Apathies and Artifices in Education

Part 1 of piecing a few things togther...

I just finished a spate of talks and workshops over the last two months, and a few key points are sitting with me a lot as we look to the Fall and the 2026-2027 academic year. I want to use the next few posts to explain them and piece them together.

This piece will explore the militant apathy and what it means for higher education in this moment. The second piece will wade into the audacious ask of higher education, and the final piece will situate those two as we look towards the fall and what will be academic year 5 of GenAI’s presence.

Militant Apathy and The Artifices of Education

In March, I attended NERCOMP and Beth McMurtry of The Chronicle of Higher Ed was the keynote. She shared this piece about militant apathy by students returning from the pandemic.

It’s a great term, and she uses it as a way of exploring the different ways students felt disconnected upon returning from the pandemic. Many argue that students came back different. I have thoughts about who actually changed (I’m always leary when we decide the students are different but we are somehow the same).

Left unaddressed in the article but to me, glaringly relevant, is that students’ apathy lay also in the artifice.

During the pandemic, we sent everybody online. That was the right thing to do. But we also told students, in lots of direct and indirect ways, that this was still their education. This was still college, and it was still worth the tuition. This was still the experience they were paying for.

Then, as soon as institutions decided it was time (which is its own question about the real motivators there when schools claim to care about students’ health), we summoned them back.

When we summoned them back, we did not really account for what had just happened. We didn’t own the contradiction. We said, “No, no, you have to come back to the classroom. Learning is better face-to-face. This is why you need to be here.”

There may be parts of that that are true. There can be real value in being in person, and there are also real burdens as well.

But if learning in person is much better than learning on Zoom enough to bring people back and jeopardize some people’s health, then students had a pretty fair question: if this was less good, why did it cost the same?

Or, if the online version was equivalent, then why exactly are they being asked to commute, rearrange their lives, spend the time, spend the money, and physically come back into the room?

There is a falseness there that higher education hasn’t owned up to. And I believe that students felt it as one more part of the artifice of higher education. They may not have always named it that way, but they felt it. That is where some of that militant apathy came from. They had just been moved through a set of contradictions and then asked to pretend the contradictions were not there.

AI has extended that same dynamic.

Now the apathy is not just about the classroom; it is about what we ask students to do.

For so long, we have relied on a set of arguments that felt stable enough. You need to write this paper. You need to do this research. You need to complete this discussion post. You need to show your work. You need to learn how to do this because it won’t be done on its own. Nobody is going to research a hundred articles for you. Nobody is going to produce the report for you. No one is going to do the tedium of a million tasks between you and the thing we want you to; so you have to do that in order to demonstrate the things that we are explicitly saying you much be able to do.

To clarify, I know that’s not what we see, in terms of what we’re asking of our students. But that can be how they experience it, especially in courses they feel disconnected from (but more about that in part 2).

And now students are looking at us, looking at these tools, looking at the world they are being told they are preparing for, and asking: really? Not always out loud, but that’s part of their tendency to use AI tools in lieu of doing “the work.”

I do not think the answer is that the work does not matter. Reading matters. Writing matters. Research matters. Thinking carefully and making meaning across complexity absolutely matters. I teach literature, writing, and history. I am never not going to say those things matter.

But we need a better reason than a grade or we need a structure of what grades mean and do (the answer is definitely not this!).

Because grades, for students, can feel like hoop jumping. Assignments can feel like compliance. So much of what we have built asks students to prove that they did the thing, not necessarily that the thing changed them, helped them build something, helped them understand the world differently, or helped them move toward the person they are trying to become.

That was true before and AI just makes it harder to ignore.

We have to reconcile that higher education is structured around efficiency. Not because faculty do not care (faculty care deeply). But because we inherited systems built around convenience, grading, semesters, credit hours, seat time, text-heavy assignments, and all kinds of structures that were never necessarily designed because they were the best way people learn. They were designed because they were manageable. They were scalable. They were legible to the institution.

The ruling contradiction is that education is structured around efficiency and convenience to the institution’s benefit and moments like the pandemic and now AI make that glaringly evident. Claims to community, to care, to the institution being anything other than self-serving falls apart. When saving money, time, or resources become the grounds upon which it requires students to do things, how can we not expect students to respond with their own approaches being efficient or doing so with a sense of apathy.

After all, in a knowledge society and a world where maintaining or moving into middle or upper class can be so precarious, students feel obligated to go to college, invest in it (more about that part 2), and as adults, be told that all this is better for them.

Students turn toward AI is often their own increasingly realized of the gap between what we say the work is for and what the work actually feels like.

The question AI is forcing: What kinds of learning experiences are still worth showing up for when the baseline production of work is cheap, but the cost of accessing education is incredibly high? I think it is a question we should have been asking much more seriously already.

“Because I said so” is not going to carry us very far. “This will be important someday” feels too vague and wish-washy, when the bill comes due months after graduation. “You need to know how to do this because the real world will demand it” becomes shakier when the real world is also being remade by the same tools we are trying to keep outside the classroom.

I don’t think we can make students care by forcing them back into the old structures. I also think a lot about challenge my friend, Rhoan Garnett has grappled within learning spaces, that we can’t care more about the student succeeding than they do.

The hopeful part, for me, is that this does not have to end in cynicism. It can be an invitation to be more honest with students. To name the artificiality where it exists even before AI—the institutional artifices. If we can’t name those and how they permeate everything in the learning space, then we don’t have legs to stand on to address the artifices of AI. But turning to that, naming it and being honest, at least opens up the conversation and how we are all navigating the artificies and unfulfilled promises of efficiency. To me, that is where the conversation can then allow us to sit with students to navigate the impossibilities of the moment and when it does and doesn’t make sense to engage with AI in their own learning.

Let’s stop here and pick up with the audacious ask in the next part.

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The Update Space

Upcoming Sightings & Shenanigans

• Keynote speaker at the Reimagining the Liberal Arts in the Age of AI Conference, July 21-23 at the University of Mary Washington.

• EDUCAUSE Online Program: Teaching with AI. Virtual. Facilitating sessions: ongoing

Recent Recordings, Resources, & Writings:

• Davis, L., & Eaton, L. (May 2026). Expanding OER with GenAI. EDUCAUSE Review.

• AI x Higher Ed Podcast with Anand Rao & Stefan Bauschard. Episode: Universities Must Adapt to AI—Here’s How They’re Doing It (May, 2026)

• Damm, C., & Eaton, L. (2026, March). From prompt to practice: A framework for transparent GenAI use in higher education. EDUCAUSE Review.

• Eaton, L., Nemeroff, A., & Sun, X. (2026). AI-assisted course design and development. In K. S. Ives, M. Cini, & R. Schroeder (Eds.), AI applications in online higher education administration: Strategies for maximizing returns and improving outcomes. Routledge.

• Margin of Thought with Priten: Season 1, Episode 5: How Can We Center Pedagogy During the AI Tech Wave? (February 2026)

• Online Learning in the Second Half with John Nash and Jason Johnston: EP 39 - The Higher Ed AI Solution: Good Pedagogy (January 2026)

• The Peer Review Podcast with Sarah Bunin Benor and Mira Sucharov: Authentic Assessment: Co-Creating AI Policies with Students (December 2025)

• David Bachman interviewed me on his Substack, Entropy Bonus (November 2025)

• The AI Diatribe Podcast with Jason Low (November): Episode 17: Can Universities Keep Pace With AI?

• The Opposite of Cheating Podcast with Dr. Tricia Bertram Gallant (October 2025): Season 2, Episode 31.

• The Learning Stack Podcast with Thomas Thompson (August 2025). “(i)nnovations, AI, Pirates, and Access”.

• Intentional Teaching Podcast with Derek Bruff (August 2025). Episode 73: Study Hall with Lance Eaton, Michelle D. Miller, and David Nelson.

• Dissertation: Elbow Patches To Eye Patches: A Phenomenographic Study Of Scholarly Practices, Research Literature Access, And Academic Piracy

• AI Syllabi Policy Repository: 200+ policies (always looking for more- submit your AI syllabus policy here)

Finally, if you are doing interesting things with AI in your higher ed classrooms, consider being interviewed for this Substack or even contributing. Complete this form, and I’ll get back to you soon!

We periodically host small-group workshops and leadership sessions for higher ed teams. You can learn more about our current offerings here.

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AI+Edu=Simplified by Lance Eaton is licensed under Attribution-ShareAlike 4.0 International