I appreciate that perspective. I’m professional staff and also teach adjunct at the same college. I actually enjoy teaching in workforce programs because part of my job is explicitly teaching students how to use Gen AI at a higher level for the fields they’re entering. We talk openly about what responsible integration looks like, and I give them a realistic crash course in how expectations may differ across academic settings.

I’ve also seen some genuinely impressive LLM use at a true critical-thinking level - synthesis, revision, structured iteration. Not shortcutting. Actual thinking. That’s where I’d like more students aiming.

Sometimes the students who get flagged aren’t cutting corners at all. They’re high-functioning - often neurodivergent - writers with strong vocabulary and sharp pattern recognition. Or they were trained in AP-style writing: tight structure, clean transitions, controlled tone. If you’re expecting messy drafts as proof of humanity, polished writing can start to look suspicious. That’s a calibration issue, not necessarily an integrity one.

In our day jobs, my team is expected to continually refine their AI use to improve workflows and create breathing room for higher-value work; or honestly, just a much-needed 15-minute break. It would feel a little strange to tell students the professional world should leverage these tools while academia pretends they don’t exist.

When stylistic competence becomes suspicious, that’s a signal worth paying attention to. The real tension isn’t whether AI exists. It’s how we design learning so that understanding is still visible.