GeneralGenerative AI can be summarized as “quantity over quallity”Which fully explains why CEOs and middle managers love it more than anyone.
I think you mean “generative”. If so, you are entirely accurate in your description.
I meant AI as a normal person would know it today.
That would then be ‘generative’. It’s important to note the concept of “general AI” exists and it means a machine that can actually think and reason (for example, humans have “general intelligence”). The “AI” that exists today is called “generative” because it doesn’t actually think, it just generates information based off of extremely large quantities of data and gives the impression of thinking/understanding what it outputs, but it does not.
Ah, I didn’t consider that, I’ll update my post.
One might call it sloppy, even
That’s what we’re seeing all over the place - you get more work done, but then other people have to fix or error-check your work, slowing them down.
So all the individual workers get more work done, but the organisation doesn’t get more work done.
Actually, what I have seen all over the places is people reviewing my manuscripts by passing them to chatgpt and sending revision requests without even reading the article.
It happened to me being asked to do a major review because I was not describing enough in detail how I trained LLM models in my research; my research was not about LLMs and never mentioned LLMs anywhere.
I tend to distrust studies entirely based on models. Modelling is good, but you should use it together with some substantive experimental data.
When LLMs help researchers quickly identify the best projects, as in some technical fields, researchers will become more discriminating about which projects they develop. On the other hand, if LLMs mostly accelerate writing and analysis, as in fieldwork-based disciplines, the fraction of investigations that are published may increase.
Ok, do we have any evidence of which of the two phenomena is actually happening at the moment?
Research has always been full of people publishing a lot of trash. If anything this should lead to changing the incentives for researchers, such as not evaluating them on the publication count. Not really on demonizing LLM use in a research setting.