We Taught the AI. Now It Teaches Us. · Uri.AI<br>← All postsAI + TeachingJul 2026 · 7 min read<br>We Taught the AI. Now It Teaches Us.<br>By Uri Schonfeld<br>AI is the new guy on the team. He's smart, talented and learning fast. The boss wants us to show him the ropes. He picks things up quickly and some things he's already doing better than anybody else. Soon, he'll know all our tricks. Will they still need me?

Artificial Intelligence is based on machine learning, mostly "supervised" machine learning. We, the supervisors, show the machine learning model 10,000 cats, and 10,000 non-cats, and it slowly assembles in its mind a high-dimensional "map" (I use a lot of quotes) to help it learn what's a cat and what's not. We are the ones that teach the machine learning model, the "AI".

And now the roles are about to reverse. The AI will be the one teaching us.

Will it take our jobs?

First thing to ask: is this going to take human teachers' jobs? And an immediate follow-up question: teach what and to what end? When the pocket calculator became cheap and popular, we started questioning whether or not we should still be learning the multiplication table by heart. The answer still isn't clear. But now, if AI can do everything (or will be able to within 2 to 10 years), what's left? Do we need to learn how to program? Learn how to 3D model? Do we need to learn how to play musical instruments or do music production?

So the open questions are: Who will do the teaching? What will they teach and to what end?

What chess can teach us

We can learn a lot from how chess has evolved in recent years. Computers now easily dominate even the best player in the world, Magnus Carlsen. It was reasonable to think that once chess was "solved" it would cease to be interesting. Much like tic-tac-toe isn't very interesting. Or alternatively, that we will watch different software programs battle each other, cheering on to our favorite version. That has not happened. People are as excited about chess as they ever were, excited to learn chess, compete and watch others play.

Not only that, having chess programs readily available uncovered new techniques in chess, new variations of openings were shown as ok, preparation for a competition was transformed thanks to chess programs, real-time analysis of games became possible and more.

Furthermore, and relevant to our teaching topic here, the ability to learn and practice chess in a more effective way by younger players results in stars like Gukesh and Faustino Oro solidifying a career in chess at such a young age.

So the takeaways from chess to me seem like:

Humans will enjoy learning and performing even if computers are much better.

Humans will enjoy watching other humans perform and compete.

Computers can help us learn things more effectively and at a younger age.

That last point is important and further supported by research.

What the research says

Chess is one anecdotal case study, but the research points the same way. The classic paper by Bloom from 1984 showed that the average student working with a personal tutor outscored 98% of students in a conventional classroom. Two standard deviations (two sigmas) better. The problem, which he called the "2 sigma problem", was that it was too expensive to provide every student with a personal tutor. One-on-one tutoring doesn't scale.

Guess what, Bloom. It's possible now using AI!

A randomized controlled trial in Harvard’s Physical Sciences 2 course (N=194) found students using a custom AI tutor learned significantly more (more than double the learning gains), in less time, than with active-learning instruction.

The biggest opportunity: homework

I think the most obvious opportunity to change the way we teach is in the homework workflow. Homework sucks. Not because of the reasons the kids will tell you, and not just for the kids, but it sucks at the university level too. Homework assignments suck because the feedback (the actual learning) comes with a big latency, happens at most once, and is usually limited.

The reason for all of this is that teachers don't scale. I'm sure all the teachers would tell you themselves. If you have 18 students in your class, and you need to read a five-page report and give detailed feedback to each, this would take a long long time. As a result, the feedback will likely be less extensive, the timeliness of it will suffer as well, and by the time the student receives the feedback, they already forgot what they thought while making it, they may or may not read the feedback and would likely not follow up with follow-up questions or try to fix their mistakes. One time, limited feedback given a long time after the assignment was submitted. And for that reason, the current workflow for homework sucks. I rest my case.

For the first time in history, we don't have to do it this way. LLMs can give the student feedback in real time, they can correct any misunderstandings they have, they can teach the student things they may...