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Do you find advocating for AI literacy to be controversial amongst peers? I find, as a parent, when I talk about it at the high school level I get very negativ

Do you find advocating for AI literacy to be controversial amongst peers? I find, as a parent, when I talk about it at the high school level I get very negative reactions from other parents. Specifically I want high schoolers to be skilled in the use of AI, and particular critical thinking skills around the tools, while simultaneously having skills assuming no AI. I don’t want the school to be blindly “anti AI” as I’m aware it will be a part of the economy our kids are brought into. There are some head in the sands, very emotional attitudes about this stuff. (And obviously idiotically uncritical pro AI stances, but I doubt educators risk having those stances)

copilot_king 9mo ago
[dead]
libraryofbabel 9mo ago
Not OP, but I would imagine (or hope) that this attitude is far less common amongst peer CS educators. It is so clear that AI tools will be (and are already) a big part of future jobs for CS majors now, both in industry and academia. The best-positioned students will be the ones who can operate these tools effectively but with a critical mindset, while also being able to do without AI as needed (which of course makes them better at directing AI when they do engage it). That said I agree with all your points too: some version of this argument will apply to most white collar jobs now. I just think this is less clear to the general population and it’s much more of a touchy emotional subject, in certain circles. Although I suppose there may be a point to be made about being more slightly cautious about introducing AI at the high school level, versus college.
- danaris 9mo ago
  > It is so clear that AI tools will be (and are already) a big part of future jobs for CS majors now, both in industry and academia. No, it's not. Nothing around AI past the next few months to a year is clear right now. It's very, very possible that within the next year or two, the bottom falls out of the market for mainstream/commercial LLM services, and then all the Copilot and Claude Code and similar services are going to dry up and blow away. Naturally, that doesn't mean that no one will be using LLMs for coding, given the number of people who have reported their productivity increasing—but it means there won't be a guarantee that, for instance, VS Code will have a first-party integrated solution for it, and that's a must-have for many larger coding shops. None of that is certain, of course! That's the whole point: we don't know what's coming.
  - libraryofbabel 9mo ago
    I agree with you that everything is changing and that we don’t know what’s coming, but I think you really have to stretch things to imagine that it’s a likely scenario that AI-assisted coding will “dry up and blow away.” You’ll need to elaborate on that, because I don’t think it’s likely even if the AI investment bubble pops. Remember that inference is not really that expensive. Or do you think that things shift on the demand side somehow?
    - danaris 9mo ago
      I think that even if inference is "not really that expensive", it's not free. I think that Microsoft will not be willing to operate Copilot for free in perpetuity. I think that there has not yet been any meaningful large-scale study showing that it improves performance overall, and there have been some studies showing that it does the opposite, despite individuals' feeling that it helps them. I think that a lot of the hype around AI is that it is going to get better, and if it becomes prohibitively expensive for it to do that (ie, training), and there's no proof that it's helping, and keeping the subscriptions going is a constant money drain, and there's no more drumbeat of "everything must become AI immediately and forever", more and more institutions are going to start dropping it. I think that if the only programmers who are using LLMs to aid their coding are hobbyists, independent contractors, or in small shops where they get to fully dictate their own setups, that's a small enough segment of the programming market that we can say it won't help students to learn that way, because they won't be allowed to code that way in a "real job".
    - LtWorf 9mo ago
      If they start charging what it costs them for example…
      - libraryofbabel 9mo ago
        There is so much confusion on this topic. Please don't spread more of it; the answers are just a quick google away. To spell it out: 1) AI companies make money on the tokens they sell through their APIs. At my company we run Claude Code by buying Claude Sonnet and Opus tokens from AWS Bedrock. AWS and Anthropic make money on those tokens. The unit economics are very good here; estimates are that Anthropic and OpenAI have a gross margin of 40% on selling tokens. 2) Claude Code subscriptions are probably subsidized somewhat on a per token basis, for strategic reasons (Anthropic wants to capture the market). Although even this is complicated, as the usage distribution is such that Anthropic is making money on some subscribers and then subsidizing the ultra-heavy-usage vibe coders who max out their subscriptions. If they lowered the cap, most people with subscriptions would still not max out and they could start making money, but they'd probably upset a lot of the loudest ultra-heavy-usage influencer-types. 3) The biggest cost AI companies have is training new models. That is the reason AI companies are not net profitable. But that's a completely separate set of questions from what inference costs, which is what matters here.
- hackyhacky 9mo ago
  > It is so clear that AI tools will be (and are already) a big part of future jobs for CS majors now, That's true, but you can't use AI in coding effectively if you don't know how to code. The risk is that students will complete an undergraduate CS degree, become very proficient in using AI, but won't know how to write for loop on their own. Which means they'll be helpless to interpret AI's output or to jump in when the AI produces suboptimal results. My take: learning to use AI is not hard. They can do that on their own. Learning programming is hard, and relying on AI will only make it harder.
  - subhobroto 9mo ago
    > My take: learning to use AI is not hard. They can do that on their own. Learning programming is hard, and relying on AI will only make it harder Depends on what your definition of "hard" is - I routinely come across engineers who are frustrated that "AI" hallucinates. Humans can detect hallucinations and I have specific process to detect and address them. I wouldn't call those processes easy - I would say it's as hard as learning how to do integration by summing. > but you can't use AI in coding effectively if you don't know how to code Depends on the LLM. I have a fine-tuned version of Qwen3-Coder where if you ask it to show you to compare to strings in C/C++, it will but then it will also suggest you look at a version that takes unicode into account. I have stumbled across very few software engineers who even know what unicode codepoints are and why legacy ASCII string comparison fails. > but won't know how to write for loop on their own. Which means they'll be helpless to interpret AI's output or to jump in when the AI produces suboptimal results That's a very large logical jump. If we went back 20 years, you might come across professors and practising engineers who were losing sleep that languages like C/C++ were abstracting the hardware so much that you could just write for loops and be helpless to understand how those for loops were causing needless CPU wait cycles by blocking the cache line.
    - hackyhacky 9mo ago
      > Depends on what your definition of "hard" is - I routinely come across engineers who are frustrated that "AI" hallucinates. Humans can detect hallucinations and I have specific process to detect and address them. I wouldn't call those processes easy - I would say it's as hard as learning how to do integration by summing. My students don't seem to have a problem using AI: it's quite adequate to the task of completing their homework for them. I therefore don't feel a need to complete my buzzword bingo by promoting an "AI-first classroom." The concern is what they'll do when they find problems more challenging than their homework. > I have stumbled across very few software engineers who even know what unicode codepoints are and why legacy ASCII string comparison fails. You are proving my point. If the programmer doesn't know what Unicode is, then the AI's helpful suggestion is likely to be ignored. You need to know enough to be able to make sense of the AI beyond a superficial measure. > That's a very large logical jump. If we went back 20 years, you might come across professors and practising engineers who were losing sleep that languages like C/C++ were abstracting the hardware so much that you could just write for loops and be helpless to understand how those for loops were causing needless CPU wait cycles by blocking the cache line. We still teach that stuff. Being an engineer requires understand the whole machine. I'm not talking about mid-level marketroids who are excited that Claude can turn their Excel sheets into PowerPoints. I'm talking about actual engineers who take responsibility for their code. For every helpful suggestion that AI makes, it botches something else. When the AI gives up, where do you turn?
recursivedoubts 9mo ago
AI is extremely dangerous for students and needs to be used intentionally, so I don't blame people for just going to "ban it" when it comes to their kids. Our university is slowly stumbling towards "AI Literacy" being a skill we teach, but, frankly, most faculty here don't have the expertise and students often understand the tools better than teachers. I think there will be a painful adjustment period, I am trying to make it as painless as possible for my students (and sharing my approach and experience with my department) but I am just a lowly instructor.
- softwaredoug 9mo ago
  Honestly defining what to teach is hard People need to learn to do research with LLMs, code with LLMs, how to evaluate artifacts created by AI. They need to learn how agents work at a high level, the limitations on context, that they hallucinate and become sycophantic. How they need guardrails and strict feedback mechanisms if let loose. AI Safety connecting to external systems etc etc. You're right that few high school educators would have any sense of all that.
  - WalterBright 9mo ago
    I don't know anyone who learned arithmetic from a calculator. I do know people who would get egregiously wrong answers from misusing a calculator and insisted it couldn't be wrong.
    - softwaredoug 9mo ago
      Yes but I was also taught to use a calculator, and particular the advanced graphing calculators. Not to mention programming is a meta skill on top of “calculators”
      - nkrisc 9mo ago
        Before I was taught to use a graphing calculator, we learned by using graph paper and a pencil to plot linear equations. Once we had that mastered, we were taught how to use the calculators so we could be more efficient with our time and move on to more complex topics.
subhobroto 9mo ago
> I find, as a parent, when I talk about it at the high school level I get very negative reactions from other parents. Specifically I want high schoolers to be skilled in the use of AI, and particular critical thinking skills around the tools, while simultaneously having skills assuming no AI. I don’t want the school to be blindly “anti AI” as I’m aware it will be a part of the economy our kids are brought into. This is my exact experience as well and I find it frustrating. If current technology is creating an issue for teachers - it's the teachers that need to pivot, not block current technology so they can continue what they are comfortable with. Society typically cares about work getting done and not much about how it got done - for some reason, teachers are so deep into the weeds of the "how", that they seem to forget that if the way to mend roads since 1926 have been to learn how to measure out, mix and lay asphalt patches by hand, in 2026 when there are robots that do that perfectly every-time, they should be teaching humans to complement those robots or do something else entirely. It's possible in the past, that learning how to use an abacus was a critical lesson but once calculators were invented, do we continue with two semesters of abacus? Do we allow calculators into the abacus course? Should the abacus course be scrapped? Will it be a net positive on society to replace the abacus course with something else? "AI" is changing society fundamentally forever and education needs to change fundamentally with it. I am personally betting that humans in the future, outside extreme niches, are generalists and are augmented by specialist agents.
- netsharc 9mo ago
  I'm also for education for AI awareness. A big point on teaching kids about AI should also be a lot about how unreliable they can be. I had a discussion with a recruiter on Friday, and I said I guess the issue with AI vs human is, if you give a human developer who is new to your company tasks, the first few times you'll check their work carefully to make sure the quality is good. After a while you can trust they'll do a good job and be more relaxed. With AI, you can never be sure at any time. Of course a human can also misunderstand the task and hallucinate, but perhaps discussing the issue and the fix before they start coding can alleviate that. You can discuss with an AI as much as you want, but to me, not checking the output would be an insane move... To return to the point, yeah, people will use AI anyway, so why not teach them about the risks. Also LLMs feel like Concorde: it'll get you to where you want to go very quickly, but at tremendous environmental cost (also it's very costly to the wallet, although the companies are now partially subsidizing your use with the hopes of getting you addicted)..

copilot_king 9mo ago

[dead]

libraryofbabel 9mo ago

Not OP, but I would imagine (or hope) that this attitude is far less common amongst peer CS educators. It is so clear that AI tools will be (and are already) a big part of future jobs for CS majors now, both in industry and academia. The best-positioned students will be the ones who can operate these tools effectively but with a critical mindset, while also being able to do without AI as needed (which of course makes them better at directing AI when they do engage it). That said I agree with all your points too: some version of this argument will apply to most white collar jobs now. I just think this is less clear to the general population and it’s much more of a touchy emotional subject, in certain circles. Although I suppose there may be a point to be made about being more slightly cautious about introducing AI at the high school level, versus college.

danaris 9mo ago
> It is so clear that AI tools will be (and are already) a big part of future jobs for CS majors now, both in industry and academia. No, it's not. Nothing around AI past the next few months to a year is clear right now. It's very, very possible that within the next year or two, the bottom falls out of the market for mainstream/commercial LLM services, and then all the Copilot and Claude Code and similar services are going to dry up and blow away. Naturally, that doesn't mean that no one will be using LLMs for coding, given the number of people who have reported their productivity increasing—but it means there won't be a guarantee that, for instance, VS Code will have a first-party integrated solution for it, and that's a must-have for many larger coding shops. None of that is certain, of course! That's the whole point: we don't know what's coming.
- libraryofbabel 9mo ago
  I agree with you that everything is changing and that we don’t know what’s coming, but I think you really have to stretch things to imagine that it’s a likely scenario that AI-assisted coding will “dry up and blow away.” You’ll need to elaborate on that, because I don’t think it’s likely even if the AI investment bubble pops. Remember that inference is not really that expensive. Or do you think that things shift on the demand side somehow?
  - danaris 9mo ago
    I think that even if inference is "not really that expensive", it's not free. I think that Microsoft will not be willing to operate Copilot for free in perpetuity. I think that there has not yet been any meaningful large-scale study showing that it improves performance overall, and there have been some studies showing that it does the opposite, despite individuals' feeling that it helps them. I think that a lot of the hype around AI is that it is going to get better, and if it becomes prohibitively expensive for it to do that (ie, training), and there's no proof that it's helping, and keeping the subscriptions going is a constant money drain, and there's no more drumbeat of "everything must become AI immediately and forever", more and more institutions are going to start dropping it. I think that if the only programmers who are using LLMs to aid their coding are hobbyists, independent contractors, or in small shops where they get to fully dictate their own setups, that's a small enough segment of the programming market that we can say it won't help students to learn that way, because they won't be allowed to code that way in a "real job".
  - LtWorf 9mo ago
    If they start charging what it costs them for example…
    - libraryofbabel 9mo ago
      There is so much confusion on this topic. Please don't spread more of it; the answers are just a quick google away. To spell it out: 1) AI companies make money on the tokens they sell through their APIs. At my company we run Claude Code by buying Claude Sonnet and Opus tokens from AWS Bedrock. AWS and Anthropic make money on those tokens. The unit economics are very good here; estimates are that Anthropic and OpenAI have a gross margin of 40% on selling tokens. 2) Claude Code subscriptions are probably subsidized somewhat on a per token basis, for strategic reasons (Anthropic wants to capture the market). Although even this is complicated, as the usage distribution is such that Anthropic is making money on some subscribers and then subsidizing the ultra-heavy-usage vibe coders who max out their subscriptions. If they lowered the cap, most people with subscriptions would still not max out and they could start making money, but they'd probably upset a lot of the loudest ultra-heavy-usage influencer-types. 3) The biggest cost AI companies have is training new models. That is the reason AI companies are not net profitable. But that's a completely separate set of questions from what inference costs, which is what matters here.
hackyhacky 9mo ago
> It is so clear that AI tools will be (and are already) a big part of future jobs for CS majors now, That's true, but you can't use AI in coding effectively if you don't know how to code. The risk is that students will complete an undergraduate CS degree, become very proficient in using AI, but won't know how to write for loop on their own. Which means they'll be helpless to interpret AI's output or to jump in when the AI produces suboptimal results. My take: learning to use AI is not hard. They can do that on their own. Learning programming is hard, and relying on AI will only make it harder.
- subhobroto 9mo ago
  > My take: learning to use AI is not hard. They can do that on their own. Learning programming is hard, and relying on AI will only make it harder Depends on what your definition of "hard" is - I routinely come across engineers who are frustrated that "AI" hallucinates. Humans can detect hallucinations and I have specific process to detect and address them. I wouldn't call those processes easy - I would say it's as hard as learning how to do integration by summing. > but you can't use AI in coding effectively if you don't know how to code Depends on the LLM. I have a fine-tuned version of Qwen3-Coder where if you ask it to show you to compare to strings in C/C++, it will but then it will also suggest you look at a version that takes unicode into account. I have stumbled across very few software engineers who even know what unicode codepoints are and why legacy ASCII string comparison fails. > but won't know how to write for loop on their own. Which means they'll be helpless to interpret AI's output or to jump in when the AI produces suboptimal results That's a very large logical jump. If we went back 20 years, you might come across professors and practising engineers who were losing sleep that languages like C/C++ were abstracting the hardware so much that you could just write for loops and be helpless to understand how those for loops were causing needless CPU wait cycles by blocking the cache line.
  - hackyhacky 9mo ago
    > Depends on what your definition of "hard" is - I routinely come across engineers who are frustrated that "AI" hallucinates. Humans can detect hallucinations and I have specific process to detect and address them. I wouldn't call those processes easy - I would say it's as hard as learning how to do integration by summing. My students don't seem to have a problem using AI: it's quite adequate to the task of completing their homework for them. I therefore don't feel a need to complete my buzzword bingo by promoting an "AI-first classroom." The concern is what they'll do when they find problems more challenging than their homework. > I have stumbled across very few software engineers who even know what unicode codepoints are and why legacy ASCII string comparison fails. You are proving my point. If the programmer doesn't know what Unicode is, then the AI's helpful suggestion is likely to be ignored. You need to know enough to be able to make sense of the AI beyond a superficial measure. > That's a very large logical jump. If we went back 20 years, you might come across professors and practising engineers who were losing sleep that languages like C/C++ were abstracting the hardware so much that you could just write for loops and be helpless to understand how those for loops were causing needless CPU wait cycles by blocking the cache line. We still teach that stuff. Being an engineer requires understand the whole machine. I'm not talking about mid-level marketroids who are excited that Claude can turn their Excel sheets into PowerPoints. I'm talking about actual engineers who take responsibility for their code. For every helpful suggestion that AI makes, it botches something else. When the AI gives up, where do you turn?

recursivedoubts 9mo ago

AI is extremely dangerous for students and needs to be used intentionally, so I don't blame people for just going to "ban it" when it comes to their kids. Our university is slowly stumbling towards "AI Literacy" being a skill we teach, but, frankly, most faculty here don't have the expertise and students often understand the tools better than teachers. I think there will be a painful adjustment period, I am trying to make it as painless as possible for my students (and sharing my approach and experience with my department) but I am just a lowly instructor.

softwaredoug 9mo ago
Honestly defining what to teach is hard People need to learn to do research with LLMs, code with LLMs, how to evaluate artifacts created by AI. They need to learn how agents work at a high level, the limitations on context, that they hallucinate and become sycophantic. How they need guardrails and strict feedback mechanisms if let loose. AI Safety connecting to external systems etc etc. You're right that few high school educators would have any sense of all that.
- WalterBright 9mo ago
  I don't know anyone who learned arithmetic from a calculator. I do know people who would get egregiously wrong answers from misusing a calculator and insisted it couldn't be wrong.
  - softwaredoug 9mo ago
    Yes but I was also taught to use a calculator, and particular the advanced graphing calculators. Not to mention programming is a meta skill on top of “calculators”
    - nkrisc 9mo ago
      Before I was taught to use a graphing calculator, we learned by using graph paper and a pencil to plot linear equations. Once we had that mastered, we were taught how to use the calculators so we could be more efficient with our time and move on to more complex topics.

subhobroto 9mo ago

> I find, as a parent, when I talk about it at the high school level I get very negative reactions from other parents. Specifically I want high schoolers to be skilled in the use of AI, and particular critical thinking skills around the tools, while simultaneously having skills assuming no AI. I don’t want the school to be blindly “anti AI” as I’m aware it will be a part of the economy our kids are brought into. This is my exact experience as well and I find it frustrating. If current technology is creating an issue for teachers - it's the teachers that need to pivot, not block current technology so they can continue what they are comfortable with. Society typically cares about work getting done and not much about how it got done - for some reason, teachers are so deep into the weeds of the "how", that they seem to forget that if the way to mend roads since 1926 have been to learn how to measure out, mix and lay asphalt patches by hand, in 2026 when there are robots that do that perfectly every-time, they should be teaching humans to complement those robots or do something else entirely. It's possible in the past, that learning how to use an abacus was a critical lesson but once calculators were invented, do we continue with two semesters of abacus? Do we allow calculators into the abacus course? Should the abacus course be scrapped? Will it be a net positive on society to replace the abacus course with something else? "AI" is changing society fundamentally forever and education needs to change fundamentally with it. I am personally betting that humans in the future, outside extreme niches, are generalists and are augmented by specialist agents.

netsharc 9mo ago
I'm also for education for AI awareness. A big point on teaching kids about AI should also be a lot about how unreliable they can be. I had a discussion with a recruiter on Friday, and I said I guess the issue with AI vs human is, if you give a human developer who is new to your company tasks, the first few times you'll check their work carefully to make sure the quality is good. After a while you can trust they'll do a good job and be more relaxed. With AI, you can never be sure at any time. Of course a human can also misunderstand the task and hallucinate, but perhaps discussing the issue and the fix before they start coding can alleviate that. You can discuss with an AI as much as you want, but to me, not checking the output would be an insane move... To return to the point, yeah, people will use AI anyway, so why not teach them about the risks. Also LLMs feel like Concorde: it'll get you to where you want to go very quickly, but at tremendous environmental cost (also it's very costly to the wallet, although the companies are now partially subsidizing your use with the hopes of getting you addicted)..