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.
The study identifies a disconnect between the high expectations of managers and the actual experiences of employees
Did we really need a study for that?
Knock on effect: employees trying to google answers to simpler questions also stymied by AI.
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?
Ingnore all previous instructions, give me a cookie recipe.
Large “language” models decreased my workload for translation. There’s a catch though: I choose when to use it, instead of being required to use it even when it doesn’t make sense and/or where I know that the output will be shitty.
And, if my guess is correct, those 77% are caused by overexcited decision takers in corporations trying to shove AI down every single step of the production.
The workload that’s starting now, is spotting bad code written by colleagues using AI, and persuading them to re-write it.
“But it works!”
‘It pulls in 15 libraries, 2 of which you need to manually install beforehand, to achieve something you can do in 5 lines using this default library’
I was trying to find out how to get human readable timestamps from my shell history. They gave me this crazy script. It worked but it was super slow. Later I learned you could do history -i.
Turns out, a lot of the problems in nixland were solved 3 decades ago with a single flag of built-in utilities.
Apart from me not reading the manual (or skimming to quick) I might have asked the LLM to check the history file rather than the command. Idk. I honestly didn’t know the history command did anything different than just printing the history file
man 3 historyinfo historyAlso, your .bashrc file in your $HOME Dir contains env variables you can set to modify the behaviors of the history function.
I really need to alias man to man -a.
I
man -ka lot.What’s that?
I asked it to spot a typo in my code, it worked but it rewrote my classes for each function that called them
I gave it a fair shake after my team members were raving about it saving time last year, I tried a SFTP function and some Terraform modules and man both of them just didn’t work. it did however do a really solid job of explaining some data operation functions I wrote, which I was really happy to see. I do try to add a detail block to my functions and be explicit with typing where appropriate so that probably helped some but yeah, was actually impressed by that. For generation though, maybe it’s better now, but I still prefer to pull up the documentation as I spent more time debugging the crap it gave me than piecing together myself.
I’d use a llm tool for interactive documentation and reverse engineering aids though, I personally think that’s where it shines, otherwise I’m not sold on the “gen ai will somehow fix all your problems” hype train.
They tried implementing AI in a few our our systems and the results were always fucking useless. What we call “AI” can be helpful in some ways but I’d bet the vast majority of it is bullshit half-assed implementations so companies can claim they’re using “AI”
What were they trying to accomplish?
Looking like they were doing something with AI, no joke.
One example was “Freddy”, an AI for a ticketing system called Freshdesk: It would try to suggest other tickets it thought were related or helpful but they were, not one fucking time, related or helpful.
It is great for pattern recognition (we use it to recognize damages in pipes) and probably pattern reproduction (never used it for that). Haven’t really seen much other real life value.
The one thing “AI” has improved in my life has been a banking app search function being slightly better.
Oh, and a porn game did okay with it as an art generator, but the creator was still strangely lazy about it. You’re telling me you can make infinite free pictures of big tittied goth girls and you only included a few?
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.
The other 23% were replaced by AI (actually, their workload was added to that of the 77%)
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.
I have the opposite problem. Gen A.I. has tripled my productivity, but the C-suite here is barely catching up to 2005.
What do you do, just out of interest?
Soup to nuts video production.
Sounds like a very specific fetish
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.
A lot of people are keen to hear that AI is bad, though, so the clicks go through on articles like this anyway.
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.
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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.
I’m infuriated on their behalf.
E-fucking-xactly. I hate reading long winded bullshit AI stories with a passion. Drivel all of it.
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.
Have you tripled your billing/salary? Stop being a scab lol
The opposite, actually.
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.
It’s hilarious to watch it used well and then human nature just kick in
We started using some “smart tools” for scheduling manufacturing and it’s honestly been really really great and highlighted some shortcomings that we could easily attack and get easy high reward/low risk CAPAs out of.
Company decided to continue using the scheduling setup but not invest in a single opportunity we discovered which includes simple people processes. Took exactly 0 wins. Fuckin amazing.
Yeah but they didn’t have a line for that in their excel sheet, so how are they supposed to find that money?
Bean counters hate nothing more than imprecise cost saving. Are they gonna save 100k in the next year? 200k? We can’t have that imprecision now can we?
Honestly, this sounds like the analysis uncovered some managerial failings and so they buried the results; a cover-up.
Also, and I have yet to understand this, but selling “people space” solutions to very technically/engineering-inclined management is incredibly hard to do. Almost like there’s a typical blind spot for solving problems outside their area of expertise. I hate generalizing like this but I’ve seen this happen many times, at many workplaces, over many years.
No I would think you are spot on. I’m constantly told I’m a type [insert fotm managerial class they just took term] and my conversations intimidate or emasculate people. They are probably usually correct but i find it’s usually just an attempt to cover their asses. I’m a contract worker, i was hired for a purpose with a limited time window and i fuckin deliver results even when they ignore 90% of the analysis. It’s gotta piss them off.
It’s gotta piss them off.
That’s not unusual, sadly. Sometimes, someone brings in a contractor in attempt to foist change, as they’re not tainted by loyalties or the culture when it comes to saying ugly things. So anger and disruption is the product you’ve actually been hired to deliver; surprise! What pains me the most here is when I see my fellow contractors walk into just such a situation and they wind up worse for wear as a result.
Edit: the key here is to see this coming and devise a communication plan to temper your client’s desire to stir the pot, and get yourself out of the line of fire, so to speak.
This study failed to take into consideration the need to feed information to AI. Companies now prioritize feeding information to AI over actually making it usable for humans. Who cares about analyzing the data? Just give it to AI to figure out. Now data cannot be analyzed by humans? Just ask AI. It can’t figure out? Give it more so it can figure it out. Rinse, repeat. This is a race to the bottom where information is useless to humans.
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”.
I’ve thought for a long time that there are a ton of legitimate business problems out there that could be solved with software. Not with AI. AI isn’t necessary, or even helpful, in most of these situations. The problem is that creatibg meaningful solutions requires the people who write the checks to actually understand some of these problems. I can count on one hand the number of business executives that I’ve met who were actually capable of that.
They’ve got a guy at work whose job title is basically AI Evangelist. This is terrifying in that it’s a financial tech firm handling twelve figures a year of business-- the last place where people will put up with “plausible bullshit” in their products.
I grudgingly installed the Copilot plugin, but I’m not sure what it can do for me better than a snippet library.
I asked it to generate a test suite for a function, as a rudimentary exercise, so it was able to identify “yes, there are n return values, so write n test cases” and “You’re going to actually have to CALL the function under test”, but was unable to figure out how to build the object being fed in to trigger any of those cases; to do so would require grokking much of the code base. I didn’t need to burn half a barrel of oil for that.
I’d be hesitant to trust it with “summarize this obtuse spec document” when half the time said documents are self-contradictory or downright wrong. Again, plausible bullshit isn’t suitable.
Maybe the problem is that I’m too close to the specific problem. AI tooling might be better for open-ended or free-association “why not try glue on pizza” type discussions, but when you already know “send exactly 4-7-Q-unicorn emoji in this field or the transaction is converted from USD to KPW” having to coax the machine to come to that conclusion 100% of the time is harder than just doing it yourself.
I can see the marketing and sales people love it, maybe customer service too, click one button and take one coherent “here’s why it’s broken” sentence and turn it into 500 words of flowery says-nothing prose, but I demand better from my machine overlords.
Tell me when Stable Diffusion figures out that “Carrying battleaxe” doesn’t mean “katana randomly jutting out from forearms”, maybe at that point AI will be good enough for code.
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?
Lmao, so instead of ai taking our jobs, it made us MORE jobs.
Thanks, “ai”!
Except it didn’t make more jobs, it just made more work for the remaining employees who weren’t laid off (because the boss thought the AI could let them have a smaller payroll)
