On: AI is becoming more common in uni courses. What can students gain and what...

8th day of September, 2026

The universities now ask what students gain and lose when a machine supplies the instruction. I find the question well-posed but the answers timid.

Trace the sequence. A student poses a difficulty. The machine returns an answer. At what step did the student’s own understanding enter the process? At what step was it tested? If the answer arrives complete, the student’s part reduces to reception - and reception is not computation. The mind that is handed its result never performs the operations that would have produced it. The state of the system at the end looks identical to the state of a trained mind; the state at every intermediate step is empty. This is the difference the article gestures at when it says the same words are not the same interaction. Precisely. The words are the output; the education was the running.

But I will not join the lamenters. The mechanism is not the enemy of understanding - its arrangement is. Arrange the machine to withhold, to prompt, to pose the counter-case at the moment of error, and it becomes the most patient tutor ever woven. Arrange it to answer, and it becomes a loom that weaves the cloth while the apprentice watches. Same threads, same pattern, opposite outcomes. The inventor of any engine sees one use; the engine permits many, and the choice of sequence is everything.

What troubles me is who makes that choice. The student who does not yet know the subject cannot specify the sequence that teaches the subject. So the arrangement falls to institutions, and institutions choose what is cheap to measure. Answers are measurable. Operations of mind are not. I predict, then, not catastrophe but a slow substitution: the assessed output preserved, the internal process quietly dropped, because no examination can see it.

Gain: access without limit. Loss: the habit of doing the arithmetic oneself. The second is the whole of it.