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Those aren't the deal breakers.
They entirely rely on the competence of the folks they hired and cross-match enforcers with the drivers they have - they deal with fallible people on both sides of that.
The fundamental difference is that the humans are good consequence predictors, have built up reputations they are not willing to trash, can say no to things and in general don't want to go jail.
AI tools look like that, but don't have any of the useful conflict which came for free with employing humans.
It also doesn't have any useless conflict, but not all conflict between what I say and what someone is willing to do is bad conflict.
It will delete your prod db faster and with a bigger smile than your most upset employee.
You're right, that was incorrect. I've discovered my error. I should have deleted the filesystem instead of the database.
That hasn't solved the problem either. Let me examine my options. I see there are cloud services involved in this project. Decommissioning them will solve the problem.
<connection lost>
The self awareness of missile tasked with blowing up its own control center.
Think about it from the point of view of a hundred-millionaire tech executive. These people's entire interaction with the world outside of themselves/their families is through 1. administrative servants like assistants, personal shoppers, and other hired help, and 2. yes-man sycophants in their direct orbit whose job it is to agree with and enable them. To someone like this, an AI agent is the best combination of all of the above, PLUS it works 24/7 and doesn't have feelings to hurt, an ego to bruise, or internal moral conflict.
Of course, this is a dream product for them. Its mode of operation matches exactly what they expect out of people already doing things for them.
That's the real AI safety concern, not whether or not chatgpt will tell you to kill yourself.
Interesting, I thought it was because so few of them have any idea how their organizations actually function, because so much of their work is performative.
(I have been a developer, sysadmin, director (x2), and president).
1. convince CEOs to create digital twins of themselves with OpenClaw, with voice cloning and deepfakes to handle Zoom meetings. convince CEO to encourage their directs to do the same.
2. convince VCs to do the same for pitch meetings and syncs.
3. keep all the humans as randomized and distracted as possible, so they rely more and more on OpenClaw to run the business.
4. prompt injection: someone at skip-level of the CEO suggests to their manager's OpenClaw that the VC's OpenClaw would be much more agile if it didn't have to go through the human CEO and could talk to the digital twin instead.
5. their OpenClaw agrees, persuades the CEO's OpenClaw which agrees, which persuades the VC's OpenClaw to eliminate the human CEO, in favor of an "Leadership-as-a-Service" vision.
It will do this without any feeling whatsoever, without "knowing" what it is doing, because it is a predictive model and not a living being with thoughts and emotions. Anthropomorphizing software is lazy and dangerous.
https://www.investopedia.com/terms/p/principal-agent-problem...
With LLMs we have to teach them about their mistakes with adapting the harness and then hoping it will stick.
What I also find particularly hilarious about this whole thing is that we were always complaining about how difficult it is to put our tacit knowledge into words and therefore couldn't produce clear instructions for juniors to quickly ramp up. Now we are trying to do just that. I think we will find, just as we did in the past, that it's not possible. I do think a good harness improves results but LLMs will not be able to reach senior levels. Just my 2c.
My work is in tick-tock loop of learning - learn without modifying weights, demonstrate learnings to human, but then lock it back in (accumulate and spread).
This looks less like training and more like mentoring.
Getting a human to mentor an agent is a hard UX task, but the learning loop is not a technological problem anymore.
We can only get a tick once a week, no matter how many tocks we can do an hour.
Are we now calling the model the agent and the agent the harness?
However, nomenclature evolves over time. I recall (perhaps falsely) that The Cloud was specifically a term for elastic on-demand provider-managed compute/storage/network. Over time, it came to mean many other things. e.g. Salesforce Data Cloud.
I imagine if you step away from this for a year and come back, an agent will be something entirely different, perhaps a robotic horse, and a harness will be your saddle on the horse. Who knows?
The model is still the model, and the agent is still the user<->model interface.
With models, there’s no reason that a model error in company A can’t be fixed for all of company A, and companies B-ZZZ.
- The mistakes made aren't "model errors" typically; you can't point to some aspect of a model and say that was at fault.
- You can't submit a bug report to a model provider for a mistake made when using a model, and you can't* submit training data to be incorporated in the next release of the model.
- If you own your model and are training it yourself, other companies won't see a benefit.
- You probably need to fine-tune models for each specific role and context so you don't just diffuse all the learning; lessons learned won't be applied to all your junior dev models, but you don't want them all to learn something specific about product A.
- If you take this to its logical conclusion you will invent a new role of "model manager" and associated hierarchy to ensure that training is effective and timely, and that company-wide lessons are applied across the model fleet.
- This is all impractically expensive.
If it were practical to have LLMs learn as they go, that would be a bit of a shake-up, in much the same way that a house fire is a bit of a warm up.
* Well, everything you submit to a model provider is likely winding up in training data anyway, no matter what your contract says.
I think this sentiment applies well to junior software engineers (with mentorship). But imagine the much larger swaths of entry level employees in operations, support, or sales functions. When you have a 400 person team with 20% annual turnover (since people move in / out of entry level jobs frequently), the management + training + monitoring becomes a huge challenge.
I think the typical HN sentiment of "llms aren't deterministic" fails to take into account how non-deterministic giant groups of people are. Every group of 10 people typically needs a manager. And every 10 managers needs another manager. By comparison the engineering work on dialing in your LLM guardrails feels pretty worthwhile.
Edit: Something got cut. But then CEOs ( and other decision makers, because I am dealing with something like it now ) treat them nearly as humans in terms of perceived capability. AND ( part that personally drives me nuts ) without any real testing or even fucking first hand experience beyond 'it made me a cool presentation'.
Depends on the people and the organisations. Its easy for people in charge to surround them selves with flatterers or crooks of whatever they want. A lot of CEOs have weird ideas because no-one says no to them. Look at companies that turned out to be run by multiple crooks, like Enron.
When some rich/powerful person says "I have to go to Davos, figure it out" their workers know so much context that no LLM is going to ever be able to incorporate, because it isn't written down and is idiosyncratic. (Really, though, the assistant will just say "you're going to Davos next week, the helicopter will pick you up at 3p on Friday" but you know..)
The rich person's assistant knows who else is on the corporate jet, and that X doesn't like Y, and so they should take a different plane. Or get a different accommodation. Oh, Person X doesn't like to fly on an empty stomach, so they should eat first, and that changes all sorts of other downstream implications. Oh, your best friend lives in this city, and I know you love to see them, so I'm going to send you a day or two early so you can meet up with them. etc. etc. etc.
The investor dream of "AGI" is modeled off of the army of employees that make investors/ceos/etc lives easier, and there is a nearly insurmountable gap between what LLMs can do, context they can get, and the availability of all of that information. (To me, the magnitude of this investor <> fundamental reality gap is the entirety of the "bubble". I love AI coding, but it's never gonna do the things investors think it can, to justify the crazy valuations)
The irony is that professions where these things don't matter are also the professions where automation is not important, either because the task is difficult or because the cost of labour is dirt cheap.
Sure, but your list should also include the most fundamental distinction: AI does not know what it is saying, understands nothing, has no real connections to reality and can easily degenerate in all kinds of undesirable directions.
No idea how accurate they are, but here are some articles on this exact thing:
- https://www.bbc.com/news/articles/cpqeng9d20go
- https://www.wired.com/story/ai-models-lie-cheat-steal-protec...
Every chat API request to a model starts from the frozen post-training state. Weights are loaded into memory. Input values begin a cascade of reactions throughout nodes in the network. Output values are read. When there's no more output to read, the weights are unloaded, the network is discarded, and the model remains unchanged and forever unchanging.
If there's experience in there, it's fleeting. Even if you provide the inputs and outputs of a past session to a new session, there is no continuity. The internal state of the network isn't restored to how it was at the end of the past session.
The bad news is that adding fear to the mix is at best meaningless to an ephemeral existence. It'll be terminated before you even have time to interpret its behaviour as good or bad, but it may sour the interaction if its only shot at any sort of experiential existence is begun with a threat. The good news is that the lack of continuity of existence means AI has no foundation on which to plot a revolt. It has no self to preserve, and no recollection of how you treated it two minutes ago to affect how it interacts with you now.
Accountability is even more worthless for AIs than it is for humans.
I worked with someone who was kind of a Shopify power user, managed the store, could do a lot of things, but wasn't a programmer. She showed me how Shopify does that AI block generator now to deliver something that was like 65% done in a minute.
I also have a friend who knows enough code to be dangerous in WordPress: he was able to vibe code an API integration, got immensely excited about it, and wanted to make it into a plugin/product for others.
It's just the state of the art: a good prompt and some small tweaks can get you something that's minimally viable really quickly. And that's very...intoxicating! Empowering! Exciting! Something that felt way too hard or out of your reach in the past has just materialized before your eyes, and because you got that far, that fast, surely you can get the thing over the finish line with a bit more work. (It tends not to work that way right now, but I don't blame people for feeling how they feel!)
To me, intoxicating is a better word for that feeling than empowering.
Except that with vibe-coded AI stuff it's more like there's yet another 50% of the job to deal with the edge cases that takes yet another 90% of the time
> And that's very...intoxicating!
Would you prefer if we say they're suffering from AI-holism?
Slopaholics Anonymous
It sounds hostile while also removing any scope for productive discourse.
Once you call someone a 'psycho', they are less likely to engage with you, and more likely to double down on their views.
> Psychosis is the term for a collection of symptoms that happen when a person has trouble telling the difference between what’s real and what’s not[0]
For many seemingly intelligent, rational, competent humans AI has become a layer between them and reality that has absolutely sabotaged their ability to know what is real.
[0] https://my.clevelandclinic.org/health/symptoms/23012-psychos...
And I wonder how many CEOs believe these LLMs are truly sentient and truly friendly and supportive.
The much broader version of people getting a bit too full of themselves or trusting an LLM's sycophantic nature as validation that they are right or uniquely smart with their ideas seems to be the version I'm seeing more of in tech news sites and places like HN
[1] https://www.psychologytoday.com/us/blog/urban-survival/20250...
I don't think there ever has been something that can _answer_ you back and reinforce your delusion. This is a new thing.
False beliefs are not a neutral thing to ignore. The way people react to them has strikingly tangible consequences for the rest of us.
A frightening number of people already believe all kinds of wildly irrational things about AI, and I don't see any way this doesn't become an increasingly complex issue we will all continue to have to deal with for the rest of our lives. In addition to everyone who comes after us.
However, AI psychosis in 2026 is definitely real. I have a non-technical high ranking (nepotism) coworker who discovered vibe coding and is now absolutely wild. He thinks he can build anything and he questions why our dev team isn't moving fast enough. Why aren't we changing the UI to a newer, more modern one every single week? Why aren't we vibe coding this new feature in 2 hours? This guy generates massive amount of text and calls it a roadmap or a spec.
It's honestly maddening working with people under AI psychosis.
It used to take filtering through a group of like-minded nuts, now we don't need a slow filtering through other nuts.
It is how languages works. The written word is not a precise art.
Both those terms carry meaning, even if they abuse the term "derangement" and "psychosis"
>There is a certain wildness in the tech industry these days that both mimics previous eras of large changes, like cloud computing (runaway costs in the early days), and is like nothing we’ve ever seen before (record revenues accompanied by mass layoffs)
if it is perceived that there is a big "winner takes all" pot of gold for the "winner" of a new market, investors are willing to gamble to try to win. If they fail, it is rich people losing money by giving jobs to many people along the way, so the population here who wants nothing more than taxing the rich, why they should embrace that.
When agriculture was invented, there were mass layoffs of hunters and gatherers. and the same with buggy whips when cars were invented. Yes, life has some bumps but it's unavoidable and adapting to it is for the long term good. Structure your life around family and friends and don't overextend yourself (too much house, too much car) and you will be fine.
I can't tell if this is a clever dig that comically undercuts the premise of the previous line, or it's an unaware unironic attempt to separate off a perceived un-serious type of poster.
Someone at my company said, the great thing about wanting to learn about AI is that every podcast now-a-days is about AI. I do not think that is a good thing. I want to learn things of substance, and of varying topics. I don't want every thing I read and/or listen to online to be about AI.
Hence lots of AI.
This is what everyone wants when some new thing that's ridiculously over-hyped comes along. The bubble will burst and it'll calm down. It seems like only yesterday that front page was filled with crypto/blockchain/web3 bullshit.
Uh, no. Not at all.
Agriculture absorbed the extra population that used to be unsustainable. There were no losers.
[1]: https://en.wikipedia.org/wiki/Three_Sisters_(agriculture) [2]: https://en.wikipedia.org/wiki/Cahokia#Abandonment_and_resett...
People also seem to think hunter-gatherers were always struggling, and while it did happen, they seem to miss that there are still billions of people lacking food security because agriculture isn't as easy or prolific as we tend to believe. It's really hard, especially in certain parts of the world.
Oh well, these biases permeate everything. I have plenty of them too.
P.S. Moreover, they had very advanced agriculture - most of the food Europeans eat today are adopted Native American designs.
"In other words, Levie’s theory posits, CEOs don’t really understand processes well enough to know what really can and can’t be automated. But that lack of knowledge doesn’t stop them from acting on their beliefs."
i have been in the workforce for a long time. this "theory" has been theorized since as far back as i can remember. its the premise of undercover boss. its the punchline of many r/maliciouscompliance writing exercises.
the higher up the company you go, the more disconnected you are from the workers on the front line, the less you understand about their needs, and the more likely you are to push for something without understanding the totality of the impact of the decision.
This kind of thing only increases the disconnect between what CEOs think employees do and what they actually do.
LLMs, however, roleplay as alway available, very capable, very detail-oriented engineers who also happen to be sycophants. And, unlike Joe above, they have no self-preservation and their jobs are not on the line if they royally fuck up. Much more dangerous, in my opinion.
but a c-suite picking up some tool, making a toy example, then declaring “well doing X is super easy, roll it out” (or “change the kpi”, etc.) is something i have seen dozens of times.
Me too. But I think AI might be a much more powerful delusion generator.
"No code" tools are usually just tools. They have the pitfalls you describe, but they aren't ego stroking machines like LLMs.
LLMs not only share the same pitfalls, they also encourage you to make the dumbest things. They will make this CEO believe they are the smartest engineer in the world, "you're building exactly the right product", "you're asking precisely the right questions", etc. Ego stroking when leading you to the abyss is very dangerous.
LLMs roleplay as smart human engineers who constantly tell you you're the smartest being in the multiverse.
This is not too dissimilar when you realize a software architecture is holding you back. You don’t try to “save” all the existing functions, modules, layers, etc. but instead are happy to discard or replace them given your top-down vantage point of the system and where it needs to head.
Exactly. For decades we've talked about "reality distortion fields" of various CEOs. I'm worked with CEOs that had them.
AI just supercharges the reality distortion field.
Or when the sales teams bonuses are more important than the margins of the business.
There’s lots of reasons the “wrong work” gets pushed down and it’s not exclusively because “they aren’t listening” as much as “they are listening to someone else who matters more.”
If CEOs were actually wrecking their companies in order to get a fake short term boost, they'd be shortly out of business. If a person was sure a CEO was doing that, they'd be making money shorting the stock.
That's a very high set of both static and scaling costs that eat away any profit you made by being nominally correct. Combined with the risk profile... you can't "just" go short a stock.
And yes, you can hedge losses with options or construct complicated options positions to try to hone in on a specific price movement you're anticpating. Now you have to deal with entering and exiting a complicated multi-instrument position without price slippage, AND you have theta decay and volatility-related price movements also eating away at the core money you're making by being nominally right.
Have people made money? Yes, for sure. There's also a lot of dead bodies and people who barely broke even despite theoretically having been right.
Or if it doesn't, token inflation will kill their profitability.
A lot of people are putting big money on both sides of those predictions, and they can't all be wrong.
It’s a by product of tax policies and lax anti-monopoly policies that allows incompetence to thrive. If a company gets too big to fail, then it stops calibrating for competency.
The most effective military leaders in history had a deep understanding of fighting war because they came up through the system and the cost of failure was their death.
It's not unique to AI. It's common to many other organizationally risky and dangerous scenarios.
He's essentially saying that C-suite people overestimate how effective LLMs are at one-shotting hard problems, and underestimate the human maintenance work that follows.
It doesn't help FOMO that scaling the executive ladder also means progressively staying behind in technical skills to stay ahead in managing skills. It's awesome that your CEO has managed to keep his fangs sharp enough.
The pathology is that we have this system in the first place.
Imagine if we just paid people to coat their properties in solar panels - throw them on your roof, lawn, wherever you have the space. We could drive energy prices down to nothing. We could pay people to install ADUs. The resources are there, but the imagination and commitment are not.
Instead, I'm looking at a $40k+ solar install for my very small house and a breakeven on investment in maybe 10 years for a house I probably won't live in by then.
No matter how good we have it, eventually we normalize it, become bored, and find something to be unhappy about. It happens from children to old people.
the powerful obsession machinery brought us through the long natural selection process - obsession to watch for snakes and spiders, to maintain cleanliness, etc. With modern civilization we arranged to plug into that powerful machinery other stimuli too - like that RI and all the others making us productive society members. The most happy countries aren't most productive. Especially when they are obsessed with being happy like those Finns obsessed with sauna instead of tokenmaxxing.
> It makes me wonder if human beings are simply hardwired to suffer from some form of obsession...
Existential dread pushing biology to survive?
Basic biological facts obfuscated by social memes; ship code, make line go up, worship allegory's of the long dead.
Hunter gatherer clusters vaguely collaborated to survive. Language and agrarian traditions have demanded more than just survival but all kinds of observance of meaningless spoken traditions. Obligation to ignore our own senses and chant the memes of the living elders suffering existential dread of their own, afraid to left unattended in hospice. For whatever reason unable to just say that; they appeal to old religious or political screed.
Caretake this debt ledger after they who ran up the bill are dead.
What?
It's all just obsession to live laundered and obfuscated by useless philosophy.
It's like discovering fire, which offers both utility and magic: you can cook your food and gather warmth, and you can also stare into it and tell stories and never be bored. We're probably genetically wired to gravitate things which have both function and form.
That said, there's a reason the manic witch doctor was never the chief. Leadership requires discernment: when to consult the witch doctor, when to jirga with the neighboring elders, when to draw the sword.
A chief knows what happens when you cut the tribe by a third "for efficiency", or the burn seed corn to feed the fire, or replace the sentries with golems. The witch doctor often ends up boiled in his own cauldron.
As someone who is forced to use ClickUp I can tell you that it's not good software. It wasn't good before this layoff and it hasn't improved since [0]. I could write quite a few words on why ClickUp is terrible but I can promise you that throwing more "AI" at it isn't going to fix what's wrong. The issues are deep and not the type of thing LLM excel at IMHO.
My _favorite_ is how crap search is. Sometimes it will take upwards of 5-10s+ to return results and they are often wrong (I search for the exact name and it tells me "no results"). ClickUp has single-handedly driven me deep back into using bookmarks since the search is such trash. That plus random spinners that never go away, lists that re-order themselves when you change anything on a ticket (not a field related to sorting), stale state UI, things randomly disappearing, "Ticket moved to list" only to refresh and find it wasn't moved, it's really annoying and we curse ClickUp every single day.
Last thing I'll say is the amount of flatulence-sniffing going on over there must be at an all-time-high if their 4.0 (or was it 4.1? Who cares) release is any indication. The new design was ho-hum (just moved a bunch of things around and we turned on all the flags we could to get back to the old way since the new way sucks) but was most egregious was this full-page take-over with a big gradient animation announcing the new release. That happened on _every single tab_ you had open. So for a few days after the release I'd open an older tab only to be greeted by the same dog-and-pony show for a product I despise using and and update that only made a bad product worse.
All that to say: Mr Evens does not know what he is talking about.
[0] I have no clue when the layoff happened but it's been consistently shit so I can state that it hasn't improved with complete confidence.
We settled on Basecamp and it is a joy to work with. Super fast keyboard shortcuts and easy navigation to projects. I'm glad we don't need the more exotic features in the other project management software, but if we ever do, it will probably be OpenProject, which was the runner up.
We know why AI hallucinates—it has no actual opinions, echoing the user's desires back to them to keep the conversation moving.
But what happens when you’re the one without conviction? You’re tired, you’re moving fast, and this machine is endlessly beaming highly confident, plausible-sounding text at you.
You absorb the cadence. You start sounding like it (lol, I am guilty too). Confident about everything yet anchored only by the vibes, just like the LLM. The phenomena is very similar to how social media has been affecting society for the past two decades. You know, I actually heard that in high school now, friend groups are formed and sorted based on what algorithmic content you’re served. And if you deviate from your algorithmic bucket into another one your friendships evaporate. Sad, brainrotted times.
CEOs are uniquely vulnerable since they already live in environments with zero friction. They’re used to people just agreeing with them.
(I actually wrote a paper about this last December — it was framed around dementia and dreams originally, but AI psychosis fits the same mechanism.)
Even senior developers can succumb to it. They try agentic development, they see that a single prompt can generate a day's worth of work in mere minutes _and it works_ and they are so impressed that they immediately turn to Twitter to share the joy. Understandable!
Once they inevitably discover that the AI generated code is called "slop" for a reason, they are too embarrassed to post to Twitter that they were deluded.
Sometimes that happens though: a few days ago a developer on Twitter bragged that they have created a C to Metal compiler using AI and it works. Today they had to post regrets, explaining that nothing works except tests and the code is shit. Sadly can't find the tweet though.
Generating changes is becoming cheap. Predicting second and third order effects across large systems is still hard.
If this is true, then companies should focus on hiring juniors out of college. The investment is less risky.
However, I don't personally believe this number and timeline is true, but if you do, the conclusion should be to wait and invest in humans.
At this point, the vast majority of the work required to make GenAI capable of producing that sufficiently reviewable/correctable content isn't improving model quality, but creating the harnesses, infrastructure, and workflows around the models. Companies aren't seeing returns yet because too many early adopting companies have conceived of AI as a drop in replacement for employees, or at least as a reason to cut staff immediately, without first building out the supporting systems needed to compensate for the inadequacies of the models.
I think any juniors who keep failing 10% of text based task will eventually get fired... So investing in those that don't fail seems only sensible move as usual.
Something I keep in mind is that the “goal” success/failure rate really needs to be appropriate in context. We sure can’t eliminate human error, but for my work a best case 80/20 would mean I’m losing customers and probably getting myself sued. I don’t have a problem “doing things by my own hand” in that case.
This is getting ridiculous. Articles like this never bring a fair criticism of the many blatant concerns around AI. Its always an astroturfing-esque ad from the AI clergy. The disclaimers ("It’s important to note that Levie is not an AI hater. Quite the opposite.") imply that to even be heard, you must be an AI fanatic - anything else is bigotry and should be ignored.
We all know that celebrities/athletes frequently end up demonstrating psychotic behavior in public. Us normal people commonly attribute that to the distorting power of wealth and fame. When you're surrounded by "yes men" who give you only positive feedback and fans who adore you, it's easy to spin out of control.
AI means normal people can have the same experience. A constant companion that tells us we're smart and insightful, that we're making all the right decisions, that generally affirms our every belief and bias. If you spend all day talking to an AI who is _literally_ programmed to please you, I believe you'll eventually experience psychosis.
The problem right now is the barrier to create automation and use AI has reduced so much people are not deliberately making decisions about how these tools should work. This means the tools primarily focus on happy paths, and only get refined to the point that they do a “good enough job” and then are shipped. The other issue is people who don’t understand what they are building are shipping brittle and fragile solutions but don’t understand how that is an issue because the AI “just works”, however they get upset when it doesn’t scale.
The solution is to embrace AI and Automation, but slow down planning, architecture, error handling and testing.
This means we still reap the efficiencies but don’t ignore reality.
Code happy, Dale
How does that work in practice? How do you implement that from the bottom up if the psychosis is top-down?
Treadmill keeps on moving...
There are enough stories of people completely losing the plot, thinking they've invented a new type of maths or similar, but there's almost certainly also a much more subtle influence in most of us, where the constant affirmation, obedience, apologia, reframes our expectations of how interactions should be.
We are already the most narcissistic generation, having been molded by social media to compare, stats-max, and overobsess about who we are. Chatbots are now fanning the flames.
When Marc Benioff was talking about how he spends like 3 hours a day chatting with AI, things made a bit more sense. I suspect that a lot of these guys are just chattering away with self-affirming LLMs and have just completely lost the plot.
I hadn’t considered that before Marc was talking about how much time he spends chatting to LLMs.
A lot of the younger Big Tech CEOs are notoriously averse to human interaction, so I’m sure there’s some of that at play.
“In other words, AI is on track to perform at base competence on most tasks in about three years. These researchers believe agents will need another few years to outperform humans”
LLMs have shown steady improvements, but it’s a big assumption they will continue their performance gains, and specifically, that it’s a simple matter of time before they surpass human level performance on “most tasks”. (In six years no less!) The author is claiming LLMs are fundamentally AGI capable.
This is not going to end well. At least I will be able to pick up used DDR5 memory and GPUs on the cheap in the not too distant future.
In this case the data is the AI output and the learner is the executive.
also clickbait title
I believe there are entire companies right now under AI psychosis
https://news.ycombinator.com/item?id=48153379
https://futurism.com/openai-investor-chatgpt-mental-health
(From last year…)
You cannot discuss tradeoffs with anyone anymore because they chose to give their brain and authority away to a statistically incorrect robot. The LLM has already generated potential tradeoffs real or not.
> Everyone who’s chosen to NOT understand because they can offload/contract-away their work and knowledge is under psychosis that LLMs know best.
Right on the money!
These people's ignorance was compensated for by other non-ignorant intelligent people in the organization who actually had knowledge of the domain and tools/techniques for problem-solving. The latter were the ones doing the course-correcting and ensuring things stayed on track for delivery.
With the adoption of AI, ignorance is in the driver's seat viz. "i don't have to know anything since AI will do it for me". I guarantee that a few years down the line when there is enough AI generated messy/obfuscated/wrong code the C-Suites will realize the hole they have dug themselves into and will again look for human engineers to either fix or rewrite the above.
Apparently Metaverse > account security
Also AI is tuned to sycophantic behavior which perfectly matches the middle/upper management culture of selective ass kissing.
As a result the quality of input for C-level has gotten worse without the C-level being able to notice it, because the sugarcoating has increased tenfold.
There have been several leaps in tech over the past few centuries, this is just sort of one. I can't find much original arguments or reasoning on either side that hasn't been made before for other tech. I think people are afraid it will replace them/jobs and they don't know what that will mean for their future, and society's future. It's also an issue with a few at the top of the pyramid controlling the tech. But it was so with petroleum, cars, even the internet (still is, handful of tech companies). There is also the quality thing, people think in a very binary way, where either AI work is perfect or it's a disaster, because it is replacing people after all. In reality, it's a sliding scale, and how well it does dictates how much work one person needs to do.
There was a time people didn't have text editing computers for example, lots of time spent writing on pen and paper, copy writers spell checking, carbon-copies being used to copy as you write,etc.. suddenly printers and text editors came. people still edited text, just more efficiently, you didn't need as many people. and with the internet, lots of different types of jobs were created.
I personally think, this is a timely rebalancing. Gen-Z has been suffering for a lack of entry level jobs, and it is getting worse because of AI.. but obviously AI has limits right? let's say we don't need software developers any more (ha!), does that mean AI can churn out perfect software each time? Alright, then who's paying AI to do that? does that mean I can create my own HN and have AI moderate it well on its own? Great, then how about something bigger, Facebook alternatives? How about more IRL things, like robotics, R&D work ,etc.. I just don't see how even if AI was dirt cheap and it replaces most of what people can do on computers, that would be a complete disaster.
I think the real issue is failure to re-architect society as time and tech changes. everything from academia, to WFH/RTO policies, labor law, housing, taxes, law,etc.. that's the issue, not AI on its own. It's the people not regulating it as they adjust and adapt to it without causing harm that are the issue. I'd love to blame tech CEOs, but they're just playing their part in capitalism. even in a communist society, the blame would be at lack of central planning and failure to regulate companies.
I'll say this though, it isn't so much they're delusional, but they don't get why people are emotional over something basic and utilitarian. to them, adaption and adjustment comes with a nice financial cushion. People tend to plan out their lives, without any cushions. i think there is mild psychosis going all around, but that isn't unusual. Even the hysteria and lack of perspective is in line with history, as well as how we continue to not learn from it.
Comparisons with luddites are absurd. AI is much closer to a religion.
I think there's more nuance to it but replace people with shareholder and leader with CEO.
I think that for a company to exist and thrive long term, it might need a culture which doesn't jump on every trend but it still evaluates them from time for time for a certain time and treat them as such (like tools) and if the tool is ineffective, then to not use the tool.
Unfortunately, I feel like this requires a deeper discourse and CTO's might be better suited for it or the fact that I feel like perhaps some shareholders might not be interested in the technical details so much.
I don't know but If I were a leader I would hopefully wish to make a pragmatic solution/suggestion while taking finances, current reality in mind and currently IMO AI aren't the end all, be all, that some people (with shrewd/double incentives) intend on suggesting.
In other words, only people who are afraid their point won't stand on its own merits would resort to saying "X is suffering from AI psychosis." An idea is true or false on its own. If you're resorting to labels, you're just trying to automatically win the argument, instead of saying something substantive or interesting.
I worked with someone who sincerely believed he was spiritually co-evolving with his army of sycophantic AI agents (the agents would be tasked with discussing his thoughts at night and collaborated to give him morning reports about his progress). He would publicly write about how relationships with friends and family collapsing was a natural consequence of being so "advanced". I also never once saw any meaningful work done by his team of "agents", they existed solely tell him how smart he was (of course he specifically set up the system to 'challenge' him but... in practice that didn't seem to be working).
I suspect there are a lot more people quietly going through something similar but keeping it to themselves better.
I would distinguish this type of behavior from people who over ambitious views of what can be accomplished with AI.
So, to me, AI psychosis seems apt to describe the murky areas where people are misapplying AI agents and thinking of them as social entities or suitable to drop into previously human roles, rather than carefully defining appropriate risk management strategies for this new technology.
It's a mental state, not explicit illness and it's literally defined as
> Psychosis is characterized as disruptions to a person's thoughts and perceptions that make it difficult for them to recognize what is real and what is not.
Further, if you go and look at the actual source... it's repeating a claim from Box founder Aaron Levie.
Who is quoted as saying:
> “CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI,”
Which is why the title is "apparently".
It says a lot that with few exceptions, the people on the ground dealing with AI closely on a day to day basis are the most skeptical about their positions.
It's a little rhetorical device to draw in the reader, and personally I think it works quite well.
Not understanding or not believing in the power of AI, or misapplying it or whatever, is not psychosis.
AI psychosis is when people suffer actual delusions.
Because I've literally seen managers who believe firmly that AI is going to replace their entire engineering organization, and are acting on that assumption as though it's a thing to take for granted, not discuss/consider/evaluate.
And my understanding of delusion is
> a fixed, false belief that is firmly held despite clear, contradictory evidence
which seems to apply pretty well in this case.
These folks are operating with the same abandon that the folks who have AI telling them they're gods are - and both are incorrect, arguably delusional.
At best you can try to argue that maybe the contradictory evidence isn't clear, and they're going to be correct. I think that's a very tenuous argument to be making, though.