The Despair of the Professor in the Age of A.I

This question, which unfolds throughout a conversation with Krishna, appears in the first chapter of the Bhagavad Gita, a book I somehow did not know existed until I took a Hinduism class in college. I was not a good student, routinely skipping class, but, worried that there would be a price to pay for my truancy and bad grades, I tried, sometimes. A few books got read, including the Gita, which I didn’t really understand until my professor—the sort of charming, gray-haired stoic found in religion departments of liberal-arts colleges across New England—explained, in a capacious and friendly way, that one should do their duty without considering the outcome. And, even though I don’t remember doing particularly well in that class, I have spent the last twenty-five years thinking about Arjuna’s despair and Krishna’s command. When I think about whether my nine-year-old will need to go to college, I mostly hope she won’t, because I don’t think this country should rely so heavily on a credentialling system that’s far too expensive, inaccessible, and time-consuming to be worth it. But I do worry that she will miss out on experiences like mine, when a nineteen-year-old was forced to read something he wouldn’t have otherwise and was guided toward a revelation, however banal or vain, by a patient professor. How do you place a value on something like that? There will always be idealistic, ink-stained people who want to devote their lives to scholarly pursuits—their role to inspire young people to love ideas as they do. But this transfer, more than anything else in the academy, has been increasingly blocked by A.I. in the classroom. This past April, Jane Sloan Peters, a professor of religious studies, wrote a stirring Substack post in which she described a course she had designed, some years ago, about what people throughout history have been willing to endure for their faith. The class, called “Letters from Prison,” typically culminated in students trying to synthesize an overriding theme about what they had read. “When I began teaching this course four years ago, students struggled to come up with their own themes,” Peters wrote. But, through brainstorming and revision, the students would ultimately land on some understanding that both felt personal to them and proved they had grappled with the assigned texts. Last year, the struggle ended—or, at least, got subverted. “Not one of my sixty students in ‘Letters from Prison’ struggled with this task,” she wrote. “I received tidy summaries of the text—the kind of compelling reviews you’d find on a book jacket—as well as perfectly vapid course themes that somehow took account of everything while not saying much.” What Peters suspected was that many of the students had asked A.I. to help. Like so many professors who have been confronted with the dispiriting new reality of student work, Peters adjusted, adding some handwritten brainstorming processes to her course, in the hope of making it A.I.-proof. But when she presented these new expectations to her students, something unexpected happened. “A wave of sadness washed over me, and I actually got choked up in front of the class.” Peters writes. “ ‘Before AI,’ I told them, ‘Students used to work hard to come up with their own ideas. I’d help, and they’d struggle, but they’d come to something that was their own. That doesn’t happen anymore and I grieve that.’ ” In the past few years, I’ve spoken to a number of academics and instructors at the college and high-school level who have said similar things. They talk about a sense of loss and of despair, because the one thing that brought them meaning has been erased, or blotted out, by the arrival of A.I. Most, like Peters, do not blame the students, nor do they believe all students welcome the changes wrought by the new technology. “I’ve seen students respond with this disdain for teachers who just let A.I. use happen,” Peters said. “There’s this indignance, like, ‘Why don’t you want more from us than this?’ So, even if they’re using it, they’re still wanting us to hold them to a higher standard.” “This is an exacerbation of a transactional model of education that has lasted for a long time,” Peters told me. Students are told that they’re in school to get a degree, one that comes with a high price tag and, for many, a debt burden. They are told that they will be assessed by the work they turn in. And, because A.I. allows them to turn in what Peters admitted was superficially “pretty good quality material,” they might not see why it’s such a big deal when they can’t explain what they have generated. “There are these waves of relief that wash over me when I see misspellings and poor grammatical structure in sentences,” Peters said. “When I can tell that they’re really working through it themselves.” The teachers and professors I’ve spoken to have varying perspectives on what A.I. is doing and what it may yet do. But common concerns emerge. What follows are testimonials from Peters and eleven other faculty members at colleges across the country on how A.I. has changed their work.

Susanna F. Boxall Lecturer in philosophy, California State University, Chico I am very grim about the outlook of my career. I am about to be forty-five; if my job still exists by the time I am fifty, I will consider myself lucky. The introduction of A.I., plus the demographic cliff, has had a devastating effect on higher ed. I think that big research schools will weather the storm, but lower-tier universities like mine will shrink or go away entirely. Already before COVID, there was a big push for online education; post-COVID, many programs switched to online to survive. However, with the introduction of A.I., all of those programs have become diploma mills. I taught online before and after A.I. In the pre-A.I. era, online education was qualitatively inferior to the in-person experience, but it was not a joke. Now, online classes are a simulacrum of education: the students pretend to learn, and I have to pretend that I am teaching them something. In-person classes can still maintain some degree of rigor, and cheating can be reduced to zero as long as all assignments are done in the classroom. The problem is that this is not a solution to the enshittification of education—I can no longer assign papers because seventy to a hundred per cent of the students will use A.I. This term, I was able to do a comprehensive oral final with a single class because it was a small seminar with eleven students. Even then, I had to book a room for a six-hour slot in order to have a meaningful conversation with my students—scaling this when you have a hundred and fifty-plus students is impossible. Furthermore, because not all faculty are as concerned as I am about A.I. use, and because the students are using A.I. in online classes, the students are much less cognitively capable than they used to be.

Kevin Sun Teaching assistant professor of computer science, University of North Carolina, Chapel Hill I’m quite pessimistic about the impact of A.I. on both education broadly and my career personally, given the recent decline in C.S. enrollment. The most obvious change in my teaching has been the elimination of difficult homework problems, which used to be a major component of my course. I’ve been trying to lean into social pressure as a source of motivation for students to learn, with group quizzes and in-class presentations, but there’s only so much an individual instructor can do given the systemic forces of A.I., grade inflation, the job market, student evaluations, etc. I’m worried that these forces allow many students to coast through school without learning as much as they used to. I acknowledge Bryan Caplan’s point that college is mostly about signalling, not learning, so it’ll survive as long as it’s a useful signalling device to employers. But, as college gets easier, the signal gets weaker, so who knows how things will change. On a positive note, A.I. has helped me write course syllabi, lecture plans, exams, etc. It’s possible to use A.I. to grade and/or provide feedback to students—though I haven’t done so yet. I have also used A.I. to help me create in-class assignments in which students evaluate A.I.-generated code/content. In C.S., A.I. has shifted the emphasis from writing code to evaluating code. To train students in this, I present them with A.I.-generated code that is either correct or subtly incorrect, and I ask them to evaluate it. I have a colleague who has completely embraced A.I. My understanding is that his course is much harder than it used to be, but students are allowed to use A.I. during exams. I see the motivation—A.I. is supposed to enhance our skills/productivity, so students should be expected to produce more—but I don’t want to create a situation where students are helplessly dependent on A.I. because they don’t have a solid grasp of the fundamentals.

Daniel Silver Professor of sociology, University of Toronto, Scarborough A.I. has fundamentally changed how I teach, and it demands basic reflection about what we are trying to accomplish. It has added a huge amount to my workload this year, since I spent a lot of that time trying to create new types of sociology assignments. The idea, basically, is to create multi-agent simulations where students create representations of the theories of writers like Adam Smith or Max Weber, and then they experiment with them. This was a huge commitment from me, the students, and the T.A.s, but it was worth it. The best final projects showed far more creativity and intellectual work than the typical second-year essay would have. Beyond that, students still would use A.I. in a thoughtless way, as a replacement for their thought and judgment. So I made a point to just call them on it, and make them meet with me personally. I saw dozens of students, often for thirty- to forty-five-minute conversations. I wanted to understand where they were coming from. I would give them a zero on the assignment and allow them to redo it, after we talked about intelligent use. They usually improved, but not always. I felt that the act of meeting them was the most important part, so they felt that somebody, especially a professor, was paying attention to them and what they produced, which, alas, is rare in larger universities. I also show them “replacement-level work,” on the model of the sports analytics concept of “wins above replacement.” These are basically variations of A.I.-generated versions of assignments. The students can see clearly how they all kind of look the same. Those are C-level answers, at best, and the students know they need to produce work that is better than what the replacement would be. Over all, A.I. did really knock me out of a fairly comfortable set of teaching habits, which is producing a lot of emotional upheaval. But I do feel we all, including the students, are learning how to live with it, and we’ll come out better on the other side.

Elizabeth Strom Associate professor, School of Public Affairs, University of South Florida I teach a lot of fully online classes. There is really no way you can prevent use of A.I. in a fully online class. There are a few situations where A.I. responses are so off the wall I can give the student an F on the assignment, but most of the time it can be difficult to figure out the provenance of a short essay written by a student I’ve never met. They don’t know me or, often, the other students in the class, so there are fewer social norms that reinforce doing their own work. Usually a handful of students will be very interested in the topic and take advantage of the many opportunities to meet with me in person or on MS Teams, and make an effort to complete the readings and discuss assignments with me, but they are the minority. For others, it’s just an easy way to get three credits. I have tried to frame assignments to make it harder to avoid doing the readin

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