> Let the students use the AI tools they like […], but test regularly and early on the skills/knowledge they're meant to be gaining offline and in person. I very much doubt there is any agreement on what those skills are. Creating the idea of “what to learn in the new world” is itself IMO an important academic creation, but there’s no reward for doing it and no way to know if you’re on the right track (you just have to wait and see). Employers are also just adapting. Wait until companies are paying unsubsidized “list price” for LLM usage. Then we can have a better idea of the worth of the automation and what skills should stay with humans.

Yeah, I'm 45 and I'm like you - no social media, relatively under connected, and still feel swamped constantly by emails and calls and especially texts. They eat up half my productive time every day, and most of them are things I'm looped in on that I don't even need to respond to. Okay so let's say that's the new cognitive burden. The new escape hatch is "AI". Now you don't need to read your mail or write responses! Let an LLM handle that for you! And now your friends and coworkers will send you AI generated mail anyway, so if you're actually taking the time to read and respond to it yourself you're a chump, right? Noise machines. Humans are noise machines. Ever try to sleep till noon and notice that everyone else seems like they can't feel alive unless they wake up and make the maximum amount of noise and racket possible? What could be better for a gibbering species of ground dwelling apes than a miraculous machine that gibbers for them, to point back and forth at each other?

Same, but also because it feels like it takes longer for an LLM to do it. I think that's something people who are into gathering personal metrics should do - measure how long it takes to type a prompt / have the LLM fix things vs just doing it yourself.

You're right. But I like to add artwork to my presentations. My artistic skills have not advanced beyond 2nd grade. So I'll make a line sketch, and give to AI to "fix" it. The results are nice and I use them. I have no interest in learning how to do art well myself, so using AI for it is appropriate. But I still write my code myself.

At this rate humans will become avatars remotely controlled by LLMs. Ironic conclusion of the consciousness debate.

> which you can only obtain by having a strong CS base and coding manually for years. I hope this isn’t the case. It is the route I took, but it also doesn’t seem to be a likely route going forward. Strong CS grounding is feasible for sure, but I have a hard time believing that a meaningful number of people will be spending the requisite years coding manually.

I keep trying to convince people that English majors and Philosophy majors will benefit the most from LLMs. English majors in particular, have been trained to be VERY exact in how they word things. That awareness of how to structure the English language, it will benefit those who use LLMs. Then again, maybe someone will just make a LLM that’s built to turn poor English and poor reasoning into excellent English and excellent reasoning. Maybe this is just a technical puzzle that needs solving.

I disagree with you, for the very reason you give: > Then again, maybe someone will just make a LLM that’s built to turn poor English... into excellent English That's already been done, for some (pretty weird) definition of "excellent". I work with, or at least in the vicinity of, someone who is very good at getting work out of LLMs. He has a whole system of CLAUDE.md files and skill files and things. He makes TONS of typos. When I first saw that, I was itching to go in and fix them all, it seemed viscerally wrong to be adding an extra layer of correction required between the instructions and the LLM's behavior. But in practice, I don't think it mattered at all. The LLM didn't care. Typos in particular might require a bunch of RLHF in the chatbot, but my hypothesis is that the LLM is already mapping messy human input to the nearest surface of some high-dimensional manifold and the added noise of typos is inconsequential to where it ends up (as long as there isn't any real ambiguity -- though even there, you could probably construct cases where that would help rather than hurt!) Typos are different from sloppy writing, but I think the AI companies have put a lot of work into training these chatbots on dealing with typical non-English major writing with all of its imprecision. Also, it's easier to construct cases where that imprecision and sloppiness would help rather than hurt: a mistake in the input that is common enough to show up in the training data is going to be a good match for the needed correction as well as associated corrections. The precise language could easily result in the LLM overestimating the user's competence. That doesn't address whether an English major's careful composition would help for hard tasks where getting the specification right really matters -- perhaps that was your point? I guess it's an open question whether "boiling away the typos" and "boiling away a poorly articulated specification" are related enough.

Isn't the fun part having the thing work how you wanted it to? Why shouldn't I be keen to automate the process away?

different strokes for different folks. I'm def. in that end result camp, i get the biggest thrill out of seeing something work. For me, coding agents are awesome because i can bring a lot more to life in much shorter of a time frame. I do enjoy the process and problem solving of coding, it relaxes me. On the other hand, i really really enjoy when an idea i have is on the screen and working.

I'd argue that this is an adjustment period that society has to go through. The way we are using electronic devices today, in some years it will probably be looked at like smoking cigarettes. And I'd argue that a lot of the "decline" is due to a shift of skills away from things that mattered more in the past toward other things that are not measured/perceived by the older generation.

Interesting analogy. I believe regarding addictiveness they may be compared. > a shift of skills away from things that mattered more in the past toward other things that are not measured/perceived by the older generation. Do you have any ideas what these things might be? As someone in his twenties, I’m sometimes saddened by observing that some of the skills I acquired over a long time (e.g., writing, coding) may become obsolete or won’t be respected anymore just now that I‘m finally getting good at them.

it happens, things change and the change is only speeding up. I think the real skill to have going forward is the ability to acquire new skills. I tell my boys "get good at learning and you don't have to get good at anything else".

Thinking is the skill that becomes obsolete.

Ages ago I had similar thoughts. Everything changed when I came to terms with the concept of change being the only constant. A bit of a cliché, perhaps, but profoundly true.

Or when the Internet came and made memory kinda obsolete. Why remember facts if you can simply index them and then lookup on demand. But now we delegate thinking itself, so I wonder what is left.

This is an age-old argument actually, the same one was raised when the printing press was invented and reading became a more generally available skill.

There’s the saying that we overestimate what we can achieve in the short term, but underestimate what we can achieve in the long term. Optimizing for the short term is therefore counterproductive if it impairs us for the long term.

“ But I think the overall creativity and originality is a lot lower. Therein lies the trade off. Your implicit gamble is that you expect machines to continue to get better in the future. What if they don’t?

To me it is crazy that you are being downvoted. My experience in academia was that an incredible amount of time was devoted to data cleansing analysis, coding, etc., which were completely non-core to the actual underlying academic pursuit.

>Now I work mostly with PhDs who were at the top of every academic environment they've ever been in. And yet I can see their thinking skills rapidly declining as well; tomorrow most regular people's thinking skills will definitely be weaker than those of the LLMs of tomorrow. And physical skills in most cases will be weaker than those of the robots. That leads to the question - what would most people do?

I feel the opposite. My brainstorming has increased rapidly. I can now just throw ideas at an LLM to rapidly validate.

Using AI to inform architecture doesn’t seem so different from googling architecture in this case. Architectural patterns are mostly well understood and well documented these days and are something that you could piece together via Google search pre AI. The thing that AI brings to the table that wasn’t google able in the past is code generation. Previously you had to understand the architecture patterns to implement them yourself, but now the AI can just do it for you.

It's incredibly difficult at this point to "skate where the puck is going" as Gretzky is said to have done. No one knows what knowledge work will look like in five years. People used to memorize log and trig tables, and no one would say that's part of being a competent mathematician at this point. That said, assessments of poor critical thinking skills jump out at me more than the rest. That sort of thing seems likely to matter until machines can replace us completely.

This goes with calculator to do basic math, contacts apps to store phone numbers instead of remembering them, and watches to tell time imo. Sure we could use our brain power with old techniques to do these, but why? I don't want to do any of these. I'd rather use that brain power for other problems. Same with maps. I don't want to have to store a bunch of location or routing data in my head. I think what you're pointing towards is going from having problems to solve to not having any problems to solve. That's definitely a danger, but right now is still early in the AI era so obviously it'll feel like we went from solving problems to letting the new tool solve them for us. There are still many problems to solve.

Build one myself and make a ton of money. Or wait for the next guy/company to do it.

You are not storing these things in your head at the expense of anything else. You’re “training” the existing underutilized capacity in your brain for something useful.

The exams need to change. Now that we have LLMs the value a human can bring to a task has changed and it’s that new value that has to be tested. It’s like testing your drawing ability in a photography class. The difference is that now nearly have subject and testing method we have has become obsolete. Drawings courses still exist as will traditional courses, but the main stream has changed and exams and schools need to adapt.

It's not just 'a person' or 'a student', we as a collective become more dumb. Very simple example to highlight this: Most developers use(d?) stackoverflow. Everything related to software development is stored there. The LLM's trained on it. Now a huge set of developers now longer go to stackoverflow to get answers. Or add to the collective. Stackoverflow is losing money (ad revenue). If / when stackoverflow goes away we will lose a huge amount of collective information on software development. We, as a group, will take a huge step back.

So is dead and has been for some time. 1500 questions per month. https://data.stackexchange.com/stackoverflow/query/1926661

I really wonder if it's important to learn all that low-level stuff at this point. Most programmers today will never write a binary tree or a hash table. Modern high-performance ones are generic components you get from libraries. Even MIT gave up on teaching from Structure and Interpretation of Computer Programs. I got all that stuff. I've wired up a 4-bit adder on a solderless breadboard for an architecture class. I used to have a well-thumbed copy of Knuth handy. I've designed and built a switching power supply. But I'm not up to date on using Claude Code, and should be.

IMHO, I think it's good to have some exposure to low-level stuff. There's a good amount of work you can't do without understanding the low-level stuff, but there's more work you can't do well without having at least an idea of the low-level stuff. Start the kids off with high level stuff, but make them do some embedded systems on their way through. At least for an engineering degree. Also, do a bit of lower level communications somewhere in there; expose them to tcpdump/ wireshark, but they need not develop expertise.

I will add, too, although less relevant to education than just generally - for all the talk that these tools must be useless and incorrect, that just plainly does not map to my experience using these tools. AI can chew through a debug log on a custom system and pick out root causes on behaviors very effectively, in my experience. It is just hard to reconcile that denigration of AI with the typical experience I have using these tools in the real world. It is not omnipotent or God, but it can effectively assist in work. There is a certain cognitive dissonance I feel when I walk away from using the tool to help accomplish particular tasks, then hear over and over people say the technology is fundamentally useless and fundamentally does not work. I guess I am just not enough of an academic to understand how something can accomplish work yet fundamentally isn't, somehow.

A reckoning is coming for school. Learning the rote stuff is no longer essential. Now they need to learn, how to teach "how to think". How to invent, how to be creative. Art++, Woodshop++, Math--

Probably not a bad thing, the coursework is antiquated and meeting students with new advanced tools and the awareness of AI's impact on things in the coming future I imagine there is some apathy and laziness here but idk how unjustified it is "Noooooo you need to manually code on paper in assembly" Alright, well maybe the CS grads need to, but why expect that of everyone else