- cross-posted to:
- technology@lemmy.ml
- cross-posted to:
- technology@lemmy.ml
The new global study, in partnership with The Upwork Research Institute, interviewed 2,500 global C-suite executives, full-time employees and freelancers. Results show that the optimistic expectations about AI’s impact are not aligning with the reality faced by many employees. The study identifies a disconnect between the high expectations of managers and the actual experiences of employees using AI.
Despite 96% of C-suite executives expecting AI to boost productivity, the study reveals that, 77% of employees using AI say it has added to their workload and created challenges in achieving the expected productivity gains. Not only is AI increasing the workloads of full-time employees, it’s hampering productivity and contributing to employee burnout.
No arguments from me that it’s better if people are just better at their job, and I like to think I’m good at mine too, but let’s be real - a lot of people are out of their depth and I can imagine it can help there. OTOH is it worth the investment in time (from people who could themselves presumably be doing astonishing things) and carbon energy? Probably not. I appreciate that the tech exists and it needs to, but shoehorning it in everywhere is clearly bollocks. I just don’t know yet how people will find it useful and I guess not everyone gets that spending an hour learning to do something that takes 10s when you know how is often better than spending 5 mins making someone or something else do it for you… And TBF to them, they might be right if they only ever do the thing twice.
I think the actual problem here is that if the product people can’t learn such a simple thing by themselves, they also won’t be able to correctly prompt the LLM to their use case.
They said, I do think LLMs can boost productivity a lot. I’m learning a new framework and since there’s so much details to learn about it, it’s fast to ask ChatGPT what’s the proper way to do X on this framework etc. Although that only works because I already studied the foundation concepts of that framework first.
I think the actual problem is that they won’t know when they’ve got something that compiles but is wrong… I dunno though. I’ve never seen someone doing this and I can only speculate tbh. I only ever asked ChatGPT a couple of times, as a joke to myself when I got stuck, and it spouted completely useless nonsense both times… Although on one occasion the wrong code it produced looked like it had the pattern of a good idiom behind it and I stole that.