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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
The core issue feels like the dead torrent problem.
Its distributed, so it needs to be hosted, by several locations. Which becomes probitive over time as.it becomes huge. Its also massively inefficient for what its trying to do.
At some point, its basically just one server farm somewhere hosting a glorified MySWL database that doubles as a space heater for the entire planet every time you need to add a row.
I was thinking that with legal backing, blockchain could be a good record of ownership for deeds. Like NFTs but for physical property.
The history of ownership and the public visibility are good features there.
Lack of reliable, authoritative attribution of changes and no rollback or compensatory transactions are all dealbreakers.
Yeah who doesn’t want a ledger you cannot change, sounds like a good idea. /s
In the case of deeds, i think it is desirable because it gives you an immutable history of ownership.
There are other problems but i don’t believe that is one.
No it doesn’t. It only works because 51% doesn’t change the ledger.
You already have this with a simple database for ownership. It already exists, and ledgers made out of paper predates that.
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?
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.
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.
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.
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.
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
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.
That “AI” is a completely dumbed down one with reasoning disabled. Of course it’ll make stuff up.
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.
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?
You’re lost in the sauce. Do you know any other writers in real life? How do they feel about this?
Could you tell me which part of my argument you think is wrong?
You didn’t make an argument, you listed your justifications for using plagiaristic genAI as a shortcut instead of doing the actual work yourself.
I did make an argument. My argument is that authorship is grounded in the origination of the ideas and intent, control over what goes into the work, endorsement of the final form, and responsibility for the result. Assistance with the linguistic realization does not, by itself, transfer authorship.
I’ve thought through that position, refined it, and I’m willing to defend it. Calling AI use “plagiaristic” or a “shortcut” doesn’t actually address the argument.
So which part do you reject: that I originated the ideas, that I exercised control over the final work, that I endorsed it, or that I’m responsible for it? And why?
None of “your work” is yours in any meaningful way the second you use a tool that cannot exist without plagiarism therefore any aspect of its contribution immediately forfeits all ownership of the ideas conveyed. Because they’re not yours, they’re stolen by an inherently plagiaristic tool. Unless you’re using a local model trained exclusively on your own writing, none of your AI powered work is in any way yours. Even then it still wouldn’t be original or created by you, it would be algorithmic nonsense. You are not a writer if you use an LLM to do the actual writing. Couldn’t even write that fuckin response without your gpt slop.
I spent this morning sitting with this exchange, coffee in hand, reading back over what I had written.
I’m not especially interested in responding to the insults. And I’m going to set aside the argument about how AI systems are trained, plagiarism, consent, compensation, and so on. Those are legitimate ethical questions and I share them, but they are a different conversation.
The part that stayed with me was the simpler claim underneath all of that:
“You didn’t write this.”
And the more I thought about it, the more I realized that my original answer had blurred together several different things.
I had been treating “writing,” “authorship,” “ownership,” and “responsibility” almost as synonyms.
They aren’t.
You can originate an idea, develop an argument, direct how it is expressed, edit it, approve the final version, and take responsibility for publishing it without necessarily having composed every sentence yourself.
Nickiwest had responded to my original comment and said “That sounds more like the job of an editor than the job of a writer.” and that got me thinking about my old work as an art director for a studio.
I could come up with the concept, find references, explain what I wanted, reject drafts, change direction, combine ideas, and go through revision after revision until the finished image expressed what I had in mind.
That was real creative work.
But I still wouldn’t say I drew the picture.
The idea might have been mine. The direction might have been mine. The judgment might have been mine.
The drawing wasn’t.
I think AI creates a similar complication with language.
If I give an LLM a thought and it produces a sentence, then no, I did not necessarily compose that sentence in the ordinary sense.
If I argue with it, reject things, rearrange them, rewrite parts, refine distinctions, change the reasoning, and decide what survives, then I have obviously contributed something substantial. But calling every form of that contribution “writing” may sometimes be too simple.
Sometimes “writer” will be perfectly natural.
Sometimes “editor,” “director,” or simply “AI-assisted” may be more accurate.
What interests me more than the title is what happens during the process.
I can put a half-formed thought into language and look at it from the outside.
Sometimes I read a sentence and realize, that sounds like something I believe, but it goes further than I mean.
Sometimes two ideas I had been treating as the same turn out not to be the same at all.
Sometimes an argument looks convincing in my head and falls apart the moment I see the missing step written down.
Sometimes the model gives me wording I dislike, and figuring out why I dislike it forces me to understand my own position better.
Then I put that thought back in and try again.
The result I am looking for is not better prose, it is a better thought.
That is basically what happened to me this morning.
My original position was that the work was mine because I chose it, shaped it, approved it, put my name on it, and accepted responsibility for it.
I still think responsibility matters enormously. If I publish bad reasoning, false claims, unsupported accusations, or generic slop, I do not get to shrug and say, “The AI wrote it.”
I chose to publish it.
But I no longer think responsibility settles the question of who “wrote” something.
An editor can be responsible for publishing a piece without having written it. An art director can shape an image without having drawn it.
So now I think the more interesting questions are smaller ones.
Who originated the idea?
Who developed the argument?
Who decided what belonged?
Who noticed the mistakes?
Who revised the thinking?
Who directed the expression?
Who actually composed the prose?
Those answers may not always point to the same person, and maybe that is fine.
What I don’t think follows is that the human contribution disappears the moment a machine becomes involved.
My ideas do not disappear. My judgment does not disappear. The things I accept, reject, revise, and ultimately stand behind do not disappear.
But neither do I need to pretend I personally composed every sentence if I didn’t.
I’m comfortable with that distinction.
And I think it leaves me somewhere more interesting than where I started.
What fascinates me about A.I. is the strange process of having a thought, seeing it reflected back, noticing where it fails, and slowly discovering what I actually mean; what I believe.
This reply is a product of that process. I do not care what title we end up giving the result, I enjoyed spending my morning with 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?”
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.
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.
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.
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.
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.
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.
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.
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
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.
AI is changing everything. Its not a lie, its absolute truth.
The problem is the changes are fuckawful terrible for everyone and everything.
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’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.
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.
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.
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?
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 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.
In the same line of thinking, this is why I hand wash my car, because the automatic car wash either does a bad job (touchless) or will scratch the paint up all over (brushes). Many people don’t care very much about their cars though, so why put in the effort?
I find unreliable tools to be one of the most infuriating parts of my job, and unfortunately my entire job has effectively pivoted to spending all day babysitting an AI that frequently ignores instructions and can’t learn without a ton of expensive fine-tuning training.
I don’t let AI touch any of my personal code I care about, and with how much of the code at work is written by AI, it’s pretty demoralizing. Why put in any effort designing something if it’s just going to get blown away by a coworker’s agent the next day?
Arguing with the AI over why its code review is wrong is also a whole other part of my day now…
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.
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.
AI is any compute model performing complex enough reasoning that the output does not always resemble the input. They are by definition non deterministic and the same ask can provide different outputs without being influenced by other inputs.
So its a lottery
No
I put in a 5 and get a triangle. I put in the same 5 again and get a transvestite. This is intended behavior.
That system isn’t a magic box. It’s a bag of variables linked together by statistics and what’s basically automated guessing.
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?”
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 generally respect this guy’s opinion (I probably use the term “enshitification” multiple times a week!), but pretending that “AI” and “Chabot” are interchangeable terms seems wildly reductive, and the subtle presumption that the process of changing is a binary changed/non-changed situation instead of a curve is just ignorant.
If the internet was “turned off” after 4 or so years not much would have changed, either.
To the average person (and this includes politicians, basically anyone not a software engineer developing the tools )who Cory generally writes to try and inform, they are the same.
Should they be? No. But that’s a whole different thing and trying to change that in the general public mind doesn’t change his current point about AI as the public thinks of it right now.
Speaking at the level of your target audience is wise, but there is a point where information is not just simplfied, but lost, and I think equating chat bots with AI in the broader sense is past that point. It would be like equating websites with the internet.
I think the comparison is acceptable with maybe a terminology clarification in the footnotes, because “AI” is the false term under which this current bullshit is being marketed.
And people who believe the core mechanism in large language models to be AI are so uneducated that they will probably neither understand the distinction to legitimate AI research, nor bother to read footnotes.
That’s exactly the thing. Those who understand such a footnote don’t need it, and those who might learn more from it are unlikely to understand it. The above commenters are simply being pedantic.
Pedantic or AI bros ;) I find this new generation of gullible tech users scary. Recently saw someone voice their disappointment with Codeberg’s anto-vibecoding stance, and the person was describing themselves as “tech optimist”, which I believe is a great way to self-out as being extremely gullible.
And people who believe the core mechanism in large language models to be AI
What does that mean? Transformers aren’t AI? What? I don’t think you understand this as much as you think you do.
Think all you want, statistical text prediction has nothing to do with AI. The “intelligent” algorithms are all in the pre- and postprocessing steps that make the output sound good enough to fool gullible people into assumong intelligence.
Is equating chatbots with AI any different than equating a bunch of if/else statements with AI? Is any of this AI considering none of it involves actual intelligence or informed decision making?
Sure AI is more than LLMs, but those are the face of it in the public’s eye and is what’s driving these trillion dollar corporate valuations, which then lead to every company on earth declaring that their product is “AI!”
What’s lost? I can’t think of anything.
Words are meant to convey meaning, and I bet you would lose a lot of non-technical people if you tried to explain the intricacies of what makes large language models worse than content recommendation systems, and doing this would be redundant for technical users.
So Corey can safely use the two words interchangeably and communicate with technical and non-technical alike.
As a non-techie: websites are the internet.
Like, I conceptualize the internet as basically just a giant shared network, but the point of it is the websites (for me).
I apologize to anyone I may have just gravely offended.
I apologize to anyone I may have just gravely offended.
lol
I don’t know how “non-techie” you are, but a good example is online games. When you’re playing Fortnite, Roblox, World of Warcraft, etc you’re not going to a web page, but you’re on the internet.
I straight up almost called it a series of tubes, lol.
Yeah, that’s probably why I do think of it as a shared network, I just don’t play online games, so that’s not what I associate with the internet.
There are other examples but I take your point.
Cory generally writes to try and inform, they are the same.
then he has completely failed to understand the concepts for people using him an a information proxy
isnt he supposed to help inform? or is he just an echo chamber to the lowest-common-loudmouth?
Stepping up and doing it better is free.
Too busy using AI at work to make everything easier for my coworkers and earn another raise
Good luck when they stop subsidizing the tokens 👍
I already got two raises in the past 18 months and it brings me joy to see things happening at work more efficiently, all on 20$ claude subscription, that’s fine ill pay $100/mo for the same stuff in a year, easily worth it (my employer pays it anyway)
Sorry if it replaced your only marketable skill or something, and we absolutely should have universal basic income for these kinds of cases!
I think you’re making a strawman argument here. He isn’t arguing that it’s a binary switch that has failed to throw, he’s arguing that we don’t have compelling evidence that the ends justify the means:
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.
And this is completely true! Supposedly “data informed” organizations are trying to find a yardstick that shows actual, meaningful improvement in business outcomes from AI. In my own organization we have people touting LOC yet again because “big number”, but anyone who’s ever worked in software can tell you it’s an asinine metric to use as a KPI.
It’s inherently unscientific to start with the answer and work backwards to a satisfactory question. His point that this push is coming from the least knowledgeable of real processes- and more closely resembles religious fervor than business acumen- seems to at least warrant consideration.
The world is full of people who insist that “AI is changing everything” but who – when pressed – have to admit that what they mean is that they’re pretty sure that AI will change everything.
If Donald Trump ordered Big Tech to turn off all of your country’s chatbots tomorrow, nothing would change. Every one of your country’s ministries and corporations would chug on with nary a hitch. Households, too, though perhaps a few of the younger members of those families would have to do their own homework again.
He is definitely pretending that change is either on or off.
Are CEOs jumping the gun on how quickly they adopt AI into workflows? Definitely. However, there’s a big difference between “AI isn’t at a threshold where it is disruptive” and “AI isn’t disruptive”. Or, to belabor the metaphor: CEOs are jumping the gun, but the race is about to start and they’re on the correct track.
If you watch a full podcast (he has done a ton in the last couple weeks), he clearly identifies AI as not a mere hype technology, as something interesting and potentially useful from a technology perspective, and he definitely doesn’t conflate a chatbot with all AI. That doesn’t undermine the vast problems with it, how it’s being used against regular workers, the threat the bubble poses to the economy, the criti-hype cycle, etc.
I think you’re oversimplifying “Cory Doctorow” based on the article you’re reading or specifically how he presents a more complex idea to different audiences.
Watch the Jon Stewart podcast interview if you want more nuance:
A key word in that sentence is “if”, it is a rhetorical example, that’s probably pretty much correct at this point. It’s not a recommended course of action, it’s a declaration that it contrary to crazed hype, it isn’t currently as core to everything as would be befitting the current hype level.
I would argue that the CEOs aren’t on the correct track, they aren’t really in a particularly specific trajectory. I just had a debate with someone on this and their stance was “well in a hundred years do you expect things to be like they are”. My response “I cannot possibly speak to that, but we need to speak to today instead of pretending we know how things will be in a hundred years and pretending they are already at that level”. The “imagine a hundred years from now” by a relative outsider to the tech is dominating CEO mindset, and that’s problematic.
Once the bubble pops, we will almost certainly see a more durable and sane adoption for these technologies. For now, the hype is a problem as it enables some of the worst possible stewards of the technology and favors grift over progress.
Corey Doctorow isn’t speaking to you, he’s speaking to the many, many people who have been fooled by the ai craze.
And often I wonder, how many people have been fooled, and how much of the enthusiasm and over the top fantasy is astroturfing by a few people incentivized to sway public opinion?
And how much of the doomerism is a campaign to keep the common man from using a revolutionary tool for, well, revolution, by alienating those most likely to do revolutionary things with it?
Once you look at the actual numbers for pollution, water usage, etc it becomes very clear that the issues are vastly overstated. So, why?
That’s one for the fooled side.
Yeah. I guess we’ll see.
EDIT: you should go on claude’s reddit and look at all of the tools people have built to keep companies and politicians accountable, to renegotiate billing, to improve their lives at the expense of capital. Or you can just go on thinking you’re right!
Fuck reddit but i have a friend who automated fooa requests with claude, sent foia requests to every county in the state and has all the tracking and everything automated. Only thing he needs to do is review the emails before they get sent. It’s amazing and he’s bring transparency to every corner of the state using ai.
Yeah I personally use it to analyze public data bases for fraud.
I keep comparing the datacenter numbers to Bitcoin - only BTC, not all of crypto, is still using more electricity than AI. That may change in the future, but JFC people, where was the outrage about the global Ponzi scheme?
“AI” and “Chabot” are interchangeable
In the same way that most people if you say you’ll take them to their destination with your vehicle, they assume in your car and not on the back of your bicycle, although both are technically correct.
I generally respect this guy’s opinion (I probably use the term “enshitification” multiple times a week
A lot of people don’t use it the way he used it though. He used it specifically for two sided markets (eg a service that has both businesses/advertisers and personal users) where the focus shifts to the business customers, but people have started using it to mean anything that used to be good but isn’t good any more.
If the internet was “turned off” after 4 or so years not much would have changed, either.
That’s a questionable statement that may reflect on your main argument. After all, when was the Internet “switched on”? Sounds very binary to me.
To be clear, Doctorow discussed switching off AI and proposed that there would be little to no change on the world. I was just changing the technology to show the flaw in the stance.
and thereby revealed the flaw in your own counterargument.
Can you elaborate? I’m not following what you’re saying.
I think it’s a worthy simplification that sums up the current state of things well. We have AI that broadly has different uses and then we have the ChatBot/ChatBot derived AI applications. The market is not going insane over the broader AI category. Executives are not tripping over themselves to say things like machine vision is going to replace all labor, or at least all white collar labor. The chatbot is the only thing in the conversation of consequence.
All the “everyone says AI is the reality, so everyone feels like they must say AI is the reality” refers to this specific category. It might be veering towards being oversimplified, but it’s trying to balance a perspective that is also oversimplified. Generally, we aren’t good at weighing simple straightforward takes against complex nuanced takes, so you have to “net it out” to have any hope of the point landing.
“Chatbot” style AI is wildly good and bad at varying kinds of tasks, and a lot of that has to do with how it has been prepared.
Some LLMs have been trained to make images - I’ve not been too impressed with them, but that’s what they’re “good” at - and better than the LLMs that have been trained to write computer code when you ask the coding LLMs to draw a picture.
The code writing LLMs have actually improved the most at reviewing code over the past 8-9 months, and that ability to review their own code makes them dramatically better at writing code as well.
I find Google Gemini to be pretty impressive at scanning laws and regulations and finding, not creative, but functional solutions to stated problems within the constraints of (often frustratingly bizarre) legal structures.
And all of them will lie to you, tell you what a great idea you have, etc. They’re not really lying, they’re mostly just taking what they read at face value without checking corroborating sources enough to find the obvious (to you) blunders. If you want the LLM to be sure, ask it to go on the RAG (Research Augmented Generation) - check everything before saying it, they can do that, especially “paid mode” engines, but it reduces their capacity for analysis of complex problems by 3-10x, because they’re spending so much context window “being sure” - you can alternatively spend 3-10x as long solving complex problems / accomplishing complex tasks if you have them do their homework, verify everything from “the best” available sources 3x and build up a local document set of “trusted information” which is used in preference to whatever it might find at random on the internet. This isn’t as sexy as “Hey Claude, code me up a database that does X Y Z” and getting the result in 30 seconds, but it is how professionals have been doing their jobs for centuries: learn reliable information first, then act on it.
Pretending AI and Chatbot are interchangeable is a marketing strategy by the companies who make these advanced chat bots. “They are artificially intelligent bro”.
I don’t disagree that the term AI has shifted significantly in the last 4 years or so, but I was actually meaning it in the other direction, as in, there is more to generative AI (what people are calling “AI” these days) than just chat bots.
Oh look it’s arbitrary-narrow-definition-that-fits-the-argument-I-want-to-make man!
Oh look it’s arbitrary-narrow-definition-that-fits-the-argument-I-want-to-make man!
I’m saying there’s more to generative AI than chatbots. My definition of AI is broader. What are you going on about?
That your definition is only advantageous to the argument you want to make. Everybody else understands “common usage” by non-technical folks. I’m a “technical folk” working in the area and I understand the “common usage” by the “regular folk”.
Honestly, I didn’t jump on the AI hate train like everyone else did. And I was wrong. I literally only use it to make profile pictures on steam to make a sekiro photo. Other than I literally can live without it.
And at this point all of the damage it is doing to our communities; I am angry at this point that people in positions of power are blatantly ignoring the people they represent who say they don’t want this. This is almost as bad as the epstein corruption. Just blatantly lying to our faces and ignoring frustration.
Not just ignoring it but trying to grift to their supporters that these ‘contrarians’ aren’t Americans and flew in. I’m so unbelievably sick of conservative influence in my home country just using lies as a real mantra. Because everyone around me values money over anything else and it seems like they genuinely are dissonant and don’t understand this is a bubble waiting to burst unlike anything we have ever seen.
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
I’ve seen nothing that AI can do that justifies the economic or ecological cost.
AI is changing everything… Mostly to bad, that’s the part they keep.
