Great piece. When I started teaching a few years ago - I tried using AI detectors once. Even then - when it was fairly obvious what was (and wasn't) written by AI, they were effectively useless. I tried 3-4 and they all gave wildly different answers.
I find it compelling that the focus shifts from the final output to the actual learning process, especially how struggle and confusion are treated as meaningful signals. It makes me think that smooth, perfect submissions don’t always reflect real understanding, and might even hide it. This perspective really changes how I see assignments not just as results, but as evidence of thinking.
This piece reframes something I've been sitting with — we obsess over the output artifact while the process that produced it tells you everything. The three questions at the end are the sharpest part: most AI-tutor claims skip straight to the sigma comparison without asking what axis they're even measuring on. The construct mismatch isn't a technical problem. It's a measurement problem
This piece reframes the AI debate perfectly. We keep asking 'Can AI do the task?' when we should be asking 'What happens to me if I don't do the task?' If the goal of life is just the final 'artifact,' then AI is a miracle. But if the goal is the development of the person, then the shortcut is actually a detour. The struggle isn't a bug; it's the core feature of human growth.
You're right that AI didn't create the problem - it just made institutional dishonesty about what we're actually measuring impossible to ignore. The insight that genuine learning leaves traces in process, not just artifacts, reframes this entirely. What strikes hardest is recognizing that students and professors aren't villains; they're both trapped in a system that has always rewarded performance over understanding. The challenge now isn't detection software or better AI tools, it's whether institutions have the will to build infrastructure that captures the actual struggle, the productive confusion, the revision cycles that reveal real thinking.
Great piece. When I started teaching a few years ago - I tried using AI detectors once. Even then - when it was fairly obvious what was (and wasn't) written by AI, they were effectively useless. I tried 3-4 and they all gave wildly different answers.
I find it compelling that the focus shifts from the final output to the actual learning process, especially how struggle and confusion are treated as meaningful signals. It makes me think that smooth, perfect submissions don’t always reflect real understanding, and might even hide it. This perspective really changes how I see assignments not just as results, but as evidence of thinking.
This piece reframes something I've been sitting with — we obsess over the output artifact while the process that produced it tells you everything. The three questions at the end are the sharpest part: most AI-tutor claims skip straight to the sigma comparison without asking what axis they're even measuring on. The construct mismatch isn't a technical problem. It's a measurement problem
This piece reframes the AI debate perfectly. We keep asking 'Can AI do the task?' when we should be asking 'What happens to me if I don't do the task?' If the goal of life is just the final 'artifact,' then AI is a miracle. But if the goal is the development of the person, then the shortcut is actually a detour. The struggle isn't a bug; it's the core feature of human growth.
You're right that AI didn't create the problem - it just made institutional dishonesty about what we're actually measuring impossible to ignore. The insight that genuine learning leaves traces in process, not just artifacts, reframes this entirely. What strikes hardest is recognizing that students and professors aren't villains; they're both trapped in a system that has always rewarded performance over understanding. The challenge now isn't detection software or better AI tools, it's whether institutions have the will to build infrastructure that captures the actual struggle, the productive confusion, the revision cycles that reveal real thinking.