I’m curious if someone coming into that fresh, without having had the mental exercise of, for example, grappling with data structures and (lower-level) algorithms in practical applications by hand, could achieve a mindset that useful and productive?

When I was in design school, as much of our work was in physical media — graphite, cut paper, paint, vine charcoal — as was practicing great kerning and getting experience with the digital tools. Even though you still had to make the individual strokes and choose appropriate tools in the digital realm, there was still a perception of the process that was obviously lacking among those that came from strictly digital backgrounds. It’s similar to seeing someone who’s only worked with photo references try life drawing — there’s an entire part of the cognitive process not being used when you’re drawing something that’s already 2D. Sure, they can learn, but unless they’re forced to, they’ll probably just keep taking a picture and drawing that. But image generating, even with extremely granular inpainting and such, is so different it’s not even comparable. I’d hesitate to say that someone with a lot of experience doing very advanced image generation would be dramatically further along than a complete beginner if they learned to draw which is not true of the photo reference artist, and even less true of a purely digital artist that did life drawing on a tablet.

Kind of like how millennials, many of whom always had access to technology, but also experienced dial-up-era computer use, are generally more technically savvy than the your stereotypical “iPad kid” that can’t even traverse a directory structure.

The question is what higher level skills there will be to focus on?

I am not convinced that there are tasks, like project management or architecture, that the Ai is inherently worse at.

>But maybe I've also been able to spend more time on a higher level skill? Maybe the doctors got worse with the images but had more cognitive resources to think about the patient's context?

That's not the way the economics behind this work.

Supposing the AI priests are right (they aren't) and using AI creates a thought surplus on the user, freeing cognitive capacity to think of higher things. What do you think will said user's boss want to do with that surplus? Let the user develop higher-level cognitive abilities? I don't think so.

The doctors in the article performed worse post-AI: suppose AI saved them so much time that they did 100 exams in the time they used to take doing 10 exams. What will their employers do with that freed up labour time? They'll of course have the doctors do more exams and perhaps fire some now-redundant doctors that are no longer needed. The surviving doctors are left deskilled, doing the same or more work, and society gets worse quality medical care. But hey, its not all bad - the employer gets to save on labour, and shareholders will be happy.

In the eyes of many ceo’s, you are slowly becoming useless.

We never learned how to use IBM punch cards. Writing functions by hand for modern languages is fast becoming anachronistic.

You’re fucked once you have to start getting AI to produce code for languages you’ve never actually worked in.

You will have to write code to understand deeply what goes on at the low level. Without a solid understanding of the low level, you won’t truly know what optimal solutions look like on a high level. You will be flying by the seat of your pants, churning out code that works but has bad low level quirks sprinkled through the code base. The AI will say it’s fine, but you’re just building up shitty software. Feels like shit, run likes shit.

Once someone new comes along who has worked with the language manually and can get AI to produce effective high quality code, you’ve lost competitive advantage. They can build way better versions of whatever you do. You’re finished. You’re a low quality engineer.