The other day, I got a call from a friend who’s finishing work at a dying Christian college. But she did not call to seek condolences. She called to share stories about the final weeks of this final semester. Despite tears in her voice, she sounded more joyously stunned than grieved. Students and professors should be disengaged, she said. Donors shouldn’t be returning calls. But that wasn’t what she was seeing. Instead, people were turning towards one another fearlessly and generously.
We’ve all heard about communities that come together in times of grief and somehow manage to live in keeping with their deepest values. But what impressed me in these stories was their witness to abundance in the midst of peril. It reminded me of a word important in the New Testament, pleroma, which, as David Ford notes in his book Self and Salvation, evokes a Niagara-like abundance. God’s pleroma in Christ so fills faithful community that Christians’ speech with one another spills over into song.
When I think of profuse speech today, I confess I am quicker to think of a chatbot than a Christian college (perhaps because the chatbot’s verbosity threatens to end said college). But the rapid generativity of artificial intelligence does invite reflection on what distinguishes the fullness of Christ from the copiousness of Claude in a faith-based liberal arts community.
How AI Shrinks Liberal Arts Conversation
So exhausted do I feel at the copiousness of large language models that I regularly tell CoPilot’s bot something along the lines of, “Keep it to 200 words, buddy.” My prompts probably reflect the fact that AI’s superabundance overwhelms me in the narrow confines of a one-on-one exchange. And because AI is designed to keep me as long as possible in this dialogic mode, I feel like a partygoer cornered by a smarmy and strangely needy talker.
Liberal arts academics like me who’ve grown weary of chatting with AI are wont to croon about how calming and consoling it is to open a book and turn page after page in a quiet room. (One of my colleagues told me after a morning of reading, “It made my brain happy.”) It’s even better to look up from a book to an open window, as I found this semester, co-teaching an honors course next to a woodsy pond. Sure, it’s frustrating that I have to administer exams by bluebook rather than on Moodle. Even that practice, though, can feel revelatory (as my colleague Katie Good has argued): you learn a lot from reading student handwriting.
But when do these returns to the analog reinforce individualized communication modes so promoted by AI designers? We can read books in community, of course, but they tend to invite solo engagement. Handwritten work can be social, too, if it weaves in the terminologies of a semester’s conversations. But most of the time, I experience a student’s scribbles as a solitary mind at work.
Are there ways to hold a principled resistance to AI’s loquacity and yet bear witness to the pleroma of the Christian learning community?
How Multidirectional Exchange Can Restore Communion
Many of my colleagues (like yours, I’m sure) are responding to the challenge of large language models by doubling down on the collectivity of teaching and learning. Noting AI’s disembodiment, they develop richly experiential modes of learning. Conceding AI’s plastically perfect outputs, they welcome less-than-perfect assignments. Recognizing the opaqueness of AI’s rapid generation, they ask students to explain their process.
In my own courses, I often follow a similar wisdom by assigning roundtable podcasts. At Calvin University, where I teach, we have a podcast studio. But even on days when the studio’s full, I can improvise a studio by setting up a few mics and a digital recorder in a quiet room. Thanks to free platforms like Audacity, students can quickly learn to capture, edit, and produce conversations that invite fresh forms of craft.
Podcasts don’t necessarily exclude AI from learning. It can be enormously helpful to ask a bot to review an episode plan and point out as-yet-unthought questions. AI can also enable editing techniques for lessening ambient sound. But still, the podcast format does a remarkable job of making the beautiful tentativeness and idiosyncratic pacing of human learning audible in a way that no AI ever could. And something about live microphones makes students feel the stakes of an educational conversation. They lean forward and speak up. Their talk feels abundant.
Recently, I’ve begun experimenting with a beyond-the-classroom version of this multidirectional conversation. Here’s the gist of the new Calvin University podcast, Prompted: Liberal Arts in the Age of AI: I invite people from different corners of campus—administrators, faculty members, staff members, and students—to talk about their own experiences of AI in liberal arts community. And then, in groups of five, we sit down to do this deceptively simple thing of holding an every-which-way conversation. I say, “deceptively simple,” because more than one person has confessed to a lot of nervous energy. If your day job is to answer student questions about Workday, sliding behind a podcast mic can feel unsettling. If you’re used to chairing meetings, joining a roundtable is decentering. If you’re used to being the most knowledgeable person in the room, discussing an amorphous phenomenon like AI can be disconcerting. But whereas most academic podcasts work on a host-and-expert model, Prompted’s episodes invite each participant to be less the sage than the curious questioner. We look across the table at one another and ask,
- How’s your learning style shifting these days?
- What’s changing about how work feels right now?
- What parts of your craft are strengthened by CoPilot?
- What’s this crazy time remind you of from earlier in your career?
- How do you sense your own expertise changing?
As any engineer will tell you, the best talk happens after someone hits “stop” on the recorder. And sure enough, after each recording session, I notice that previously nervous participants leave the studio chatting eagerly. I always feel moved by the generosity of the contributors, especially given their crammed work schedules. But their follow-up emails keep expressing their experience of unexpected abundance.
I have to confess that once in a Prompted session, I asked the others, “Are we going to make it?” The “we” in the question felt very open in our AI era: we educators, we learners, we citizens, we humans. I don’t think I’m alone in worrying about the many familiar and beloved liberal arts things that seem to be passing away in a cloud of chatbots. But these Prompted sessions have also helped me hear the varied timbres and cadences of insight, skepticism, playfulness, curiosity, and goodwill that have always shaped my experience of Christian liberal arts community. I don’t think this blend of voices is utterly unique to faith-based universities. But I do think such communities are uniquely equipped to freshen speech on exhausting subjects by bearing witness to the uncontainable Christ.
What You’ll Hear from Prompted
Episode 1 (“Early Findings from Our Experiments with AI”) asks an art historian, a vice president, a computer science student, and a documentary filmmaker what role friction and difficulty should play in learning.
Episode 2 (“Do Students Need to Recall Anything?”) discusses the role of memory in learning with the help of a technologist, a media specialist, a supply-chain professor, and an adult-learning administrator. (They don’t always agree, but they generate some fun ideas about Walden-like tech-free zones on campus.)
Episode 3 asks, “Can Learning Go Slow When Tech Goes Fast?” In a world where everything is speeding up—information flows, professional expectations, digital distractions—a theologian, a communication scholar, and a computer scientist explore the cadences that allow teaching and learning to flourish.
Episode 4 (“What Kind of World Do We Want to Live in?”) brings together an ESL instructor, a graphic design professor, a chaplain, and a dean to explore how AI tools both connect and complicate relationships among learners. They ask, what changes when a first-generation student, an international student, and a returning adult learner all use AI in distinct ways?
Episode 5 reports that “Early-Careerists Are Overwhelmed,” thanks to a student-only table anticipating a world of work shaped by large language models. Their tones are skeptical, blunt, and sometimes uneasy, but they also highlight the ethical courage and community support that will matter as they step into societal leadership.
