Posted by alanwreath 2 hours ago
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.
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.
As usual it's communism for the plebs and something entirely different for the capital wielding class.
If you wish to change it to "the law of society" which is what "society" backs with violence, go for it.
Bad example. Ask Bezos how much he paid his wife after the divorce.
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.
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)
By complaining together, we can create changes that make life more fair.
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.
the same consultants can be blamed if decision backfires
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.
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
It sounded like they had a "Stellantis discount" for people who said something.
Nice guy, actually.
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.
It is reasonable to assume, that this could be walked back in such a way that no one is held accountable.
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.
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.
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.
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.
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.
Their entire management skill involve the application of one of the following options:
1 - Fire People
2 - Spend Money
3 - Call a meeting
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.
I'm prosperous because god/market deems me worthy.
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.
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.
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.
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)
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 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.
Clearly a lot of careful thought went into their strategy of using AI and firing engineers.
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.
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.
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.
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.
What does hype even mean concretely? I think this is just a coping mechanism if you ask me.
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.
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.
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.
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
> 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.
In that order, apparently.
Step 1: 30 minute conversation with AI on how to use AI. Step 2: fire everyone.
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.
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.
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.
That made reading their subsequent layoff blog posts pretty depressing
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.
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.
https://books.worksinprogress.co/book/maintenance-of-everyth...
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.
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 the verge is covering it too:
https://www.theverge.com/transportation/956316/ford-quality-...
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.