Ford AI hiccups push carmaker to rehire ‘gray beard’ inspectors
bloomberg.com
bloomberg.com
You just have to get the input coefficient right. The least amount of acceptable quality with the least amount of costs is the sweet spot. /s
They can do what works, or they can fail. Large enough companies with enough inertia can do really dumb things for a while, but even giants fall.
Perhaps that's where it gets interesting.
Are you saying companies have to mandate AI everywhere?
Or are you saying the exact opposite, as your second sentence suggests?
I haven't heard of AI mandates in small companies, only in big ones.
That is essentially not an argument in any direction.
Trust without verification though, we're waiting for AI's Challenger disaster equivalent.
> The latest layoffs across all tech companies. So far in 2026, there have been 421 layoffs at tech companies with 157,807 people impacted (882 people per day). In 2025, there were 783 layoffs at tech companies w/ 245,953 people impacted (674 people per day).
Quoting the host of the recurring Quiz Broadcast sketch from That Mitchell and Webb Look: "Books mention 'hope'. What was 'hope'?"
At one point my boss asked why my AI usage was lower than other team members. I instantly knew what to do. Every session is now run at ultracode effort. My automated PR review bot averages like $80 in usage per PR review.
Oh and my favorite: Use 5 independent subagents to review code change and summarize the findings, and for any finding determine if they are real concerns
-Claude, burning my company's money.
And the planet... While I experience some schadenfreude when reading these comments from programmers, I also can not help to wonder when this insanity will this end.
Just a bit after anthropic and openAI unload the "value" of their companies into retail investors.
When AI use starts to be a line item cost on public companies' financial reports + Anthropic and OpenAI have IPOed and have to file financials too + they kill their growth-hack monthly all-you-can-eat plans.
The entire house of cards falls down when the success metric shifts from "Are you using AI?" to "What return value are you getting for the money you're spending on AI?"
Some smart companies / departments are going to be able to demonstrate stellar AI ROI, but I'm going to be shocked if the bulk of current demand isn't revealed to be naked. Mostly because middle management is always stupid about adopting and using new technology.
AI companies are running out of money to subsidize those queries, and worse are needing to show a profit. All while they are having a harder time to raise more money as investment.
If nothing changes, things should become more rational soon.
... now... IMO, I place the odds of nothing changing very low...
Eg by doing that I was able to develop non-essential features which increased our quality of life for devs last month without going through our PO who'd need to price it - because that does let's you create changes in an incredibly hands off manner with miniscule amount of time investment if you already know what you want to achieve, and how the end result should be...
Admittedly, that's a pretty narrow usecase which is rarely the case- but if it is...
It's interesting that LLM barely had any vetting period or experimentation phase. Suddenly everyone was supposed to test it in production, it seems.
I'm not too proud to admit that this whole thing scares me though. I fail to see how anything will get better.
I’ve sadly had the same thoughts lately to cash out my 401k and say farewell to software development. I’m hanging in for a little longer, I think the AI/greed fever breaks sometime soon (months not years).
Yes, all developer-focused AI subscriptions have been cancelled, and only AI features tacked onto existing subscriptions are part of the AI strategy (eg: Jira+AI, Confluence+AI, Analytics suite du jour+AI, Microsoft Copilot Pro (SHUDDER), etc etc etc.)
Yes, it is virtually impossible to get any additional spending approved.
Yes, there is no more Claude, there is no more Codex, it is all gone now. The AI hype occurs only in company-wide emails about commitment to modernization (with AI), reorganization (with AI), and consolidation (with AI), where no actual strategy is proposed other than what the management consultants advise (with a caveat that there is no budget for anything other than AI features that are tacked onto existing subscriptions at no additional cost.)
2. Your responsibility doesn't end because your manager says so.
3. It's not just about the employee who actually burns the tokens, but also about the rest of it: the idiocy up to the top, and the irresponsibility of the companies offering the service.
Then pretend it was 5 million nails a day from a newly invented nail machine gun. This also has no provable and substantial benefit. Build a house that way and it will quickly be more nail by mass than everything else combined.
I'm sounding a bit like a broken record, but the only political system with a proven track record in modern society is still social democracy: educate the people so they don't bash each other's heads in, distribute wealth and power better, and regulate the markets. It unfortunately died through the unholy matrimony of material well-being and social media.
Similar issues exist in communism too. It doesn’t mean you can just go “but communism” to dismiss me when I raise an accurate and valid critique of the system Ford operates in.
The really stupid thing is that shareholders are also rewarding useless burns of their money. It's capitalist Stakhanovism.
Get ready for that promotion!
There's so, so much mechanically simple but time consuming refactoring that should be done but nobody ever does that because there's never enough free time. Or even various utility scripts and at least finding out of date docs (or writing very basic ones where none exist, though it'd be hard to get them not to feel like slop writing). Or figuring out what additional custom linter rules would be useful, how to improve the CI pipelines and so on.
If I had the Anthropic Max 20x subscription, I could make a large part of the technical backlog disappear (relatively safely).
Most of the tasks you have listed you could do with Haiku, GPT mini, or DeepSeek Flash.
An Anthropic Max 20x subscription is considerable overkill for this sort of task.
What's the rush? Friday will still come at the same speed, and it's unlikely you will receive an increase in pay to account for your increase in productivity.
Updated version: Tokens expand to exceed the budget available.
Fantasy: automated productivity
Reality: automated bullshit makework and bureaucracy
The AI initiative there is a lot more in "let's try to find ways that this can be useful" instead of "let's use this to the maximum extent".
So far it has been a mostly positive experience. We could figure out ways where it saves time instead of burning money in a token pit.
The only downside is that code reviews are becoming the bottleneck. Every PR still needs a human reviewer, and that is not changing. The influx of PRs increased slightly, the rate of reviews not as much.
Value is measure in generalized labour, since that the universal measure of human effort. The genealized amount of time a human being must spend to produce something from its parts. Generalized labour is also what's bought from labourers. You don't pay them to do something specific, you pay them to labour in general.
This contrasts against specific labour, which is whats actually required in the moment. Generalized labour power must be the right kind of specific labour to actually produce anything of value.
The AI leaders have been told that AI is labour. To the extent that it currently is, which I believe is only the case because the market hasn't adjusted, it's not the right specific labour to male anything valuable.
It seems to me that the text is saying that generalised labour produces value, but then only specific labour produces actual value. What is the difference between actual value and value in general? Is some value somehow more valuable that other? Are we even speaking the same language? Is this just making shit up as you go along and hope nobody notices because the general idea is appealing?
Unfortunately the only phone line was answered by an AI bot who stubbornly refused to move the booking, simply telling us there was no availability within an hour of our booking.
Fortunately my partner was passing so was able to go in and speak to someone is person who was happy to move our booking back 2 hours. Lunch and drinks for our party must have come to several hundred pounds.
I'd estimate our party was between a third or maybe half of all the customers there. Had we chosen to book elsewhere I bet someone would still be patting themselves on the back about how clever they were to save a few minutes a day on actually answering the phone to actual customers.
And yes, this does mean they view us workers as somewhere between slaves and robots, replicable by a token predictor.
I’m sure they’re having a great time, and getting filthy rich doing it, but I don’t enjoy having my livelihood attached to the consequences of their repeatedly-stupid-behaviour.
We still need the humans, there are no cases for novel useful work I can think of, or have seen, where humans are no longer required.
I think objections to the Theory of Evolution and some objections to the feasibility of Artificial Intelligence have many similarities. Most people (because of their world view) assume an “intelligent” Designer is mandatory for organisms to evolve and for nature to work. They assume the nature is “random” and directionless by itself. Only a higher (supernatural) intelligence (God) can give it a “direction”. So “intelligence” is basically an external, supernatural and unexplainable (since its above our nature we don’t have access to it) phenomenon.
The exact same argument applies to AI. But instead of atoms and DNA we have bits and activations. AI is random and directionless. Only a superior intelligence (a human) can give it a direction. Like nature, a computer can’t have intelligence by itself. Intelligence is external, supernatural/supercomputational and unexplainable. You can’t compute it, you can’t understand it, you can’t replicate it.
This is because human intelligence, like God’s intelligence, lives in a supernatural realm. Some people even believe that it’s the same thing as (or a copy of) the divine intelligence. Some others don’t believe that but still have trouble accepting their human intelligence is not a unique phenomenon and not something above this mundane world.
There, I said it. I think without this warning most of the debate and “philosophical” arguments against AI are useless. They are more like wishful thinking, shaped with the world view of the person. It’s about belief and not technical feasibility.
From the technical perspective, most of these rehired Ford folks will be replaced again in a few years. This was about overestimating the short-term effects of the automation. But in the longer term Ford will indeed have much less humans.
BTW, this new trend of “extracting the knowledge of skilled senior workers to replace them” deserves its own name. This is not a good thing for humanity, but this is exactly what they are doing.
Some people have not learned that velocity at small scale without global synchronisation is just thermal agitation.
"Slow is smooth, smooth is fast."
- US Navy SEALs
Corp CEOs / CFOs golf buddies coouldn't stop yapping about how much they saved paying people less by offshoring. So step 1, they fire a bunch of people and send work overseas, driving up their financial metrics for 5-6 quarters until their staff and their organization finally break at stage 2. Turns out cultural and communication barriers are things we haven't really figured out how to communicate across efficiently, and that only a handful of people are truly rockstars at it; others just aren't cut out for it. Stage 3 anyone that is competent to get another job already left, leaving a smoldering shell of company that dies by attrition at stage 5.
I am quite heartbroken. Your /s comment is a reality for others.
It doesn’t take long for the cracks to show:
- Not enough program/project management.
- An intuition that service dropped but no good metrics.
- Retrain the outsourcers after the first team quit.
- Inability to size new projects.
- Shadow IT departments form in the business units.
- The outsourcers don’t care about things like vendor consolidation or holding other vendors feet to the fire.
All of this might still be worth it if it’s done strategically to improve a chronically underperforming IT department. It’s rarely effective when rushed to cover up poor performance of the core business.
presumably this/these are the Moloch the other poster alluded to
There are some cases where the outcome is bad (like the case at Ford now), and lots of people point out to that and say "I told you so". But those are the exceptions, not the rule.
It's easy to see, from the outside, that a given cut stands a high chance of hurting a company. But cuts must sometimes be made regardless
In a sense, using an LLM agent is like providing instructions to a very smart, very quick junior who despite being brilliant has some blind spots and lacks institutional knowledge. That's something that seniors excel at, so by firing your seniors you've fired the people best positioned to make full use of LLMs.
>Over the last three years, Ford says it has hired 350 veteran engineers, many of them former employees and others from suppliers
And not all former employees were laid off. Senior 'greybeards' have many job opportunities elsewhere and often leave for better offers.
> And not all former employees were laid off.
Thanks for confirming that the article does say that Ford did, indeed, fire and rehire some employees.
You just want to believe in the narrative that companies who lay people off for AI will regret it. Narratives are dumb.
I'm just reading what's written:
> And not all former employees were laid off.
To me, this is very clearly saying that SOME were former employees that were laid off, just not ALL were.
This article may not mention anything but it doesn't exist in a vacuum. Go search "Ford Layoffs 2025" and see for your self
It's not up for debate whether they did or didn't lay people off recently. They unambiguously did.
Deflection.
aye.
I've posted this here at HN several times but I had my intern try to track down how many CVEs from a list of vulns we found were being exploited in the wild -- couple years ago, pre mythos that is. I also took the list to Copilot and Claude.
All 3 got different answers, albeit off by one or two. The intern told me at least he didn't know about X, which was far more useful. I later had him whip up a plan and some basic code to patch some of them, and the experience comparing his answer to Copilot was similar to before as well -- both mostly worked, but didn't, and in different ways, and mostly due to not knowing institutional best practices.
That is either betting on AI being better than humans then, or closure of the company.
I do think LLMs and agents and all are great at helping you through tough problems but we aren’t there yet on getting them to do all the work while we just architect and design. Again, it’s close, and for your use cases you might be there already but for low level and big corporate lift and shifts, it’s not there yet.
I have agents, agents of agents, and I still find myself having to carve big chunks of my project off and feed it to the dogs because it’s garbage code. (GLM-5.2)
It’s human in the loop over and over again tho
Some might hate that writing code (which they enjoy) is turning into that, others might doubt the efficacy of doing that and the claims about it working so well.
Personally, I’d say that docs help as long as they’re meaningful and not too long (even AI tools have limited context), but you probably also want to codify what you can into code.
For example I wrote a tool in Go and goja called ProjectLint (not public yet but anyone can do that in a week) where you write custom rules in regular ECMAScript that can check whatever you want - code conventions across languages, project structure and architecture and all the stuff that goes under “In this project, we do X but don’t do Y” that just telling an LLM about (or colleagues) will be worth nothing (even memories and focus are limited), instead CI gates that.
I guess I reinvented a simplified and stack-agnostic version of ArchUnit but whatever, it works for me and I can use the same tool in Python and Java projects and elsewhere as well as parallelize all the read only checks and run sequentially the potential-write ones that might auto-fix stuff.
For me, my human only productivity in the firmware work I do is usually around 100-500 loc a day on good days. Obviously more when clean-slating the initial work on a project , but that’s typically a day or two and the same ratios apply.
With ai tools, I roughly 4x that with the same effort, or 2x it working lazily from my phone playing with my 2 year old.
The code is typically also more compact so the LOC metric is strong here IMHO.
Overall I have about the same number of bad-unproductive days, far less bugs (but worse bug hunts) and 10x better documentation lol.
Coding is definitely a different job though.
And the verge is covering it too:
https://www.theverge.com/transportation/956316/ford-quality-...
Thats partly why they get so far.
They delegate and hire subordinates to do a job. It is by design that the communication won't involve 100% of the work done
You hire people to do a job, not to be a remote controlled puppet
I guess its impossible for an executive to know ALL the details of the work they delegate, but I'd be willing to wager that executives who understand the details function better in the long run.
It certainly isn't tautological that executives be imbeciles about the businesses they run.
But that want is limited (needs to be), and also it depends on the IC to explain things
It’s also worth mentioning that it still might be the right business strategy for some companies / industries. We are only 3 years into the revolution of AI for business processes and in previous revolutions there were riots, sabotage efforts, factories still being created in the style of the previous revolution, etc.
"everyone! ship ship ship! make production ready versions of what was triaged from the hackathon! nnnowwwwww"
"everyone! wow 80% correct, prompt engineer it to be stricter.... and with a bigger model! wow 98% correct! this whole division is made redundant!"
"everyone! its not 98% accurate and even if it was, thats a huge set of errors given our volume!"
"everyone! our AI bills have skyrocketed! they're charging us differently because we're an enterprise! kill the AI, kill the AI"
LLMs can write code. They're actually pretty good at it. So problem solved, right? Cost centre cost reduction. Bam!
In reality the more competent in the job were really good at understanding business problems and holding domain specific knowledge, working with the other people on the team to translate that into a problem a computer could solve, and with understanding and diagnosing what was happening in the broader system, not just in a "program."
Someone needs to write the prompts given to the LLMs and decide if what they came back with even makes any sense. Someone needs to respond to pages in the middle of the night. Someone needs to be able to look at the system and have a bigger picture understanding of how it fits with the business' needs, etc. etc. That's a software engineer.
I honestly think not enough in middle and upper management really understand what software development actually is.
If anything, I feel like AI has made domain expertise more important, not less, as the "confidently wrong" error case for agents has no one able to sanity check it. At least before AI a human would dip their toe in the water and usually realize that having no idea what they were doing, and not even being able to understand what the comments mean, was a sign that they need to go find someone more experienced to help.
Yeah, this is nuts because at every company I've worked at it's assumed that engineers are thinking about things like product market fit, how a feature would be sold/ the "value" of the feature itself, how we would support the feature (not just the code, but how support would manage it), etc.
I don't think people realize how much of a hand engineers have in these conversations because we don't champion that, but we think a lot about the product as a whole. Obviously we don't spend as much time thinking about how the product will be sold as a sales person will, but we absolutely think about it, in my experience.
We think a lot about the business, like a massive amount about the system as a whole across these organizational boundaries.
my company spends millions a year on tokens and when asked about ROI the CTO just says "LoC is up! LoC isn't a good measure of productivity but it's a measure, right? right?"
(most of them are for fairly innocuous stuff...)
Few of the issues I've experienced with the car were clearly tied to quality issues: 1) Battery died a few times, but maybe that was user error 2) squirrels/rats nibbled the engine cable harness, a not-uncommon occurrence in our area. Only 3) auto-unlock on passenger side being unreliable is clearly a quality/design issue.
Honestly, I actually love the Escape. The pedal feel is very responsive in all driving modes, compared in particular to the 2020 Hybrid Rav4, which felt like driving a boat (maybe I didn't find the drive mode?), or the 2020 VW Tiguan which had a shockingly slow automatic transmission for an ostensibly "sporty" vehicle. And I'm not even a car guy. I also love its actual buttons on the dashboard, instead of the idiotic "everything on a huge touchscreen" that too many cars do nowadays.
The fact that you find this acceptable is amazing to me.
Sounds like a complete failure of quality control.
They still don't have a solution to the problem. The shavings amount/size is supposedly common among all engine manufacturing processes, but the new engine design has such tight tolerances that it's now problematic.
None of the US automakers have good quality reputations. If you want something that works reliably, get a Toyota.
- Peugeot 2008 owner but not much longer
But in terms of reliability, here Toyota is king
If I hadn't already landed a job somewhere else, I would only return with a 20% pay bump and an iron-clad contract.
I would recommend IT/server administration as that is a constant business need, if you prefer stability with more limited upside.
The defining motto of the corporate world
This has nothing to do with LLMs and instead is almost certainly about their MAIVIS and AiTriz pilots, which use old school CNNs on custom IBM hardware to do visual inspections.
I don't know when the "MAIVIS and AiTriz pilots" you mention were implemented but another possibility is the Ford PR team saw that 'AI Backlash' stories are currently trending and opportunistically focused on that to explain a positive news event which likely had many causes. IMHO, we should view these 'AI Backlash' themed stories as no more valid than the 'AI Downsizing' themes they previously seized on to justify layoffs they wanted to do anyway.
First day on the internet propaganda-discourse machine?
If the article doesn't support your preconceived biases that's no problem, assume the title is true on it's face and comment reinforcing it. If neither of them support you then attack them. Welcome to internet comment sections.
Submitters: "Please submit the original source. If a post reports on something found on another site, submit the latter." - https://news.ycombinator.com/newsguidelines.html
(We've reverted to the article's title now)
p.s. Article titles are sometimes rotated by the publications, in which case the submitter usually followed the guidelines but it takes time for us to catch up.
After a quick search I found a publication actually mentioning about these tools:
Ford previously told Business Insider that it had developed two bespoke AI-enhanced scanning tools that helped validate that cars were properly assembled before rolling off the lot. The tools, called AiTriz and MAIVs, both debuted in 2024. https://autos.yahoo.com/policy-and-environment/articles/ford...
And after doing cursory research on these tools, it is clear they are rudimentary (as compared to SOTA LLMs), they were essentially smartphone mounted on stands and doing visual checks using the camera - so OP could be very right.
https://www.businessinsider.com/ford-uses-ai-cameras-in-fact...
LLMs are not calculators.
Where does this article say otherwise?
I don't have high hopes that there exists a bulletproof solution to this.
These are no general purpose machines. They are shipping a subset mindset not general intelligence like they want us to belive .
It's a model of language, yes? Trained on a big corpus of text.
I have read a lot of stories and accounts in which people were told not to do something and inevitably they did it. Like, lots. Far more than stories and accounts in which people were told not to do something and they then didn't do it.
If I'm reading a story or account of something, and it's really hammered home that they've been told not to do something, it's kind of inevitable that they will then do that. I'm not even an LLM and I noticed that's the way these things usually go.
So is an LLM just doing what it's been trained to do? Sometimes in the stories and accounts, there's a whole lot of time and tension before the bad thing happens, but that's just part of the fun.
He valuations of a bunch of AI unicorns disagree.
The more interesting question, I think, is what proportion of businesses will choose the learn from Ford’s experience without first choosing to relive it?
Often people, and therefore also organisations, struggle to usefully learn from the experience of others without repeating the same mistakes, and experiencing the same pain.
You just want to make sure you have it, and not your boss using it against you.
How many tens of trillions of capital have been incinerated in reducing the quality of life for workers compared to actually uplifting them?
Industrial capitalism has been fantastic for quality of life. Here I am sitting in an air-conditioned office browsing HN during a workday, instead of slaving away in the fields as a peasant farmer. I'll take more automation please.
Why is AI different?
Because it happens in a computer and many people think that makes something easy, like CGI or computer hacking in movies. It's intangible magic and belief is the product sold to investors.
While it was significantly better than previous attempts, it still misses very basic things - sporadically. Eg. A clear design requirement was essentially adding clients, explained clearly and comprehensively. The ability to add clients was entirely missed in the build and iteration (there were multiple 'please check its all done' separate agent runs/checks).
I can imagine in a fully autonomous deployment, in even moderate complexity, even to this day would still occasionally mess up - badly enough to cause non-trivial business issues.
I haven't managed to really figure out what's the best way, but my latest thinking is really having boil down tasks to almost unit operations "add UI button, wire to Api call. End".
You could ask it to go through the spec point by point and then mark what is done and WHERE/WHY, then it'd point you towards exactly what might be missing.
For you, the best way is to break your code down into modules insofar as possible, so that you don't overrun the context window. Opus Max starts forgetting things the minute it begins compressing your conversation -- and multiple compressions can make for gaps in memory.
I find that it's also important to have another model serve as review/critique. I use Opus Max for code and 5.5 Pro for immediate code review. The latter will often pick up on things that might have been missed, and will usually provide good suggestions.
Your own conclusion, smaller, concrete units, is the right direction. Except by units I don't mean partitioing the program into smaller units (files, modules). In fact, you should stop thinking about implementation at all. I'm thinking more about the way of asking the LLM to build it. One feature at a time etc. so you can tighten the feedback loop. Then you can early on (in the first hour say): "I also need a way that the user can add/manage clients - basic CRUD" and that small sentence might be enough the model makes it all (UI, API, backend etc.) to enable that and put it in a proper place in the app. A big ambiguous spec defers that discovery to the worst possible moment.
That's not a sentence they literally gave the agent. This is their full quote.
> A clear design requirement was essentially adding clients, explained clearly and comprehensively.
Why are you assuming they described this so ambiguously?
And at that point you might as well just code the thing yourself.
https://books.worksinprogress.co/book/maintenance-of-everyth...
But this is difficult to implement since AI doesn't have a body to follow someone around and it would take immense amounts of compute to do so using telemetry and cameras. You would literally be spying on employees 24x7 for weeks at a time with the express goal of replacing them someday.
Isn't this almost exactly what Zuck is trying to do at Meta?
https://www.reuters.com/sustainability/boards-policy-regulat...
Buy a BYD / Xiaomi / Zeekr / Xpeng...
A company with 1000 employees that builds 100 houses at a time might cut a dozen employees to create three robot crews. A 10,000-employee company that builds 1000 houses at a time would still only need to experiment with a handful of crews, affecting only 20-30 or so employees.
I marvel that a company has let themselves grow so out of touch with their business that they can't understand the impact of changes without carnage at this scale.
the ~game~ matrix
Cars are more and more becoming white goods appliances with the driving experience becoming less and less a priority. Even enthusiast cars now are about raw numbers and need electronics to reign them in to make useable for the average driver on the average road.
The average user probably doesn’t even want to drive and have AI do it for them.
Repairability is becoming less viable as mechanical parts replaced with screens and digital locks. Parts availability is already an issue, only going to get worse especially with the pace of new cars are being churned out from China.
The end will be car as a subscription. We already have it with leasing, and BMW having to pay to use your electric seats.
Pardon me?
We're living in the dystopian present, where most everyone has a car or several. Cities are crowded with cars -- both moving and parked -- and it's awful for humans who aren't cars.
I can't wait for the moment people switch to a subscription and the cars are shared and drive themselves. The streets will be just as full of moving cars, but at least the parked cars hopefully disappear, giving us more space for trees or sidewalks or anything but cars really.
I see no reason to assume that this would lead to the disappearance of parked cars or to more trees. Our corporate overlords will want to make use of that space for more cars or infrastructure to support the new car network, why would they ever just give it back willingly?
* Their "not owning" means a swap to a subscription/license for the car, which could still be exclusive rather than shared.
* Your "not owning" assumes a reduction in the number of cars per capita.
In other words, the "dystopia" they are referring to is one that still has today's problems of gridlock, land use, urban planning, etc., with new kinds of problems layered on. Cars not being user-repairable, being nickel-and-dimed on features, a monopolistic used-parts market, and a general shift towards whatever boosts the car-manufacturer's profit margin.
Self-driving cars may have a control agent at the HQ that places car orders as needed.
I can see a lot of companies coming to this realization over the coming months and years.
It's just so strange any other profession have unions or bodies that protect their job against this sort of practice.
if software devs were lawyers then AI would've been banned
If the company tries to layoff 10% "due to AI" the remaining 90% can strike.
History is full of union solidarity vs idiotic management.
Be sure to have “updated your rate schedule” recently, which explains why you’re now twice as expensive as before.
They know how bad they screwed up and how bad they need you now. I’ve never had anybody refuse a giant rate bump now that we were all on the same page.
I think companies would more careful about how fast and lose they operate, if firing may mean having to contract with a 3rd party.
AI is pretty good at scaling existing knowledge, but if the actual knowledge is just in the head of an engineer who can hear that a press is acting up, the model doesn't really have much to go on
In other words, they don't really have a plan, but they are happy playing with people's lives via layoffs, since it's the 'in' thing to do. The incentives are huge on the upside and zero on the downside for them.
I'm prosperous because god/market deems me worthy.
If my employer offered me a deal that would allow me to retire early, comfortably, to train my AI replacement, I'd take it. If they succeed, well I'd have gotten laid off anyway. If they fail, I get to laugh all the way to the bank with my newly found free time.
Ideally of course everyone, irrespective of any immutable traits they may have, gets to enjoy a healthy, satisfying, and stable life with plently of avenues for upward mobility. Short of that ideal, a society which equally burdens the rich and poor with devastating, seemingly random, unavoidable life-chaning events is decidedly better than one which only affects the poor.
So for these reasons I don't advocate for the actions of "the kid" but I don't think the consequences of his actions were in any way "bad" per se.
And why does the board/shareholders allow a CEO to continue into their position by just following everyone else?
I'm sure things are different at massive scales, but I run my own side business (photography). I watch the local market, and I have the attitude of "Whatever everyone else is doing, I want to do the opposite." and it's worked for me so far. The area doesn't need yet another "dark and moody" photographer with boring sepia edits, blurry photos with a film preset, and the same exact font and colors on the website as everyone else.
You don't become a pioneer in your industry by just cargo culting everyone else. It's low effort leadership and if I were on the board it certainly would not inspire my confidence in their ability to run a company. You're telling me not a single person at the table asked "Do we have these engineers' institutional knowledge documented somewhere before we fire them all??"
You usually don't become a CEO of a long established company by being a pioneer either though...
You may be able to argue this particular case though, as he is a marketing guy and he was a pioneer in marketing as few others capitalized on social media/YouTube when he did.
But I feel like that's completely unrelated to how adjacent that's to what I'd consider a pioneer in a CEO position. Hence me pushing back a lil
Once you were dumped for AI gamble, you will never do the extra work, because you will probably be dumped in year or so, when someone else will get same or different stupid idea.
But it's not stupid idea, it's more like desperate attempt to remain in game in competitive market by doing what everyone else does. Idea crafted to final decision by people paid to see a bigger picture ... which unfortunatelly stop seeing smaller things which matters.
There's not a single person only making good decisions. Bigger the corp, much harder to keep it successful.
Reason why You and I are not in their position is that we would probably make much more mistakes.
the same consultants can be blamed if decision backfires
1) you can only get promoted if the company grows and/or someone above you leaves, or dies, or ... Btw it really requires leaving permanently. They leave for 10 years due to being in coma after a traffic accident? Nope.
2) the oldest person gets promoted (and that means ancienneté: longest in the company). No arguments, no exceptions. To the point that there are plenty of teams that have a manager (who gets the 10% pay boost) and an actual manager (who makes things work). Often not the same person.
3) No mobility (technically, yes, there's mobility, BUT your ancienneté resets in many cases. So it's really stupid to do)
Credit Agricole, a "cooperative" bank that is ruled by union contracts that impose strict limits on how many commas in the rulebook are allowed to move per decade. A company where any change gets so stuck committees they found it easier to implement changes through parliament than through the company's own management structure. Several times.
Total, government owned oil company that gets special tax treatment and gives free shares to French presidents and ministers who leave office. Actually has a good reputation as an employer, but not because there is any chance in hell of getting promoted.
EDF, the power company (mostly nuclear), who are positively famous in how difficult they are to work with, both internally and externally. But, have a good reputation as an employer.
France Telecom, which used to be a subsidiary of EDF. They split off to remove worker protections from their (many) employees. Still extremely tied to the government. They have an extremely poor reputation as an employer (as in they have driven employees to suicide).
If you try to start any such companies in France, the government is going to outright sabotage you, whatever the laws say.
They are often both illegal and unenforced. Your old employer isn't going to waste time hiring a private detective to track down every former employee's new work place that you didn't include on LinkedIn.
We already do with legislation that requires severance packages and tax benefits for hiring. Many countries go much further.
> There’s no reason we couldn’t decide that we want to err on the side of employing too many people.
Yeah that's not how a company should run.
That doesn’t follow. It could just as easily bias a CEO towards over hiring, or finding ways to retrain existing employees, or any one of a million things that’s not the status quo.
It’s also possible that there currently exists pressure to push CEOs to lay off too many people and a little pressure in the opposite directions puts CEOs in a position where they are free to either layoff or hire as they see fit.
> Yeah that's not how a company should run
That should is attaching a moral judgement to this, and that’s not up to you. Many people think that the one of the primary purposes of a company is to provide employment. Even in the US our system makes it easier to hire someone than it is to fire them.
This is not good for society.
One might bring up the personal consequences bourne by surplus employees who're then laid off during the unavoidable corrective phase - or is that not something society should care about? What are you optimising for?
reading this article I think that is not what happened in this specific case:
> Over the last three years, Ford says it has hired 350 veteran engineers, many of them former employees and others from suppliers, to help address seemingly intractable quality woes that have cost the automaker billions.
> “Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product,” Poon said. But “we recognized that for us to enhance some of our automation and machine learning and artificial intelligence tools we needed to ensure that they were trained by the most experienced individuals.”
That is, Ford had been slowly relying more and more on automated tools (if the "rehiring" is over three years, then this all precedes our current "AI" ecosystem) and realized that now that they want to add modern AI tools, they need experienced engineers to train the newer systems, and are hiring people from the open market, where some of these folks were former Ford employees, but nothing like "were laid off due to AI".
That is this doesnt sound at all like "Ford fired 350 engineers to be replaced with AI and is now backtracking", which is certainly what the headline here implied.
The retention rates before COVID are back, and companies have way more people than they might need, that's the real reason so many places have started to slash, but blaming AI is easier.
https://en.wikipedia.org/wiki/Great_Resignation
Kind of made sense to me, I saw some of those outcomes happen in a former employer as well, they had an influx of income during 2020 that was not going to stay around forever (restaurant industry).
Risk is inconvenient to shareholders, who also happen to be the people with the most political power in the US. They're:
1) retirees living off a pension/retirement fund backed by shares of companies like Ford
2) investors who have plenty of money to ~~bribe~~ donate to political campaigns or
3) C-suiters put in place by the other two groups who are compensated primarily in shares.
These groups are all incentivized to see the risk to their income streams minimized as much as possible. Show me the incentives, and I'll show you the outcomes.
Thus, we got rid of the risk.
Don’t blame a customer for the vendor’s irresponsibility.
Just because I would not be destitute tomorrow does not mean that my life (and those of my family) would not be deeply impacted.
The article makes no such claim. What is your source? Absence of evidence is not evidence of absence. Or, are you just making things up that you believe are likely, like an AI would?
If you say something is illegal and costs $X as a fine, you don’t curb behavior, they just bake the fine into their business model.
Their entire management skill involve the application of one of the following options:
1 - Fire People
2 - Spend Money
3 - Call a meeting
It is reasonable to assume, that this could be walked back in such a way that no one is held accountable.
Because we've been alive in America long enough to see this cycle thousands of times. The execs rarely face the music for bad decisions. A round of layoffs looks like a failure to us, but to the investors it was a good idea that didn't work out so there's no punishment for trying to save money.
Are there any recent documented instances of executives being punished in some level of career-affecting way for bad performance?
Even when they get fired they get golden parachutes.
Example: Sam Altman founded a complete failure of a location-based social network, where the board tried to remove him twice, lied about being chairman of the YCombinator board, and now gets to be CEO of one of the most valuable companies in the world where the board tried to remove him as CEO once.
Failing up is very common in our corporate system.
It sounded like they had a "Stellantis discount" for people who said something.
Nice guy, actually.
Some of the things an owner would obviously get used to, but it felt like you were constantly struggling with it to do simple things that you don't even really notice doing in most vehicles.
The infotainment system was constantly having trouble, like freezing up or just shutting down for no apparent reason and not turning back on. I remember a lot of issues with the backup camera. Not unique for a modern car, but this one had more than its fair share of glitches. I think I had to reset it twice. It also developed an issue (sorry can't recall what it was exactly) that persisted for a day or two which spontaneously resolved itself while I was driving back to the dealership.
I want to say it had hardware AC controls (which is good), but I think I had it for three days and only figured out how to adjust it the way I wanted it on day three. I don't recall if I didn't understand that something was a button, or if a button actually had several different "modes" which weren't readily apparent, like being a combo rocker/push button. Normally these sorts of things are obvious from how the dash is deaigned, but my wife and I took three days to puzzle it out.
There were some other minor problems, but altogether it felt poorly thought out and kind of low quality, which clashed with some of the "luxury" accents my model was equipped with, like wood paneling and the lights which spelled out "WAGONEER" on the ground at night when you opened the door, which felt gimmicky. That money would have been better spent on refining the UX.
I actually don't think it was a bad drive, if you were just driving. I was just constantly frustrated trying to do anything else with it.
Leadership made a decision and that decision was bad. This happens all the time, including allocating budget for staff. Any effective organization is going to judge the outcomes of these types of decisions and it's going to come up in performance and hiring. If this was an isolated situation then possibly they won't fire anyone over it. But you really need the context to judge whether the response was correct.
Wasting company resources and making the company look bad in the press won't be rewarded, and that includes at the board level to the CEO.
By complaining together, we can create changes that make life more fair.
Even if you categorize missing out on some bonus or something as a consequence, it pales in comparison to the damage they've done and the lives they've severely disrupted and possibly irreparably damaged by firing people on a whim. (And I consider firing people because you fell for the AI hype / obvious marketing to be a whim)
That said, this application of AI was profoundly stupid from the outset. You don’t necessarily fire people for a bad result from a reasonable decision making process, but you do fire them for poor judgment and reasoning. There’s nothing that can fix that except for not letting those people make decisions anymore.
Which I guess is getting at another thing. The failure was predictable. People shouldn't be rewarded for failing to avoid obvious predictable failures. Maintaining their status quo could also be seen as rewarding them.
Workers get fired when they are wrong at much smaller scale, why not these people? They are not special, they are simply lucky and connected.
https://news.ycombinator.com/item?id=42639566 ("Pharaoh must signal, to shareholders, to a board, and to their peers. There will be no consequences for failure to adhere to this proclamation.")
Salesforce will hire no more software engineers in 2025, says Marc Benioff - https://news.ycombinator.com/item?id=42639417 - January 2025 (390 comments)
https://www.salesforce.com/company/careers/jobs/?search=soft... (724 results, as of this comment)
I can't speak for how these particular executives were handled. I've never worked at a place where people were quickly fired for mistakes unless it was something extreme. It's usually based on track record rather than a single thing. Most employers understand that if they fired people for making mistakes they would run out of employees very fast. On the other hand, someone who learns from a mistake probably isn't going to do it again so you may have a better employee than a hypothetical replacement. It's also generally understood that people with a large scope of responsibilities have a large blast radius when things don't work out. It just comes with the territory and it's not exclusive to the executive suite.
This shows to me that you have a lot of faith in these companies that I can't share based on my own experiences.
My experience is more like: the defining characteristics of what gets you more opportunities is personal attachment to the boss. They like you? You get more. The whole performance review culture, as an example, is based around phony justifications around this. They get to re-define what "getting results" means to favor buddies. This is the only determining factor, period, and people come across to me as absurdly foolish when they believe something else.
As usual it's communism for the plebs and something entirely different for the capital wielding class.
Bad example. Ask Bezos how much he paid his wife after the divorce.
If you wish to change it to "the law of society" which is what "society" backs with violence, go for it.
Nobody should "sacrifice future career prospects" just for a job. And if they do, it's hard to blame the employer on this, especially considering the premise implies they had choice in the matter.
That's why I'm saying to separate the process from the result when determining consequences. Someone who consistently exercises good judgment and who makes well-reasoned, thoughtful decisions is likely to achieve good results more often than someone who doesn't. But, event then, some things just don't work out and it impacts people's lives.
I would absolutely fire those idiots at Ford though. There's nothing wrong with trying to leverage AI. Personally, I like AI tools and I rely on them daily. But if someone lacks the judgment to figure out when a job should be performed by a human then they shouldn't be able to make decisions about how to use AI. These people are clearly out of their depth and just faking it. Clown show.
riff-raff cogs get fired for making bad decisions all the time. also if not punished for making decisions. how do execs ever get punished because all they do is make decisions.
Sometimes things don’t work out. That doesn’t mean it was a punishable offense to try.
It reminds me of the conspiracy theories I would hear as a child along the lines of powerful people running the world in shadows. I certainly feel like the ways people like executives keep getting away with unethical and in some cases illegal behavior is there's forces in the shadows supporting their behavior. I was told in history class that throughout history when such types of people arose such as kings in France or massive dictators who conquer countries, that the "good" or "masses" of humans eventually over throw them - well here we are and why isn't that happening?
I see instead a class of people weak, afraid, and defeated and continually asking others "why aren't you doing anything" without the awareness to see "You are the one who is supposed to do something" edit: applying this to myself, I'm certainly trying. Before I was fired at Capital One (as an engineer) I would continue to ask tough questions of integrity to executives and my team and managers, things about integrity, things about inconsistencies in our stated values and how we were actually delivering work. I took some heat, was not very liked, and took continual abuse from my team until I was eventually kicked out. I am happy to share how little I noticed people who felt uncomfortable with team culture and executive communication were just silent and afraid, and in denial as I got attacked and abused by management.
One for lay-offs, because it was the best move at the time with the knowledge they had.
Second for quick correction, ability to pivot and execute quickly.
It's been always like that
I would rephrase it as it’s only as good as you know what you are doing. Even if the trained input is good, keeping it to scope and making sure it delivers without workarounds requires a human brain who have the past experience.
I'm not talking about rocket scientist code either - I'm talking about things using raw for( instead of range-based for, or writing code that is absolutely fucking riddled with imperative logic, hacks, and kludges, when something should clearly be data-driven. Stuff that is so bad I have to tell it to start over. It routinely designs amazing architecture and absolute shit architecture, sometimes on the same day. It's just so weirdly inconsistent. If you ask it to fix a bug then you have to double check if it used a hack and sometimes it will admit to it. Sometimes it lies.
I just do not see how AI is going to replace large numbers of seasoned engineers. That would be a disaster for companies that try it. Could it replace large numbers of juniors? Yes. And maybe I am being fantastically naive. I'm 100% willing to concede that it's possible or even likely.
"Welcome back, you are now two levels down"
AI is confidently wrong a lot. And so you can imagine a lot of execs thinking the AI can do a lot more than it really can.
It's OK to just say that the plan was to rehire back the engineers for far less compensation.
Our AI sucked but that doesn't mean less AI. We need better AI, not humans.
Just two days ago at work a call of 15+ people spent a non-trivial amount of time recounting the scars of colleagues being laid off, or they themselves having to sign severance papers, only to be saved in the final hours. These events happened 10-15 years ago and they still cost the company time a decade later, not to mention that trust that erodes with these events.
If companies want people to focus on work, those people need to feel secure in their jobs. Laying them off and hiring them back is not job security. It’s a signal that management has no idea what they’re doing. Why would these people follow the leadership of those who can’t even solve the issue of staffing without making a mess of it?
It’s also bad when seemingly competent employees are laid off while incompetent ones stick around. It sends a signal that it doesn’t matter what you do, so why try.
Firstly, the "AI" discussed here is not LLM's. They are talking about visual quality inspection systems. There's been many other articles in the press: Ford's new quality automation is computer-vision defect inspection, built on IBM's visual-inspection tech, iPhones photographing parts on the line, running since 2020. By most reporting it works fine, pushing detection rates from ~70% manual to 99%+. This is classical CNN at work doing the job of quality inspectors... completely unrelated to desk-work by an engineer or what LLM's do... yet that's exactly the inference the headline invites (and many here in the comments seem to be making).
The timing only underlines it: rehiring is presented as the cleanup. Apparently the rehirings started 3 years ago, so whatever it's undoing is older still and therefore unlikely to be LLM driven. While ChatGPT did come out 3.5 years ago it seems doubtful someone would fire people left and right the moment they saw the first ChatGPT... only to then regret almost it immedaitely and rehire them - all within the span of 6 months.
This further supports that the article is about years-old automation bet being quietly unwound, and is completely unrelated to mainstream discussion about AI and jobs today.
Also, 350 rehires is just noise. Ford is shedding thousands right now: plant pauses, battery-plant retooling, projected restructuring in the 8–13k range.
Finally, as always with corporate announcements... ask why an internal staffing decision is even a press story. To me this feels like PR (a nice feel good story that ties into to a subject people discuss a lot now). It takes the sting out of all their announced layoffs. There's probably also internal company politics to it (someone suggested rehirings and now want to say 'see what a great idea this was' and maxx it out).
So maybe the key is firing everyone and then rehiring the good guys after you implement automated systems.
Though I’m somewhat surprised. I didn’t expect Porsches to top a reliability measure. I thought they were in the “fancy but unreliable” bin. Interesting.
An expensive process.
American automakers love crowing about that survey because it's easy to do well on. And then the car falls to shit six months later, but hey, it held together for the first 90 days so all good.
At a past role with a Tier-1, we bought part of the dataset. A quick regression showed that satisfaction was strongly correlated with buyer age, and there was very little signal otherwise. (Young people with overtime work and daycare pickups don't respond to surveys unless they have a serious axe to grind while retirees aren't so constrained)
I no longer want to make connection with any coworkers.
The short sighted gains (and I’ll assume that they are chasing quarterlies as usual) are to be had by firing most of the junior engineers, keeping the seniors because with AI they can n* their productivity.
Basically you can fire 2x junior engineers for every senior engineer you keep. But the senior engineers are the keystone here, and without juniors eventually becoming senior engineers you’ll eventually be screwed.
But, that’s a problem for the -next- c-suite gang… so…
I'm not sure this story is illustrative of that, when you have a VP of engineering saying “Over prior years, we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.”
He's saving face while almost certainly trying to figure out how to make the new systems work so that next time he won't need to rehire engineers.
Yup. They jumped the gun. Now they need to hire them back so they can loot their expertise and never hire another senior. I'm not saying this will work, but it's pretty obviously the plan.
Now, that training[*] will be for both AI models and lower-salaried hires.
Perhaps a second mistake by those who thought they didn't need their most experienced people: Now they think they just need to train the AI better, and then new-grad "AI native" hires will be the most cost-effective way to operate/oversee the AI and do whatever it can't.
[*] edit: originally typed "replacement" when I meant to type "training"
And to gloss over how that improvement would actually happen. (Not knowing what they've currently done and want to do, but for example, guessing: probably in partnership with vendors, consultants, etc., iterative and experimental process and tools improvements, and involving a variety of approaches and refinements.)
And for people focusing too much on AI, Xiaomi kicked their first vehicle into production with a fully automated factory three years ago [0]. That's where the industry is going and has tried to go for decades now.
They might want to also reduced head out on the designing side, but it's also an ongoing trend that started before the AI boom.
That's not an industry that will keep hiring as much as they did in the past, however it turns out.
Even when AI gets better, we will always need people who can troubleshoot AI itself.
Clearly a lot of careful thought went into their strategy of using AI and firing engineers.
My point being, Ford's had shit for brains for decades. Its a fucking wonder any of their vehicles make it out of the parking lot.
I'm not saying it was a perfect car. The interior was cheap, the sheet metal seemed to be recycled tin cans, and it definitely showed its age by the time I got rid of it. But that engine and drivetrain seemed to be bulletproof.
Pretty much everything Ford brings to the US that was designed in Europe is loathed by anyone who has to own it out of warranty.
Turns out that when you have a building full of engineers in Germany or England their domestic engineering culture results in work output not all that different from the sort of stuff people chastise BMW and Land Rover for.
That said, the Escort, and to a lesser extent the Focus, are generally considered very good vehicles.
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In that order, apparently.
Step 1: 30 minute conversation with AI on how to use AI. Step 2: fire everyone.
Step 3: Rehire key personnel at lower cost than whomever was fired in Step 1. Step 4: Take credit for cost reductions . . . and give yourself a raise!
C-suites completely disconnected from reality and assuming we've already achieved ASI/AGI, and marketing teams & business journals are only furthering that narrative.
It's so weird. I don't know what it is about AI that causes people to throw all thought and caution to the wind and charge forward blind. Its like they've been chomping at the bit for decades to get rid of those pesky humans and are so hyped up over it they can't see clearly anymore.
It's just a hype cycle. In my 15 years in data, I've seen around 3-4. Every time leadership get way too invested in the possibilities, and they waste tons of money on doomed efforts. A good example of the prior one was "Big Data" which was even more pointless than the current AI boom.
Don't get me wrong, there is valuable tech there (at the very least, being able to reliably generate structured data from unstructured input is incredibly valuable in data), but the current hype is way off the charts.
What does hype even mean concretely? I think this is just a coping mechanism if you ask me.
Er, what? Intricacies of a transformer pipeline might be boring and nerdy, but the results are not. BTW, I've yet to find any strong argument on why the current ML approaches are bounded below the level you find appropriate to be bored.
https://www.gartner.com/en/research/methodologies/gartner-hy...
The idea is there’s a rush of irrational exuberance when an “innovation trigger” makes a new toy looks promising, and everybody rushes to use it for everything, regardless of whether its suitability-for-purpose is proven. Inevitably many of those pioneers find that it’s not good for their particular problems after all; usage reaches a “peak of inflated expectations,” and crashes into a “trough of disillusionment.”
Then the tech enters a quieter and more gradual “slope of enlightenment” as people work out use cases where the tech actually adds value; then adoption reaches a “plateau of productivity.”
Worth a glance at the way they map this to prior waves of technological exuberance.
From your video, it looks like your definition of hype involves a situation where eventual adoption increases above what is in the hype today.
Here's what the parent comment thinks:
> It's just a hype cycle. In my 15 years in data, I've seen around 3-4. Every time leadership get way too invested in the possibilities, and they waste tons of money on doomed efforts. A good example of the prior one was "Big Data" which was even more pointless than the current AI boom.
Obviously the parent doesn't think of hype the way you think of it because they claim that big data was pointless -- they don't see the eventual "slope of enlightenment". They think of hype cycle in the colloquial way and I was responding to that.
I see this all the time in the website and frankly the patronising "but actually hype means something else" is pointless and pedantic. I urge you to respond to words within the context and not bringing in academic definitions.
I think the tech is useful, but the hype is ridiculous so I expect lots of companies to have large share price declines et al when this settles.
Big data also had a good core, but all the e-commerce sites building a data lake wasted lots of money.
For those that lack initiative, strategy, a real understanding of their business, engineering, etc., the spewing words is the whole thing. It overshadows their entire understanding.
> Its like they've been chomping at the bit for decades to get rid of those pesky humans and are so hyped up over it they can't see clearly anymore.
This is precisely it. Here's my analysis:
AGI is a savior figure for the capitalist class. A tech version of the Second Coming, delivering them from the pesky demands of workers, like a living wage or (gasp!) sick leave.
That's why they're all so obsessed with it, it has religious-ideological component to them. When you hear them talk about AGI, there's always this weird eschatological vibe with it.
Unfortunately, they're blinded by their beliefs and can't think things through even one step further. Even if their cyberjesus comes down to them through the machine and replaces all workers, who's gonna buy all their stuff then?
All they're doing in their capitalist zealotry is ringing in the end of capitalism.
Knowledge or skilled workers can be used by the AI for swarm training data generation; what value do the execs have to AI?
I think the most beautiful part of capitalism is selling elites rope to hang themselves.
> A tech version of the Second Coming
These guys have squeezed out every cost and slack from their system. They've found the exact revenue-maximizing prices and segmentation for their products. They've cut quality to the point where customers will just barely not reject their product. They have used every legal and accounting trick at their disposal to keep that line going up. But, next quarter, line must still go up!
The final massive cost to cut are all those damn human bodies that they they still have to keep around. They've driven down salaries and benefits to the minimum they can get away with, and they've extracted the maximum value from employees they can. But they haven't figured out how to get rid of them entirely. They are staring down the barrel of the gun and just can't see a way to cut this cost further. Now, magic AI comes along, and everyone is saying that the black box can replace those bodies. The C-suites believe it. They have to believe it. Line must go up! This is how they'll do it for a few more quarters. This is why the messaging is so unified across the industry, across every C-suite out there. They all need to believe.
The real danger for the economy is when the runway finally runs out. And I believe we are at a perfect-storm scenario... AI is obviously a giant wash-trading bubble that alone would be sufficient to trigger a repeat of the 2007ff crisis. But on top of that, we got the issue you mentioned, i.e. everyone running out of kool-aid and noticing it too late, with no easy way of turning around, and we got the war risk and supply chain shocks thanks to Iran and Russia, and and and.
1. Zero personal risk because cargo culting is a valid excuse in Executive World. If investors are on board, its good, no matter how stupid or destructive it actually is.
2. Top leadership's friendship with the country's leadership equals access to cheap debt financing since money is all fake and generated out of thin air
3. Too big to fail
My favorite theory about this is that we're all used to "speech == intelligence" and now that we have something that can produce coherent speech, it seems like it must be intelligent to people who don't know how it works. Even people who know how it works still anthropomorphize it to a weird degree. So a business person sees this thing that's both intelligent (to them) and superhumanly fast and it seems like the ultimate silver bullet.
That made reading their subsequent layoff blog posts pretty depressing
Reminds me of this disaster at Toyota,
https://www.wsj.com/business/autos/toyota-bet-technology-wov...
The editorialized headline is also misleading: "Ford rehires 350 engineers after AI fails to preserve expertise or train juniors" - there is nothing in the original story that suggests Ford were expecting AI to "train juniors".
And since the Bloomberg headline is behind a paywall the editorialized headline is most of what we have to go on.
This Verge story would be a better link: "Ford had to hire back former engineers to fix mistakes made by its automated systems" https://www.theverge.com/transportation/956316/ford-quality-...
And the crucial detail: nothing indicates Ford laid off the 350 people who were re-hired. It looks to me like it could be bringing back people who retired.
The headline gives the impression that Ford fired 350 engineers and tried to get AI to train the replacements and then re-hired them when that didn't work.
That impression is false, which means we're wasting time having conversations about it.
(The top comment thread on here right now - https://news.ycombinator.com/item?id=48674446#48675092 - starts with the assumption that Ford execs made the mistake of laying off 350 people and then discusses if they got good severance packages etc. - here's the best comment I've seen calling that out so far: https://news.ycombinator.com/item?id=48674446#48675486)
won’t someone think of the lightcone!
You're absolutely right, Charles Schwab, we should cut 10% of our workforce tomorrow!
It’s a disease that has spread throughout all of capitalism.
But that’s USA 250 years.
We will still see several reports of over adoption, mistakes, regression… all will only serve to learn, refine, and hopefully regulate.
I think it’s pretty naive to expect the entire world will simply discard the technology and go back to having humans doing it all.
It’s to replace 99% of your staff. In every industry.
Ai will be a useful tool, but either companies like OpenAI are massively overvalued or the economy will completely vanish at a high speed and their valuation will be meaningless.