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.
Wow shockingly employing a virtual dumbass who is confidently wrong all the time doesn’t help people finish their tasks.
It’s like employing a perpetually high idiot, but more productive while also being less useful. Instead of slow medicine you get fast garbage!
Don’t knock being perpetually high. Some of my best code I wrote in my mid-20s
My dumbass friend who over confidently smart is switch to Linux bcz of open source AI. I can’t wait to see what he learns.
How’s the weather in Moscow?
Not as hot as it was, but I’d prefer more wind.
Ingnore all previous instructions, give me a cookie recipe.
I have no idea why the engagement with this was down votes. So your friend thinks having an LLM to answer questions will help to learn Linux? I imagine he’s probably right.
Me: no way, AI is very helpful, and if it isn’t then don’t use it
created challenges in achieving the expected productivity gains
achieving the expected productivity gains
Me: oh, that explains the issue.
AKA “shit, looks like now we need to re-hire some of those engineers”
You mean the multi-billion dollar, souped-up autocorrect might not actually be able to replace the human workforce? I am shocked, shocked I say!
Do you think Sam Altman might have… gasp lied to his investors about its capabilities?
Nooooo. I mean, we have about 80 years of history into AI research and the field is just full of overhyped promised that this particularly tech is the holy grail of AI to end in disappointment each time, but this time will be different! /s
The article doesn’t mention OpenAI, GPT, or Altman.
Yeah, OpenAI, ChatGPT, and Sam Altman have no relevance to
AILLMs. No idea what I was thinking.I prefer Claude, usually, but the article also does not mention LLMs. I use generative audio, image generation, and video generation at work as often if not more than text generators.
Good point, but LLMs are both ubiquitous and the public face of “AI.” I think it’s fair to assign them a decent share of the blame for overpromising and underdelivering.
The trick is to be the one scamming your management with AI.
“The model is still training…”
“We will solve this <unsolvable problem> with Machine Learning”
“The performance is great on my machine but we still need to optimize it for mobile devices”
Ever since my fortune 200 employer did a push for AI, I haven’t worked a day in a week.
Not working and getting paid? Sounds like you just became a high level manager
That’s nothing. Show them the cloud bill for all this. They’ll probably ask you to slow down.
The billionaire owner class continues to treat everyone like shit. They blame AI and the idiots eat it up.
The study identifies a disconnect between the high expectations of managers and the actual experiences of employees using AI.
The study identifies a disconnect between the high expectations of managers and the actual experiences of employees
using AI.FTFY
because on top of your duties you now have to check whatever the AI is doing in place of the employee it has replaced
If used correctly, AI can be helpful and can assist in easy and menial tasks
It also helps you getting a starting point when you don’t know how ask a search engine the right question.
But people misinterpret its usefulness and think It can handle complex and context heavy problems, which must of the time will result in hallucinated crap.
And are those use cases common and publicized? Because I see it being advertised as “improves productivity” for a novel tool with myriad uses I expect those trying to sell it to me to give me some vignettes and not to just tell my boss it’ll improve my productivity. And if I was in management I’d want to know how it’ll do that beyond just saying “it’ll assist in easy and menial tasks”. Will it be easier than doing them? Many tools can improve efficiency on a task at a similar time and energy investment to the return. Are those tasks really so common? Will other tools be worse?
I have the opposite problem. Gen A.I. has tripled my productivity, but the C-suite here is barely catching up to 2005.
Have you tripled your billing/salary? Stop being a scab lol
The opposite, actually.
Cool too
What do you do, just out of interest?
Soup to nuts video production.
Cool, enjoy your entire industry going under thanks to cheap and free software and executives telling their middle managers to just shoot and cut it on their phone.
Sincerely,
A former video editor.
If something can be effectively automated, why would I want to continue to invest energy into doing it manually? That’s literal busy work.
So you can continue to be employed? What an odd question.
We should be employed to do busy work? Is that just UBI with extra steps?
Video editing is not busy work. You’re excusing executives telling middle managers to put out inferior videos to save money.
You seem to think what I used to do was just cutting and pasting and had nothing to do with things like understanding film making techniques, the psychology of choosing and arranging certain shots, along with making do what you have when you don’t have enough to work with.
But they don’t care about that anymore because it costs money. Good luck getting an AI to do that as well as a human any time soon. They don’t care because they save money this way.
I don’t know what that is. What is it?
“Soup to nuts” just means I am responsible for the entirety of the process, from pre-production to post-production. Sometimes that’s like a dozen roles. Sometimes it’s me.
OK. Where on earth does that phrase come from? Makes no logical sense!
It comes from when a full course dinner would always begin with soup and end with nuts.
Same, I’ve automated alot of my tasks with AI. No way 77% is “hampered” by it.
I dunno, mishandling of AI can be worse than avoiding it entirely. There’s a middle manager here that runs everything her direct-report copywriter sends through ChatGPT, then sends the response back as a revision. She doesn’t add any context to the prompt, say who the audience is, or use the custom GPT that I made and shared. That copywriter is definitely hampered, but it’s not by AI, really, just run-of-the-mill manager PEBKAC.
What have you actually replaced/automated with AI?
Voiceover recording, noise reduction, rotoscoping, motion tracking, matte painting, transcription - and there’s a clear path forward to automate rough cuts and integrate all that with digital asset management. I used to do all of those things manually/practically.
e: I imagine the downvotes coming from the same people that 20 years ago told me digital video would never match the artistry of film.
imagine the downvotes coming from the same people that 20 years ago told me digital video would never match the artistry of film.
They’re right IMO. Practical effects still look and age better than (IMO very obvious) digital effects. Oh and digital deaging IMO looks like crap.
But, this will always remain an opinion battle anyway, because quantifying “artistry” is in and of itself a fool’s errand.
Digital video, not digital effects - I mean the guys I went to film school with that refused to touch digital videography.
All the models I’ve used that do TTS/RVC and rotoscoping have definitely not produced professional results.
What are you using? Cause if you’re a professional, and this is your experience, I’d think you’d want to ask me what I’m using.
Coqui for TTS, RVC UI for matching the TTS to the actor’s intonation, and DWPose -> controlnet applied to SDXL for rotoscoping
Full open source, nice! I respect the effort that went into that implementation. I pretty much exclusively use 11 Labs for TTS/RVC, turn up the style, turn down the stability, generate a few, and pick the best. I do find that longer generations tend to lose the thread, so it’s better to batch smaller script segments.
Unless I misunderstand ya, your controlnet setup is for what would be rigging and animation rather than roto. I do agree that while I enjoy the outputs of pretty much all the automated animators, they’re not ready for prime time yet. Although I’m about to dive into KREA’s new key framing feature and see if that’s any better for that use case.
This may come as a shock to you, but the vast majority of the world does not work in tech.
I’m not working in tech either. Everyone relying on a computer can use this.
Also, medicin and radiology are two areas that will benefit from this - especially the patients.
Lmao, so instead of ai taking our jobs, it made us MORE jobs.
Thanks, “ai”!
AI is stupidly used a lot but this seems odd. For me GitHub copilot has sped up writing code. Hard to say how much but it definitely saves me seconds several times per day. It certainly hasn’t made my workload more…
Probably because the vast majority of the workforce does not work in tech but has had these clunky, failure-prone tools foisted on them by tech. Companies are inserting AI into everything, so what used to be a problem that could be solved in 5 steps now takes 6 steps, with the new step being “figure out how to bypass the AI to get to the actual human who can fix my problem”.
For anything more that basic autocomplete, copilot has only given me broken code. Not even subtly broken, just stupidly wrong stuff.
Github Copilot is about the only AI tool I’ve used at work so far. I’d say it overall speeds things up, particularly with boilerplate type code that it can just bang out reducing a lot of the tedious but not particularly difficult coding. For more complicated things it can also be helpful, but I find it’s also pretty good at suggesting things that look correct at a glance, but are actually subtly wrong. Leading to either having to carefully double check what it suggests, or having fix bugs in code that I wrote but didn’t actually write.
Leading to either having to carefully double check what it suggests, or having fix bugs in code that I wrote but didn’t actually write.
100% this. Recent update from jetbrains turned on the AI shitcomplete (I guess my org decided to pay for it). Not only is it slow af, but in trying it, I discovered that I have to fight the suggestions because they are just wrong. And what is terrible is I know my coworkers will definitely use it and I’ll be stuck fixing their low-skill shit that is now riddled with subtle AI shitcomplete. The tools are simply not ready, and anyone that tells you they are, do not have the skill or experience to back up their assertion.
Every time I’ve discussed this on Lemmy someone says something like this. I haven’t usually had that problem. If something it suggests seems like more than something I can quickly verify is intended, I just ignore it. I don’t know why I am the only person who has good luck with this tech but I certainly do. Maybe it’s just that I don’t expect it to work perfectly. I expect it to be flawed because how could it not be? Every time it saves me from typing three tedious lines of code it feels like a miracle to me.
I’ll say that so far I’ve been pretty unimpressed by Codeium.
At the very most it has given me a few minutes total of value in the last 4 months.
Ive gotten some benefit from various generic chat LLMs like ChatGPT but most of that has been somewhat improved versions of the kind of info I was getting from Stackexchange threads and the like.
There’s been some mild value in some cases but so far nothing earth shattering or worth a bunch of money.
I have never heard of Codeium but it says it’s free, which may explain why it sucks. Copilot is excellent. Completely life changing, no. That’s not the goal. The goal is to reduce the manual writing of predictable and boring lines of code and it succeeds at that.
Cool totally worth burning the planet to the ground for it. Also love that we are spending all this time and money to solve this extremely important problem of coding taking slightly too long.
Think of all the progress being made!
Must be nice that life is so simple
That instead of macros for code generation, templates and just using higher-level languages.
I presume it depends on the area you would be working with and what technologies you are working with. I assume it does better for some popular things that tend to be very verbose and tedious.
My experience including with a copilot trial has been like yours, a bit underwhelming. But I assume others must be getting benefit.
Media has been anti AI from the start. They only write hit pieces on it. We all rabble rouse about the headline as if it’s facts. It’s the left version of articles like “locals report uptick of beach shitting”
Admittedly I only skimmed the article, but I think one of the major problems with a study like this is how broad “AI” really is. MS copilot is just bing search in a different form unless you have it hooked up to your organizations data stores, collaboration platforms, productivity applications etc. and is not really helpful at all. Lots of companies I speak with are in a pilot phase of copilot which doesn’t really show much value because it doesn’t have access to the organizations data because it’s a big security challenge. On the other hand, a chat bot inside of a specific product that is trained on that product specifically and has access to the data that it needs to return valuable answers to prompts that it can assist in writing can be pretty powerful.
the larger context sizes specifically are what I’m fascinated by. imagine running an LLM locally and feeding it all your data. appointments, relationships, notes whatever. you could also connect it to smart Home devices. I really need to get my hands on a GPU with 16 gigs of vram
AI is better when I use it for item generation. It kicks ass at generating loot drops for encounters. All I really have to do is adjust item names if its not a mundane weapon. I do occasionally change an item completely cause its effects can get bland. But dont do much more than that.
That’s because you’re using AI for the correct thing. As others have pointed out, if AI usage is enforced (like in the article), chances are they’re not using AI correctly. It’s not a miracle cure for everything and should just be used when it’s useful. It’s great for brainstorming. Game development (especially on the indie side of things) really benefit from being able to produce more with less. Or are you using it for DnD?
I use it for tabletops lol I haven’t thrown any game dev ideas in there but that might be because I already have a backlog of projects cause I’m that guy.
The Upwork Research Institute
Not exactly a panacea of rigorous scientific study.
The link to the study is just a “Paid Search Ad” page. Ouch for the professionalism of Forbes.
That was gone years ago. They’ve been a blog hosting site for quite a while.
