keeping it real. Gudrun Nunes is who suggested Angela credit to her.

And yes Nick Fonders, he/him pronouns, teaching too many classes at too many places. But I did teach a class on AI ethics in the spring of 2026. So yes, Keith, a- as we connected at ACPA, I, I was nudging you to say “Let’s keep this conversation going.” I think the fast version is I am part of a research project that is focused on queer students thriving in college, and that’s an undergrad-focused study.

Undergrad students have a lot of feelings about AI. We’ll unpack that more as we talk. And then in that course I taught in the spring with doctoral students, I learned a lot about how people feel like they can pay to play, is the cleanest way to word it before we get into a deeper conversation of yes I…

Some people do believe AI will get them doctoral degrees, and I look forward to chatting with this group about what that feels like ethically.

Keith Edwards: Yeah. Awesome. And Chris, we’ve known each other for a long time, back to my days at Macalester College, where you still are, and Chris is a faculty member on sabbatical.

So thank you for joining us from your sabbatical. But why don’t you tell folks a little bit more about you?

Chris Wells: My pleasure. Thanks for having me. My name is Chris Wells. I use he/him pronouns. I’m a environmental historian and a professor of environmental studies at Macalester College in St.

Paul, Minnesota. I have spent a big part of my career teaching writing and using writing as, as one of the tools for critical thinking, exploration, opening up the world refining ideas and have taken that very seriously over my career. And so when the first ChatGPT model was released and I plugged something in and got an incredibly fast halfway decent-sounding response, I was kinda blown away.

It felt like a little bit of a parlor trick, to be honest. And I didn’t take it too incredibly seriously. But I guess I played around with it enough that when GPT-4.0 came out a little bit later all of the algorithms started saying, “Hey, go read this thing about this new model.” So I went back and started playing with it, and I’m not sure I’ve slept that well since.

The, the implications that it has for what I think of as core activities in higher ed are enormous. And until fairly recently, I’m not sure people have really truly started to engage with it as anything more than a parlor trick, which, as I said, is how I reacted to it initially. But I have to admit that the more I know about it, the more I find myself oscillating between the two extremes that you sketched out, Keith.

I think it’s all true at the same time. And so is all the stuff in the middle. And so I’ve been thinking and writing about this quite a bit. I started a Sub Stack which I suspect is how you know that I’ve been thinking about this. And I don’t- I expect all of us to continue to have to think about this for a long time.

Keith Edwards: Yeah. It’s true, and I saw some things on your LinkedIn and your Substack, and as I mentioned, we’ve known each other for a long time through, through Macalester College and know that you’re so committed to your students, and so committed to teaching, and so committed to the ideas of scholarship.

To see you openly wrestling with not a purely ideological perspective, but like, how do we use this? How do we think about it? How do we… How do people think about it? We shouldn’t think about it that way, and just really openly wrestling was really interesting to me. And so le- let’s begin.

You are an environmental studies professor, and I think a lot of the reactionary anti-AI perspective is rooted in people’s concern for the environmental impacts. And as I think about that and I read about that, I think there’s some real legitimate concerns about environmental impacts. And then I see some things that I think, oh that, that’s not really how it works.

That’s a little bit overblown. And so who better than an environmental historian who’s thinking about AI to help us unpack that? There certainly are clear environmental concerns. What would you want folks to know and understand about the environmental aspects of AI as we understand it now, which will probably be dated by the time we get done with this conversation, but what would you want people to understand as we think about it now?

Chris Wells: Yeah, that… Thanks for the small question. I’ll do what I can do. It is a lot to process in the same way that AI itself is a lot to process and actually I think that one of the reasons we find the conversation migrating towards those poles of best thing ever, worst thing ever is that’s how historically our society has reacted to most new transformative technologies.

So in some ways there’s nothing particularly new about AI. It is a new transformative technology that does lots of things that weren’t possible before. And some of those things are great, and some of them are destructive, and people have lots of feelings about their world being- upended. And that’s all totally normal.

Doesn’t make it any less tumultuous or chaotic, or it doesn’t make the feelings less intense. But I think at least for me, as someone whose scholarship has focused on how big technological systems and environmental transformations coexist it’s helpful to remember that even though this feels like uncharted territory, and in some ways it is, we’ve never had computers that could simulate thinking in a compelling way before or do real work for us in quite the same way that AI can.

It is a new technology, and we’ve got lots of experience with new technology. And so we can look at how earlier technological revolutions unrolled and make some guesses in-informed guesses about where things might head with AI as well. When it comes to the environmental impacts in particular, though I think the headline that I would use is that they are absolutely worth taking seriously, right?

We are at a moment when we desperately need to be decarbonizing our energy system, and We are responding to that moment with a massive data center build-out that is quite electricity hungry, right? That’s not great. That just structurally that’s a problem that we need to deal with.

The problem is not AI per se, it is increased energy use at a moment when we need to be thinking about ways to reduce it. But also at a moment when we really need to be working on decarbonizing it. So that’s… it’s serious, and it’s worth taking seriously. And to go back to your opening remarks I think it’s easy to get wrapped up in the, the two extreme versions of taking it seriously.

One is, “Oh my God, this is the worst thing ever. If you touch AI, you are a moral reprobate, and you’re gonna destroy the planet and everyone on it, and stop it you evil person.” On one hand. And then on the other saying, “Eh, no big deal,” right? Really if you look at it it’s not that important.

Really it’s, the water use is comparable. This is from a Google study. The water use is comparable to a handful of golf courses in Arizona. Which begs the question about maintaining water, maintaining golf courses in Arizona rather than calling AI’s footprint into question, at least in my book.

And so I think the place that I try to land with my students anyway is to say the, the important questions are what are we actually talking about? How much computer use are we talking about? What does the data center build-out look like? What’s projected versus what’s real? Where did the burdens of expansion actually fall?

Data centers have highly localized impact in addition to the sort of aggregate increase of electrical use. What kind of power is flowing into a data center? One that’s powered by new solar installations is gonna look really different from one that’s powered by a nuclear facility, which is also not carbon, but not environmentally great either versus one that’s a coal plant, right?

It– these are not the same thing. And then of course who has the power? Who’s calling the shots? What’s the regulatory apparatus? What kind of collective decision-making are we actually engaged in? Who’s shaping the future that we’re all gonna have to live with? And those are profound on the one hand, and also these are the mundane questions of environmental policy no matter what your topic is.

Google Assistant: Yeah.

Chris Wells: So these are big challenging questions, and they require a collective response. And there are good answers and bad answers. But for anyone to assume the entire outcome rests on their individual decisions is also perhaps steering, steering the direction in a- Direction that’s not gonna help us reach those collective decisions as quickly or as well as we might want to.

Keith Edwards: Yeah. That’s a helpful framing. Nick and Angela, do you wanna add anything to this environmental perspective before we move on?

Angela Lowe: Yeah. Thank you, Chris, for your thoughts. As I was… that’s definitely something that I include in my presentations that is one of the top ethical concerns with AI usage.

And as I think about it, I actually go back to the language that we use. And we’re doing it right now. When we say AI, we use it actually interchangeably with the larger umbrella of what AI is and what generative AI is, which is what is making the headlines right now. Technically related, but if you wanna get into the nitty-gritty, those are different terms.

And w- so if we go back to the umbrella term of AI, that has two lanes of thought for me. First is with the larger umbrella of AI, it has been around for a very long time. It’s already been integrated into a lot of our systems. It already has data centers that have been around taking up energy and water.

So when we think about environmentalism, the conversation has already been here. It has not magically appeared just because there are new data centers being built. A- and so I do encourage people of, like we should already be caring about the environment. We should already be caring about how our technology is utilizing resources.

And so how are we having a conversation environmentally long-term? Because we don’t know how the conversation of AI will continue to evolve over time. So if we’re only concerned about it in regards to generative AI data center facilities, then that will die once that shifts to something else. The second lane of thought is that i- if we’re concerned about generative AI, which we definitely should be, it’s exponentially increasing the amount of data centers and therefore the resource we are using then there are still other ways that we can nuance that conversation, going back to our title.

A- and that includes things along the lines of there are generative AIs that are more localized, and therefore using significantly less AI energy than the larger generative AI companies. And- Bringing it down to the individual, if you are just using AI for an individual prompt and asking a quick question or if you’re generating a video, those are very different ways to use generative AI and will use a very different amount of energy.

So that is one individual practical tool somebody can consider when considering i- is this ethical to just ask a question or if I’m producing a whole video with this generative AI tool.

Keith Edwards: Yeah. I wanna move us along, Nick, but please chime in on the environmental aspects. But I wanna move to you, Nick, as, as you mentioned.

We… You and I had a conversation at ACPA at a Student Affairs NOW reception about this class you were teaching, and I understood it as a focus on AI ethics and people coming in with kind of these reactionary perspectives and really when they explore more of the reality, coming to more moderate places.

Can you help us unpack a little bit about what that looks like and what you’re seeing emerging as you talked about doctoral students and undergrad students? Help us understand what you’re seeing.

Nick Fahnders: Yeah. I wanna give virtual high fives to Angela and Chris because usually I’m the one that’s pretty macro.

So in this case, I’ll be very brief and very micro in terms of application. My department chair at Northern Illinois when I was teaching that class in the spring, h- more than once in a department meeting talked about not using AI, not asking AI to be told thank you or please because words like please and thank you use energy.

So her, her TED Talk was like, “Don’t ask the question. Get it, get the results you want. Don’t use resources and energy that don’t need to be used.” And initially I was like, “That’s really funny.” But as I watched Students use AI. She had a really good point. Her na- By the way, honor shout out to Suzanne Degges-White.

Yeah, it, there’s something to be said for how you coach any AI platform to do what you want it to do and how many resources you’re using when you’re not good at utilizing a technology platform. So you need to be able to say, “Hey, AI, this is the feedback I need to give a student. Hey, AI, this is the assignment I need to, figure out.”

And what I can tell you all is at least 30 students, at least 30 undergraduate queer folks all triangulated that they tried to use AI in some way for a class, and most of it was, to your point, Keith, earlier about cheating, and AI did not help them cheat. They… It… AI failed their tests.

It did not complete the assignment. It did not get information done correctly because they said, “Here’s my ask.” They did not take the time to get to know what the system they were using did, did/does, and they did not they did not take any responsibility for their own learning, which is hard ’cause i-i-it’s easy to think, oh, I can get this degree, I can use this technology to, fast-forward my progress.

But if you’re not really paying attention to yourself, you’re not getting the results that you need, which is, which was learning 30 years ago. So Angela, I think the biggest piece I’m still sitting with too is you said AI’s been around for a long time. I know that’s true. I think we could have another chat or a, an earnest question about how long AI has been here, ’cause it’s it’s flashy now, but it’s not like it’s new.

Yeah.

Keith Edwards: Yeah.

Nick Fahnders: Yep.

Keith Edwards: I wanna bring Chris in because, Yeah … in one of your Substacks you shared a story, I believe it was from a student y- with a metaphor about elevators, and ever since reading it, I just, every time I read something about AI I was like, “Where’s the elevator metaphor?” So tell us about the elevator metaphor, Chris.

Chris Wells: Sure. The just a little bit of context. The, the name of the Substack is Teaching Upside Down, and the, the whole thing is based on an insight that, that got me thinking about this in a lot more depth, which is that a l- a lot of the teaching instruction that I have seen, especially at higher ed levels, use Bloom’s Taxonomy as a way to talk about different kinds of learning and the ways that you can scaffold things so that you start with basic knowledge and understanding and build up towards what is often considered as the, the tip of the pyramid which is making things.

And if you think about, What making things has traditionally done in higher ed assignments, or any assignments really it asks students to do all of the other things. The, you need to gather a bunch of information. You need to understand what’s going on. You need to analyze it and pick it apart.

You need to try to put the pieces back together and build an argument that draws on all that evidence and analysis and even accounts for things that you’re not pulling into the essay itself. You have to craft the argument. You have to marshal the evidence. You have to put it into a very particular form.

And then on the other hand, it’s extraordinarily easy to grade, right? I’m a very skilled reader of thesis statements by this point, and I can read the first paragraph, see the thesis, and have a pretty good sense of if they actually deliver what this paper is gonna get, right? If you have a B+ thesis, flawless execution is still gonna earn you a B+.

That’s just how it works. And AI complicates that enormously because creating things is now as easy, or can be as easy, as pushing a button.

And so I can no longer trust the essay produced outside of class as a proxy for the learning that students have done. Okay, so that’s necessary context.

Now the elevator metaphor. We were doing a, a faculty learning community at Macalester this summer. We got to- together for an entire month and spent over 25 hours together chewing on all sorts of AI-related questions. It was fantastic. But one of the best things we did was on the very first day, which was to bring in some student panelists, and one of those students said, the way I’ve been thinking about AI is that it’s kinda like an elevator.

If your goal is to get to the 30th floor, then it’s great to have it. But if your goal is to get some exercise, you’re better off taking the stairs.” And I think that, that encapsulates a lot of the problems that classroom teachers or education educators of all stripes are facing right now, which is, how do you find the productive struggle when creating things is easier than it’s ever been and requires less thought than it’s ever required?

And if you start to think like an architect you can know that there are elevators tucked around in the back, but if you design a grand staircase and you put art on the walls, and you talk about how great it is, and everyone is suddenly gathering on the stairs and walking up and down, you’re gonna have a very different experience than- If you walk in and the elevator’s right there.

Keith Edwards: Yeah.

Chris Wells: Likewise, the, the point might not be to take the stairs. The point might be the specialized weight room on the 30th floor, in which case, take the elevator. Or the point might be to break out the schematics and understand how the elevator works, right? That’s also legitimate. But thinking like an architect and understanding that when we make assignments, we are designing for a particular kind of learning experience for the students, and we need to think about how AI factors into that, whether to thwart it or to aid it.

That, that feels like the big challenge of the moment, and the student just nailed it.

Keith Edwards: Yeah. Yeah, and I, to be honest, I’ve– I wanna come back to Nick and then to Angela, but I’ve thought about that in my own AI use. And to be honest, sometimes I just wanna get to the top as fast as I can.

This is not about good thinking. This is not about rigorous… this is about, not about creativity. This is just about, I need- Not about

Chris Wells: being a learner.

Keith Edwards: It’s, yeah. And sometimes it’s not about being… Sometimes it is about being a learner and exploring and critical thinking and changing my mind and changing my perspective, and so that, that analogy has really helped me.

Nick, I’m wondering as, as you’re thinking about these doctoral students and the undergrad students what does that sort of bring up for you?

Nick Fahnders: Two quick streams of response because you asked for two streams. So for doctoral students, it– The, the truth is, before AI, there are people in our field who paid for editors to edit their doc- like, their dissertation.

They paid money to get someone to say, “Yeah you did great work, but I’ll get you to the finish line.” In this day and age, AI is a resource that is an alternative to that, that is more cost-effective. So how do you work through the ethics of somebody who’s like, “I just can’t afford to pay for an editor, but I want to be done with this degree, and I’ve done all the work, and I just need someone else to help me?”

That’s an ethical dilemma that we can unpack. So in, in the doctoral space that’s the loudest debate I’m having with my colleagues right now. In terms of undergrad and master’s students, they– they are so smart and so critical about AI usage that it really comes down to, I think- in, in the faculty seat if I’ll that, that’s the seat I’ll sit in right now.

In the faculty seat, how do I make them think about learning and building skills and tools? ‘Cause people had people before AI. You people got, syllabi and assignments and stuff from friends and peers in a fraternity or sorority or, their, on their residence hall floor. This is dehumanizing a resource that gives you a chance to learn.

So as an instructor, my job is to challenge people to just enjoy the learning process and not feel performative about get the A, get this assignment done. And to give them good feedback that does not feel AI related ’cause I, every… Honestly, everyone in the room, I’m looking at you, Keith, but everyone.

Every assignment I’ve given feedback on in the past eight months I’m, I worry that they think I used AI to give them feedback.

Google Assistant: Yeah …

Nick Fahnders: I didn’t, but that’s a totally valid critique or question. So it, it makes me anxious. Yeah. Yeah.

Keith Edwards: Angela, I wanna move to you.

And I’m curious ’cause, ’cause Nick and Chris, as faculty, are talking about lots in the classroom application and you’re outside the classroom in your focus. So I’d love to s- kinda hear your perspective on that. But you’ve been offering sessions on AI and how to use and how not to use AI as a student affairs professional.

As we think about not just the learning in the classroom and assignments, but what we’re doing beyond the classroom, what would you wanna offer folks about engaging with students around AI and our own AI use? Any cautions- … and possibilities?

Angela Lowe: Yeah. Thank you, Keith. Two main things when delving into AI and forming your own practice and forming students’ practice.

The first is, i- it– as I mentioned in my intro, I got into it because I recognized that it was becoming very quickly a daunting practice topic to delve into. And at this point, w- we’ve had the conversation about AI, generative AI, for a couple years now, at least at this peak of it. And so if you’re trying to delve in and you’re like, “This is too much,” my– it’s not groundbreaking advice.

It is just to start. I think of it the same as going to the gym. When you’re starting to get in shape for the first time, it’s not about being the expert. It’s not about knowing all the things, all the tools in the room. It’s just about getting into the gym. That’s half the battle, and if that is just trying out whatever approved AI your institution has and seeing how it works, if that is reading one article every couple of weeks to just see what the top headlines are I understand that it is a lot, and that is not the ask here, that the, the ask is to become familiar with it both for you and your students’ sake.

If you are worried about that “Once I get in, I won’t be able to stop,” that is a possibility, but if you are coming in with that intentionality, we do see research that the more AI literate somebody is, the less likely they’re actually to use it because they understand the repercussions, and they’re able to parse out what is and isn’t appropriate for my role or just in general ethically.

The second thing is thinking, thinking on a larger framework. Right now, a lot of professionals are waiting for that federal institutional departmental policy, and unfortunately, a lot of us professionals are stuck waiting. Very little has happened federally. It’s b- it’s been to the discretion of the institutions or departments at this point, and that is a little all over the place in terms of how different institutions have started to begin handling it.

And i- if you are caught in that, you’re confused, you’re frustrated by the lack of clarity, then th- the pro and the con is that means it’s up to you. Start building your own framework for what you think ethical AI usage is. Start asking yourself the questions, “Is this good or bad use of AI?” H- what would AI at its best look like?

What are the weaknesses of it? And if it does have a weakness, how am I making putting boundaries, safeguards around it? I have my own ethical s- AI statement that I use for the foreseeable future to help me determine how I want to continue to interact with AI because as I continue to delve in it, I always wanna come back to the statement of this is my grounding statement.

This is the line that I wanna draw for myself to not move any further than this, but still to be able to explore and learn about this topic

Keith Edwards: Chris and Nick, what does that bring up for you?

Nick Fahnders: I think Chris is gonna have way cooler things to say, and Angela, in a quick response I really s- I cosign everything you said.

It’s really the biggest aha moment or light bulb moment that came from my AI class that I taught in the spring was that AI… I did an exercise for 30 minutes with the class about dissertation work, and AI said in three different iterations, and when I say iteration, platforms like Copilots, ChatGPT Gemini, all of them universally said, “We are not creating new content, so we cannot be co-authors on your dissertation.”

This is… You, you- you’re cheating if you’re using us for that. So AI said that universally, and we talked about that. And people stepped back and said, “But I just wanna think about how to think,” and AI is a tech- is a tool to think, and that’s… I think that’s true.

So yeah, to your point, Angela, I think it comes back to how you use a technolo- how you use a resource while doing your own thinking, and it still comes back to you doing your own thinking.

Keith Edwards: Yeah. It’s very different- Of course. Yeah … to say here’s the assignment I’ve been given.

Write my response.” Yeah. And it’s very different to say, “Here’s the assignment. Here’s an outline of the response. What am I not thinking about? What have I not considered? Are any of my positions less defensible than others?” And getting some feedback and thinking through. That’s a really different kind of way of engaging.

Again, it goes back to if is your goal to take the elevator or to g- to get exercise, right? To get to the top, use the elevator. If you wanna think, then maybe it’s something a little bit different.

Nick Fahnders: Yeah. If anyone’s watched the movie Just Go With It with Jennifer Aniston and Adam Sandler there’s a Cary Grant reference that he always took the stairs.

And that’s what kept him in shape, and yeah, like, how are you taking the stairs? Or when do you need to take the elevator?

Keith Edwards: Yeah. Separate from the elevator metaphor, Chris, what is this evoking for you?

Chris Wells: Yeah. No, I… as long as we’re talking movies I… One, one that I think of often and here I’m gonna betray my very solid Gen X generational status is Good Will Hunting.

Angela Lowe: Oh.

Chris Wells: There’s a scene in that movie… glad you approve. There’s a scene in that movie where Will, the, the genius who has a photographic memory and can… There, there’s a great bar room scene where he is taunting a Harvard graduate student that his education is one that he really could have gotten for a few bucks in late fees From the library, right?

Yeah. But there’s another scene where he is trying to do some homework for Minnie Driver’s character. And she says, I wanna be a doctor. It’s important that I learn this.” And I think that, like taking the stairs, is really important, right? That there are reasons why when you are working on a dissertation, for example that it is important that the dissertation reflect the new knowledge that you yourself are generating knowledge that you are sharing with other people because that’s what a dissertation is, right?

Yeah. And there are other kinds of writing that aren’t that exactly.

There are certain k- the big debates in the world of fiction that I find fascinating because f- fiction is about creating art. We’re gonna police the tools that artists can use to make art? That- Yeah

that’s an interesting stance to take. I understand exactly why people are taking it, because there’s something about the contract with the reader and expectations when you pick up a book and who, what does it mean to have an author’s name on the cover? But if you scratch the surface even just a little bit, you run into questions like what about ghostwriters?

Nancy Drew is a series written by a bunch of different people, but they’re all Nancy Drew books, and is that subverting the reader contract? And I just, authorship is one of those things that once you really start picking at it, falls apart. There, there are a lot of, I, I call them convenient fictions.

Bound up in the idea of putting your name on a piece of writing and publishing it, because, I mean- What about the editor, the copy editor, who’s actually going in and changing your words? What about the developmental editor who helps you think through some of the big arguments for your book?

What about the endless ideas you get from conference presentations and talking things out, hashing it out over a beer with your friends, right? Acknowledgement sections are not citations, and they only… they all say “I’m sure I’m forgetting people. I’m so sorry.” It takes a village to write a book.

I am just the person who wrote it. Authorship is complicated and messy and human, especially for lengthy things. And if I had to guess, I would guess that AI is convenient enough and in powerful powerful interests are invested enough that it is likely that the ways we think about authorship now with regards to AI are going to change.

That said, we’re not there yet by a long shot. And I do think that when you’re talking about creating new knowledge and… l- look at the tempest in a teapot over the math proofs OpenAI proving the, I forget the name of the theorem. There goes my home Google listening and- Stop.

Keith Edwards: That’s so perfect.

Google Assistant: Situation where people are obsessed about something trivial. There is no recognized mathematical proof-

Chris Wells: Stop.

Doesn’t wanna shut up. Sorry about that. It’s like the, the helpful AI chatbot that Zoom put in our faces asking us to record-

Keith Edwards: Yeah …

Chris Wells: and take notes when we started up the podcast.

Keith Edwards: It ma- it makes me think too it’s not just all about writing. I remember seeing Mark Cuban talk about when he works with companies, he has them…

He takes their benefit contracts, which are 150 pages, puts them in AI and says, “How’s this company getting screwed?” He used a different term. But that’s a really good use because if I start on page one, I’m not trying to go back to the elevator. I’m not trying to be an expert on benefit contracts.

And if I start on page one, by the page 147, I don’t remember what’s on page one. And so every November we’ve gotta choose between the three different insurance options, and I’m thinking, “Oh, this will be really helpful,” here are these different agreements which are mind-numbing and I can’t track on the details what would be best.

These are our priorities, right? So there are things that particularly where our human capacity to retain the details, to have the memory to track on things gets lost in lengthy long form information. Most of us probably just got our iPhones or our Macs updated with a contract agreement. Did you read the whole thing?

Absolutely not. But you said you did, and maybe you said you did twice. But that’s a great example of where, and perhaps on purpose, people are making these things so lengthy and so jargony and so misunderstandable that maybe we can start to cook some of those things down. Nick, what are you thinking?

Nick Fahnders: First of all, I could not agree with you more, and yeah, I scroll down as fast as I can ’cause what is time? So I just want my phone to work. And I say, “Sure, I, I, yes, I’ve, I consent to everything.” Should I do more reading? Yes, and to that tune in a master’s class I taught in the spring on student development theory, I did an inbox assignment where they were given…

The class was put into groups of four or five students and were given a real anonymized but real prompt around a functional area. So res life, like my roommate is the worst. Fundraising slash donor, I’m not gonna give money anymore if you don’t, … do this thing for me.

So i- in all those different groups, they had to respond as a group with a professional response, and then I prompted them to use AI for an AI response, and then I had them analyze the differences between what they did as a group and what AI did, and then present… They presented on that in class. And the consensus across all five projects was AI cannot think.

Like- … we have realized that we did the work, and AI is a resource, but we don’t wanna lean on AI because AI is not gonna help you solve that mystery. So yeah, like a, a really cup-filling, a, a little bit optimistic i- in, in this conversation, but we love we love some hope right now in, in this time and place.

Weird to, to have them all come to the same conclusion that AI wasn’t effective for critical thinking, and that same cohort I’m teaching this fall in a class, and I can tell that they’re thinking critically because they know AI is a resource, but they know that they are their best resource. So it’s really cool to see.

That’s great … that they know that it’s there, and they shouldn’t ignore it because they’re gonna get jobs where people tell them to use AI to, figure out a, a, a formula for something or do some, a- analysis that they don’t have time to do, and they’re doing their own thinking.

Keith Edwards: Yeah.

Angela, I’m gonna put you on the spot. I wanna move this to our last question because of time, but I’m gonna put you on the spot. What are, in your opinion, some really good uses of AI for student affairs pros? And maybe what are some not so great uses?

Angela Lowe: Sure. So I mean we’ve established in this conversation that i- if you just need to, the, the mundane, the common, being able to use it so that you are maybe getting some time back for tasks that are not really, they’re not helping you grow, learn, think critically or creatively, then that is I think a great way to use it.

Examples that I have used is if you are in a professional development center, if you are writing a resume, you have the job description, have AI compare your resume to the job description, and have it give you recommendations for how you can improve it such that it matches the description, rather than just having the AI write the resume for you.

You and so many other people are put as submitting AI resumes if that is the way you are gonna go about it. In the I recently did one f- presentation for student conduct administrators and the common student conduct thing to do is write a reflective paper. But now the question is, AI can write the student’s reflective paper.

How can I possibly get them to do something a bit more creative but still reflective? And I put in prompts to the AIs and was like, “Hey, I had a student violate a drinking policy. What are some creative sanctions that I can assign?” And just having it as a brainstorm partner is a really… i’ve I worked in student conduct for a little bit, and so looking at those examples I was like, “Yeah, I would use these.”

And some of them I’ve thought of, some of them I haven’t. As we’re g- having, a- as you all were talking an article came up to mind from the Chronicle of Higher Education, and it actually noted hey the arts, the visual arts, the performing arts, they’re actually doing okay in the age of AI.

And so the question is like wait, like the starving artist, why are they doing okay? Why are they still having the same h- like hiring numbers? And the theory is that because as artists you are trained to just think and generate ideas upon ideas, and so you’re constantly thinking about the next thing, and you’re also trying to stand out from your peer.

If you are using it just to be the common and the same as your peer, then by all means. But we are seeing in the hiring numbers and the s- student struggling post-grad, I know there are other factors right now in this economy, but if they are the same as their next peer, then of course they’re being cycled out of those, those job hiring processes.

So my, my most hopeful example that I’ll leave the listeners with is one that I always come back to of why have I not written off AI as this terrible bad i- in this world? And I think of D- Danielle Boyer, who is Anishinaabe roboticist. Danielle has created what is called the Sko Bot using a local AI, and it is an effort to revitalize languages of indigenous cultures and peoples that otherwise might be being lost at this point in time.

So Danielle has used, like I said, local AI, real human voices, so you have a robot that you can converse with and start building a fluency for a language that you may not have many conversation partners with otherwise. And that is why I have not completely written AI off of if Danielle Boyer is doing this amazing creative work, what can my next student do with AI that I have not dreamed of doing?

Keith Edwards: Yeah. Nick, you want to chime in there? And then we’ll move to our last question.

Nick Fahnders: I do. I do. Angela, I think what a gorgeous framing you just literally just said about conversation partners, and my brain goes to what privileged seats we sit in if you’re faculty or a supervisor, like when you don’t have people to help you do your work, AI can be a resource.

So I’m cur- I’m getting to know you both, Angela and Chris. Like i- in your seats, have you felt like AI has made you less lonely in the work that you do? And if so, how? Or do you have good people that are good conversation partners, Angela? Again, to you that, that term was gorgeous, so gonna give you credit when I say it, like tomorrow in class.

Angela Lowe: Thank you.

Nick Fahnders: But yeah, no, like I’m really curious what your thoughts are.

Angela Lowe: I don’t think AI has improved or hurt my social awareness social abilities. Yeah. I, I think that is the way I use it and that I am simply using it as a resource and a technology, not as a replacement. But I do think students are and that is a positive and a negative.

I think of some institutions that are using AI chatbots to help students who have stigmas about asking for help. And that is more students that we, than we think, and it is reaching students who have unfortunately been burned by in institutions or professionals. I wish I could say better in that regards, but that is the reality.

And so knowing that they can talk to a technology and still get their answers and still hopefully get the resources that they need to be successful in college, I call that a win.

Keith Edwards: Yeah.

Angela Lowe: However, we are seeing some really concerning things in regards to, yeah, some people do use it as a replacement to community.

And that is not just students, that is in a variety of nations in a variety of different s- human situations. But building relationships and then having breakdowns when eventually they reach the end of how much that AI can synthesize information because if you talk to it every day for hours on end, you’re going to reach the limit of how much data it can store, and it will shut itself down.

And that is like the I think it’s a little too early to see, but they are reacting to it like the friend died. And that is really concerning. So pros and cons, as we’ve talked about everything else Chris or Keith I’m curious to hear what your thoughts are.

Chris Wells: Yeah I’ll jump in for a minute.

The, I don’t know if folks have seen it, but if you haven’t I recommend it. It… this is maybe the only bureaucratic report I have ever recommended that people go out and proactively find and read. But MIT released a 50-page report on AI in higher education that’s really focused on the MIT context.

And they talked about MIT as a residential education experience. And one of the things that they really keyed in on and this was coming out of their interviews with faculty, staff, students across the institution over a period of many months was that one of the unexpected or one of the more significant effects that AI was having was on social relationships, and i- in, in ways that actually affected the kind of education that people were receiving.

So some really simple examples to take a, a big idea and make it concrete study groups, right? There, there’s a long tradition at places like MIT for students who are taking really challenging courses that wrestle through problem sets week after week, of forming study groups and getting together and tackling those problems together.

And more and more, they found in their interviews that students are staying in their dorm rooms and tackling them with an AI.

And so even if they figure out a way to find, to take the elevator-

…

Chris Wells: In, in using the AI, and you absolutely can set up a chatbot so that it can help you learn things in a way that is productive instead of damaging.

You’re still missing out on something that has been really important in the kind of experience that MIT was creating for its students, right? Office hours are another example. Professors deciding to hire a chatbot instead of an undergraduate research assistant right? Th- Great, so you taught a chatbot how to do the research.

What are your undergrads learning? That the purpose of those undergraduate research programs is seldom to advance the professor’s research first and foremost. It’s to teach the next generation of researchers what it looks like to be part of a group of people who are tackling a hard problem together, led by someone with a lot of expertise and a group of people who are learning, right?

Who, but who are smart and talented and focused and wanna figure it out. So I think that captures for me something that’s really important which is that AI is not just changing assignments. And, elevators in a building affect more than just assignments. I guess they, they also affect other kinds of learning that we do, and I think that chatbot piece where students are so invested in a particular model that they feel like someone died when it gets retired, like that’s worth taking seriously.

Keith Edwards: Yeah. For

Chris Wells: sure. There, there might be some good things in having a non-human conversational partner, but there are definitely some problems- Yeah … if you take that too far.

Keith Edwards: Yeah.

I, unfortunately I’ve gotta move us along. We are running out of time. The podcast is called Student Affairs Now. We always like to end with this question about what are you thinking, troubling, or pondering now?

And I feel like we’ve given folks lots to think, trouble, or ponder now themselves. But what are you thinking, troubling, or pondering now? And if folks wanna connect with you, what’s the best way for them to do that? So Angelo, what are you pondering now?

Angela Lowe: I’ve, i- in, in addition to just gathering information about technology and AI and learning the good and the bad I find myself gravitating to poetry written about AI because poets are like, “No, it cannot replace us.”

And so I find that very just interesting. I have a background in art so that I think that’s just my artistic background, like crying out for something original and beautiful. But also just positive examples of technology in general, not necessarily AI related. I already gave the example of Danielle Boyer.

The other one that I recently have really found hopeful is learning that there is an uncensored library on Minecraft of all things, and it has been put together by Reporters Without Borders who are recognizing that there is literature that is actively being destroyed and censored and abolished by certain states and nations.

And so collecting that and putting it in a, to a, a fully accessible place and keeping this literature alive I found that incredibly hopeful in the day of such strong technological advances. Where people can find me my email is angela.noelle.lowe@gmail.com, and you can also find me on LinkedIn.

Those are the best ways to get in touch with me.

Keith Edwards: Awesome. Thank you. And Chris, what are you thinking about now, and where can folks connect with you?

Chris Wells: Oh, man. Too many thoughts running around. Th- I think one of the things I’m pondering most I, I was … I heard a panel where someone said, “AI is the greatest tool we’ve ever had for learning and also the greatest tool we’ve ever had for avoiding learning.”

And I guess I’m pondering the ways that both can seem true simultaneously and and require different sorts of responses and uses. There’s no straightforward way to think about AI, as much as I wish there were.

Keith Edwards: And if folks wanna connect with you when you’re no longer on sabbatical- Oh

what’s the best way for them to do that?

Chris Wells: Yeah. You can find me on LinkedIn. And I write on Substack at Teaching Upside Down.

Keith Edwards: Yep. And we’ll get a link to that Substack in the show notes. Nick, what are you troubling now?

Nick Fahnders: I think it’s less about troubling and more about care. I’ll keep it simple ’cause this has been a great conversation.

So my quick aside is I’m just so grateful for the folks that have been this, in this room and the conversation we’ve had. But for the listeners, if you’re ever feeling lonely, don’t use AI when you feel alone. You have your own point of view. You have something to say, and you’re, you’ve got community in, in the at least the four of us, if not more folks.

My last name is spelled the same way. I’m a pretty analog social media person. So if you can spell F-A-H-N-D-E-R-S on LinkedIn, Instagram, Facebook, wherever e- email me yeah, happy to chat. But you’re not alone. And use AI as a support, but don’t let it be your crutch. And that’s an ableist term, and I said that on purpose.

Keith Edwards: Awesome. What a great way to end. Thank you all so much. This has been terrific, and I really appreciate your good thinking, and you’re willing to dabble in the messiness today. This has been super, super helpful. I also want to thank our sponsor of today’s episode, Suitable. As a student affairs pro, you know the impactful learning that happens outside the classroom.

With Suitable, you can increase active participation, track and assess experiential learning, and even guide your students through personalized paths. And with Suitable student org management tool, you’ll unify organizations, events, and workflows where students expect it right on their smartphones. Visit suitable.co to book a demo for your campus.

As always, a huge shout-out to Natalie Ambrosey, who does all the behind-the-scenes work to make us look and sound good. We love your support for these conversations. Your listening, sharing, and recommending makes all of this possible. If you wanna help us even more, subscribe to the podcast, to the newsletter, and on YouTube.

Every week we share a newsletter where we share the week’s new episode. If you’re so inclined, you can also leave us a five-star review so conversations like this reach even more folks. I’m Keith Edwards. Thanks to our fabulous guests today and to everyone who’s watching and listening. Make it a great week.

Thank you.