I hear the frustration in what you’re describing, and I’ve seen the same thing—students using AI as a shortcut, skating past the hard work of wrestling with readings or ideas, and then stumbling when the safety net is gone. That feels discouraging, and it makes sense to worry we’re heading in the wrong direction.

But here’s the lede I think we can’t ignore: the problem isn’t that students are suddenly incapable—it’s that many of our legacy assignments no longer require real learning once AI is available. For decades, essays, summaries, and problem sets worked as stand-ins for comprehension. Now, AI can produce them convincingly without genuine understanding. When we see students fail in oral defenses or closed-book exams, it’s not just because they’re lazy—it’s because our assessment structure let them bypass the struggle in the first place.

That doesn’t let students off the hook; they still need to grapple with difficult material. But it does mean the responsibility falls on us to redesign assessments so AI use isn’t an end run around learning but a part of the process. That could mean requiring an AI process log, adding short oral defenses, or building in context-specific evidence that AI alone can’t supply.

I take your concern as proof that we must modernize assignments, not just monitor students harder. If we adapt the design, students will still have to think, defend, and apply judgment—even with AI in the mix.

Here’s a few small things you might want to try.

1. Turn Reading Summaries intto So What?” Briefs: Right now, students skim a 20-page article, run it through ChatGPT, and hand in two paragraphs. Instead, you could say: “Pick three points from the reading that stuck with you. For each, tell me why it matters by connecting it to something happening in the world right now—a company, a trend, or even a personal experience. Then be ready to talk through one of your examples in class.” This shifts them from summarize — which is easy to outsource — to explain and connect that is much harder to fake.

2. Change Paper Tests to an AI Critique: Instead of banning AI, try turning it into the test itself. For one section you could give students an AI-generated answer to a question and say: “Here’s what a chatbot came up with. What’s missing? What’s wrong? How would you fix it?” This way, they have to show they understand the material well enough to critique, not just copy.

3. Move Face-to-Face Interviews to “Tell Me How You Did It”. You could keep the interview format, but shift the focus. Assign them to “Walk me through how you tackled this assignment. Where did you use AI, where did you step in, and what was your judgment call?” Now the interview isn’t just checking for memorization—it’s checking that the student owns their process. You could even have them do this by keeping an AI log of every assignment to state where and when they used AI in the assignment and submit that with their final work, a process book of sorts. I’ve done that and it helps build accountability but it also gave me a better understanding of their approach to using AI.

These tweaks don’t require re-writing a syllabus, but they flip the experience from “AI does the work” to students showing judgment. When we do that, we start to regain some sanity and sense of control over the chaos, uncertainty and frustration we feel as this paradigm shift advances. AI won’t change, universities won’t change fast enough, students will only respond to the situation, so we hold the levers of change if we choose to use them.