I don’t know if I agree with you because someone still needs to tell an LLM what the project is for it to work and a normal person who has no science or computer science background can’t do that efficiently or check the technical aspects of a project to make sure the AI isn’t doing something incorrectly (and eventually the AI will do something incorrectly usually). I think we need UBI sooner rather than later because so many jobs will be obsolete, but if I’m chatting with an LLM or you are and we say “is the docker container up?” or “you built a page and there’s no clear way to navigate it” or “test for what would be exposed data in the case of a breach” the AI can do that, but a normal person doesn’t even understand any of that stuff to chat with an AI about that. I know it’s awful right now for coders who are getting paid less or are underemployed, but that seems to be more of a UBI problem instead of an LLM problem. There are legitimate environmental fears however, but LLMs and data centers seem to be a cherry on top of egregious environmental policy. Environmental catastrophe is headed this way with or without the cherry and it’s not clear to me if we had good universal public transportation and banned gasoline that somehow data centers would still be an existential human risk.
I think the problem is that decision makers /people in power often don’t understand the technical jargon either. All that matters is, “is it working?” So once they see that they can get it “working” without paying for the expertise, they will take it.
The thing is also - the LLM will eventually get it wrong, but the frontier models are pretty good at fixing it if you can articulate the problem. Even non technically.
Under the hood? Impossible to understand. But it works!
Counterpoint - system architecture is really built around helping humans to build mental models of systems. If your plan is to have LLMs to all the work in the future, those mental models no longer matter the way they did in the past.
Probably, systems will break, and LLM costs will rise, and the arithmetic will shift - but that isn’t happening fast enough to stop the brain drain and negative pressure on employment and compensation.
I don’t know if I agree with you because someone still needs to tell an LLM what the project is for it to work and a normal person who has no science or computer science background can’t do that efficiently or check the technical aspects of a project to make sure the AI isn’t doing something incorrectly (and eventually the AI will do something incorrectly usually). I think we need UBI sooner rather than later because so many jobs will be obsolete, but if I’m chatting with an LLM or you are and we say “is the docker container up?” or “you built a page and there’s no clear way to navigate it” or “test for what would be exposed data in the case of a breach” the AI can do that, but a normal person doesn’t even understand any of that stuff to chat with an AI about that. I know it’s awful right now for coders who are getting paid less or are underemployed, but that seems to be more of a UBI problem instead of an LLM problem. There are legitimate environmental fears however, but LLMs and data centers seem to be a cherry on top of egregious environmental policy. Environmental catastrophe is headed this way with or without the cherry and it’s not clear to me if we had good universal public transportation and banned gasoline that somehow data centers would still be an existential human risk.
I think the problem is that decision makers /people in power often don’t understand the technical jargon either. All that matters is, “is it working?” So once they see that they can get it “working” without paying for the expertise, they will take it.
The thing is also - the LLM will eventually get it wrong, but the frontier models are pretty good at fixing it if you can articulate the problem. Even non technically.
Under the hood? Impossible to understand. But it works!
Counterpoint - system architecture is really built around helping humans to build mental models of systems. If your plan is to have LLMs to all the work in the future, those mental models no longer matter the way they did in the past.
Probably, systems will break, and LLM costs will rise, and the arithmetic will shift - but that isn’t happening fast enough to stop the brain drain and negative pressure on employment and compensation.
I agree about the risk of brain drain with fewer people learning to code.