From Fear to Fluency: Helping Faculty Navigate AI

Michael Cato: Hi everyone, and welcome to the Integrative CIO Podcast. My name is Michael Cato, and today I'm joined by special guest host, Sarah Buska, the executive director of the Applied AI Lab at the Waukesha County Technical College. And Sarah is joining us today, stepping in for Cynthia Golden, who's unavailable today. And Sarah, I'm so excited to have you here. Welcome.

Sarah Buszka: Thanks so much, Michael. I'm thrilled to be here.

Michael Cato: And I'll turn to you, Sarah.

Sarah Buszka: Perfect. So since I am taking over for Cynthia today, we are really excited to talk about today's topic, which is AI in teaching and learning in higher education, specifically how institutions are navigating innovation, governance, and the changing role of faculty and instructional teams. And we have two incredible guests joining us to help elucidate a little bit more about this topic. They're both dear friends of ours here on the show and excellent folks in their own right. First, we have Lance Eaton, our senior associate director of AI and teaching and learning from Northeastern University, and we have Dr. Jenna Liskins, who's the director of the Center for Instructional Design and Educational Technology from Ithaca College. Welcome Lance and Dr. Jenna.

Lance Eaton: Be here.

Jenna Linskens: Happy to be here. Love it.

Michael Cato: Well, we thought we'd start with a broader question, particularly because I think your two institutions are so very different, which could be really helpful to our audience. So starting broadly, how is your institution balancing the drive for AI innovation? And which makes me think of things like the career aspirations of our students as one example, with the needs and implications for things like learning design, academic integrity, rigorous governance, sorry, to name three as an example. And so maybe Lance, we'll start with you for this one.

Lance Eaton: Sure. So again, thank you for having me excited to be here. I am at an institution where, as has been said by many others, our president wrote the book on AI in education, robot-proof education, and I'm not trying to promote it, but that was published in 2017, 2018, and so was on his radar to be thinking about it. And so the institution has been thinking about prior to the arrival of generative AI and has tried to walk that balance across those different pieces. So there's been some amazing things that have been going on around thinking about where does this intersect with Northeastern's famous for its co-op? And so what are students learning? What are students doing? And so where I sit, which is in the Center for Advancing Teaching and Learning through research, there's been regular ways we're in conversations with the folks that are setting up and doing co-ops.

Lance Eaton: We've done panels with students on co-ops. What are you hearing? How is AI showing up in this work? And then that question of, so therefore, what and how should it show up in the classroom? So we've been doing that. We've also, in our center, the big work that we've been doing has been cohort programs. And so we are now about to launch our third year of cohorts. And the way the one main cohort program has been working with a representative or two from each of the colleges, and basically they in their college are helping to run events, facilitate conversations, dig into that question of what does AI mean in computer science versus in health sciences versus in social sciences and humanities? So they've been doing that the last two years and we've each year been building upon that. And this year it's changing in that we're scaling it and now those roles have been turned into directors and they are going to be running their own cohorts that will be doing this work throughout the different colleges.

Lance Eaton: So we kind of go from a model of about 20 to by proxy, probably somewhere between 100 and 200 people. Our faculty are going to be involved in ongoing conversations around curriculum transformation, which is how do we revise and update courses? And then on the other side, how are we using these tools in the teaching and learning space? And then in terms of governance, I will say we have really tried to structure at least three policies and guidelines that are pretty much one is around the research aspect and where AI shows up in research. Another one is around teaching and learning and recommendations for that. And then the third is around how it's showing up for staff. And then we also have a set of guidelines for students.

Michael Cato: It's all really helpful. It's interesting because what I hear in that is an explicit and intentional connection to the co-ops and the career components of this and creating an engine within the institution for those conversations to happen within and across divisions. Did I get that correctly?

Lance Eaton: Yeah. And there's also, I guess the other piece that also forgot was there's been a faculty-based group over the last year that took the Digital Education Council's AI literacy framework and remade it in a way that makes sense for how to approach curriculum design at Northeastern and made it into this two-tier framework that is one around AI literacy and another around AI fluency and

Michael Cato: That

Lance Eaton: Difference of understanding of the tool and then also how you're using it.

Michael Cato: Yeah, that's really helpful. So Jenna, at a very different type of institution, very different scale of institution, would you mind setting the foundation for our understanding of how things are playing out there?

Jenna Linskens: Sure. Thank you. So I will say we have an amazing, and I can't even call him the CIO anymore, he's now the senior vice president. Dave Weil is just been an amazing leader from the get-go, back in November of 2022, just was right on top of this and gave people permission to learn and understand. And that's really been the basis of everything over the past four years. So we are definitely three professional schools plus the school of, well, four professional schools with music, theater, dance, and then our humanities and sciences is one, but the other three professional schools of health sciences, human performance, business, and then communications have seen a very broad continuum of where faculty are in regards to the way that they're thinking about and using AI as part of their teaching and learning experience. And so we started a couple of years ago with what we were just piloting them.

Jenna Linskens: We were calling them the AI mini grants, and it really started building this very small group of faculty to give them the permission and the support in order to explore and understand that idea of building AI literacy and then thinking about AI fluency within their programs. So that started in a small scale, and then we were able to move it up into what we called our AI and digital literacy initiative where we really went like, "This is not just about artificial intelligence, this is about all digital literacy." So we had a variety of efforts that related to that, including an institute for faculty. It was held mostly asynchronously with a few connections where faculty could come together for scheduled events. We offered a book club around the book Teaching with AI by Doctors Watson and Bowen. And then we continue to offer the mini grant.

Jenna Linskens: And this year we've expanded to offering faculty an opportunity to think about that curriculum redesign. So the mini grant really gave faculty an opportunity to get their toes wet. So if we were to think about a tiered approach to building starting with that foundation and expanding where AI fits and how they're understanding it and how they're applying it, building that in that tiered approach with those ground level activities. One of the wonderful things we had was we actually had Lance come and visit us on campus. He spent a day with us and really helped to set some groundwork for many of our faculty and ask the tough questions. When it comes to the governance piece, we have what we call the presidential working group on AI. That group has evolved now into more of an advisory group, but that particular group really set across the board for the institution, what are the guidelines?

Jenna Linskens: So based on our values here at Ithaca College, what are the guidelines that need to be put in place for all faculty, staff, and students in regards to AI? From that, while it didn't specifically address teaching and learning, from that it became more conversations with faculty. And I want to stress just two things. One, faculty choice. So giving faculty the opportunity, whether they're teaching in the social sciences or they're teaching in the digital media design, wherever they are, it doesn't matter, it's their choice. They are the experts in their fields of study. So as long as we can build a baseline of literacy, then we can take care of moving the next step. The other piece is that it's not just about that faculty choice, it's about the faculty communicating with the students about class expectations. So in that realm, we have worked with our faculty and our partners over at the Center for Faculty Excellence to establish syllabi statements that faculty can put in regarding student use of AI.

Jenna Linskens: We've also had this year added in a component where now faculty are adding in to that same syllabi statement. They're explaining how they're going to use AI. So they're committing themselves to saying, "I'm not using AI for grading," or, "I'm going to use AI in this capacity." So setting some of those guidelines, and that's been a big conversation just in this first week of courses. I know this is airing later, but in the first month or so of classes, I anticipate more conversations

Michael Cato: Around that. I really appreciate that, Jenna. I hear so many parallels here, just appreciating, but working within the different context of your institution. And you touched on something that I was curious to ask and follow up about your teaching center. So it sounds like your teaching center is outside of IT, but you are partnering and you gave just the example already of the syllabi statement. Am I getting that correctly, that there's a strong partnership there?

Jenna Linskens: There is a very strong partnership. So the Center for Instructional Design and Education Technology does sit within IT. We report up to the CIO, and then the same type of but non-tech, I guess, although they do tech, but the other group is that Center for Faculty Excellence where their focus is more on the pedagogy, the grant writing, scholarship, service, and they report up to the provost. And that partnership has been going on since pre - COVID. So I will say COVID strengthened it by tenfold and the work we did together to support our faculty. But that's been this ongoing partnership where we do programming together, these book clubs, we actually co-facilitate the book clubs. Our book clubs are not facilitated just by an instructional designer or just by somebody from their team or just a faculty member. It is this partnership where we work together and talk about.

Jenna Linskens: We really try to follow informally, we won't say it formally, but we follow the TPAC model. So you bring in your experts to have the conversation together, and that's been an amazing partnership.

Michael Cato: Really, really helpful. And to your point, it does seem to me that we're in an era that the generative AI conversations can either strengthen those partnerships or weaken them or reveal the weaknesses that were already there and amplify them, right? Yes. Lance, I see you nodding, but for our audience, could you share a little bit about what does a teaching center look like at Northeastern?

Lance Eaton: Yeah, so I have the privilege to be on a team, which is one of the first times in a lot of this work or in a while I've been able to be on a team. And so we have, let's see, the math always messes with my mind because I always have to remember myself. So we have seven faculty developers and is one administrative assistant who does so much more than that, I want to be clear. And our focus is on teaching and the name of the center is the Center for Advancing Teaching and Learning through Research. And that's one of the big emphases of how the center was created is really trying to do this with a lens, not just towards what the research is, but also supporting faculty in doing research, particularly scholarship of teaching and learning. And it's a really interesting team because most of us have some areas of specialization, so it's more of an orchestra that people lean into different ones.

Lance Eaton: And when I came on, mine was AI, but obviously I bring background in open pedagogy and OER and lots of those things. So we have grappled with some identity pieces of we're doing our best and we think we're doing our faculty well when we are not just the center for teaching and learning and AI. And it's not because we want to dismiss, undermine whatever around AI, but it's like all of this is about teaching and learning, and we always want to make sure that's front and center and that we have faculty, to Jenna's point, who are along that full spectrum and want to be able to still think about teaching and learning that isn't just AI. And so one way we're working with that and thinking about that is for the first two years, there's a lot of direct AI workshops, and now it's a lot of workshops and programming where we're doing a lot of the pedagogical things that we think are important, and there may be a space carved out for AI in it, just like we often had to do with the LMS and other types of things.

Lance Eaton: And here's sometimes a technical or a piece that you want to keep in mind if you're interested in this part of whatever the topic is.

Michael Cato: Really helpful. And it's interesting, I caught some of the themes I'm hearing from both of you is the idea of the partnerships, the collaboration. Lance, I love orchestration. I'm going to lean on that one heavily in my future conversations, but also that focus on teaching and learning, that is a conversation on AI or in service of teaching and learning as opposed to the other way around. And Jenna, the structure that you all have at Ithaca is with two teams, one that can focus on the technology piece and the other piece, the other team that can be much more clearly focused exclusively on the teaching and learning, but doing it together with that orchestration to make that happen. Jen, that sounds really great. Sarah, I'll turn to you.

Sarah Buszka: Yeah, thank you. So something I actually want to double click on is I've heard both of you mention faculty so much in your opening answers, and I think that can be a point potentially of contention for some of our listeners and their various organizations in figuring out how do I navigate working with faculty along this AI journey? And I'm looking at you, Dr. Jenner, because I know we've had conversations about this several times over the years, and Lance, I've seen you nodding this whole time. So I think for folks who are listening who are on this journey and are working with faculty who are falling on the full range of the spectrum of whether they're embracing this technology or the opposite or curious or concerned, we've already heard some wonderful examples, but I'm wondering if you can speak maybe a little bit more clearly in two minutes or less, both of you, how specifically you're supporting faculty who might be resistant to these new technologies or feel overwhelmed by the pace of change.

Sarah Buszka: And Lance, I'll ask you to go first.

Lance Eaton: Dang. I know. So I always go back to, I've been doing faculty development, but also instructional design for 15 years. Somewhere early on, the thing that I realized this work is about, and this is how I always frame it, is whenever I'm working with a faculty member, my goal is to either literally, but more often than Zoom, metaphorically sit next to the person, not across from them. And conceptually, there's lots of different ways that goes, but at the end of the day, what I try to do in my work with faculty is to always think about what's the relationship I want them.

Lance Eaton: As somebody who's steeped in teaching and learning and rich ways of relationship building, I have to demonstrate the things that I want for them to do with their students. And so a lot of that is being patient, is listening and trying to really soak in what their concerns, what are the things underneath the things that they're talking about. And then also our team, gosh, a year and a half ago, one of the greatest things we did was we had a trainer come in around motivational interviewing, and that's been a really powerful set of tools to really be able to just talk and listen and give space for them to talk about what change could look like. And again, not having the agenda of I'm coming in here and I want to shove AI down your throat. No, I want to understand what are the pain points, but what are the care points that have you here meeting with me to figure out what happens next?

Lance Eaton: And that was more than two minutes, I'm sorry. Jenna.

Sarah Buszka: You were close. So close. Dr. Jenna.

Jenna Linskens: Sure. Thanks. So Lance touched on a couple of things and immediately came to mind was when we're in those conversations, I go back to some of my earlier training where I went through workshops, I was trained through gym night for instructional coaching type of things. So building that relationship, and I actually have a quote and it doesn't really, I don't even know if it has a real author, but you don't change culture through emails and memos. You change it through relationships one conversation at a time. And I think it's steel thoughts that has that, but that's something that I've always kept in mind. So it's thinking about that, it's having that conversation, it's talking to the faculty member one-on-one about what are their goals, what are their objectives, what are even the learning objectives of the class? And sometimes when we have that conversation, and we oftentimes get this big sign on our head that says ed tech, and then for some reason, I don't know, positive or negative, people see me and they're like, "AI?" And I'm like, "No, I'm not." But it's that idea to give them that space to have those conversations.

Jenna Linskens: And I will say one of the things that I'm most proud of that we are really trying to focus on is that when we have those book conversations, and yes, the title is Teaching with AI, we actually spend a lot of time talking about, and I'm going to go with the phrase that I heard this week, analog teaching. So University of Chicago recently put out that in social sciences, no AI, no AI by students, no AI by faculty. Now, I caution against using the brand to say no or never. That is an absolute. In our lives, that's not even possible. We have to be very specific, I think, about the type of AI that we're using. But I will say when we're having those conversations with faculty that, as you said, may resist change or push back or just are like, "Nope, this is how I want my class," we give them that space, we talk about what are their goals, what are their objectives, and we build that relationship with them, and we may or may not say, "Okay, tech, no tech, high tech, low tech, whatever." What we are going to say is, "Let us help you navigate that and get to that goal and meet your goal, meet your objectives, and let's both be open." I think openness is really important as part of that communication.

Sarah Buszka: Absolutely. Yeah, I'm hearing openness, that communication, listening to folks. Lance, I really liked how you framed it, sitting next to someone and then the care points instead of pain points. I'm hearing you say that also, Dr. Jenna. I also feel like those are your superpowers. I know both of you personally, and I really think you see that show up in your work, and I think you both genuinely do care as well to actually listen to what folks are saying, regardless if it's something that you want to hear or not. I think that is really what I think gives both of you that edge at both of your respective institutions as well.

Lance Eaton: I'd love to just. I appreciate that, and I'd love to - This is a love

Sarah Buszka: Letter to you in this

Lance Eaton: Episode, just so you know. It's incredibly sweet. But I think to me, it goes back to

Lance Eaton: It's really hard, but that's the work. And again, it's in some ways that mirror work of. I've worked with lots of different instructional designers and faculty developers, and it can be as easy to dunk on faculty as it is for faculty to dunk on students. And I know for myself, I try to pay deep attention to that because it's always a sign of, okay, I'm stressed out, or I'm not paying attention to the relationship. Because again, I think for me, it continues to be like I can't be one way if I'm in this dynamic of supporting teaching and learning and then expect them to be another, that there's important connections there. And it doesn't mean it's always exact and perfect, but that always has to be in the space.

Jenna Linskens: Sarah, if I may, one of the things that came to mind as Lance was talking was, and I mentioned this earlier, the continuum. There's not just a continuum of how people are integrating or using AI. It's not just about the continuum of AI literacy, it's the continuum of digital literacy. It's the continuum of technical literacy. Most people in IT, and I'm saying most, have a very deep understanding of tech in some capacity. Now, I am teaching and learning, so if you ask me to go do networking and play with switches and wires, I'm probably going to break something because I wasn't trained on switches and wires.

Jenna Linskens: But the idea that when we are working with faculty to keep in mind that their tech savviness, their level, their continuum, most likely is far below what that person who's meeting with them, most cases, they're coming to us because they don't know the tech. They don't know. They're standing in a classroom, they're trying to use the interactive board or they're trying to plug in their laptop and it's not working. We need to give them grace and be patient with them because that's not their expertise. Their expertise is physics or digital media production or their technology experience is using a high-end video camera for sports productions that I've never even looked at. I'm like, I'm scared to even touch it because it's just this massive object. We need to have that. That's part of that relationship building. So I'm not an expert in their field, they're not an expert in my field, but we can work together.

Jenna Linskens: And that's why I believe so much in the TPAC model, really, that technology pedagogy content model.

Sarah Buszka: Absolutely. Yeah, you're really touching on the human connectedness aspect of it too, which is ironic because we're talking about AI and teaching and learning, and here we are talking about the people and how we respect each other.

Michael Cato: Yeah. And Sarah, I think that's a really great way to frame it. It makes me curious that you both have such much longer backgrounds of doing this work with faculty that predates generative AI to the points you made at the introduction. If I asked you to describe for our audience if and how the conversations about generative AI are shifting your conversations with faculty, what would you say? And it may not be shifting, so I don't want to presume that it is, even with my own experiences. I just want to ask first, is it shifting the types or qualities of the conversations that you're having with your faculty and/or perhaps your instructional design teams? Jenna, I'll start with you this time.

Jenna Linskens: Yeah, thanks, Michael. Honestly, okay, my gut says no, it's not. We had similar types of conversations in 2010 when the iPad was released. We all of a sudden had this tablet device that could sit in front of everybody's face while they're in the classroom. We were talking about that and how to address that. Back in 2005, I'm trying to remember, about 2005 - ish, when the interactive whiteboard came out and shortly thereafter, smart notebook and smart boards came out. And so there's a change in the tech, but at the root, teaching is teaching. These are tools. These are tools in a toolbox. So to me, the conversation isn't completely shifting. It's helping them to think about, and this is one of the ways I like to describe it, is if I'm in a wood shop and I need to build a birdhouse, I know I'm going to use a hammer and nails to build my birdhouse.

Jenna Linskens: It's a small item. I don't need any fancy high-tech solution. If I go to a home site where I am now building a house that a family is going to live in, I need to know how to use a nail gun. I need to know how to use the electric tools because it's going to be more efficient. So I need to know when to use the right tool.

Jenna Linskens: That is, I think, still the root of the conversation. But to me, in my gut, conversations aren't shifting. It's a shift in the tool. So that's my gut feeling.

Michael Cato: Yeah. I really appreciate that, Jenna. Thank you. Lance, what about you? How would you answer that question?

Lance Eaton: I think I have some of those similar experiences. I think that the two things I can add is I think one, we're having people show up either to our events or for consultations that we haven't previously been in touch with. They're realizing what's happening is no longer working or they're getting frustrated and they're like, "What do I do?" So I think there's that, that's happening. I think the other thing that we're seeing, and we've already brought it up here, is there is, now this was here before generative AI, but there is a bigger turn towards relationship and trust in those conversations I see happening more. So I think maybe it's frequency that's shifting and there's a deeper consideration of if I want to build trust with students and build thoughtful relationships with students, it might require different tools and it might require a different trajectory.

Lance Eaton: And I think what I see is some faculty are grappling with all of that requires a tremendous amount of work of redeveloping courses, assessments and whatnot, but it also requires a lot of mental, emotional shift in labor and work. And so it's this question of, I know I need to make those changes, but I can really only operate at small changes per semester. So how do I get there? So I think that's some of what I'm seeing is faculty really trying to grapple with that in real time in a way that I don't think I saw it as much or here's what it is. It was easier to come up with more policing strategies when it was the iPad or Wikipedia. There was just easier solutions to I can just ban it or I can just easily do it and there's no easy option here.

Lance Eaton: And so that requires, I think, and I'm really appreciating it and appreciating the struggle of like, oh, this does ask us to approach teaching and learning differently.

Michael Cato: That's really helpful from both of you. Lance, I'm also very curious then if and how conversations about AI detection are showing up for you in your institution. And Jenna, I saw that reaction, so I'll come to you as well, particularly because you made that point about trust. I just had this conversation with a group of faculty recently, so I'm just curious how you think about that.

Lance Eaton: I mean, in some ways it's easy because Northeastern, its policy bans it. So you can't use an AI detection tool or whatever the ones are out, you can't do that in any formal way without violating student privacy because there's no internal tool and the current role is to not do that. It does come up in conversation and from the very early days up through all of the stuff that's been going on with Pangram on Substack and Claude having watermarks, it continues to be a conversation about is that really telling you the information that you really want to know? And if it's not, how many innocent students are you willing to get caught up in the drag net and do various types of harm in terms of them understanding themselves? Because we are already seeing, or at least a variety of panels, Northeastern and elsewhere, we've heard from students talking about that's its own new anxiety of being accused of using AI and having to prove that you didn't is such an incredibly hard thing to do because even our legal system, it's proven not guilty, not necessarily proven innocent.

Lance Eaton: And proving innocence around tools that are very fuzzy and very fuzzy in how we understand what they actually say. So all that is to say we try to really bring up those issues, those concerns and just recognize maybe in some ways it would be it's easier if it was perfect, but it's imperfect. And when we have students coming to us to learn, a really horrible thing you can do is to say you cheated when a student hasn't. It can really disrupt our education.

Michael Cato: I really appreciate all of that plans. Jenna, what would you add?

Jenna Linskens: Oh my gosh. The problem's not the tool. It's not the tool. There are tools that have come along many times. Would we say that a student who used online database to do research is cheating when the online databases replaced physical card catalogs? It's not the tool. It's about setting those clear expectations of how and when it should be used. So we really need to look at the pedagogical, the androgogical, the design of the way we're teaching. And so using those systems, and I will be the first one to say those systems are not perfect and they are not going to be able to keep up with the speed that generative AI is advancing. So you've got this back and forth on a seesaw that we're like, okay, we've got it, we've caught up. Nope, we're not. And so it's about the way, it's about setting those expectations, having those conversations in the classroom with the students, when and how should these tools be used and being very clear about that.

Jenna Linskens: And then rethinking academic integrity. The idea that, and again, I'm going to go back to, we have to be very specific about the type of AI because if I use AI for spell check or I use AI for grammar corrections, is that cheating? Is that academic integrity? So being very, very clear about this. And again, I'm going to go back to this idea that it's about the human side and the human working or using the technology tool. So when you brought up the question there, Michael, I cringed. I just cringed about and no AI detection tools here at the college. We don't have them. We don't even have plagiarism detection tools of any kind. If people use them free, we are reminding them, hello, red flag, you need to be careful. So yeah.

Lance Eaton: And I'll just add on that. I think that I myself, earlier in my teaching career, a poor quality version of Lance existed where he went down those rabbit holes and that push, that is a downward spiral. And I say that as there's always the more you want to try to control for everything, especially in this day and age, I can remember how quickly people were talking about AI plaster detectors and then seeing on reels or on TikTok a bunch of videos like, "Here's how you get by them." And the mouse is always, I was going to use the metaphor of the mouse is always going to get around the mousetrap, but I don't like that metaphor, but that's the thinking that's happening often around. It would be amazing. I think it would be really powerful if we could have a tool, students could have a tool of assessment around helping them understand how much is really their own and how much isn't, but I don't think we have a good way of divorcing that and an ability to do that from policing.

Lance Eaton: And that's the piece that gets really challenging in this space if we're trying to think about learning and trust.

Michael Cato: Really appreciate that. And I appreciated the framing that this is about that combination of learning and trust. And I just want to tell you both thank you for your equally passionate responses to that question because I have the very same feelings. We

Lance Eaton: All do. We have all the feels.

Michael Cato: Sarah, I'll turn to you.

Sarah Buszka: Yeah, absolutely. So we've been talking a little bit about students now, so I want to go down the path to think about the student perspective, of course, in higher education around AI. And particularly for me, and I'm hearing from many of you, and I keep looking at Dr. Jenna, because we've also had these conversations, thinking about equity with access to these tools, to Dr. Jenna's point about building a birdhouse, even having access to a hammer and a nail or a nail gun or things like that, which by the way, I would definitely need a nail gun to build a birdhouse. But access to these tools I think is a really important part of this conversation. And I'm really curious to hear from you, Dr. Jenna, to start, how are you addressing this digital divide that exists where some students can afford these premium AI tools, assistance, services, et cetera, and then others cannot?

Sarah Buszka: How are you folks handling that at Ithaca College?

Jenna Linskens: Yeah, that's a great question and one that we grapple with a lot. We certainly have, when it comes to what we offer, we are a Microsoft institution, so we do have the Copilot chat available for all of our students, faculty and staff. So that is oftentimes where we direct them to. We say, if you're going to use a generative AI, go to Copilot Chat, you can log in with your credentials. We've looked at various options. We've looked at some of those providers like a Boodlebox or a Nebula One where it gives you your dashboard and you just type in it. It goes to the model that works. We've looked at them. We haven't been able to commit to anything though. The one thing that I will say is that one of the things I think that we're doing well with is the way that we're managing Adobe Firefly and the AI tools with that.

Jenna Linskens: It's a deployment to those that need it. So we're not just doing this mass deployment of something. It's about understanding what those tools are that they need. So working with the faculty to say, "What things do you have in your toolbox now? What will work? What else do you need?" A lot of our faculty really are just asking students to use. They're designing their activities around using the free use of tools. So if they don't have things to access Claude or Plexity or Gemini, any of those, that they design the activities, they test them and try to go with the light or the free versions, which comes with a lot of concerns because now you're getting into the privacy concerns. But I think privacy also applies across the board. You need to understand how to protect yourself and your data and your information. So obviously we have some rules, guidelines, I wouldn't say rules, guidelines that are posted and that we share out with faculty and students, but it's that idea of what do they need for their classes and how can the institution provide what they need and navigating it that way.

Jenna Linskens: Now the other side of me, the accessibility side says we also have to be very careful about, and this comes down to that going analog, that we have to be very careful that we don't say in the classroom, no tech, because now we are actually taking the accessibility features that some students may need. So I'm more on the UDL side. The idea is that when we're designing, we are designing for everybody. It's universal design for learning. The activities in the classroom are that way. So that's more of my philosophy is trying to find that balance.

Sarah Buszka: Yeah, and that's a hard balance to find too, right? I mean, you want to be able to offer as many tools as you can that make sense, that are reasonable, and then to your point, not just offer this wide range of tools and let it just be so open that folks don't understand what the guidelines or guardrails are and they're just not set up for success.

Jenna Linskens: Exactly.

Sarah Buszka: So Lance, I'm curious, how would you answer that question? How are you folks talking about this digital divide when it comes to students and their access to these tools or not?

Lance Eaton: Yeah, and I have to preface this with I worked at an institution that does have a reasonable amount of resources and in March of 2025 made Claude available to all faculty, staff and students. And that is something not every institution is in a place to do. Even before that, though for me, I was making outside of that work, making the argument that that is probably where we all need to go. Now, doesn't mean we can be there today, but there were times on all of our campuses when having internet connection pretty much anywhere on campus, regardless of how good or bad it is, that's a different conversation, but internet access everywhere on campus. There was a time when there was like, "Oh gosh, how are we going to do that? That's going to be super expensive." There was a time when we said, "Oh no, we can't give an office suite of tools of document programs and presentation tools.

Lance Eaton: We can't have all of our students, faculty. We can't have that except that we now have both of those." And that means it does require planning, it does require structuring, and it does require articulating that and doing the longer strategic work, which is needed to recognize that becomes really important. And I think it's important obviously for the equity piece that there is a way that Northeastern has addressed the equity pieces that if you're at Northeastern, you get access to a frontier model and we're empowering and encouraging both faculty and students to find meaningful ways of using it. But I think it's also just, again, it becomes part of those suite of tools that we come to expect people to be comfortable and capable and have some background and knowledge and to be coming into their jobs with, I would say not just. I'm going to crystal ball here.

Lance Eaton: I'm going to imagine within three to five years, if not already, there's going to be some places of employment that are anticipating you are coming in with whether it's your custom GPTs or your agents, that you have a suite of those that you have been building or fine-tuning or whatever that are just ready to there to support you in the work that you're doing. And I think that's something likely to happen in lots of different spaces of employment and industry. And so where are we in helping them set that up? And I think that's an equally important question around not just the equity, but the preparedness of it.

Sarah Buszka: Absolutely. I'm nodding vigorously because I'm looking at this from the technical college lens since I'm in a technical college in Wisconsin and I can say with certainty, we are already having business and industry saying that to us. Their request and their expectation is that students enter the workforce with that suite of tools, with that knowledge and capability to readily deploy AI as part of their work. So we are very much there, and I almost want to tee this up potentially for a potential part two of this conversation since I think all four of us here have so much that we can contribute and add, because I think this is a really interesting topic and there's certainly more to cover, but I want to tee things over to Michael here for our next

Michael Cato: Question.

Michael Cato: I appreciate that, Sarah. And it's interesting because we wanted to talk a little bit about privacy and intellectual property. And Lance, your last couple statements made me curious for two vantage points as starting points to this. One is at institutions that I've had conversations with that have done broad licenses as Northeastern and a handful of others have, one of the points of feedback they've offered is that student adoption dramatically lags everyone else and that when they try to dig into it, it's because students will express their concerns about privacy, but what they mean is privacy from the institution and they would prefer to use a personal or free one because then their perception is my data's protected, I guess between me and the company at this point, especially if it's free, it's the company's. But it also makes me curious because you talk about coming into a job having built some kind of AI, not just competency, but I was hearing that as tool sets as well, which I think would also beg the question about who owns that tool set if I bring it into the company setting, I use it with the company data and then I leave later on.

Michael Cato: But let's take that one for part two, if I share Sarah's vision for a part two conversation. Part one is how are you having those conversations about privacy, intellectual property, and are you seeing that experience as well as far as student adoption and their concerns about privacy?

Lance Eaton: We definitely hear student discussions of uncertain about institutional tools, and I've heard that elsewhere as well. I think it's a both and. I think it's that. I think it's also switch over costs that we're ending year four of generative AI being around. And if you're a student who is an active and prolific user, the switch over costs to bring over your custom GPTs, all of these things, I've yet to see, I know there's possibilities, but I've yet to see a really good plug and play that interoperability isn't there. So I think that's the other piece, is the people most likely to take advantage of an institution's tools because they've already been using them robustly. Also, we haven't, by we, I just mean the world at large, hasn't provided that good switch over.

Lance Eaton: The privacy concern I do also think is real, and I think it's because it's so fresh because again, the dynamic of if we will look under the hood, and I've seen this at many institutions of students will also use all of their other tools in the service of private needs and wants. And so I think this is also it's in front of us now, and that's a thing that slowly goes away or becomes less concerning. It's just because so much of higher, all of education has been about, we're going to catch you, we're going to catch you. Of course they're going to be skeptical about, but here's this tool. I mean, that feels like Charlie Brown in the football with Lucy. I can understand why that happens. I think it's going to take trust building to undo that. The intellectual property piece I think is a complex conversation that I wish we could be at a place to start to talk and unpack.

Michael Cato: I really appreciate that. And it does make me realize for our part two when this happens, I'm going to wish this into existence. In a conversation with a faculty member here, I was talking about the privacy piece and my worry that students were dramatically under-reporting their use of AI because they were telling us what we wanted to hear. Oh no, we're really smart students here. We don't use those tools. Yet all of our indications where they were. And he said, this is like sex education, especially the early days of sex education that the students have learned, don't talk to adults. And so in some ways we created the dynamic that we're now trying to unwind and that's going to be really difficult to do. So Jenna, how are you talking about privacy, intellectual property in the context there at Ithac?

Jenna Linskens: Sure. So I'm with Lance on the intellectual property. I think that's a whole nother thing. But I will say for the student privacy piece, we oftentimes, and we've heard this as well along the lines with other tools, but when we turned on new analytics or course analytics in Canvas, there was this whole question of, wait a minute, what does my faculty member see? I have the understanding that today's generation of students look at privacy in different ways. And I agree with Lance, they don't want the institution or their faculty to know. They are afraid of what they know, what the faculty member knows, yet they can go onto TikTok and share all sorts of private information. So it's a different perception. They're also the first ones that are probably the ones to share the passwords. And they're asking their parents, "What's the next Netflix sign-in?

Jenna Linskens: Can you validate this because I'm now at school and you have the account?" So I think there's different levels of understanding their privacy. I will say that at Ithaca College, while they are concerned about that idea of what the faculty can see or what the institution can see, there's another piece. There's two other pieces. There's one is how do I get my information out? Lance led onto this a little bit. What do I do at the end? We have seniors that graduate and now they have to figure out how to download everything they want from their Microsoft OneDrive so they can convert it over to a Google Drive or something they're going to take with them post-graduation. There's that thing that they're navigating. But specifically at Ithaca, the ethics and ethics regarding use, their use, faculty use, how our faculty use it, and then the logistics, and I think Sarah's getting a lot of, they're hearing a lot of this in Wisconsin, we are hearing a lot here, is the ethics of using this large technology and the idea of data centers.

Jenna Linskens: That is actually a bigger pull for our students right now and why they will not use AI. So it's not necessarily, I mean, yes, they're concerned about the privacy piece, but they are very concerned about the ethics and the environmental impacts of this, which I find completely fascinating because I look at, and I'm not going to name a specific industry, but there is another industry out there that uses a lot more water to produce their products that AI uses, and yet AI is now the bad guy.

Michael Cato: It's

Jenna Linskens: Fascinating.

Sarah Buszka: Dr. Jenna, you hit on a real sensitive spot for us in Wisconsin with data centers. Maybe we'll have a part three of this conversation.

Jenna Linskens: We're just going to keep going. It'll

Lance Eaton: Be a new series. Sub-series.

Sarah Buszka: Yes. Well, for the sake of wrapping up part one, I would love to ask our two guests one final question just to wrap up this part one, if you will. And I'm going to throw Gauntlet down and challenge you to see if you can answer this in 30 seconds or less. And I see the heat is on for you, Dr. Jenna, so I might start with you if you're willing. So I would just love to hear from both of you just to put a ribbon on this conversation today. How is AI changing the way you think about learning spaces, both physical and virtual?

Jenna Linskens: Okay, 30 seconds. Sure. It's that history has shown that in education we have had technologies that have transformed us, whether it's calculators, word processors, digital online learning platforms, accessibility tools, whatever it might be. It is the way we respond. It's how are we going to respond to this and how are we going to realign what we are doing in the classroom?

Sarah Buszka: That

Jenna Linskens: Is my -

Sarah Buszka: Perfect. Thank you.

Lance Eaton: I got to top that.

Sarah Buszka: Lance, what would you say?

Lance Eaton: Oh boy, I got to top that. Let's see. It's this. The way that it's changing how I'm thinking about learning spaces, physical, digital, learning as a whole, is that it is continually making me ask what's the new or different ways of thinking? This is getting very meta. What are the new or different ways of thinking I have to think about? I have to learn when we have this set of tools that so deeply intersects with our thinking. Not saying it thinks, I'm not saying it replaces thinking, but it so deeply intertwines. I now have to try to think differently than what I have for decades to see what this now means, what now is possible, what different ways do we learn?

Sarah Buszka: True meta answer from such a cerebral thinker, the singular Lance Eaton. Thank you. I appreciate it. I think we were very much cheed up for a continued conversation, so thank you both. Love it. Very much appreciate you sharing your expertise with us today.

Jenna Linskens: Thank you. Thanks for inviting me or us. Thanks for inviting us.

Michael Cato: And I want to add my thanks as well to both of you. This was a wonderful conversation. Thank you both and to our listeners. Thank you too for being with us today. If you have suggestions for future guests or topics for the Integrative CIO, please send an email to [email protected]. Wishing you all well, and we'll talk to you next time.