I agree that AI presents an immediate and existential threat to our existing education system. I'm hopeful, like you seem to be, that this threat will bring reform and reimagination rather than replacement. I'm curious why you use "safety" as the overarching category. Are you connecting the threat to education with broader safety concerns like those in the "existential threat" conversation? Or are you implying that positioning concerns about education as "safety" concerns is a helpful strategy because "safety" is dominating the discourse right now?
Thank you for this! The problem I keep coming back to is we’ve largely moved away from offering a shared vision of the “good life.”
Our times are different, but I do find some comfort in Humboldt's attempts to reform education away from pure job training. Perhaps the liberal-arts goal of educating the whole person will need to begin much earlier.
This touches on a broader question of how we will continue to learn what to want if AI mediates the environment to such a degree that we are not exposed to consequences of our actions. If we don’t make errors we can’t learn and if AI is undertaking activity for us we cannot error correct. What AI can help us do is understand our own errors better - more precise credit assignment and much better evaluation. But as you say we have to design institutions explicitly with this in mind
The eight-week study measures whether students can still write an essay once the AI is taken away. I'd suggest the better test is retention: what they still hold from the essays they did write. A great essay that doesn't last beyond submitting it is arguably close to not having learned at all.
I see two different losses in my own work. I've been writing software for 35+ years, and I now spend most of the day answering an AI's questions about the code it's writing. My hands-on coding has gotten rusty. That's ordinary disuse. I played sports for decades, and if I went out and competed today the guys I used to beat would beat me, but a few weeks of practice would fix most of that. The other loss doesn't fix that way. At the end of the day I don't have nearly the mental picture I used to of what got done, what's outstanding, and how what we built actually works. Practice won't bring that back, because it was never something I built in the first place.
That's the students' situation too. My skills come back because they were built before the AI arrived. A student who never builds them has nothing to come back to, and a test of unaided performance can't tell rust from never-learned. It also matters for the economists' model you quote: "the rigor of verification" assumes the verifier holds a picture of the whole, and answering questions about the work doesn't build one.
'As preposterous as it is, the idea that we should teach “thinking”, instead of teaching boring old facts has gained a lot of support in modern educational curricula.'
Sadly, this preposterous idea goes back at least 100 years to the theories of John Dewey, one of the biggest influences on American education to this day.
Insightful! I like that you point out that while working on problems we are also working on ourselves. Just like weightlifting - it’s supposed to be hard; we don’t grow without it. But the human tendency to look for what’s easy will always be there.
We need to make this distinction especially for students. Calculators didn’t make it obsolete for children to learn arithmetic, even if they’re not writing out equations as adults. In fact with large language models available, learning to read and write is even more important in order to “validate” the output. Maturity and critical thinking isn’t inherent; it has to be trained.
AI can replace part of our thinking. But the constraints of reality don’t disappear. We still need resources. We still need to maintain our position. Competition remains. And bad decisions still have consequences.
Say you have a proposal due tomorrow. AI can generate it. But you can’t just submit it without looking. You have to verify the data. Check the logic. Judge the ideas. Think through what happens next. If the proposal fails, you bear the consequences, not the AI.
When everyone has AI, generation becomes cheap. Being able to generate something is no longer enough. You need to know where the AI is right, where it is wrong, what can be used, and what cannot.
Reality is still selecting among people. If you can’t judge AI, you lose your position. If you want to maintain it, you have to improve your judgment.
AI changes which abilities we need. It does not remove the real-world pressures that force us to develop them.
I think the core issue is still needs and constraints.
Humans are self-maintaining structures. We need resources. We need to maintain our position. We also face competition. None of this disappears as AI gets better.
If AI can eventually check other AI, that just means the tool has advanced another step. Human needs will keep moving forward too.
We used to travel by carriage. Then by car. Then by plane. Transportation kept improving. But human needs did not stop at the carriage. Our range of activity expanded, and so did the range of competition.
AI will be the same. It will keep taking over existing tasks. But our needs will keep changing, and the baseline for competition will keep rising.
So the key question is not whether humans will still need to check AI. As long as needs and constraints remain, people will have to keep finding new ways to maintain their abilities and their position.
Excellent piece. Thank you. An important part of the frame whenever people talk about disempowerment and “loss of control”
I agree that AI presents an immediate and existential threat to our existing education system. I'm hopeful, like you seem to be, that this threat will bring reform and reimagination rather than replacement. I'm curious why you use "safety" as the overarching category. Are you connecting the threat to education with broader safety concerns like those in the "existential threat" conversation? Or are you implying that positioning concerns about education as "safety" concerns is a helpful strategy because "safety" is dominating the discourse right now?
Thank you for this! The problem I keep coming back to is we’ve largely moved away from offering a shared vision of the “good life.”
Our times are different, but I do find some comfort in Humboldt's attempts to reform education away from pure job training. Perhaps the liberal-arts goal of educating the whole person will need to begin much earlier.
This touches on a broader question of how we will continue to learn what to want if AI mediates the environment to such a degree that we are not exposed to consequences of our actions. If we don’t make errors we can’t learn and if AI is undertaking activity for us we cannot error correct. What AI can help us do is understand our own errors better - more precise credit assignment and much better evaluation. But as you say we have to design institutions explicitly with this in mind
The eight-week study measures whether students can still write an essay once the AI is taken away. I'd suggest the better test is retention: what they still hold from the essays they did write. A great essay that doesn't last beyond submitting it is arguably close to not having learned at all.
I see two different losses in my own work. I've been writing software for 35+ years, and I now spend most of the day answering an AI's questions about the code it's writing. My hands-on coding has gotten rusty. That's ordinary disuse. I played sports for decades, and if I went out and competed today the guys I used to beat would beat me, but a few weeks of practice would fix most of that. The other loss doesn't fix that way. At the end of the day I don't have nearly the mental picture I used to of what got done, what's outstanding, and how what we built actually works. Practice won't bring that back, because it was never something I built in the first place.
That's the students' situation too. My skills come back because they were built before the AI arrived. A student who never builds them has nothing to come back to, and a test of unaided performance can't tell rust from never-learned. It also matters for the economists' model you quote: "the rigor of verification" assumes the verifier holds a picture of the whole, and answering questions about the work doesn't build one.
'As preposterous as it is, the idea that we should teach “thinking”, instead of teaching boring old facts has gained a lot of support in modern educational curricula.'
Sadly, this preposterous idea goes back at least 100 years to the theories of John Dewey, one of the biggest influences on American education to this day.
Insightful! I like that you point out that while working on problems we are also working on ourselves. Just like weightlifting - it’s supposed to be hard; we don’t grow without it. But the human tendency to look for what’s easy will always be there.
We need to make this distinction especially for students. Calculators didn’t make it obsolete for children to learn arithmetic, even if they’re not writing out equations as adults. In fact with large language models available, learning to read and write is even more important in order to “validate” the output. Maturity and critical thinking isn’t inherent; it has to be trained.
If we become useless, we become useless, there is no turning around. The steering will be done by the IA itself if we let IA happen
so what will humans do?
We will try to escape that hell by plugging into some kind of VR or video games where all that never happened I guess.
Where we are still the main characters.
This is very depressing
AI can replace part of our thinking. But the constraints of reality don’t disappear. We still need resources. We still need to maintain our position. Competition remains. And bad decisions still have consequences.
Say you have a proposal due tomorrow. AI can generate it. But you can’t just submit it without looking. You have to verify the data. Check the logic. Judge the ideas. Think through what happens next. If the proposal fails, you bear the consequences, not the AI.
When everyone has AI, generation becomes cheap. Being able to generate something is no longer enough. You need to know where the AI is right, where it is wrong, what can be used, and what cannot.
Reality is still selecting among people. If you can’t judge AI, you lose your position. If you want to maintain it, you have to improve your judgment.
AI changes which abilities we need. It does not remove the real-world pressures that force us to develop them.
True at present; much less so once AI becomes able to check other AIs' work with a suitably low error rate.
I think the core issue is still needs and constraints.
Humans are self-maintaining structures. We need resources. We need to maintain our position. We also face competition. None of this disappears as AI gets better.
If AI can eventually check other AI, that just means the tool has advanced another step. Human needs will keep moving forward too.
We used to travel by carriage. Then by car. Then by plane. Transportation kept improving. But human needs did not stop at the carriage. Our range of activity expanded, and so did the range of competition.
AI will be the same. It will keep taking over existing tasks. But our needs will keep changing, and the baseline for competition will keep rising.
So the key question is not whether humans will still need to check AI. As long as needs and constraints remain, people will have to keep finding new ways to maintain their abilities and their position.