it’s getting to the point where I notice people say it a lot, especially IRL now for whatever reason recently.

And for clarity I’m not in research or anything, so these people just mean ‘LLM/image gen’, not utilities like OCR or (usually not) transcription.

Some have argued it’s just more efficient (which I can kind of get), while others think you’re actively hindering your intelligence somehow.

On the first point:

I’ve tried it occasionally to see how it compares to my own skill, and while it produces a functional result, it’s always very derivative work to the point where you can find things with the exact same names of other ‘public’ (but not libre) works, and often isn’t the ideal solution to what it targets. So I can see how you can get things out of it, but it never felt really that profound to me.

But for the second… isn’t this supposed to be the tool for people to do things they aren’t experienced in? If anything, you probably need to be able to understand how to write pertaining to the task so the token probabilities are biased toward writing from that area.

And even then, if all you end up doing is prompting AI, then wouldn’t you ultimately serve no purpose outside of being glorified QA?

I guess I’m trying to figure out what exactly non-users would be ‘falling behind’ in that affects them more than those who use AI?

  • Dogyote@slrpnk.net
    34·
    1 month ago

    I think about it like this: let’s say you don’t use AI but a majority of other people do. Let’s assume AI helps the majority do things faster or cheaper than you (maybe that’s not true yet, but it will probably be true soon). In this situation, if you’re not using AI then you’ll almost always lose to those that are. Therefore you should learn how to use it or else you’ll be left behind.

      • Dogyote@slrpnk.net
        2·
        1 month ago

        The information in your link is about school aged children, and it doesn’t say AI use automatically makes you dumber. It says:

        The relationship between AI use and student performance is complex How AI use relates to student performance is complex, varying with how students use it and what for. PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores in science than students who do not use AI. In these scenarios, students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schooling ahead of their peers. However, weekly users of AI for general purposes have similar performance outcomes to non-users. Students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly higher scores in science. However, these opportunities are more common among socio-economically advantaged students, risking a growing AI divide.

        So I’d conclude that kids shouldn’t be handed AI when they’re young. Not only that, they shouldn’t get to use it until they’re taught how.

        I have a young kid and I don’t know what to do. I’m leaning towards keeping them away from AI as long as possible in the hopes that they build a very strong knowledge and problem solving foundation. Then AI can hopefully multiply their abilities.

        And that brings me back to my original point. It will likely provide a competitive advantage to those that use it over those that don’t, but the size of that advantage depends on the abilities of the user.