你不能把所有细节都交出去。你能做的是交出其中的一部分,但要在某件事上做得好,就必须知道,或者能够算出,交出的是哪一部分。如果你不擅长,你不会知道。因此,本质上,没有自身对某件事的精通,就不可能靠 AI 做得好,而要想最初就精通这件事,需要彻底颠倒那种想把它交出去的思维方式。对细节极度感兴趣并专注,是建立专业知识的唯一途径。
I think behind a lot of the enthusiasm around AI is a dream of being able to manifest things into reality without having to get into the details.
But you cannot escape the details. There's no level of abstraction that solves this. The closer you look at anything, the messier and more nuanced it gets. You've got to get deep, you've got to get meticulous, to do anything novel or good.
You can't hand off all of the details. What you can do is hand off some of them, but to be good at something is to know, or be able to work out, which 'some'. If you aren't good, you won't know. So inherently you can't do something well with AI without being good at the thing yourself, and to become good at the thing in the first place requires a complete reversal of the mindset that would lead one to having wanted to hand it off. Being incredibly interested in and focused on the details is the only way expertise develops.
Many are captured with the idea of how reality might be if one could be good at things without caring about the details, and are enthusiastic about LLM technology because it seems like a more credible way to get there than all the previous technologies that promised to bring this reality about. But LLMs, too, will fail in this because reality doesn't work that way, and there's no reason it should.
It's not a good thing to not have the knowledge or skill to do something, and it's not empowering to hand off the details. The extent to which that can be successful is the extent to which you have played no role; have done nothing at all. Which is the precise opposite of empowerment.