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You are going through your studies just as a (potentially major) new class of tools is appearing. It's not the first time in history - although with more hype this time: computing, personal computing, globalisation, smart phones, chinese engineering... I'd suggest (1) you still need to understand your field, (2) you might as well try and figure out where this new class of tools is useful for your field. Otherwise... (3) carry on.

It's not encouraging from the point of view of studying hard but the evolution of work the past 40 years seems to show that your field probably won't be your field quite exactly in just a few years. Not because your field will have been made irrelevant but because you will have moved on. Most likely that will be fine, you will learn more as you go, hopefully moving from one relevant job to the next very different but still relevant job. Or straight out of school you will work in very multi-disciplinary jobs anyway where it will seem not much of what you studied matters (it will but not in obvious ways.)

Certainly if you were headed into a very specific job which seems obviously automatable right now (as opposed to one where the tools will be useful), don't do THAT. Like, don't train as a typist as the core of your job in the middle of the personal computer revolution, or don't specialize in hand-drawing IC layouts in the middle of the CAD revolution unless you have a very specific plan (court reporting? DRAM?)

Yes but it’s different this time. LLMs are a general solution to the automation of anything that can be controlled by a computer. You can’t just move from drawing ICs to CAD, because the AI can do that too. AI can write code. It can do management. It can even do diplomacy. What it can’t do on its own are the things computers can’t control yet. It has also shown little interest so far in jockying for social status. The AI labs are trying their hardest to at least keep the politics around for humans to do, so you have that to look forward to.
"The proof is trivial and left as an exercise for the reader."

The technical act of solving well-defined problems has traditionally been considered the easy part. The role of a technical expert has always been asking the right questions and figuring out the exact problem you want to solve.

As long as AI just solves problems, there is room for experts with the right combination of technical and domain skills. If we ever reach the point where AI takes the initiative and makes human experts obsolete, you will have far bigger problems than career.

That's the sort of thing ideas guys think. I came up with a novel idea once, called Actually Portable Executable: https://justine.lol/ape.html It took me a couple days studying binary formats to realize it's possible to compile binaries that run on Linux/Mac/Windows/BSD. But it took me years of effort to make the idea actually happen, since it needed a new C library to work. I can tell you it wasn't "asking questions" that organized five million lines of code. Now with these agents everyone who has an idea will be able to will it into reality like I did, except in much less time. And since everyone has lots of ideas, and usually dislike the ideas of others, we're all going to have our own individualized realities where everything gets built the way we want it to be.
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AI being capable of doing anything doesn’t necessarily mean there will be no role for humans.

One thing that isn’t clear is how much agency AGI will have (or how much we’ll want it to have). We humans have our agency biologically programmed in—go forth and multiply and all that.

But the fact that an AI can theoretically do any task doesn’t mean it’s actually going to do it, or do anything at all for that matter, without some human telling it in detail what to do. The bull case for humans is that many jobs just transition seamlessly to a human driving an AI to accomplish similar goals with a much higher level of productivity.

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I hear what you are saying. And still I dispute "general solution".

I argue that CAD was a general solution - which still demanded people who knew what they wanted and what they were doing. You can screw around with excellent tools for a long time if you don't know what you are doing. The tool will give you a solution - to the problem that you mis-stated.

I argue that globalisation was a general solution. And it still demanded people who knew what they were doing to direct their minions in far flung countries.

I argue that the purpose of an education is not to learn a specific programming language (for example). It's to gain some understanding of what's going on (in computing), (in engineering), (in business), (in politics). This understanding is portable and durable.

You can do THAT - gain some understanding - and that is portable. I don't contest that if broader AGI is achieved for cheap soon, the changes won't be larger than that from globalisation. If the AGIs prioritize heading to Mars, let them (See Accelerando) - they are not relevant to you anymore. Or trade between them and the humans. Use your beginning of an understanding of the world (gained through this education) to find something else to do. Same as if you started work 2 years ago and want to switch jobs. Some jobs WILL have disappeared (pool typist). Others will use the AGIs as tools because the AGIs don't care or are too clueless about THAT field. I have no idea which fields will end up with clueless AGIs. There is no lack of cluelessness in the world. Plenty to go around even with AGIs. A self-respecting AGI will have priorities.

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That’s ridiculous. Literally everything can be controlled by a computer by telling people what to do with emails, voice calls, etc.

Yet GPT doesn’t even get past step 1 of doing something unprompted in the first place. I’ll become worried when it does something as simple as deciding to start a small business and actually does the work.

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Real-world data collection is a big missing component at this stage. An obvious one is journalism where an AI might be able to write the most eloquent article in the world, but it can't get out on the street to collect the information. But it also applies to other areas, like if you ask an AGI to solve climate change, it'll need accurate data to come up with an accurate plan.

Of course it's also yet another case where the AI takes over the creative part and leaves us with the mundane part...

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