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PaperclipPerfector  5mo ago (text post)   26110 thread views

Culture War Roundup for the week of February 23, 2026

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The psychic cost of AI is already here

Ugh, another AI post.

Today Block laid of about half its 10k employees for AI reasons and the sock soared. Was this pr cover for shedding bloat? Maybe. Elon famously slimmed down Dorsey’s crazy bloated twitter, no AI cover story needed.

But still, the market loved this and will demand more.

Earlier this week IBM stock dived on some Anthropic COBOL skill. Was this premature doom? Maybe. But still.

Let’s put aside whether AI will destroy white collar work in a short term time horizon. Despite the outcome, the idea that it very much might is already mainstream. It’s in the water. How much is the impending fear already shaping decisions? How much psychological weight is it already causing? How much will it accelerate

Certainly people are already changing career plans, college plans, savings strategies, family planning, etc. and it will only get much worse. New broadly available opportunities in AI are not going to open up faster than the fear of AI disruption will spread; we are already in a spiral.

Like many in these spaces, I’ve been worried for a while now, but now it’s going mainstream and will cause aggregate changes in behavior which will have their own effects on society and the economy regardless of the first order effects of AI disruption.

As a minor example, my wife has wanted to move for a few years now. Unfortunately, we’re chained to a 3% mortgage without enough income to achieve escape velocity beyond moving sideways to pay more. We’re finally in a spot this year where we could be a little indulgent and justify moving into a house the right size for a young family of 7, even if means taking on some unoptimized mortgage rate increase.

But I can’t imaging compounding that risk with AI disruption. The music could stop and never start again. Our marriage is good, but my resistance causes its own minor stress. How many marriages aren’t so good, break down over things like this?

How many people don’t get married altogether, etc.

Regardless if Covid was just a flu, the real world response to the percieved threat was transformative. Regardless if AI is just a fad…

and the stock soared

30% of those gains have already evaporated and we're only 3 hours past market open. Maybe wait and see a little to see how the market prices this in with more time to consider.

[conflict of interest disclaimer: I have a modest short position in XYZ (Block) as of a couple hours ago]

You're missing the point of my post. I am emphatically not making any prediction about AIs first order effect on anything, including the market, much less an individul company's stock price. I am pointing to examples where it's already producing mainstream headlines, and (although early) seems to be quickening and broadening in it's reach. I am suggesting the depsite the realities, the costs of the narrative are surely already affecting real people.

Do you not thing there weren't CEOs out there who are udpdating on these stories? Hiring manager who update or hesitate on this news? White collar workers, who rethink their savings plans?

My whole point is not the effects of AI on the economy, which remains to be seen, but the effects of the anticipation of those effects on society, which is here today.

We don't have to agree on the CFR rate of Covid to note that schools are already closing, business trips are already being cancelled, toilet paper is already running out. 'Maybe wait a little and see how the CDC responds' is misunderstanding a comment that is specifically - regardless of how and whether this deepens and whether it's overblown, the effects are here and starting today.

You yourself gave an example of making a financial decision based on this news.

Oh I agree that the effects are here, if that was the point you were making. I didn't realize that was controversial - even in my more mainstream bubbles (non-tech friends and family) people have been freaking out for about a year (in my tech bubbles they've been low-key freaking out since AlphaGo and high-key freaking out since GPT-2).

I do agree that mainstream society is not sufficiently pricing in the magnitude of the coming changes. I think that the tech bubble is doing a better job of estimating the magnitude of the changes, but frequently getting the sign wrong in terms of the anticipated effect on any particular metric.

As a software engineer at a company pushing AI use pretty heavily this whole thing is crazy making. If nothing else AI has some of the people that are the best at branding on its side. At least on the implementation side that I've done with copilot an "agent" and a "skill" are just markdown files. Their documentation is very clear about this.

The idea with a "skill" is there's some repeatable task you might want an AI to do and you hit on a particularly effective prompt that gets it to do the thing. You codify that prompt in a markdown file in a special directory. Then when you ask your more general session to do a thing it can look in that directory for applicable skills and if it thinks one is relevant it will inject its contents ss context.

"Agents" are similar. I thinks it's been known for a long time that if you prompt the AI a specific way ("You are a software engineer proficient in ...") they can perform better at certain tasks. Agents work on this principle. As best I can tell the use of an agent can either be selected by the user or your general AI might select one based on criteria similar to a skill. It then starts a sub-session where the contents of the agent markdown are injected as a kind of pre-prompt before your actual prompt.

So when you hear Anthropic has created a skill or agent or whatever that can do X you should mentally replace that with "wrote a markdown file." "Anthropic published a new skill that makes AI good at COBOL" == "Anthropic published a markdown file that, when injected in a session, makes an AI good at COBOL." Of course, things start sounding more insane. "Tech security stocks dropped on news Anthropic wrote a markdown file." "IBM dropped on news Anthropic wrote a markdown file."

There's a slight nuance in what the market is actual reacting to. The news, and I agree this was over determined so the stock market was really behind on it, is that creating that .md file worked at least well enough to be endorsed by anthropic. Anthropic could create a markdown file that instructs claude to instantly cure all disease and grant immortality but it wouldn't work so anthropic wouldn't endorse it as working and the market wouldn't move.

Today Block laid of about half its 10k employees for AI reasons and the sock soared.

I was there. AMA

For the completely ignorant, such as myself, what is Block and why should I care? also, were they financially over-extended and this is just a way of reducing headcount and costs, but wrapping it up in "no no, we're not firing anyone because we can't afford to pay them, we're replacing them with our sexy new AI!"

Block is most well known for making the Square payment terminals and Cash App. The company overall is profitable but has been experiencing poor growth, leading to dissatisfaction among investors.

I'm seeing some reports that the company is also slashing raises and non-salary compensation like equity grants. Is that true?

No. They want to keep those who are left rather than attrit more.

Did you feel like the employees there are/were heavily using AI in their regular job to become more efficient now? Do they have have agentic AIs that can totally replace some people's jobs?

In my admittedly biased opinion, employees who used alot of AI shipped a lot of shitty slop code, while not actually producing that many more PRs overall.

I love chatbots but I hate agents though.

I love chatbots but I hate agents though.

That seems to be where I and a lot of my coworkers are landing these days. The chatbot interface is like a portal into an alternate reality where StackOverflow actually tries to be helpful.

That's... uncannily close yo my experience. No more must I try to find a forgotten answer to how to do something in Excel, I just ask the chatbot!

But where will you get your recommended dose of crazy autistic neckbeard condescension?

Why, here, obviously.

Will the company become more effective and profitable now?

Maybe. But not because of AI.

IBM is down about 5% on the week. Painful but not five alarm fire.

No, I don’t think it’s a fire Alarm. I’m not making a claim about the actual immediate affect of AI, but about the perception and how it is going mainstream. A few weeks with 1-2 headlines a week, and I think we get some level of self-fulfilling prophesy as the aggregate behaviors of worried citizens has a material effect

That’s fair. People see the headlines but don’t see the recovery.

The AI bubble is going to pop this year. Private equity no longer has enough money to continue to fund massively unprofitable OpenAI and Anthropic, or even the NVIDIA chip glut. A lot of these layoffs are either performative attempts to raise stock prices, or cutting fat that would have been cut a long time ago even if AI wasn't a thing. As long as you don't have all your savings in AI companies (or are over invested in index funds), and can avoid getting fired in the next 6-10 months, I think you will be okay.

Further reading

What would you invest in that's not index funds? Are you talking about buying real estate (which takes way too much work), buying specific stocks of non-ai companies, mutual funds, something else? I'm pretty illiterate on how to invest money, so I just stick it all in index funds. It's done very well for me so far, over the past 7 or so years, and moreover, the people I generally tend to trust about investing seem to tell me that that's the only non-risky investment.

The problem with index funds right now is that NVIDIA is ~10% of the S&P and the rest of the index is heavily invested in tech. I think the idea behind index funds is sound, but the current distribution of the market is heavily skewed towards a few companies, which I think is risky. I would seek out alternative index funds that don’t have this bias. I will give you better advice on this in a few weeks when I’ve made the transition. Right now I’m mainly invested in govt bonds and individual stocks, which maybe isn’t sound.

Yup. A way to downsize aggressively ahead of the possible next recession/ possible attempted realignment away from the USD before it hits, in a way that increases hype valuation.

Maybe AI happens and they fire everyone, maybe it doesn't and they are better positioned to ride out the next catastrophe, maybe everything stays the same and they take a 3% haircut rehiring everyone. Win/Win/Eh its fine form their postion.

"Oh? What's that? You Work For Wages Producing Goods Or Providing Services, And You Need Money To Live? Have you considered either owning assets or fucking dying instead, you broke ass bitch?"

To be clear, my thesis is not whether this is a bubble or not, rather the fact that already today, the fear is in the water and causing a mental toll on people and will affect decision making. Even if it pops in a few months, 1. That’s enough time to compound effects and 2. Does the shift in perspective just disappear?

Consider AI videos. That is certainly going dissuade may people from going to Hollywood or from seeing filmmaking as a career. Even if AI video capability stops right here and never completes the full verisimilitude, it is a bus stopped right on the edge of a cliff, and the will have a psychic toll.

Consider AI videos. That is certainly going dissuade may people from going to Hollywood or from seeing filmmaking as a career.

There is already an enormous glut of artists, to the point where I had people just randomly message me on Discord in an attempt to get a commission to make some art. And this was an issue already before AI. If anything, we need more people being dissuaded from entering creative fields.

Ahh I see. This is a much trickier problem. I think your concerns are very valid.

As Lizzardspawn says, the financial implications for a handful of AI companies will mean little to the actual deployment of current AI technology. The bubble bursting does not mean that LLMs simply go away, just as the dotcom bubble did not result in everyone switching back to fax machines and physical mail.

These models showed some immediate promise in their ability to articulate concepts or generate video, visuals, audio, text and code. They also immediately had one glaring, obvious problem: because they’re probabilistic, these models can’t actually be relied upon to do the same thing every single time.

This is outright wrong [1]. It’s trivial to run an LLM deterministically. Just do greedy decoding (or beam search, etc.) The fact that the author doesn’t know something so basic about how to use LLMs now makes me doubt that he knows enough to predict what they will or will not be able to do in the future, so I stopped reading here.

[1] Barring nitpicks about subtle non-determinism due to hardware differences or software environment differences across machines. Also, LLMs (particularly older ones) can be highly sensitive to specific changes in their inputs, but this has nothing to do with LLMs being probabilistic.

I think you can trivially make an LLM deterministic in the technical, narrow sense that for exactly the same input you get exactly the same output. Just initialize the pseudo-random number generator deterministically.

However, where LLMs differ from most classical deterministic algorithms is that they are not stable, a small change in the input might result in a big change in the output.

Suppose I have a list of strings I want to sort lexicographically. If I use std::sort (and stick to ASCII), I can expect to get reasonable results every single time. If instead I give the task to a neural network, such as a human, I will get some significantly non-zero error rate. If I use an LLM, I would also expect an elevated error rate. Of course, both the LLM and the human might also refuse to work with certain strings, e.g. racial slurs.

Generally, nobody uses neural networks to solve problems which are easily solvable by classical algorithms, teaching aside. But there are a lot of problems where we do not have nice classical algorithms, such as safely driving a car through the city or translating a text or building a website from informal specifications. So we accept the possibility of failure and hand them out to LLMs or grad students.

Just initialize the pseudo-random number generator deterministically.

You can get determinism from an LLM in a much cleaner way than by setting the PRNG seed before every forward pass. An LLM takes in an input string and spits out a list of numbers that tells you how much it wants to say each possible word in response to the input. If you convert this list into a probability distribution, then you can sample from it and you get nondeterminism that way. But you can also just take the word with the highest score as your output, and there's no nondeterminism (at least, without getting into nitpicky territory) involved.

Your point about stability is well-taken (hence why I said that "LLMs (particularly older ones) can be highly sensitive to specific changes in their inputs"), but it's not quite the same as saying that LLMs are unreliable because they are "probabilistic" (which is what the original author said). I know that this seems like I'm obnoxiously going "well, AKCHYUALLY", but if I'm going to read an 18.5k-word article about why AI is in a bubble, which would seem to require a lot of insight into the fundamental limitations of AI systems, which in turn requires knowledge of basic facts about how they work, then I would expect the author to demonstrate that he has that basic knowledge.

I read a couple of paragraphs ahead and, in addition to lumping image generation models with LLMs all under the banner of "generative AI" [1], the author writes

Moreover, the probabilistic nature of generative AI meant that whenever you asked it a question, it would guess as to the answer, not because it knew the answer, but rather because it was guessing on the right word to add in a sentence based on previous training data. As a result, these models would frequently make mistakes — something which we later referred to as “hallucinations.”

Hallucinations are not directly related at all to the fact that LLMs (which he just calls "generative AI") are probabilistic. There is nothing preventing the existence of a probabilistic model that puts zero probability on sequences expressing hallucinations. The "because it was guessing on the right word to add in a sentence based on previous training data" explanation is closer to the truth about hallucinations, which is that the LLM pretraining objective rewards merely modeling plausible text rather than correct facts, but it ignores all the other stages in LLM training that reward correctness -- most notably RLVR (reinforcement learning from verifiable rewards), which explicitly only rewards the model when it yields a correct answer to a verifiable task, and which is responsible for most of the large strides that LLMs have made recently in coding and math.

Speaking of coding, I skipped down to the section titled "To Summarize: Coding LLMs Don’t Actually Replace Software Engineers, and Never Will, Due To The Inherent Unreliability Of Large Language Models", and found this naked assertion (quoted approvingly by the author):

The Harry Potter series is a good example. In French, Hogwarts is Poudlard, which translates into “bacon lice.” Why did they go with that, instead of a literal translation of Hogwarts, which would be “Verruesporc?” No idea, but I’d assume it has something to do with the fact that Poudlard sounds a lot better than Verruesporc.

Someone had to actually think about how to translate that one idea. They had to exercise creativity, which is something that an AI is inherently incapable of doing.

There's no explanation of why an AI is inherently incapable of translating "Hogwarts" into French in a nice, idiomatic way. Hell, there's not even any evidence given that AI is incapable of this. If this is the level of argument given in the post, then I'm inclined to believe that my initial assessment of the piece's quality is correct. Which is a shame, since I'm largely hoping for an AI bubble.

(Also, just to be safe: I did not use any AI in any way to write this comment, nor any other comment.)

[1] Now, image generation models are inherently probabilistic, since diffusion models and GANs require a random noise vector.

I am with you on your overall critique, anyone who today states confidentially that LLMs will never achieve a particular milestone is oblivious of the skulls of all the other AI-skeptics who became victims of Clarke's first law. (Which is not to say that the negation is true, reverse stupidity is not intelligence and all that. Instead, I would prefer epistemic humility, where any outcome from 'LLMs are as good as they will ever be' to 'ASI and paperclips' have a non-zero probability.)

However, where LLMs differ from most classical deterministic algorithms is that they are not stable, a small change in the input might result in a big change in the output.

This is not unique to LLMs. This happens to pretty much any algorithm that feeds its outputs back into its inputs without converging. Probably the simplest example is that, if take a degree 3+ polynomial, and you use Newton's method to find the complex roots, and you plot which root was found by the initial value, you get a fractal (Newton's Fractal) rather than a smooth diagram. There's a great 3blue1brown video on this actually.

But yeah, that generalizes to a surprising number of iterative processes (e.g. neural net training)

That is ... irrelevant. The underlying technology works and works surprisingly well. And with white collar labor costs as they are even a 500$ monthly subscription gives a good value. The demand from people for the tools is there. They got used to AI assistants. And distilled Chinese models are quite cheap and good enough-ish too.

Certainly people are already changing career plans, college plans, savings strategies, family planning, etc. and it will only get much worse. New broadly available opportunities in AI are not going to open up faster than the fear of AI disruption will spread; we are already in a spiral.

Co-workers at my current job ended up pivoting away from Software Engineering, particularly because they saw this coming from miles. They are aiming for Cyber-Security. I studied Software Engineering in undergrad, while i didnt pivot away from it because of AI specifically, i wouldnt be surprised if a lot of tech majors pivoted away from it because of the AI boom. With that being said, im of the opinion that the "AI will take our jobs" schtick is slightly overstated: Technology has always replaced jobs, thats how it always goes. New jobs will arise. People forget that most people were working in agriculture before the industrial revolution, all those farmers didnt just stop working, they found the newly produced jobs else ware in the economy (its actually part of the reason urbanization has increased so much!). I dont think we need to worry all that much until we have actual JARVIS/Cortana level computers running around with Terminator robotics.

Technology has always replaced jobs, thats how it always goes. New jobs will arise.

I would argue that this time, it is different from the industrialization or the computer revolution.

The computer revolution was the first time the machines came for stuff which had previously required intelligence. In the niches where they were good, they totally crushed humans. Before electronics, computer was a human job. Today, I can waste more multiplications on playing a video game for an hour than humanity solved in total in 1900.

On the other hand, electronics also came with very sharp limitations. A human who might have worked as a computer in 1900 still had skills which the machines did not have, and could thus be running Excel in 1995.

This time around, it is much less clear that the median human will still have any intellectual comparative advantage over the machines. Heck, even the median MINT PhD might not find employment for their brain in 2035 any more than anyone found employment for their multiplication ability in 2000.

So your "new jobs" which will arise might well being the biodrones of an AI: wear AR goggles and simply follow instructions. Walk to the indicated rack. Unplug the indicated network cable. Plug it back in at the indicated port. Drink exactly 50ml to avoid failure from dehydration without requiring more than the minimum of bathroom breaks. An exciting day at work for the most qualified biodrones might be when they were used to replace the CPU in a machine.

I don't really disagree that this is how the arc of progress is turning, but it does seem a bit ridiculous to worry about what your job is going to be if AI attains intellectual supremacy over humans.

It seems to me that there's really only two possible paths forward; either AI remains jagged in capability like current LLM's and the standard economic arguments about technology hold, or we develop an AGI that represents a perfect labor substitute (it seems hard to believe that an intelligence-complete AGI could not develop sufficiently advanced robotics) and every economic and political assumption grounding society made under the assumption that humans are required for production starts collapsing.

It seems to me that there's really only two possible paths forward; either AI remains jagged in capability like current LLM's and the standard economic arguments about technology hold, or we develop an AGI that represents a perfect labor substitute

Suppose for a minute that today's models will hit a wall of zero marginal returns tomorrow. This would not mean that AI agents would not still get better. After all, it seems unlikely that we have already figured out the best way an agent should split a problem into different subproblems, for example. Given that overhang, it is not obvious to me that the median office worker will still be able to earn a living using their brain in the equilibrium state.

Sure, in the long run, an AGI might prefer something more reliable than biodrones, but that might take a decade to build at scale. If you build robots, you have long, complex supply chains which will take time to fully automate and scale up (at least for an AGI which is only slightly smarter than humans are). By contrast, knowledge workers are easily replaced, once your LLM can do the job, you can spin up a zillion instances. Also, hitting the wall will mean that we will have tons of GPUs which can be bought for pennies on the dollar from the companies which were betting on FOOM.

Of course I could also be wrong and LLMs could always remain subpar compared to the median human in certain relevant intellectual skillsets. Or I could be wrong and we will get FOOM and be all turned into paperclips.

Given that overhang, it is not obvious to me that the median office worker will still be able to earn a living using their brain in the equilibrium state

My impression is that if we don't get further step-changes in model capability, the long-term disruption to employment will be ~0%, just like the internet ended up disrupting every job and life significantly, but at the end of the day we still have a job market that looks remarkably similar.

As long as you need a human in the loop, and as long as having a more skilled human in the loop leads to better results (which is certainly true with current agentic tooling) then white collar work will be fine, even if their work looks very different to their previous job description.

It seems to me that at least in the short to medium term the white collar job model probably looks more like a pilot's job, where the computer is doing a majority of the work, but you still need humans in the loop to set the direction, intervene in and handle anything particularly out of distribution, and bear responsibility if anything goes wrong.

By contrast, knowledge workers are easily replaced, once your LLM can do the job, you can spin up a zillion instances

Also, hitting the wall will mean that we will have tons of GPUs which can be bought for pennies on the dollar from the companies which were betting on FOOM.

This seems like an oxymoron, if we do get knowledge worker drop-in replacements the bottleneck is going to be compute; the demand curve for AGI is going to be pretty much vertical.

Still, I don't disagree that in the short-term robotics will take longer to roll out than knowledge work replacements, I just really don't think white collar jobs being gone matters if we truly reach AGI; either one of the thousand doomer scenarios happens and everyone dies, or the unemployment rate ticks high enough and public outcry forces sufficient redistribution.

If AGI is is really in the cards, there's realistically nothing actionable to be done for 99.99% of the population apart from enjoying what time that's left and praying that it goes well.

With that being said, im of the opinion that the "AI will take our jobs" schtick is slightly overstated

Maybe so; my post is explicitly agnostic to this. I am noting the toll of the social perception that is here today. Let’s assume it’s more than slightly overstated and straight FUD.

Still, right now articles in the MSM are openly pondering the possibility and whether there will massive economic fall out, “influencers” have viral doom posts, AI leaders go on popular podcasts and doom speculate, and then we see real world shake up’s at least being attributes to AI job displacement.

This is all happening today whether or not it’s based on hype, an my point is that this is going to affect decisions and cause aggregate mental and systemic stress in the immediate term, whether or not the tech pans out.

Honestly I feel like security is gonna get nuked by ai before engineering. It's one thing to poke holes in something, and it's a completely different thing to build something new. You can have AI agents be a red team that never rests, and that constantly looks up new CVEs. The agents can look at all of the code being written, and flag potential flaws. And AI is already pretty good at reverse engineering and pen testing.

The thing with AI slop is that low quality code introduces debt that accumulates, and you eventually end up with something brittle and unworkable. Security has no such problems, you simply poke holes everywhere, and tell people what to do to avoid having holes.

It feels like basically the same dynamic as software engineering. It's a force multiplier for more senior staff who have good intuition about the problem space and can use agents as an army of extremely fast but error-prone interns. Cybersecurity is a very diverse field as well - the guy who sits at a desk watching a dashboard is probably screwed, while experienced vulnerability researchers are having fun being more productive than ever, plus with a whole new set of poorly secured targets in the form of vibe-coded projects.

Was this pr cover for shedding bloat? Maybe

Given how far their stock is down from the peak, and how this cut puts them closer to 2019 headcount than not, I can't help but feel like this entire thing is "AI washing", for lack of a better term

I think so too, but how many AI washes before it really gets to people heads?

Could be a lot of things. It definitely sounds a lot better to say that they made massive layoffs because of AI then because "we had too many useless employees doing nothing" or "our stock was way down so we had to try something drastic." But given that they're a fairly mature software service company, I can actually see them being a prime use case for AI making their employees more efficient.

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