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?
They (pretend to) believe, either due to experience or marketing or a combination, that AI* will be such a ubiquitous tool within their lifetime that “not using AI” would be like “not using electricity”. There are people that do not use electricity, even when it is available, today, but they are broadly considered “behind” the times and out of touch with broader (including global) society. AI advocates are unlikely to always have the same idea about exactly what the advantages are, though speed is often among them.
The actual scientific studies we have done are limited, but so far do not back up these claims. For example, AI assisted programmers self-report being faster, but are actually slower at the same tasks than a similar cohort without AI.
I have a fairly strong anti-AI bias, but my limited experiences with them have been quite poor. Maybe I’m just asking the “wrong” questions, but my experiences have had them either give an response that is internally inconsistent, contains easily refuted factual inaccuracies, or (for tasks with no reality/logic testing) absolutely the least creative, most middle-of-the-road text. I’m also aware of the human rights abuses that Amnesty International has reported around generative AI, the copyright “minefield” around models where you do not know all of the training data, and how we’ve lost at least a decade of sustainability goals because of the desire for “more compute”.
So, keep my bias in mind when considering my reply. I might already be “falling behind”.
I can think of some ways to use an LLM that are interesting to me, but for now I’m staying away from the tech until the bubble bursts and the hype disappears. It’ll be easier to make informed decisions about what, if any, to use then.
(If it really does improve society, I’m sure I can be retrained then, or at least I can be taken care of one AI-incompatibility is recognized as a disability. /s)
AI: They probably can’t define this term, but likely to have a specific product in mind.