Comment by simianwords
11 hours ago
I can't tell what specialists we will get the same way you wouldn't be able to tell me we will have Linux Kernel specialists at the year 1945.
People do more things with AI.
More things = more inventions = the field growing.
The field grows and people become specialists on what used to be a small or trivial.
A mathematician in 1500's wouldn't think algebraic topology would be a specialisation.
> I can't tell what specialists we will get the same way you wouldn't be able to tell me we will have Linux Kernel specialists at the year 1945.
How about addressing astrophysics specifically. What are you claiming about it? Are you claiming that in the future, we won't need astrophysicists at all, AI can do all of our astrophysics for us, freeing humans to specialize in... other subjects?
And doesn't the same problem exist for Linux kernel specialists? Why even become a Linux kernel specialists when AI can write your source code for you?
> people become specialists
This is precisely what is in question.
> A mathematician in 1500's wouldn't think algebraic topology would be a specialisation.
The specific subjects have changed over time, but the production of specialist mathematicians hasn't really changed. It takes hard work, grunt work, struggling, making mistakes and learning from them, as well as expert supervision. The problem with AI is that it encourages and incentivizes intellectual laziness, the opposite of what is required to produce specialists.
A related problem: LLMs have been trained with papers written and supervised by Alice-type specialists. There's a common claim that LLMs will hallucinate less in the future, but I think that LLMs will hallucinate more in the future, when specialty fields become dominated by Bob-type "specialists" who have a harder time distinguishing fact from fiction. When LLMs have to train on material produced by earlier versions of LLMs, the quality trend will go down, not up.
> The specific subjects have changed over time, but the production of specialist mathematicians hasn't really changed. It takes hard work, grunt work, struggling, making mistakes and learning from them, as well as expert supervision. The problem with AI is that it encourages and incentivizes intellectual laziness, the opposite of what is required to produce specialists
Let's take the example of economics. Economists use ideas in Mathematics like integrals, statistics, PDE's and so on. They know that these concepts exist. They know how to apply them. They don't know these concepts deep enough to make progress here.
Do you think that Economists should deeply learn integrals, PDE's, Functional Analysis and Differential Geometry and all other concepts they use? Or do you think its better for them to focus just on their specific domain while learning just enough from other domains?
You keep coming back to AI replacing mathematicians. I'm not making that claim. I'm not saying Linux kernel specialists will be replaced by AI. I'm simply claiming that not everyone needs to be Linux Kernel specialists. This is precisely what AI is allowing: it automates things I don't need to know deeply so that I can focus on things I do need to understand deeply.
> I'm simply claiming that not everyone needs to be Linux Kernel specialists.
This is an uninteresting and indeed silly claim, because nobody has ever asserted the opposite.
The point is that society needs some Linux kernel specialists, and some astrophysicists, but AI is undermining their production.
> This is precisely what AI is allowing: it automates things I don't need to know deeply so that I can focus on things I do need to understand deeply.
The submitted article is about how AI is automating the things that a specialist does need to understand deeply. It's about so-called astrophysicists using AI to produce astrophysics papers, not about how non-astrophysicists use AI to produce astrophysics papers so that they can focus on whatever their non-astrophysics specialty may be, if they have any specialty.
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