In other words, corporate leadership is starting from the premise that AI has (or will) radically change the business, and they’re working backwards from that premise to find the evidence to support this article of faith.
Sounds familiar. The proof-of-work blockchain scheme which was the fad a while ago is also often described as a solution in search of a problem.
I feel like block chain as a public ledger has found quite a few purposeful uses, and was a solution to a handful of problems most people rarely if ever encounter. Then fake money got involved
Yes, exactly.
Block chain would have been an amazing solution to most democratic vote validation processes.
It can still be used that way. While most people talk about how corrupt politicians enrich themselves with fake currencies, more legal and legitimate uses can still use decentralized ledgers for useful things. Of course these won’t make headlines.
There are far better global ledger approaches than blockchain.
I believe you, but can you name one so we can all learn more about the alternatives out there?
SWIFT is the easy one. Fun fact they looked into blockchain at one point and went “yeah, nah”
I thought Swift is currently Block-Chain based. Do you mean this Swift?
Well no, because we don’t have a problem that blockchain solves (better than open software, if it must be digital), and there are loads of problems that the blockchain doesn’t solve. Like how am I supposed to vote with that thing under no coercion.
I’m not really sure what you’re getting at. The blockchain is a good mechanism to maintain a source of truth that is inspectable and verifiable by anyone. It would only serve to certify that official counts can’t be tampered with in certain ways.
But it doesn’t replace the whole democratic voting process. It doesn’t protect against coercive voting, for instance.
My point originally was that blockchain can be of use to us, but tech bros ruined its rep. Same with AI. I’ve been waiting for routers with ai-powered (really, just machine learning) firewalls that can adapt rules to environments. But instead of that, everyone is obsessed with generative stuff that isnt very good.
Yeah I hear you, but the 51% attack exists. Like if you use paper ballots, you’re safer and it consumes less energy. There is just nothing better by using a blockchain, and paper ballots (for example) can be verified by anyone, the blockchain not so much.
Aren’t votes meant to be anonymous to avoid retribution?
Isn’t the public ledger identifying information to be used by authoritarian violence on every single voter in that case?
Proposed ideas for block chain to maintain election integrity would only use a block chain ledger to verify counts, not store voter information.
Which purposeful uses did you have in mind?
Nothing that a centralized server wouldn’t be able to handle better.
Or several other solutions for different use cases. I always remember this article about alternatives: https://gist.github.com/joepie91/a90e21e3d06e1ad924a1bfdfe3c16902
I’m glad you specifically pointed out proof-of-work blockchains.
They’re very inefficient (economically and ecologically) by design. In almost all cases this design isn’t warranted.
Alas there are other designs and while most of them are rubbish as well, a few ones are doing things quite right.I hope that just like other schemes than proof-of-work were thought of regarding blockchains, there will be AI models that are way, way more efficient and ideally can be run locally - for those cases that can use AI…
Wasn’t Nano predicated on those lines? I remember reading transactions could be done locally, even off-line, validated beetween the parts and only later added to the global ledger.
Nano uses “proof of stake” instead of proof of work to decide the order of transactions, and who receives block rewards.
The main problem with PoS is that it’s essentially the same as Federal Reserve bonds: all the new money goes towards people with extra money to freeze. This is part of why inequality has spiraled out of control since the Nixon Shock. Proof of work literally burns most of the profits because of difficulty adjustment.
A more specific problem with Nano (formerly RaiBlocks) is that the entire supply was centrally issued, with a pinky promise from this private organization that they only issued coins by CAPTCHA. If they were lying, then they could have issued 51% of the supply to themselves for permanent control. The only way we’d be able to detect it is if the price kept going down for years.
That requires a global ledger. Blockchain is an appallingly bad way to implement one.
What I understood then was that the local ledger of a given user of the coin would authorize and register the transactions done on/off the recorded balance and, when network available, would broadcast such transactions to the global ledger.
The global ledger was the total sum of transactions, not imperatively required to authorize transaction by transaction.
Funny, that you even know about Nano!
…it’s one of the often overlooked projects because it doesn’t have a ton of fuck-off-money and instead tries to focus on a solid protocol.Nano has a lot of interesting attributes, but I fail to see how what you describe would work in practice.
If both parties want to make sure there are no shenenigans at play, they need to know about the most recent state of the respective account chains, which essentially requires them to be online for agreeing on said transaction.
But overall Nano is very fast and efficient by design and only a failure in terms of “gainz for Lambo”.As we’re here in a thread about AI I should remark that machine-to-machine-payments - in this case: agent-to-agent-payments - would work pretty well with Nano as currency because of the transaction finality (typically less than 1 second) and the feeless nature of transactions.
If AI agents are looking for the most viable way to transfer tiny amounts of value fast and without fees they might find Nano and use it - who knows…
…and just like Nano showed that efficient ways to create digital money are possible I’m hoping for efficient AI models that are economically and ecologically worthwhile.What I understood then was that in person transactions could be done, as the local ledger of each user would authorize and record operations on and off the available balance and wait until network availability to syncronize with the global record.
Returning to the subject at hand: I can imagine very specialized “AI” being useful for scientifical research, where very knowledgeable people use it as a tool to facilitate processes but are nonetheless capable of reviewing whatever results it produces.
Not gigantic datacenters required for this but small, purpose made and perfected, locally run, even if on higher specifications hardware to do so, but machines built for a given task and purpose. The economic viability on it be damned; it’s a tool for research, it is not made to earn money.
To put it bluntly: if you do an offline transaction, you’re prone to fraud.
If you expect the senders account chain to have balance x (because that’s your offline record for that) and the sender has sent all funds to a different address after you synced that account chain, you receive money that isn’t there - kind of like an invalid cheque.
I have no clue how that would work in practice, because to know a random account in advance, you’d have to sync the whole amount of account chains there is (called block lattice in Nano’s case).
With a mobile device that’s hardly feasible and without a mobile device I don’t see how you’d get in contact with people to make such an offline transaction.That kind of specialized AI is what I imagine to be a use case for locally run AI, too.
After all you don’t want to build processes on an AI, where you have zero control over what happens behind the curtains.
That includes feeding potentially sensitive data back to it as well as being unable to control the training data set, its learning, version numbers, etc.
That’s top down thinking for you.
I typed into Google “potatoes pressure cooker” to get a reminder of how long to cook them. The AI told me, and correctly said that I should use the steamer sieve, but also told me to salt the water. The water that would be under the potatoes and that wouldn’t touch them.
I asked why, and the AI said that little splashes of salt water from the boiling would land on the surface of the potatoes and salt them gently, that the salt would increase the boiling temperature, and that the vapour would be aromatic.
I pointed out that the amount of salt landing on the surface of the potatoes would be negligible, that the vapour is distilled water in gas form, and that the increase in boiling temperature from salting the water is less than 1°C. The AI said, oh yeah, you’re right on all counts. Don’t salt the water.
What it has been doing was exactly what an LLM does. It gave me the received wisdom from the internet.
That aligns with what Cory Doctorow was saying here, namely that all the AI successes were from people who already knew what they were doing and could use the AI as a tool. Not from people who had no clue and just let AI do the job.
I use google “ai” in when thrifting for audio gear. Minimum 80% of the time it gets something GLARINGLY wrong. “Oh ho ho! You correctly pointed out that I was completely wrong on all counts! An astute observation! Let me try again but this time give you the CORRECT information.”
Exactly. I use AI primarily as a natural-language search engine, when searching for things that can quickly be independently verified. One of the best uses for it is when you know a thing probably exists, but you don’t know the name for it. You can describe to the LLM the object or problem in detail, and it will give you a name. You can then take that word and do a non-AI search to instantly confirm if it got it right.
I’ll never use an AI for something I can’t at least verify without an AI.
I mean, to be fair, that’s a dirt cheap model you’re talking to, and Google is not exactly at the forefront of any tier of model, cheap or otherwise.
Is that you being fair or is that you rushing to defend something?
As if you don’t know these “tools” don’t work.
It gave me the received wisdom from the internet.
I mean… it gave you the amalgamated wisdom of the internet after a very complex game of telephone.
I really like a song that has intro and outro samples and I wanted to know where they were from, so I googled. Google AI promptly informed me that the song has no samples. Guess that settles that.
My husband was recently trying to find an exact quote from Richard Pryor’s character in Lost Highway, so he Googled it.
Google’s AI overview said that Richard Pryor was not in Lost Highway and instead gave some suggestions for other films we might be thinking of.
The quote he was trying to remember was, “There’s nine people down here, and you can ask seven of them. If you can get that price from one of them, I’ll let you ask the other two.”
I do potatoes in my instant pot but leave the water in, it just gets absorbed. So the salt is effective in that case. I salt the potatoes themselves and toss them before adding the water, too, so they should get reasonably seasoned.
Also i use soup stock.
Mashed, though.
Salting the water would increase the boiling temperature I guess, but it seems like a waste of salt because that info isn’t meaningfully changing the cooking time
I use AI as a writing tool, not as a substitute for authorship.
The ideas, intent, perspective, and final judgment are mine. I decide what I want to say, what belongs in the piece, what does not, and whether the finished version accurately represents me. AI may help me organize my thoughts, clarify a sentence, improve the flow, or find wording that better expresses what I already mean. That is not fundamentally different from working with an editor, dictating to a transcriber, or revising a draft after receiving feedback.
What matters is that I review the final work, approve it, and put my name on it. By doing that, I take responsibility for every sentence. If the writing is thoughtful, accurate, and effective, I am responsible for those choices. If it is careless, misleading, generic, or full of slop, that is also my responsibility. Blaming the tool would be an attempt to avoid accountability.
AI does not decide what I believe. It does not decide what I am willing to defend. It does not decide what I publish under my name. I do.
The tool may assist with the writing process, but the authorship comes from intention, judgment, selection, revision, and responsibility. The final work is mine because I chose it, shaped it, approved it, and signed my name to it.
that’s bullshit.
Why?
“authorship is when i make a few edits and sign my name to slop”
if you have willingly handed over your primary writing tool to a machine (for which there is no real meaning, association, appreciation, or delight in words), it is difficult for me to take your commitment to writing or “authorship” seriously.
I did not say “authorship is when I make a few edits and sign my name to slop.” That is not my argument.
My argument is that authorship is grounded in the origination of the ideas and intent, control over what goes into the work, judgment over how those ideas are expressed, endorsement of the final form, and responsibility for the result. Assistance with the linguistic realization does not, by itself, transfer authorship.
You point out that the machine has no meaning, association, appreciation, or delight in the words. I agree. But I do. That is precisely the distinction I am making. The machine does not know what I mean, care whether it represents me, recognize when an analogy fails, or decide whether an argument is worth defending. I am doing those things.
You seem to be defining “writing” as personally generating the initial sequence of words. Maybe that is where we actually disagree. But that definition cannot simply be assumed and then used to prove that I am not writing. Why should authorship reside specifically in first-pass word generation rather than in the thought, intention, judgment, revision, and control that determine what the final words mean?
That is the argument I am interested in having.
i started to read your response, and then i remembered i can’t trust the degree to which you authored it.
i’m not interested.
All their comments are very clearly gpt slop.
A sneer is easier than an answer, and certainty is a lovely refuge when you have no intention of defending it.
You accuse me of surrendering thought to a machine, and then, the moment you are asked to justify that accusation, you surrender thought entirely.
How convenient.
With a wave of the hand, every difficult question disappears. You declare the words contaminated by the tool that helped shape them and thereby absolve yourself of any obligation to consider what they actually say.
No examination. No argument. No possibility of correction.
You accuse me of regurgitating the output of a machine, yet what have you offered in return?
A familiar sneer. A borrowed insult. A conclusion retrieved intact from the cupboard of approved contempt.
You recognize the hated object, produce the expected response, and call the reflex thought.
That is the irony you seem determined not to notice.
My argument from the beginning has been that a machine must be tempered by a human mind. It possesses no responsibility for what it produces. Whatever value emerges from its use depends upon the person capable of examining it, rejecting it, correcting it, shaping it, and finally standing behind it.
But a mind cannot temper anything if it refuses examination itself.
And that is where your position becomes more interesting than your insult.
A mind that refuses examination begins to resemble the very machine you claim to despise. It receives a familiar stimulus, reaches for the familiar pattern, and produces the familiar response without troubling itself over whether the response is true.
Input. Recognition. Output.
The machinery of contempt.
Ignorance itself is no shame. Every one of us is ignorant of almost everything. I have been wrong before and will be wrong again. If you can show me where, I gain something from the correction.
But there is something contemptible in making a virtue of ignorance.
In encountering an argument and proudly announcing that you will not examine it, then mistaking that refusal for discernment. In treating incuriosity as wisdom. In believing that because you have protected yourself from an argument, you have somehow defeated it.
You have not defended your position.
You have insulated it.
Those are not the same thing.
Thought requires a certain vulnerability. You must permit an idea close enough to examine it. You must risk finding weakness in your own position. You must allow the possibility that another person, even one using a tool you despise, might know something you do not.
Without that, certainty does not become strength.
It becomes brittleness.
You tried to cut me with the accusation that I had surrendered my mind to a machine. But in your eagerness to make it, you performed the very surrender you condemn.
You saw the signal.
You retrieved the response.
You refused examination.
You produced the slop.
And so the question remains exactly where I left it:
Will you defend what you believe?
Or is your conviction only strong enough to survive so long as you never allow an argument near it?
“I dont write anything but i take credit for everything”
I was reading the initial comment with peer-reviewed publications in mind and it all sounded like standard practice, but then I read yours and was like “oh, are we talking about books now?”
Either way, its still a bad look. Peer review is even worse than Op Eds, or fiction, or what have you… But its all equally socially degenerate
Interesting. When you want to criticize the argument, the words are mine enough to hold me responsible for them. But when I claim responsibility for those same words, suddenly they’re not mine.
“I don’t write anything but take credit for everything” is a straw man. If you disagree, address what I actually said.
That sounds more like the job of an editor than the job of a writer.
When I was an editor, my job was to assign stories to writers and then to work with the editorial team to revise and refine their output into an end product that the publication could stand behind.
Your process sounds a lot like that.
What matters is that I review the final work, approve it, and put my name on it.
that’s just called writing.
That’s my point.
That “AI” is a completely dumbed down one with reasoning disabled. Of course it’ll make stuff up.
Salting the water is relevant when not using a pressure cooker. It makes no sense when you’re steaming them in a pressure cooker. AI is a good tool, sometimes. But for everyday tasks, it is irrelevant and often wrong.
In my academic field of sustainability, AI still fails to explain what economic sustainability means. It’s very simple.
I lecture and explain to my students that economic sustainability is about how we assess and manage our knowledge, innovations, wealth, and other man-made capital. I stress that it is ABSOLUTELY NOT profit and revenue.
Sure enough, my students submit assignments clearly written by AI that state economic sustainability is profit and revenue.
AI is regurgitating decades of green-washing and even bad academic articles that state economic sustainability is about profits. I use that AI god mode site to test several AI’s at once and they’ve consistently gotten this wrong for 3 years.
AI has been helpful for my job, sure, but the cost in terms of societal damage is so great it makes me wish AI were never created.
What has AI changed so far?
- Hardware prices are so far up that nobody can buy good hardware anymore
- we have AI child porn now, awesome
- we have AI undressing apps, cool
- we have AI, the great cheat tool now † we have AI, the confidently wrong 20% of the time tool
- we have AI, the great misinformation tool
- we are at the brink of the largest economic collapse in human history caused again by the rich loving to play Russian roulette
- there are a limited amount of actual useful applications as well, yay
And all it cost us were millions of jobs, thousands of psychosis and deaths, hundreds of new loud polluting data centers, untold amounts of co2 when were right smack in the mids of a climate crisis…
I’m not advocating for murdering the AI CEOs, but I’m definitely a fan of at least permanent tarring and feathering
Only pro is laborious, tedious programming tasks have become significantly faster to do, along with testing edge cases and stuff a programmer should be able to do but maybe doesnt need to.
Just about everything else is negative.
Oh yeah, all that is definitely worth the list of negatives
Don’t get me wrong, there are good applications for AI, but its damn near literally 99.9% utter crap versus the 0.1% “oohh, really actually nice!”
Is it worth it? I’ll say a million times no. I wish we never got any of this AI trash, because I’d still have a job, I’d still be able to buy hardware, I would have to worry about people making porn videos about me daughter, my family wouldn’t have to deal with AI scam calls, I’d still be able to host a nice website without it being slaughtered by AI bots, and I can go on for a while.
The very little pros do not even make a dent in the negatives
If it weren’t for the overwhelming harm and the insane ramblings of those pushers, we could actually rationally discuss all of the useful things that can be done with it. There are plenty - its a pretty good tool in any engineers toolbox - but there’s no point in itemizing them because the much greater issue is the ai psychosis taking over our entire financial, economic, and governmental systems.
Eh, it also fixed search because it can read through all the SEO crap that fucked over regular search engines.
As long as you click the link to the website attached to the summary of course.
I don’t know, it’s also fun to do role play games with a locally hosted thingamabob-bot-computer-talker. I recently played a 1930s noir detective in New Orleans RPG with AI. It was neat and kept me entertained for hours.
There are also real people who would have a great time doing this with you. Ai does not need to exist in this scenario.
- two of my friends finally have diagnoses for their health problems they had been living with for decades, and can now get appropriate treatment
Trust me, bro!
They are real people these friends of mine, but you don’t know them, because they are from a different school. And you won’t see them this summer at all because… they are both actually models in Canada during the summer.
But totally cured and now they get boners also with THIS ONE TRICK that doctors HATE it!!!
I don’t know what your problem is. My friends are indeed real people. They are not cured, I said they have diagnoses.
One of them has had diffuse but severe symptoms for at least the last 15 years. Bloating, stomach pain, vomiting, circulation problems, etc. She had nights of vomiting and diarrhea where she said she thought was dying, that’s how miseable she felt. She went to many doctors, they ran many checks, and she only ever got the same result: there is nothing to be found, it must be psychosomatic, probably stress. This result, by the way, is a very common one when you’re a woman and you’re seeking medical attention, even for serious problems. Last year, she discussed all her symptoms and observations (like foods and acitivities that seemed to make the symptoms worse) with ChatGPT and it suggested it might be MCAS. She got medication that is supposed to help with MCAS and she is feeling so much better now. She is not cured, but she can have a normal life again. I can tell she has about twice as much energy as she used to have. That is a huge life quality improvment.
The other friend has had bad hearing on one ear for almost all his life. Doctors never found a cause, all they said was “well we could cut it open and take a look if you want” which didn’t sound so great so he never had it checked further. After discussion with some LLM chat bot, he went to another doctor and insisted on getting a CT scan. Turns out he has a (benign) tumor in his ear that’s been growing ever since he was a child. It will be surgically removed soon because it won’t stop growing on its own and might even grow into the brain one day. If he’s lucky, his ear might even be much better afterwards (unless too much of the structure is already destroyed by the tumor growing).
Look, I know it sounds kinda stupid, but I promise you, these are real stories. I know that if you do it wrong, discussing health issues with an LLM can absolutely backfire and be very dangerous. But if you can trust your own brain and don’t switch it off just because you’re using an AI, it can actually be really helpful.
The medical field is one of the places where AI has made real, tangible improvements.
I can’t vouch for that other person’s anecdote, but it seems entirely plausible that an LLM chatbot would be able to better diagnose an issue than a search engine, or even a human doctor, especially if the underlying issue was something like an autoimmune disease, which are notoriously difficult to diagnose.
One of the big flaws in the medical profession (and, really, most professions) is that once you are out of school, nothing forces you to keep learning as the field advances. This potentially, and counterintuitively, results in gaps in knowledge that increase the longer a doctor has been practicing. LLMs, with access to the newer medical information and with the ability to receive and output natural language, do make good tools for diagnosis.
AI, as it turns out, is also way better at analyzing MRI scans and x-rays than humans.
An old-fashioned Google search can point you to more information, if you’re curious about how AI has advanced the medical field.
Medical AI is usually more along the lines of ‘we’ve created a proprietary model for computer aided diagnostics specific to x disease being scanned with y modality and we’ve taken this through the regulatory process in z jurisdiction’ than ‘put your symptoms into an LLM lol’.
There are studies that show that LLMs (chatbots) perform as well or better than human physicians.
I’m not suggesting getting rid of physicians, though. This is a tool for humans, not a replacement.
Super cool! Well we can base your personal healthcare on AI’s sole guidance and if you are misdiagnosed, injured or dead as a result of an “oopsie”, no human will be held legally liable - fun!
So no real stakes for anyone to get it right, as with human-led interventions (with careers on the line at every stage to keep people engaged and honest). But corporations will probably just naturally do the right thing.
But you’re brave, you offer yourself as tribute to the lying machine. Tight tight tight!!!
You seem very passionate about this topic, but you’re not really adding much to the discussion.
Don’t worry, its coming across loud and clear that AI could cure cancer and you’d still think it was better to have cancer than use AI. I get it. AI = bad, full stop. Message received.
“AI” isn’t a thing. Computer vision, machine learning, natural language processing and neural networks are. These can all be useful tools when regulated and maintained with active oversight to balance with society’s other core priorities. What’s at question is the current method and human cost for this frivolously hyped, deceptively marketed lying machine with a single tangible use to date, being the operating system for Facebook’s pervert glasses. You didn’t read, of missed the entire point of, this important article, shared from an important contemporary mind.
Name and cite SPECIFIC examples of anything you claim.
P.s. you don’t “cure cancer”… cancer is a broad heading for hundreds of unique types of disease, presenting in different, completely unique systems within the human body. Like AI, “a cure for cancer” is a broad generalization of complex underlying systems that ignorant people make frivolously - People who think they HAVE the entire knowledge of the world in their brains, when they actually only have a plastic rectangle in their pants pocket with privilege-gated access to a (mostly corporate) CURATED VERSION of the world’s historic knowledge. So if you’ve “cured cancer” friend, why aren’t you treating the 20-30k humans that will die from a form or cancer today worldwide?
Funny how my experience is the American health care system is still 100% absolute shit that costs me 2k a month for the privilege of said shit. My wait times are the same, my “go fuck yourselves” are the same, my healthcare workers are still underpaid, and the systems for consumers are still shit.
“But the charts say AI is helping”
Once again it’s consumers get to wait for the piss to trickle down our backs. AI hasn’t done shit for the average Joe except make everything cost more while providing a worse service. Please, tell me how my healthcare experience has improved in the past 2 years. Go.
You are talking about a different thing than I am. The American healthcare system is garbage with or without AI, but AI is helping the medical field. Getting a more accurate analysis of an MRI scan is objectively a good thing, for example, even if the healthcare system that performed the scan is garbage.
They’re not using LLMs to analyse MRI scans. There are image processing algorithms for that, but they’re a whole other thing to what this entire thread is about.
Also, are you a fucking bot? I’ve read all your comments so far in this thread and uhh yeah. Please feel free to jog on now.
I’ve read all your comments so far
I’m flattered. Did you read the first one where I said it was reductive to equate AI with chatbots?
How is “helping the medical field” not compatible with better healthcare quality? If the end user isn’t experiencing benefits, then how can you claim that benefits have been provided? Who is getting these “benefits” if it’s not the end user? If someone IS getting benefits, yet the end users still haven’t gotten a better experience… Then can you agree that AI is only helping intermediaries? Like… The corporations who provide the garbage experience?
Do you see your logical fallacy here?
If your loved one is diagnosed with cancer early that would have been missed by a human, that’s a fucking benefit, is it not?
I’m sick of luddites.
AI is very very different from llms. And no, an LLm can’t diagnose shit. A camera trained to detect certain cancerous cells in imaging works fantastically though
…although it was originally created to identify pastries
c/nothingeverhappens
That’s awesome! Imagine if we took all the resources spent on pushing AI for stuff it isn’t good at and invested them in training models for detecting, classifying and correlating medical indicators and using that to anonymously connect people with a network of physicians and psychiatrists for further evaluation and preliminary diagnostics to help with getting actual treatment.
We could bring a more reliable version of that help your friends happened to get to more people, with less of a random chance that the model will reinforce the issues or misdiagnose people with dangerous consequences. We could improve the world.
Instead, they burn books, fire people and abuse eminent domain to displace people so they can run power lines to feed data centers fucking up the water supply for residents that got no say in whether they want oversized heaters in their backyard.
I’m glad your two friends got some use out of this. Is that really worth the price?
I 100% agree. I have no idea why my comment gets downvoted so much. I just wanted to point out that AI and even LLMs absolutely do have valuable use cases. I use them a lot and I see people around me making their lives better using them. Are they overhyped? Probably. Are AI companies using public information that should belong to everyone in an unfair way to become rich and powerful? Absofuckinglutely. Is that how it should be? Definitely not. Is AI a technology with massive potential to change the world for the better? Also yes. Does AI have the potential to completely wreck our society and economy if we do the whole thing wrong? Probably also yes. I hope we can find a way to turn this into something positive.
I have no idea why my comment gets downvoted so much.
Because your comment seemed to add an anecdotal “it also helped two people” to a long list of evils as if it were equivalent. “Sure, people are suffering because of this, but two friends of mine are better off for it” – is that really worth it?
I use them a lot and I see people around me making their lives better using them.
Aside from the nebulous question of just how it’s supposedly making lives better, and whether that actually is an improvement, the question repeats: Is a fee people’s lives getting better really equivalent to the people losing their homes, water supply or job over it? It’s not that we’re unaware that it might have benefits, it’s that those benefits are massively dwarfed by the evils.
Are they overhyped? Probably.
LLMs in particular, and dangerously so. People treat them as virtual humans, use terms such as singularity and trust them with cognitive work a linguistic model plainly isn’t capable of actually doing. They deliver a convincing imitation, but there have been too many instances of that imitation not holding up to any reasonable standard. For a more benign example, Ford had to hire back its fired engineers because it turned out that GenAI can’t actually do their job. Less benign are things like giving harmful “health advice” or reinforcing their users’ delusions and psychoses to the point where they commit violence against themselves or others.
They’re still being hailed as the future, despite evidence backing up what theorists have been warning for a while: A text generator cannot generate meaning and should not be used for any purpose where the content actually matters. That your friends’ word salad happened to resemble useful advice is nice, but it wasn’t actually advice, just the product of a high-tech advice imitator that got lucky.
Is AI a technology with massive potential to change the world for the better? Also yes.
This is where we need to specify just what we mean by AI.
Language models are useful for linguistic correlation tasks, but the actual utility of that is hard to gauge, because it heavily depends on the mode of the output and on the recipient. Specialised models may make decent assistants for certain types of specialists.
They certainly aren’t capable of the type of “nobody has to work any more” utopia that conmen like Musk and Altmann are selling to the gullible. They’re fundamentally unreliable and their consumption of resources dwarfs their sloppy utility.
So while some form of AI might hold a key to a radically better world, LLMs and generative AI aren’t it.
Does AI have the potential to completely wreck our society and economy if we do the whole thing wrong? Probably also yes.
Probably? Have you taken a look around or read the whole list you replied to? The hype already is destroying lives, and there’s a slew of experts calling out the fraudulent scheme they’re pulling on the stock market.
The one point I’ll concede to the scammers is that it has fundamentally altered our world.
Just not for the better.
I hope we can find a way to turn this into something positive.
It starts with being honest and clear about what “this” actually is, understanding what it isn’t and not making excuses for a deeply destructive technological complex just because the mathematical parrot emits some useful responses now and then.
First of all, thank you for your extensive response. I think discussions like this are important. Here’s my 2 cents, sorry if I’m not that eloquent - I’m not a native English speaker so some of this is a bit hard to put into words for me.
Because your comment seemed to add an anecdotal “it also helped two people” to a long list of evils as if it were equivalent.
Well, surely my two friends can’t be the only people AI has helped, that would be highly unlikely. So I do think it is a valid point along the other ones - AI does create value. Otherwise there would be no hype. I just think it’s dishonest to claim that AI is completely useless. If we want to turn this into something positive, we have to be honest about all the aspects.
Aside from the nebulous question of just how it’s supposedly making lives better, and whether that actually is an improvement, the question repeats: Is a fee people’s lives getting better really equivalent to the people losing their homes, water supply or job over it? It’s not that we’re unaware that it might have benefits, it’s that those benefits are massively dwarfed by the evils.
Of course it’s not. We’re totally on the same page here. I just think it’s not a matter of the technology itself, it’s how those companies (are allowed to) act. That doesn’t seem like an AI problem to me, it’s a capitalism problem. We might have different perspectives on this btw because I live in the EU. People don’t lose their home or water supply here because of AI companies.
People treat them as virtual humans, use terms such as singularity and trust them with cognitive work a linguistic model plainly isn’t capable of actually doing.
Yes. And I do think AI companies are at fault here for marketing their products dishonestly to people who don’t understand how the technology works. They exploit stupid people, and mostly stupid people in positions with too much power.
They’re still being hailed as the future, despite evidence backing up what theorists have been warning for a while: A text generator cannot generate meaning and should not be used for any purpose where the content actually matters. That your friends’ word salad happened to resemble useful advice is nice, but it wasn’t actually advice, just the product of a high-tech advice imitator that got lucky.
I think we might fundamentally disagree on this. Advice from a human is nothing but a multivariate combination of things that person has learned in the past. It’s way more complex - brains are orders of magnitude more complex than an artificial neural network - but I don’t see a fundamentally and qualitative difference here unless you believe in something like a soul that somehow magically gives more value to a human advice. If you understand that an LLM is a mathematical tool and not a human, you can use it in very efficient and helpful ways. Some questions actually better answered by something that has gathered a wide range of information from thousands or even millions of sources. Some questions that require fast answers are also better answered by AI (just yesterday I asked ChatGPT for a python script for a certain task - it took about 20 seconds and provided a perfectly working ~500 lines python script that I could use; no human could ever do that). Lots of other questions - questions that require emotional connection, personal experience, specialized knowledge - should be left to humans, of course. The amount of shitty and wrong advice I’ve gotten from people, even doctors and other experts, is immense btw. The crucial thing is that you need to learn how to test and evaluate advice that you get - from people AND from LLMs. Many people would profit from learning that skill - maybe using LLMs might even teach them that, even if it will probably usually be the hard way.
Language models are useful for linguistic correlation tasks, but the actual utility of that is hard to gauge, because it heavily depends on the mode of the output and on the recipient.
Yes, that’s exactly my point. We need to educate the recipients. That is actually one of the most important things imo. AI and LLMs aren’t going to go away, they’re here to stay. Just look at how it already penetrated all kinds of scientific disciplines. We urgently need to regulate what companies can do with it and we need to educate people on how they work and how to use them, and especially how NOT to use them. And by the way, I wish we had never made the jump from calling it deep learning to calling it AI - I think that might have prevented a lot of problems und misunderstandings.
Look, I think ultimately our views aren’t even that different. That’s why discourse is important. I just don’t think screaming “AI is bad” is going to get us anywhere (and that’s essentially what the original comment that I replied to was doing imo). We need to be specific about what the problem is: the problem is not AI, the problem is that some people are getting super rich on the expense of almost everyone else. THAT is what we need to stop. You can’t fight technological and scientific progress, what you need to fight is malicious use of technology and the exploitation of the masses for the profit of a few. I’d say we might actually in an “industrial revolution” kind of situation. Back then, workers rights and communism became a thing. We might need something as fundamental as that to deal with today’s problems. We’ll need all the social sciences now that we’ve cut funding for over the last decades because MINT was just more important to us (I say that as a MINT scientist btw).
I think discussions like this are important.
I find that writing out and defending my position helps me refine it. Sometimes, my perspective on things shifts just by trying to explain it. Discussions are the whetstone by which arguments are sharpened.
I’m not a native English speaker so some of this is a bit hard to put into words for me.
That makes two of us :D
Sometimes, these discussions help expand my Engish skills too.So I do think it is a valid point along the other ones - AI does create value.
Yesn’t. It’s a text generator that predicts a likely series of words, based on the language patterns it learned from its training material. It doesn’t so much create value as aggregate the value of other people’s work into a weighted reproduction.
However, those weights are biased by quantity, not quality. It has no way to assess which responses are good, only which ones are likely. The average value it (re-)produces is an average of the value of the training material. Models trained on a wide variety of content (such as ChatGPT) will inevitably include a lot of material of little value to specialised topics.
Hence my argument: It can get lucky and predict a high-value response, but the problem is that it isn’t guaranteed to do so. A layperson doesn’t have the expertise to tell the difference. That not only dilutes the value, it invites false confidence in the results. In cases where accuracy is critical, this may actually produce negative value if people consult an unreliable model rather than a specialist.
And that’s the critical difference to human advice: human experience is shaped by a number of factors beyond just language. We create semantic connections to abstract concepts and attach specific meaning to certain words and patterns.
LLMs don’t have that abstraction. They can predict sequences of text that sound plausible and might coincide with something describing reality, but they can’t tell whether it’s accurate.
Advice has to be grounded in reality to be useful, and that’s what LLMs are missing.
They’re perfectly suitable for tasks where correlation is enough, but if the task requires actual understanding, LLMs aren’t equipped for it.
Otherwise there would be no hype.
Hype doesn’t always need a solid reason. In this case, a lot of hype stems from the hope that we may one day have the type of Artificial General Intelligence that SciFi has long dreamed of, the illusion that they may be able to do our work for us and the promise to company managers that they may be able to save money by replacing human employees with AI.
The various executives of the big AI vendors are obviously capitalising on that, stoking the hype with grand and utopic visions because they want to sell their product.
It’s not that it’s useless. It’s that the utility is far less than the lofty promises made by people milking the hype for all it’s worth. And that little utility comes at a terrible social, economic and ecologic price.
We might have different perspectives on this btw because I live in the EU. People don’t lose their home or water supply here because of AI companies.
I’m in the EU too, I just read a lot of US news. I don’t think we should dismiss the consequences our use of US infrastructure has. Worse yet, I don’t think we should dismiss the political dependencies that creates.
We need to be specific about what the problem is: the problem is not AI, the problem is that some people are getting super rich on the expense of almost everyone else.
I think that’s only a part of the problem. The second part is the lack of understanding you mentioned, and the resulting mis- and overuse. I’ve seen people trying to argue with experts because “ChatGPT said” because they genuinely do not understand that ChatGPT is a parrot, not an expert.
And the third part, again, is the disastrous effect on our world.
You can’t fight technological and scientific progress […]
I’d say we might actually in an “industrial revolution” kind of situation.I’m not fighting it. I’m trying to pull it out of the pit that the current obsession with imitation has dug. When college students, the next generation or scientists, trades their scientific understanding for the convenience of high-tech parrots, that is the opposite of progress. It’s stagnation, fostered by those few people that are happily trading our future for their present profits.
That’s the mirage of this “industrial revolution” analogy: They’ve built something in the shape of a steam engine, promised the functionality of Spinning Jenny, sold fabric factory owners on the idea who fired their workers to buy these machines. The people they fired were promised that they’d have to work less, but weren’t told that they would be paid less too.
Now these machines turn out to not actually provide the smooth, spinning motion required for spinning thread. Factories are facing expensive production outages, compounding the expenses of getting these machines installed and can’t afford to hire all the workers back.
The machine shops built to produce these Sloppy Jennies or their parts will eventually find it harder to sell their iventory. Once they go under, their workers will also become economic casualties.
We’re at the point where we need to reinforce worker protections. We need to push for a system where our livelihood isn’t contingent on the amount of work we do. Only then can that utopia even manifest. And to actually make progress:
We’ll need all the social sciences now that we’ve cut funding for over the last decades
Yes.
We’ll need to understand the social dynamics of such technology to better prevent the disastrous side-effects. We’ll need to compare historical developments with present circumstances and plans to account for future developments. We’ll need to study the psychological effects of interacting with human-like machines to be able to correct course where needed.
Whatever control mechanism is supposed to prevent machines from producing harmful output will need heuristics based on those disciplines to assess the dangers of that output.
I’d include philosophy too. We don’t need neural networks that are a lesser version of human ones, nor just scaled-up variants that also replicate all the human inefficiencies, errors and biases. Those are the pure MINT approach to the problem, and it’s clearly coming up short.
We need to find a rigorous mechanism for representing semantic knowledge in digital systems that don’t just imitate, but surpass human cognition. We need a workable philosophical grounding for logical and mathematical approaches to modelling knowledge of concepts rather than just language.
We need to get over the error that LLMs are “thinking” or “just like humans”. They’re not, but as long as we’re stuck on the idea, we can’t fix it.
Also, we really, really should spend less time thinking about whether we could and more about whether we should.
I find that writing out and defending my position helps me refine it. Sometimes, my perspective on things shifts just by trying to explain it.
Same here. It’s the best way to test my current views and beliefs and reshape or refine them.
That makes two of us :D Sometimes, these discussions help expand my Engish skills too.
Ah yes, hello there, fellow German. :D winkt fröhlich auf Deutsch ;)
It’s a text generator that predicts a likely series of words, based on the language patterns it learned from its training material.
Yes and no. While I do absolutely agree about the problem of reliability and false confidence, I do not agree on the general understanding of LLMs. You make it sound like it’s merely a predictor of likely words, like your phone keyboard may suggest words you usually use in sequence. But it is really not that simple. I disagree with the - especially here on Lemmy - very widespread “parrot” analogy in the sense that imho people have a very oversimplified idea of what large language models actually are. They don’t just count statistics of word sequences and then spit out the most likely combination. The amount of text they learn from is so big and their structure is complex enough that they can actually learn underlying patterns about WHY words are usually arranged in a certain pattern. That way, they can absolutely learn concepts and “skills” like logical reasoning, to a certain extent. The exact patterns they learned aren’t even fully understood, but obviously it does work. Even early GPT models learned to do arithmetic - there are publications that show that GPT was able to calculate arithmetic problems that were not in the training data, although it did make mistakes. Funnily, the mistakes seemed similar to mistakes humans usually make, like forgetting carryovers in additions or subtractions. Still, it had apparently learned the concept of arithmetics, just by seeing examples (and maybe explanations - we don’t really know). Modern LLMs absolutely capable of a certain level of logic. You can give ChatGPT a task it’s never seen before and chances are it can solve it. Even if it can’t - that doesn’t make its reasoning qualitatively different from how a human brain works. My argument is that humans learn how to think “logically” by seeing examples too - and they fail at logic all. the. damn. time. Go to a city center and ask people logic puzzles - see how many will be able to solve them correctly (and maybe compare the result to an LLM). I wouldn’t even be surprised if by now, even asking medical questions to doctors would, on average, yield worse results than a state-of-the-art LLM. I did a PhD in computer science a few years ago and I can tell you, I would probably rather trust the latest ChatGPT model on most questions regarding my field than myself. It has just become that incredibly good. I’m absolutely not saying it’s perfect, it still makes stupid mistakes and you have to be aware of that, but so do people. I have not seen a single convincing argument why the concept of logic or reasoning that humans have is fundamentally different from that of LLMs. Most people suck at logic. And most men in my life regularly spit out false knowledge with a confidence only a mediocre white man and an LLM can have. ;P
In all seriousness - LLMs lack sensorimotor interaction with the world, and even if we give them robot bodies, they will never know what it’s like to be human. In that sense, they will not replace us, and they will never be human. I would even agree that they will probably never be conscious (although of course we can’t be sure, especially since we haven’t understood consciousness yet in the first place). Their biases and their “way of thinking” will also most probably always be different from humans. But I do not agree that they cannot be “intelligent” in a logic/reasoning sense and that they are merely “statistical parrots”.
The various executives of the big AI vendors are obviously capitalising on that, stoking the hype with grand and utopic visions because they want to sell their product. It’s not that it’s useless. It’s that the utility is far less than the lofty promises made by people milking the hype for all it’s worth. And that little utility comes at a terrible social, economic and ecologic price.
Agreed. I’m fascinated by how far AI has become, but it just isn’t where marketers claim it is, and we can’t be sure it will get there anytime soon.
I don’t think we should dismiss the consequences our use of US infrastructure has. Worse yet, I don’t think we should dismiss the political dependencies that creates.
True. Political dependencies are a serious problem and I’m pretty sure they play a big role in why the US actually lets AI companies get away with all the shit that they do.
I’ve seen people trying to argue with experts because “ChatGPT said” because they genuinely do not understand that ChatGPT is a parrot, not an expert.
Yeah. The point is: ChatGPT will not make you an expert. ChatGPT may act as an expert and even provide accurate information, but citing its answers will not magically make you an expert yourself. That is something that needs to be hammered into people’s heads.
I’m not fighting it. I’m trying to pull it out of the pit that the current obsession with imitation has dug. When college students, the next generation or scientists, trades their scientific understanding for the convenience of high-tech parrots, that is the opposite of progress. It’s stagnation, fostered by those few people that are happily trading our future for their present profits.
Fair enough. We need to find ways to use AI as a useful tool, not a tool to make people lazy and stupid. Tbh, I think it will happen. It happened with Google as well. People used to use Google wrong all the time when it was still new. They clicked the first search result and believed absolutely everything it said. I’m kinda old, I remember that time. :P I’m pretty sure it will be similar with LLMs. By using them, we will learn their limitations and shortcomings, and many of us will learn the hard way. The marketing strategies of AI companies are NOT helpful with that.
We’ll need to understand the social dynamics of such technology to better prevent the disastrous side-effects. We’ll need to compare historical developments with present circumstances and plans to account for future developments. We’ll need to study the psychological effects of interacting with human-like machines to be able to correct course where needed.
I absolutely 100% couldn’t agree more. AI has already had a lot and probably will have even more impact on us, on other technologies like medicine, biotechnology, probably chemistry, material sciences, and loads of other key technologies. We will have a LOT of trouble keeping up with that acceleration of technological progress as a society. In a world where even the existence of the internet doesn’t seem to have been digested fully, AI has the potential to completely wreck everything. And certain people will do all they can to exploit that to gain power and money. And we will have to be faster than them.
In that sense, I agree that
Also, we really, really should spend less time thinking about whether we could and more about whether we should.
is probably right. The EU’s AI Act is a good first step, but the world is in this together, and with the current geopolitical situation I honestly don’t see us working together here for the good of humankind. So maybe trying to somehow decelerate technological progress really can be a reasonable way to take pressure out of that system. I’m not sure it’s possible though.
Though I’m very happy for your friends, I will still vehemently say that AI is a net negative for humanity, it will end up killing us all
AI is changing everything. Its not a lie, its absolute truth.
The problem is the changes are fuckawful terrible for everyone and everything.
I don’t think they’re all lying; most are just misinformed or using the term differently than Cory.
It’s like saying “global warming is changing everything.” Technically, not true, but the knock on effects of specific aspects of it recently hit an inflection point that causes it to affect the lives of everyone.
This has also happened in the field of artificial intelligence; LLM chatbots are only the visible mushroom fruits of the vast mycelium network that has been silently growing underground for years.
silently growing underground for years.
And not so silently, for decades. Even J. Edgar Hoover was using early forms of AI to manage his data trove.
Ooo what’s the reference for this?
Hoover maintained separate, master national blacklists—such as the Security Index—which tracked tens of thousands of citizens deemed “subversive” or political dissidents for immediate detention in the event of a national emergency. He managed his master national blacklists through a fluid, multi-tiered indexing framework that evolved over five decades. These blacklists were not mere static documents; they were part of a highly coordinated operational pipeline designed for the mass roundup and indefinite detention of American citizens during a perceived national emergency.
To add or manage a person on a master blacklist, Hoover’s Bureau followed a strict administrative lifecycle:
The Dossier Trigger: When an individual was flagged via covert programs like COINTELPRO, agents opened an investigative file.
The Index Card Core: If the person was deemed a threat, a dedicated index card was generated. These cards contained the person’s name, aliases, address, physical description, occupation, and a specific "detention rationale.
"The Geographic Apportionment: Cards were duplicated and cross-filed. One went into the master archive at FBI Headquarters in Washington, D.C., and another went into the local FBI Field Office responsible for the geographic area where the target lived.
The Arrest Portfolio: For top-tier targets, field offices maintained ready-to-go arrest portfolios. If Hoover or the President gave the command, field agents could immediately seize the individual without needing to waste time researching where they were or why they were being detained.
The Fluid Evolution of Sub-Lists
Hoover managed the master blacklist by segmenting it into constantly shifting sub-indexes based on perceived ideological threats, which allowed him to scale the operation up or down
As the lists ballooned to over 20,000 active high-priority targets (and over 10 million Americans cross-indexed in general domestic files), Hoover modernized his management using early technology. The Bureau adopted mechanical punch-card sorting systems. This allowed clerical staff to instantly filter the master blacklist by city, profession, or political affiliation, providing Hoover with rapid statistical snapshots of domestic dissent to present during congressional budget hearings or White House briefings.
Here’s a link to the exact same post on Cory Doctorow’s (tracker-free) blog: https://pluralistic.net/2026/08/01/dare-snot/#i-will-fucking-piledrive-you-if-you-mention-ai-again
Work keeps insisting we use it and I keep telling them to fuck off.
I get more done than my colleagues BECAUSE i don’t use the not-actually-AI “AI” tool.
The whole world is lying because that’s how we get fucking money. What a stupid hole we’ve dug ourselves.
I can’t say AI hasn’t changed how I work, it has. Instead of going to Google, vendor docs, or the manpage for whatever code or system I am working on I will ask Claude or Gemini to take a stab at building the initial pass of the code or to look up what some cryptic error code means for me. Or even a better way to write some code that I think can be more concise.
The key I think is I never let it make the final decisions for me. The workflow is always look up information > shows it to me > ask for permission to do the thing > do the thing.
But none of that is “changing everything” in the way executives and the Sam Altman’s of the world want to profess. It is just a sometimes more efficient for me way of doing the same thing I was doing before.
A lot of people I have seen that crow about how they are using AI to change their work lives are just doing really fancy Github workflows and actions to automate something they used to still do manually for some reason. They rarely are doing anything that couldn’t be done with the time to research and test without AI.
I see a lot of useless people creating a ton of busy work that just becomes an unbearable workload for the people under them. Working in manufacturing environments which (you aren’t gonna believe this) are all horrifically understaffed is bad enough. Now i get to watch good workers get buried under Solvace/Fabriq/etc checklists and Leading2Lean/PerformOEE/etc task lists and spreadsheets and meetings to discuss kpis and metrics.
I need a new line of work
Yeah, right. My boss gave me a bunch of risk assessments to read through and let slip that AI had ‘helped’ produce them. So I said I’d get AI to summarise them. All this vast computing power and climate damage is being used for bullshit.
That’s all an LLM is, a gas-powered bullshit firehose.
Person A gives an AI a list of bullet points and instructs it to expand the bullet points into an email.
Person B receives the email and asks AI to summarize it into bullet points.
An ocean of water could have been saved if the Person A had just emailed the bullet points directly, and the information transfer would have been far superior.
Well I wouldn’t recommend data & analytics right now, if you treasure your sanity.
Imagine tech debt accumulated over decades absolutely skyrocketing because LLM can generate thousands of lines of SQL or Python that noone understands.I mean, I’m sure the same applies to all tech sectors and likely worse. I do admit it also helps us fix and uncover some old and buried bugs. It’s just not used with any sort of care or long term plan.
I’m a long term contractor. Process engineer and Certified Quality Engineer with up to date ASQ certs. I can technically go anywhere but i really love manufacturing processes.
Hate to day it, but every industry has turned into that. At least in my anecdotal experience and my network’s anecdotal experience, useless people using AI to create shit that means extra work for others is happening everywhere. Not saying you should stay in manufacturing if you hate it, but just be aware that you probably won’t be leaving that issue behind.
I’ve seen nothing that AI can do that justifies the economic or ecological cost.
It has become impossible to tell managers mesmerised by artificial intelligence that the tools are not, in fact, helpful.
This is stupid. The tools are helpful. Overhyped? Sure. But to pretend they are in no way helpful is just wrong.
Nothing is helpful until you need help. The fact that you think AI is helpful for you don’t have to force me to use AI. If you pay me $100k+ per year and you force me to use your tools to do my job why you even hired me ? To force this cult on me or to do the job ?
It’s pretty normal for an employer to dictate what tools and applications an employee uses. If you prefer gitlab but your employer requires teamcity, you don’t really get a say, right?
However, if you think you can meet your deadlines without using a code generating AI tool, then don’t use it. Ideally, if they are as useless as you imply, no one will be able to tell whether you’re using it. The conflict should only really appear if they do increase productivity, and you refuse to use them, resulting in less productivity than your peers.
Company will be able to tell if you’re using it because companies behind sota models come with monitoring. You will have meeting with hr and your manager when you will be forced to use it even if you meet quotas. They will argument it that maybe you can do more and increase your normal quota with expected ai usage increase in productivity even if you had best productivity in team without ai and your productivity stays the same. Suddenly you will be under performing because you are refusing to use ai so you will be first to fire even if you are best employee. That’s how corporations work. They are monitoring usage because it costs them money. For big corporations they pay upfront to get discounts. Company also make many trainings and meetings to encourage everyone use AI models they pay for but nobody wanted.
The conflict should only really appear if they do increase productivity, and you refuse to use them, resulting in less productivity than your peers.
While it should be easy to point out where this helps, it very much is not in reality because AI accelerates execution on ideas, but corporations nearly always suck much more at deciding which ideas to actually implement in the first place.
I predict that the longer this goes on, the more useless, untested half-features will be stuffed into software and the more bloated “fall back” implementations full of duplicated spaghetti code will exist.
If the tools don’t stick around because it’s too cost prohibitive to keep using them, we’re going to be cleaning up after the bots for a decade.
It’s been a boon for personal slopjects for me. But that’s because I could never find time for execution in the past. Now I just have the (free tier) AI slop up my ideas.
useless half features will be stuffed into software and the more bloated “fall back” implementations full of duplicated spaghetti code will exist.
Which happened without AI, too.
Remember that AI, in whatever form or field, only has to be better than the average human in the field, to be useful to a company project.
Which happened without AI, too.
Sure, but not at this speed. The bots can churn out a mountain of non-sense that does not work faster than people can review it and the bots themselves will lie to you and say “it’s all implemented”.
For people who have clear ideas of what to implement but struggle to find the time, this is a big gift. You can work hand-in-hand with the bot and say “nope, not that, this” until it implements what you had in mind. For aimless corporations with “ideation” meetings who cannot stop coming up with terrible ideas that none of their customers want, it’ll hasten the process of them making their software worse over time.
That’s exactly what I’m seeing at my current company.
That’s a fair point, but it’s not an issue with AI; it’s an issue with corporate culture. Corporate culture can and does change, especially with advances in technology, but there will be a churn period where it’s chaotic and mistakes are made.
I agree with that as well. A lot of the problem with my current company comes straight from the executive leadership level. I’m afraid that the culture will only change when they change (or more likely, the company will eventually just go bust).
They bought the lie that AI will replace all of software engineering, whereas I see the picture more like this:
https://www.normaltech.ai/p/why-ai-hasnt-replaced-software-engineers
A CEO that thinks that they’re going to develop all of the software, even with Claude code, is nuts. They simply do not have the necessary skill set to run a software project even if 100% of the hands-on programming is done by AI. They are not going to be sitting there telling a machine to move things around on a web app. They are going to believe the bot when it says that “it is implemented”.
Honestly if they hired someone who refuses to use AI in 2026 it’s on them.
I don’t need you to use you turn signals, but it’s helpful. I’m pretty sure I could come up with a multitude of situations where your first sentence is refuted without contest.
I thought the turn signals were required by law
In a lot of countries it isn’t.
Or it isn’t enforced, which is about the same thing.
But technically different ( ͡° ͜ʖ ͡°)
I have tons of random receipts that come in every month that need to be captured, memoed, categorized and sent off to finance.
I made python to read image/pdf/whatever to text, easy.
I regex the value out, hard and fragile
I try to pull the vendors name out, just not reliable
Category… nearly impossible so i need to make some form of memory system to remember once I do it.
Python renames the file with input if it needs it and provides the meta
OR
python to text because it’s effciient
api call to Ollama and let my old 2070 work it out. (highly reliable)
python renames the file and provides the meta
It’s small, low power, hard to do with code, basically the perfect use case. This is a good use of AI
Go Rewrite FFMPEG in Rust… that’s a bad use of AI.
There’s a lot of people out there using it in ways that cost a lot more than human eyes and have horrible societal and environmental impacts.
There’s a lot of people using it for dictation, document triage and basic scripting where it has great advantages and isn’t making the world a worse place.
His article is at odds with a great deal of his book. I wonder if this isn’t just a grab to get hardcore anti-ai to buy it.
I’m not necessarily suggesting Doctorow is correct with this assertion, but on a macro scale what productivity gains will generate AI provide?
Yes there’s a few skills it’s good at coding, medical research, and image recognition being a few.
The genuine question is: has this improved everyone’s quality of life?
I work at a sales-first (read: no accountability) software company, ran by inept nepo-babies and a hostile VC. I frequently have to completely re-do all of the sales engineering work when a new project starts, because they refuse to standardize or talk to each other.
After enough time doing this shit by hand, I took my best examples from previous projects and had an agent “fix the errors based on the conventions I established over here”. Instead of going line by line on these big serialized data formats now, I do about 10min of checking the results and editing down the change log.
It’s wack that I have to re-do someone else’s job still, but at least I can force some version of standardization without killing myself on the tedious bits.
That doesn’t really answer my question. It’s changed your job, but has it improved your customers quality of life?
You’re getting direct examples of people its helped, and you keep brushing it off and asking what about everybody else. You’re obviously not going to get a single answer that affects everybody, and why do small successes not matter?
Because they’re not really successes.
No one here is saying AI has reduce their workload so now they spend half their time catching butterflies.
The answers are all saying that AI has automated some mundane task that wasn’t particularly important, and now they can spend their time doing something more interesting.
Is the changes to their role, multiplied by millions of employees, actually better for humanity or society?
In a way, this is what Doctorow is arguing: where is the data showing the productivity gains.
My follow up question is, how are these productivity gains being used, if they exist.
Aren’t you assuming productivity gains will lead to free time? Why? It never has. Most of us work a fixed amount of time and get paid for that time. Not the amount of tasks we finish if that can even be measured.
Salaries have also not increased with increased productivity long before chatbots came online. So they won’t suddenly increase now.
AI is much more just like a new laptop you get from work. The new device is faster, has more RAM and allows you to do more, potentially.
The big question is, if the purchase was worth it. Unlike a new laptop, LLMs are an ongoing cost to users and providers. Nobody except for GPU producers are actually making money right now. Hyperscalers make some of the money back they themselves invested into the companies using their services, but in the end the ROI looks pretty dim for anyone.
So even if there are real productivity gains, you won’t see people relax with their kids more. And even if these gains are significant they may not prevent a huge economic collapse so we all will have plenty of time with our kids in the end anyway.
AI has automated some mundane task that wasn’t particularly important, and now they can spend their time doing something more interesting.
That absolutely sounds like a win to me. Why is productivity gains the only thing that’s important? QoL is what matters. Unless you’re a capitalist overlord.
100%! I don’t understand how this is a hard concept to grasp. I’ve been able to make productivity gains, sure, but who gives a fuck? Even if my productivity is the same, my QoL is still much improved when I’m not buried in mundanity.
The problem here is that the technology is owned by capitalist overlords.
And their goal isn’t improving your QoL. If that was the goal we would already enjoy 4 hour work week long time ago.
It’s improved mine. I save hours (that I didn’t really have anyhow) on meaningless tedium. I thought that was pretty obviously implied though?
Maybe it helps to say that this was in no way forced on me. The stuff my employer has done to “adapt AI” is laughable and seemed to be nothing more than lip service to the execs who want to slap that sticker on the product.
The gains for me personally have been strictly using it as a tool in niche situations. I prefer to do things the hard way when it’s for me but I’m not breaking my back for a corporation.
But how do you spend the time you saved?
Either you’re arguing in bad faith by nitpicking for some reason, or you are incredibly dense. Do I need to send you my calendar dude? I just freed up some time, maybe we can hop on a call and I can spell it out for you?
I dont understand. That seems like a perfectly reasonable question.
If gen AI has saved you a heap of time, how do you now use that time that was saved?
I work in government and part of my job is writing memos or documents that nobody will ever read but that some congressional mandate requires me to have on file. I absolutely offload that to AI so I can do my real job.
What a grotesque job this is.
This is another answer that misunderstands my question. It’s changed your job but has it improved the quality of life of the public served by your office ?
With ownership being as concentrated as it is now (more concentrated than during the guilded robber baron age), naturaly, most of the benefit flows to the biggest owners, and AI seems poised to deepen the wealth inequality further.
In a scenario without the insane wealth concentration, and with a dignified and decent economic floor being guaranteed universally, I would be in favor of any AI that does not burn our planet to a crisp and stink up the neighborhood with the gas turbine exhaust.
So in our world as it is, I have to be agaisnt the AI for the foreseeable future.
Not yet because people are still learning how to use it, but im literally ten times more organized than i was before i started using AI to automate notetaking planning calendaring all that.
I’m happy for you but isn’t really an answer.
“Not yet” isn’t an answer??
It’s a response but when provided as an answer to the question “is AI a net benefit to society” then it’s a “no”.
Ok so it’s still an answer lmao
LLMs are like a dishwashers. You could wash all the dishes yourself and probably get them cleaner in less time, but it’s useful to let a machine do the work, even I though it’s mandatory inspect every single dish to make sure the machine got them clean enough and re-wash a certain percentage of them. Dishwashers are useful, but the world wouldn’t end if we didn’t have them. They also have the benefit of using less water than when do them yourself, which certainly isn’t the case with LLMs.
Part of the problem is AI isn’t a literal thing with a fixed definition. It’s more of a marketing term that translates into “I want you to buy this thing”. So some things are considered AI that are legitimately useful and others are not and then there’s the debate if wether it’s because it really is AI or if it is and AI just sucks.
In other words, corporate leadership is starting from the premise that AI has (or will) radically change the business, and they’re working backwards from that premise to find the evidence to support this article of faith.
This quote is quite funny in this context, because it’s literally what people do with AI. Half of the frontpage of lemmy is AI. The other half is people saying AI is bad with no realization of the irony, because they don’t see good AI. It’s like CGI. Everybody hates CGI, except they don’t. CGI is everywhere. They just hate bad CGI.
What is AI? Explain as if i just woke up from a coma. We don’t have flying cars, we have dumpster deloreans, but everyone is talking about AI. What is it?
AI is a vague term used colloquially to describe a variety of dissimilar and unrelated technologies each carrying a unique mixture of pros and cons.
So it doesn’t actually mean anything.
Like most things, meaning depends on context. In the most common context of “news about AI” we’re talking about generative AI: image/video generators, LLMs, and to a lesser degree coding assistants. If you want to know more about what these technologies share in common, look up what a “perceptron” is and how it works.
More generally AI could mean anything from a neural network based approach to problem solving, to a completely deterministic, hand coded heuristic. A pure decision tree could be AI in the case of video game NPCs, for example.
So it’s a new synonym for algorithm.
The utility of the term “AI” depends on what you’re trying to communicate.
Since that was a lazy question I decided to be lazy and just copy paste it into Gemini. Enjoy! I have no idea what the point of this is!
Artificial Intelligence isn’t a single technology; it has been a massive umbrella term since the 1950s. Broadly, it means creating computer systems capable of performing tasks that typically require human intelligence.
If LLMs are just one tiny branch on the tree, here is what the rest of the tree looks like:
Machine Learning (ML): This is the engine driving most modern AI. Instead of a human programmer writing strict "if/then" rules, we feed the computer massive amounts of data and let it figure out the rules itself. This is what powers your Netflix recommendations, credit card fraud detection, and the algorithm deciding what you see on social media. Computer Vision: Teaching computers to "see" and interpret the visual world. This is how self-driving cars identify stop signs versus pedestrians, how your phone unlocks when it sees your face, and how medical software spots anomalies in X-rays faster than human doctors. Robotics: The physical application of AI. This isn't just mechanical engineering; it is the software that allows a machine to navigate the unpredictable, physical world. This covers everything from the Roomba vacuuming your floor to automated factory arms and those creepy, dog-like robots from Boston Dynamics. Natural Language Processing (NLP): This is the branch focused on understanding and generating human language. LLMs live here, but so do older, simpler technologies like spellcheck, Google Translate, and the early versions of Siri or Alexa. Expert Systems & Rule-Based AI: This is the older, "classic" AI. It relies on a massive database of human knowledge programmed as logical rules. When the IBM computer Deep Blue beat the world chess champion in 1997, it wasn't using an LLM; it was using raw computational power to calculate millions of possible moves and their outcomes based on strict rules. Predictive Analytics & Optimization: The invisible math running the modern world. This is AI used by logistics companies to find the absolute most efficient routes for delivery trucks, or by hedge funds to execute high-frequency stock trades based on market micro-fluctuations.I asked the question to demonstrate something. You didn’t want to participle in the discussion and that’s fine, but that doesn’t mean the question is “lazy”
I didn’t provide you with an answer to your question?
This response is irrelevent to my post.
The later section addresses this
The other question Suresh implicitly raises is: “How can you reconcile the failure of AI in the enterprise with the individual claims of skilled technologists who insist that AI is helping them do great work?”
OK, but the point still stands if you allow that: It has become impossible to tell managers mesmerised by artificial intelligence that the tools are often not, in fact, helpful.
Sure, although I would phrase it I think a bit more pointedly: “it has become impossible to tell managers mesmerized by artificial intelligence that the tools are not, in fact, capable of what they imagine they are capable of.”
This points, rightly, at it being a failure on the part of the managers - not artificial intelligence. And God knows that’s spot fucking on.
It is a double edged sword.
If you’re already experienced developer and you use it skillfully, validate produced code it can help.
If you aren’t (and unfortunately everyone thinks they are better than they actually are), it actually can do the opposite, it can help generate a lot of junk code.
Now when working in a team usually majority of people aren’t that great developers typically there might be one or two star developers. The problem is that the other people will still use AI and generate MRs. Reviewing those is extremely time consuming and no one wants to do it. It’s weird to say what’s exactly wrong with those MRs they seem to do things but they seem to do things in a more complicated way.
The thing is that no one wants to review those MRs, everyone is afraid to point AI slop, so the quality of code goes down and even the people who previously were good are getting lost in the code themselves.
It depends on the tool to be honest. If it’s Claude code and you’re a programmer, sure that’s helpful. But often it’s an “agentic workflow engine” that’s been developed in house that’s complete garbage, or a chatbot that doesn’t know anything telling you that it can’t answer your question that was put together by your company. These custom tools are almost always not helpful.
Doctorow knows this as well, he writes about this crap constantly and has broken it down by user type in other pieces.
They have uses in certain circumstances. They also have lots of negative aspects (that are broader and more systematic, as far as I can see). I think in a net-benefit sense they are not, in fact, helpful (to an organisation, or to a society).
I was talking about roof sheathing with the latest chat gpt.
It was confident the joists should go above the sheathing.
You might want a 2nd opinion, did you ask Grok?
LLMs seem to be pretty bad at home improvement sort of questions in my experience. I suspect they don’t have a team of carpenters they use to RL the models, like they do for software engineers, etc
Software is easier because you can basically ‘inspect the house’ and the ‘home inspector’ via software.
Harder to do that with a house. Also a lot of different rules based on locality.
Reminder it doesn’t know anything.
It is just mimicking text it has been programmed for.
For it to be “good” at mimicking home improvement, it’s source needed to be full of home improvement talk. The best carpenters, plumbers, whatever aren’t on reddit, or wherever talking shop. They’re working, or making OSHA jokes at the bar.
How do people work? Are there ones born knowing how to use a hacksaw?
Mostly tradies are learning by hands-on apprenticeship with a master. All that discussion is not on the internet.
How did anyone ever learn anything before chatgpt?
Personally I would ask my aunt and she would be wrong.
The better question is how will anyone ever learn after ChatGPT
I can’t be the only one who will have a hard time for me to trust any professional who became qualified after 2023.
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I work in construction and so far I must admit that I have no idea what the hype is about.
But I have decades of experience, meaning I don’t know shit about anything BUT I know how to quickly find usefull information in the codes or in pertinents books.
If I were younger I might have fallen into the trap. If so I would probably be in jail by now, because in my tests I’ve seen LLM be dangerously wrong.
Vibe construction