77% Of Employees Report AI Has Increased Workloads And Hampered Productivity, Study Finds

Don't knock being perpetually high. Some of my best code I wrote in my mid-20s

How’s the weather in Moscow?

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.

Generating multiple pictures of the same character is actually pretty hard. For example, let's say you're making a visual novel with a bunch of anime girls. You spin up your generative AI, and it gives you a great picture of a girl with a good design in a neutral pose. We'll call her Alice. Well, now you need a happy Alice, a sad Alice, a horny Alice, an Alice with her face covered with cum, a nude Alice, and a hyper breast expansion Alice. Getting the AI to recreate Alice, who does not exist in the training data, is going to be very difficult even once.

And all of this is multiplied ten times over if you want granular changes to a character. Let's say you're making a fat fetish game and Alice is supposed to gain weight as the player feeds her. Now you need everything I described, at 10 different weights. You're going to need to be extremely specific with the AI and it's probably going to produce dozens of incorrect pictures for every time it gets it right. Getting it right might just plain be impossible if the AI doesn't understand the assignment well enough.

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.

I've seen programmers claiming that it helps them out, too. Mostly to give you an idea on how to tackle a problem, instead of copypasting the solution (as it'll likely not work).

My main use of the system is

1. Probing vocab to find the right word in a given context.
2. Fancy conjugation/declension table.
3. Spell-proofing.

It works better than going to Wiktionary all the time, or staring my work until I happen to find some misspelling (like German das vs. dass, since both are legit words spellcheckers don't pick it up).

One thing to watch out for is that the translation will be more often than not tone-deaf, so you're better off not wasting your time with longer strings unless you're fine with something really sloppy, or you can provide it more context. The later however takes effort.

Turns out, a lot of the problems in nixland were solved 3 decades ago with a single flag of built-in utilities.

I didn't know about this. Thank you for the knowledge fellow human!

I don't run crazy scripts in my machine. If I don't understand it's not safe enough.

That's how you get pranked and hacked

yay!! do more stupid shit faster and with more baseless confidence!

2012 me feels personally called out by this. fuck 2012 me that lazy fucker. stackoverflow was my "get out of work early and hit the bar" card.

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.

Yeah, OpenAI, ChatGPT, and Sam Altman have no relevance to AI LLMs. No idea what I was thinking.

Aha, so this must all be Elon's fault! And Microsoft!

There are lots of whipping boys these days that one can leap to criticize and get free upvotes.

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.

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.

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, too, work in fintech. I agree with this analysis. That said, we currently have a large mishmash of regexes doing classification and they aren't bulletproof. It would be useful to see about using something like a fine-tuned BERT model for doing classification for transactions that passed through the regex net without getting classified. And the PoC would be would be just context stuffing some examples for a few-shot prompt of an LLM and a constrained grammar (just the classification, plz). Because our finance generalists basically have to do this same process, and it would be nice to augment their productivity with a hint: "The computer thinks it might be this kinda transaction"

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.

That's why I have my doubts when people say it's saving them a lot of time or effort. I suspect it's planting bombs that they simply haven't yet found. Like it generated code and the code seemed to work when they ran it, but it contains a subtle bug that will only be discovered later. And the process of tracking down that bug will completely wreck any gains they got from using the LLM in the first place.

Same with the people who are actually using it on human languages. Like, I heard a story of a government that was overwhelmed with public comments or something, so they were using an LLM to summarize those so they didn't have to hire additional workers to read the comments and summarize them. Sure... and maybe it's relatively close to what people are saying 95% of the time. But 5% of the time it's going to completely miss a critical detail. So, you go from not having time to read all the public comments so not being sure what people are saying, to having an LLM give you false confidence that you know what people are saying even though the LLM screwed up its summary.

Again, plausible bullshit isn’t suitable.

It is suitable when you're the one producing the bullshit and you only need it accepted.

Which is what people pushing for this are. Their jobs and occupations are tolerant to just imitating, so they think that for some reason it works with airplanes, railroads, computers.

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.

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.

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.

The opposite, actually.

Soup to nuts video production.

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?

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.

Yeah but the idea of AI in that kind of workflow is so that the product guy can actually do it themselves without asking you and in less than 30 mins

Wait, LLM’s can play DnD? You mean…I might finally be able to play that game?!? Hurray!

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.

A hit-piece commissioned by the Joker to distract you from his upcoming bank heist!!!!!

The summary for the post kinda misses the mark on what the majority of the article is pushing.

Yes, the first part describes employees struggling with AI, but the majority of the article makes the case for hiring more freelancers and updating "outdated work models and systems...to unlock the full expected productivity value of AI."

It essentially says that AI isn't the problem, since freelancers can use it perfectly. So full time employees need to be "rethinking how to best do their work and accomplish their goals in light of AI advancements."