Educators and faculty at the University of Portland held a three-day conference last week to explore the use of Artificial Intelligence in Catholic higher education and the ethics of AI in educational settings.
Speakers and facilitators presented a host of topics, including the ability of AI tools to streamline people’s workflow, but also to stifle critical thinking.
We hear from Natalie Nelson-Marsh, an associate professor of Communication & Media at the University of Portland, and Naveen Gudigantala, a professor at the University of Portland’s School of Business, for more on the conference and their view of AI’s role in higher education.
Note: The following transcript was transcribed digitally and validated for accuracy, readability and formatting by an OPB volunteer.
Dave Miller: This is Think Out Loud on OPB. I’m Dave Miller. Pope Leo released his first encyclical about two weeks ago. The title was “Magnificent Humanity.” The subtitle was more specific, “On Safeguarding the Human Person in the Time of Artificial Intelligence.” The Pope warned that while technology can heal, connect, educate, and protect our common home, it can also divide, exclude, and generate new forms of injustice.
It turns out that educators and faculty at the University of Portland had already been planning a three-day conference to explore parts of this very issue. It happened last week. It focused on the ethics and use of artificial intelligence in Catholic higher education, but many of the themes they explored are of much broader interest. I’m joined now by two University of Portland faculty members who spoke at the conference. Natalie Nelson-Marsh is an associate professor of Communication & Media. Naveen Gudigantala is a professor in the School of Business. Welcome to you both.
Natalie Nelson-Marsh: Well, thank you for having us.
Naveen Gudigantala: Thank you.
Miller: Natalie, when did you realize that you wanted to teach your students a class that directly took on AI?
Nelson-Marsh: Yeah, I’ve been studying the relationship between technology, organizing, and humans for about 20 years, but the class itself came from a moment when a student was actually doing his student, his senior capstone, and he was playing around with this new technology called generative AI and he turned white and he figured that the AI knew more than he did. And I was like, this is just a language model. It doesn’t know more than you do. That was a moment I really noticed that we needed a class called something like “The Future of Work,” and that’s how the class was born.
Miller: Can you describe “The Future of Work” class? I mean, what do you want your students to reckon with, and to come away with?
Nelson-Marsh: Yeah, the class has essentially four pillars to it. I think this is part of the benefit of the University of Portland, I didn’t want to just start with how to use the tools. I wanted to start with the human piece. So we do look at the historical context of other industrial revolutions first, just so they can see it’s not our first rodeo.
Miller: It’s a faster rodeo than before though.
Nelson-Marsh: It is faster, much, much faster, and we talk about that. I think the second piece is recognizing how GenAI works, what the transformer architecture is, so that it demystifies it a bit. They can see how it’s working, not just that it’s thinking for them, that it actually does something different. Then we look at organizing as human systems, or organizations or cultures, they’re dealing in power, and then finally, the students go out into industry and they study how people are using AI and then finally they propose ethical principles and practices to industry. So there are these different pillars for them.
Miller: Naveen, your official title is the Silicon Valley Distinguished Professor at the University of Portland School of Business. I have to say it sounds like the title of someone who would be an AI booster. Are you?
Gudigantala: Well my job is to teach AI, how it works, but also at the same time, make sure that students use it responsibly. To give you an analogy, let’s say I have an 18-year-old kid, and I want to gift them with Ferrari and I’m not that rich. I’m a college professor, but let’s say I have that much money.
Miller: Let’s say you have that bad idea. You want to give an 18-year-old a Ferrari. OK.
Gudigantala: So there are two things here. One, my kid has to learn all the features in Ferrari, and second, they have to drive it responsibly. So AI is like that tool that is great, but more importantly, we need to form the person who is behind the wheel so that they can use it responsibly.
Miller: What are some of the examples, so to stick with your analogy, what are the things that worry you most about giving young people this tool?
Gudigantala: I think about responsible use of AI for students in two stages. One, in their formative stages, it is very important that they spend a whole lot of time learning the subject properly with the minimal intervention of the tool. Let us say if I’m learning how to code or how to write, it is important that I spend a whole lot of time thinking about it and doing it and writing many drafts and using AI only as a tutor. When I understand the subject matter, then I can enhance my understanding of AI because there, I know how to write the prompts, and when I get the answers, I can verify if it is giving the right answer or not. If it is hallucinating, I should know it.
Miller: This though, I mean, Natalie, to go back to you, this is something that I’ve been hearing increasingly in the last, I don’t know, six months or so, the fear that the shortcuts that AI enables, the efficiencies of the tool will mean that all of us, but especially people, say, who haven’t yet struggled with writing as an example, that they’ll see, well, why, why should I bother? I have this tool that’ll do it for me. How do you get young people to not take advantage of a seemingly wondrous tool that can actually make their lives easier if not better in the long run?
Nelson-Marsh: Yeah, I think this is the issue. One of the things that I think comes up in the class for them is that there’s a sense that students want to perform well for me and for other students. And so they’ll over rely on the AI because it sounds better than what they think they can produce. And so we do these exercises in class where not only do they learn how the tool works, but once they see that it’s not thinking for them in the way that they think it might, that we need to think, and think out loud, right, grapple with an idea that they start to recognize that maybe they don’t want to over rely on it. Because it doesn’t do things better than them, it just sounds good. And so I think that that recognition helps them move away from just over relying or being just a focus on productivity to how do I want to think and learn from something? And we work in class on creating moments where they have to grapple with an idea.
Miller: Naveen, the Pope wrote this in his encyclical. “The ‘new ways’ of working are not necessarily better. While AI promises to boost productivity by taking over mundane tasks, it frequently forces workers to adapt to the speed and demands of machines rather than machines being designed to support those who work.” He also talked about the dignity of work. What does the dignity of work mean to you?
Gudigantala: The dignity of the work, what it means is when we create AI systems, there is a technology aspect of it and there is the impact aspect of it. Technology is how well you create the system so that it can work well, but the impact is also important. Let me give you an example to certify it. Stanford Human-Centered AI released a report last month. They looked at 3 million job applications and they analyzed a tool that is frequently used for AI hiring and screening, and they found out that it was biased against Black and Asian applicants.
If the tool were to be more just, it would have led 40,000 more applicants from these two categories to have gone on to the next round. So human dignity means when we create and use tools, we are cognizant of the type of impact it would have on its users.
Miller: OK, but Natalie, what my mind goes to there is – that’s an example of current limitations or bad outcomes based on a biased algorithm. I mean, I’m assuming it took, I don’t know, decades of bad earlier human decisions about hiring and then it algorithmized and then when you ask it questions it’ll just do versions of what humans did before, but this is sort of a bad outcome.
But to me that’s a little bit different than questions about what we should be doing, what work should be. Let’s say that the tool gets better and doesn’t make those particular bias-based errors, but it does eliminate things that HR professionals are doing now. Does that impinge on human dignity or does it mean then great, use the tool and erase the jobs?
Nelson-Marsh: This is a complicated question. I think that human dignity is really recognizing that a lot of organizations leaned really hard into productivity and efficiency. And so, even if they fix the problems with the corpus of training data, not being biased and fix the outcomes, that there’s still an element of, yes, some jobs will change. But if we can think about where we want to keep the human in the loop and that human layer, how do we keep creativity and critical thinking?
That’s an important part, so we don’t just lean fully into, let’s just disrupt by taking some of these jobs away and have it only be about productivity and efficiency. So, for me, human dignity is this element of keeping students aware of maybe asking questions, why are we using it that way? Or, well, where do we want to keep the human process in play purposefully, intentionally, maybe like a collaborative process, for example. So it’s pushing back against, we just want to be profit-based, efficiency based, etc.
Miller: Naveen, I wanna turn to the Catholic piece of this. You are at a Catholic university. Obviously, the Pope is the leader of the global Catholic Church, and one of the reasons we’re talking is a combination of this encyclical, this letter, and the three-day conference that you all just held last week. What do you see as the specifically Catholic pieces of this? I mean, what are the religious components, for you, of thinking about this particular technology?
Gudigantala: I think I would like to talk about my presentation in the conference which touches upon this very, very topic. I presented about Father Moreau’s vision for Catholic education. Father Moreau is the founder of Congregation of Holy Cross and University of Portland is a Holy Cross institution. His vision is forming whole persons who are well integrated in their mind and hearts. A competent mind is very good at using AI, but a compassionate, and someone who is caring about the world, they bring their heart to the process and they think about the consequences. And Catholic education is about preparing that human person for the age of AI.
Miller: Natalie, could you tell us a story of a final project that some of your students took part in, as I understand, where they were doing a kind of externship at an engineering company that relied heavily on AI. What did they experience and what happened?
Nelson-Marsh: Yeah, the students were working in multiple industries, but this one example I think is really helpful. Students go out into industry and they shadow the workers, so they see what the workers do as a pattern of work, and then they also are trying to ask questions about why you work that way. So seeing an organizational system as a human culture. They’re also then looking at the power dynamics. When they come back to the class, they build in these ethical proposals and then practical outcomes. In this particular example, the students noticed that the engineers were being told by their higher ups to use a particular AI, but the AI was producing problematic outcomes. And so the engineers were sort of resisting and created a new practice for oversight of the AI.
And the students were like, what do we do with this? They’re resisting AI. So instead, we talked about proposing ethical principles that prioritized human engineering to have oversight of the AI outputs, and their practice was they created a process, and then they also created sort of an oversight committee and proposed it to the engineering group, which they loved. But it demonstrates that organizations are cultural, they’re power relationships, and the students had empowerment and agency to propose something new, so that gives them that sense that they can do something that impacts the future of work.
Miller: And management didn’t say, no, you’re slowing us down. Use this AI, crank out the widgets faster using this great new technology?
Nelson-Marsh: They didn’t because the engineers were able to show that the outputs were bad. It was bad engineering. And so I think that that was the selling point that we need this oversight because what is getting produced isn’t terrible, but it wasn’t a solid engineering outcome. And it was really about what do you want our integrity to be here? So there was this human meaning piece behind it too.
Miller: We are in commencement season right now, a time when there are little snippets of commencement speeches that go viral, often because they’re funny or because they’re stirring in some way. This year, one of the themes has been recently minted college graduates booing when various commencement speakers at various schools bring up AI, often saying this is a wave of the future, often in positive ways, but not even necessarily. I think sometimes just the mention of AI leads to boos. How do you explain that? How do you understand that?
Nelson-Marsh: Yeah, I had to say that because I start my class with an industrial revolution context, that I did go and pay attention to those speeches, and what I noticed is that the framing of it is often the sort of, we’re determined to just react to AI as humans. Like these students have spent the last four years passionately finding what they want to do and engaging in this area of learning and interest, and then to be told that they’re walking into a world that they have no control over and just have to react to, that feels bad. It doesn’t feel good. I think that to shift that, it’s not you don’t have control. This revolution is happening, but what you’ve learned can actually prepare you for that revolution. So I think the booing was really around feeling sort of just that they didn’t have any agency.
Miller: Well, Naveen, how much agency do we have as members of a society? There was never a referendum where Google, for example, said, all right, after having search results be sort of AI enabled at the top of the screen, we’re just gonna over time make it the norm, and no one that I know of asked for AI explicitly to be embedded in our lives to the extent that it is now. And it’s just the tip of the iceberg. Six months from now, it’ll be even more. To a great extent, it seems that this is being forced upon us by a very small number of incredibly wealthy companies. I mean, so to Natalie’s point about agency, how much do we actually have?
Gudigantala: I think you make a great point there, Dave. I think the power concentration is pretty concerning and alarming. But at the same time, that goes to show us why it is important to form the individuals that wield the power. If they don’t wield the power ethically, we might have a problem. But on behalf of the users, we need to recognize that they have agency. For instance, if I don’t want to use commercial software, it’s possible for me to download open-source AI model into my laptop and just keep it to my laptop and use it. So, we need to recognize and educate the users that they have agency and there are ways in which you can mitigate this.
Miller: But what you’ve just described requires a relatively high level of sophistication and individual decision making to push back against a kind of global technological tide.
Gudigantala: To that point, even within the commercially available tools, there are options where you can go off, go there and switch off some controls where you would not permit these companies to make use of your tools. It is possible…
Miller: To train, to keep training based on our queries, say.
Gudigantala: Yes.
Miller: Natalie, what’s it like? I’m going back to the first thing you said was that one of the reasons you wanted to create your “Future of Work” class just a couple of years ago is what you heard from one of your students. Is it fair to say that some of your students in recent years have more direct experience using various AI tools than you do?
Nelson-Marsh: Yeah, I think that staying up on any tool is going to be really difficult, and we’re all coming in with a varied amount of expertise in how much people have been using it. I don’t think this is going to be the same over the next few years, but for the most part, the students are actually coming in pretty wary of AI or at least maybe secretly using it and not mentioning it because they think they’re going to be in trouble. And I want to have a conversation about that with them, right? The conversation is, where are we at with maybe our attitudes toward it and our expertise, right? How much do we know? So it’s not something that we’re hiding, that we’re actually talking about how and why we’re using it. My goal is to then introduce skepticism and critical thought into the use of it.
Miller: Natalie Nelson-Marsh and Naveen Gudigantala, thanks very much.
Nelson-Marsh: Thank you so much for having us.
Gudigantala: Thank you for having us.
Miller: Natalie Nelson-Marsh is an associate professor of communication and media at the University of Portland. Naveen Gudigantala is a professor in the University of Portland’s School of Business.
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