"The modern conservative is engaged in one of man's oldest exercises in moral philosophy; that is, the search for a superior moral justification for selfishness." ― John Kenneth Galbraith
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Jon Favreau asks author Ben Wikler about how voters respond to legislation that improves their lives over the course of time. Strategies for building winning coalitions.
Pod Save America's Jon Lovett and The Bulwark's editor, Jonathan V. Last, discuss how openly Marco Rubio and Stephen Miller are quoting Joseph Goebbles and Adolf Hitler's propaganda from the 1930s in their egregiously bigoted diatribes demonizing Democrats and claiming they are all deformed and ugly. Employing the exact tactics of the Third Reich in which Jews, Romani, LGBTQIA+, and the disabled were all targeted for being undesirables prior to the Nazis' insidious mass extermination pogrom.
Most gaming computers can run effectively with 16GB of DDR4 or DDR5 of system RAM with a decent CPU and GPU combination. For gaming having more video card memory is a better place to spend.
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Democratic Divide | The Weekly Show with Jon Stewart
Jon Stewart asks Pennsylvania's pathetic senior U.S. senator why he refuses to accept anyone in the Democratic party who disagrees with wanted war criminal Benjamin Netanyahu and his genocidal pogrom against Palestinians. John Fetterman responded that Democratic Socialists should form their own party and be excluded from the Democrats for not giving 100% unconditional support to Israel — a ride or die deal breaker. Stewart countered that the U.S. only has a two party system and that both the Tea Party and MAGA are still part and parcel of the GOP. Fetterman apparently is unaware of how his own government actually functions.
Either his stroke destroyed his cognitive functioning or he has completely sold out to AIPAC as he vehemently defended Israel as the only important issue in U.S. politics. Irrespective of Israel's actions, the United States must always and without any restrictions support them and their atrocities. There is absolutely no room for any negotiation with regards to undying loyalty to Israel at all costs. Fetterman then had the chutzph to explain to Stewart how all Jews support Israel and whatever Israel does is automatically de facto justified. Stewart immediately corrected the fatuous Fetterman that Jews and Judaism are not the same as the nation of Israel which seemed to completely confuse or anger the demented senator.
[Image ID: The Destiel confession meme edited so that Dean answers 'JK Rowling posted upskirt photos of a woman on Twitter' to Cas 'I love you'. /End ID]
No one doing this should be allowed to call themselves a feminist.
The wealthy author escalated a social media spat that resulted in posting a photo from a 2023 event at the Institute of Economic Affairs in
Let's not beat around the bush: Children's author JK Rowling sexually harassed a woman. In some jurisdictions, this would count as sexual abuse. JK Rowling has committed a sex crime against a woman and fell back on the old rape apologist standby of "she was asking for it".
She's also encouraging people to take photos of strangers in public toilets to "police their gender" which is both harassment in the general sense & sexual harassment
JKR isn't just a holocaust denying sexual harasser, shes encouraging others to do the same
If you still support JKR after all this, you should own it & make sure that everyone around you irl is well aware of the fact that you're ok with sexual harassment of women & holocaust denial.
Tell your boss, your parents, & your friends.
If you "have a right to consume HP content" they have a right to know that you're ok with what JKR has done
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[Inage Description: two photographs of a flatworm inching across moss. The worm has a pale and dark green striped body, and a red head, making it look like a stretched-out watermelon. End image description.]
People Keep Destroying Flock Cameras Across America. The Paperwork Already Saw It Coming.
Somewhere in Ashland, Ohio, a city employee is filling out a purchase order this week for a new camera pole, a new solar panel, and probably
Shawn Henry
Fri, July 17, 2026 at 1:00 PM CDT
Somewhere in Ashland, Ohio, a city employee is filling out a purchase order this week for a new camera pole, a new solar panel, and probably a new wiring harness. That paperwork has become awfully familiar in a growing list of towns, from Georgia to Idaho, where someone with bolt cutters, a hacksaw, or a can of spray paint got to a Flock Safety license-plate camera before anyone else did. The headline everyone is chasing is that vandals are destroying surveillance cameras. The more useful story is sitting in the contracts these cities signed, and in who actually pays, and who actually profits, when that hardware gets destroyed.
The incident list has grown fast since mid-June. In Ashland, Ohio, crews found shattered solar panels and camera poles apparently struck by vehicles, bats, or clubs. In Houston, police are still tallying cameras found cut in half and spray-painted along Washington Avenue. Deputies in Barrow County, Georgia found three poles sawed clean through along a rural road. And in New Bern, North Carolina, two men caught on camera cutting down a freshly installed unit became local celebrities after the police tip line filled up with joke submissions for "Batman and Robin."
None of this is new, exactly. It is just louder. Camera destruction has been reported in scattered cities since at least early 2026, and law enforcement sources have put the running national tally at more than two dozen destroyed cameras across five states dating back to April of last year. What has changed is the backdrop. The same weeks that produced these bolt-cutter headlines also produced a Georgia sheriff disciplining officers for misusing Flock data, a nationwide pattern of officers turning the cameras on their own exes, and a Supreme Court ruling that is now feeding a live Fourth Circuit case over how the technology gets used. Vandalism is the visible symptom. The credibility problem is the disease.
Read the Fine Print Before You Reach for the Bolt Cutters
Here is the detail almost nobody protesting these cameras seems to know: most cities do not actually own them. Flock leases the hardware as part of an annual subscription, and when a pole gets destroyed, the replacement cost shows up as a line item rather than a loss the company simply absorbs. Flock's own support materials describe a "Camera Protection Plan" that repairs or replaces damaged units, and the trade publication IPVM has reported replacement invoices running from roughly 500 dollars for a standard pole up to 2,000 dollars for an advanced one, with a damaged camera billed separately on top of that. Someone pays for every camera that goes down. It just is not Flock.
The bolt cutters do not send Flock an invoice. They send one to the city.
The Network Is Also Catching Its Own Vandals
There is a second irony sitting right next to the billing one. In Alexandria, Virginia, police say they identified a 21-year-old suspect accused of destroying multiple license-plate readers after another camera nearby flagged distinctive damage on his own vehicle. The dragnet built to catch car thieves just as easily catches the person trying to blind it. That is not a coincidence. It is the entire design premise of a camera network with no meaningful blind spots.
A system built to have no blind spots does not develop one just because you are angry at it.
This Fight Was Already Being Won in Court
While bolt cutters were making local news, the more consequential pushback was happening in places with actual subpoena power. A Supreme Court ruling on cellphone location tracking is now reshaping a live Fourth Circuit lawsuit over Flock's data practices, and a growing number of city councils have simply declined to renew their contracts once the public comment period arrived. Oakland's own department quietly muted stolen-car alerts after the system generated more than a million of them in a single year, which says something about how unmanageable this technology had already become on the inside, long before a single camera got touched.
What Actually Ends a Flock Contract
None of this is an argument for property destruction, and it is worth being blunt about that. Several of the men now facing charges in the cases above are looking at felony destruction-of-property counts and restitution bills that will outlast whatever satisfaction they got from a Saturday night with a hacksaw. If the actual goal is fewer license-plate cameras on your street, a more effective and legal playbook already exists. Flock contracts are typically multi-year deals that come up for renewal at city council or county commission meetings, and public comment during that window carries real weight, especially once the invoice history for a broken camera becomes public record. Public-records requests matter just as much: researchers uncovered cops using these cameras to track romantic interests largely by digging through audit logs that any resident can usually request. State legislatures are actively drafting license-plate-reader oversight bills right now, and privacy advocacy groups track deployments and pending legislation county by county. Even the private businesses hosting a camera in their parking lot are a legitimate pressure point, since those hosting agreements get renewed quietly and rarely draw the scrutiny a police contract does.
A saw shuts off one camera for one night. A council vote shuts off the whole network for good, and nobody has to explain it to a judge afterward.
“The department’s own records described repeated installation failures and extensive peeling of the pool liner weeks before the alleged vandalism was ever said to have occurred. Prosecutors asked that the charges be dismissed because the evidence no longer supported Pirro’s claim, evidence that, it bears repeating, had been available to the government the entire time”
—
Jeanine Pirro’s Reflecting Pool reckoning
This was always such a stupid thing to lie about. The evidence was out in the open for everyone to see, the entire time. Literally everyone with a pulse knew what had happened and why they were lying about it.
And what will the reckoning be, actually? She probably gets fired and replaced with someone who is equally incompetent and corrupt. Nothing happens to Trump, who repeatedly insisted there was extensive video evidence of antifa cutting a 300 foot gash through the middle of his hideous pool liner job, yet never – NEVER – produced it. And, weirdly, the damage he claims was caused by vandals matches precisely over the tire tracks he left when he drove over it for a photo op.
This is like every other thing Trump fucks up. It was fine, it didn’t need anything at all but he decided to create a problem, declared that only he could fix it, made it worse than it was before he touched it, blamed an innocent person who had nothing to do with it for his own fuck up, and is now walking away from it like it never happened, leaving behind wreckage for someone else to clean up and repair.
That’s Trump in a nutshell. The reflecting pool calamity is a perfect metaphor that anyone can understand. This is exactly what he did with the Strait of Hormuz. This is exactly what he did with the Kennedy Center. This is exactly what he does with EVERYTHING.
I will never forget and I will never forgive the people who voted for him, supported him, and now want to pretend that they were fooled.
1) Trump chooses to make things personal, see his social media posts about how he is saving the pool from all the damage the Obama administration did to it. He says it’s going to be amazing and perfect. He says it’s going to be blue.
2) Then he awards contracts based on loyalty rather than competence. Just like his cabinet hires.
3) When reality (mediocre pool results) comes crashing in, his ego won’t allow him to be responsible for it. So he has to find someone to blame.
Repeat with Iran, with tariffs, with immigration. A calmer, more rational leader would keep issues at arms length.
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
Neoclassical economics assumes rationality. The corollary of, "If you're so smart, why aren't you rich?" is "you're rich, so you must be very smart!" Thus it is that many people assume that if powerful, well-compensated CEOs insist that "AI is changing everything," well then, AI must be changing everything.
But the evidence for this "changing everything" thesis is thin on the ground. Despite a global mania that has reduced the real, pressing need for digital sovereignty to the imaginary need to create "sovereign AI," no one can really articulate the case for "sovereign AI." If Donald Trump ordered Big Tech to turn off all of your country's chatbots tomorrow, nothing would change. Every one of your country's ministries and corporations would chug on with nary a hitch. Households, too, though perhaps a few of the younger members of those families would have to do their own homework again.
(Contrast this with what would transpire if Trump directed his tech giants to switch off your country's Office 365 access, or to brick your Android and iOS phones, or to killswitch your John Deere tractors. Your country would effectively cease to exist. If "digital sovereignty" means anything, it means doing something about this urgent fact):
The world is full of people who insist that "AI is changing everything" but who – when pressed – have to admit that what they mean is that they're pretty sure that AI will change everything. Eventually. After we allow it to consume all the planet's energy, carbon, water and financial resources.
Maybe.
(They're pretty sure.)
One person who's had a lot of opportunity to observe the shear between the stated business/AI situation and the real business AI situation is Nikhil Suresh from Hermit Tech, a consulting firm of "radically ethical data wizards" (that is, tech consultants). Suresh reports on his experience talking with hundreds of executives (and, more importantly, their subordinates) about what (if anything) AI is doing for business in an essay entitled "AI Mania Is Eviscerating Global Decisionmaking":
Suresh has a good track record of writing trenchant, frank criticism of AI. You may know him from his 2024 essay, "I Will Fucking Piledrive You If You Mention AI Again":
Or possibly from his "Contra Ptacek's Terrible Article On AI," a stinging rebuttal to Thomas Ptacek's widely read "My AI Skeptic Friends Are All Nuts":
While those are important pieces of critical AI realpolitik, none of them have the heft or urgency of "AI Mania Is Eviscerating Global Decisionmaking," whose thesis can be summed up with this passage from halfway through this 6,000-word article:
[W]e’re facing a coordination problem around executives being honest around the AI gains they’ve witnessed – if they co-operate, they keep their jobs. If they defect, they will possibly be fired by their embarrassed peers (who have now been implicitly called liars, cowards, or incompetents) and then replaced with someone that will toe the line anyway. If they could all admit the truth at once there might be some hope, but there is no way to coordinate that event.
In other words, corporate leadership is starting from the premise that AI has (or will) radically change the business, and they're working backwards from that premise to find the evidence to support this article of faith.
In support of this thesis, Suresh cites "hundreds" of conversations with execs and employees who spoke to him on the condition that he would "file the serial numbers" off their stories. These, combined with his own experience consulting for large, multi-billion-dollar companies make it clear that "AI mania" is an absolutely justifiable label for the state of AI in corporate circles.
Here are a few highlights from this morning's read – moments where I had to look away from my screen and read out a passage to my wife so that we could share a "holy shit" moment.
A person worked for a division that "pivoted" to re-engineer its software to create interfaces that support AI agents. When it became apparent that only ten users had touched this expensive new technology, they "pivoted" again to support "agentic workflows." Why did they double down on AI agents after discovering such yawning market indifference for "agentic"? "Because every company has to do something agentic now."
Suresh describes this as a literal religious mania. In the 500+ employee businesses Suresh studied, the only people who were promoted – or even spared from being fired – were people who professed "religious declarations of faith" about "the transformative power of AI." Employees who voiced honest, informed objections to AI in the workplace were passed over for promotions or targeted for layoffs.
This has created a situation in which everyone – "boards, executives, employees, vendors, consultants" – has a strong incentive to lie about how much AI is delivering for their companies. Suresh says he's seen announcements from publicly traded companies about their AI triumphs that he knows for a fact never took place.
Suresh says he's never seen a successful enterprise AI project: "Every single one – we have seen 0% success in a year and a half." Not one of their clients would face a business challenge if OpenAI went out of business tomorrow. The problem most companies struggle with is that they're "terminally bad at running software projects effectively." Adding AI to the mix doesn't solve this problem – it just adds a whole new range of ways that software deployment can fail.
Chatbots don't help. The internally facing chatbot that's supposed to help employees figure out how to navigate the business sucks because it is only as good as its training data – the business's documentation of its own processes. Businesses suck at documenting their processes. Customer-facing chatbots also suck. They either can't solve your problem, or, when they seem to solve your problem, the "solution" goes nowhere.
Suresh recounts his sole positive customer service chatbot experience: a Mitsubishi chatbot with a natural sounding, responsive voice politely took all the details of an automotive failure and promised him a callback. That callback never came, but Suresh is certain that Mitsubishi has logged this as a chatbot success story, even though the experience convinced him not to buy a Mitsubishi car.
Suresh and his team at Hermit Tech now have a policy of not even asking about ongoing AI projects. They've learned that by the time an AI project has begun, no one will discuss it honestly until it reaches a crisis point.
Suresh says he frequently encounters people who reflexively utter the AI catechism: "AI is changing everything." But when he presses these people for details, they admit that their organization "does not currently use LLMs for anything, and indeed, that they cannot name a single thing that has changed other than they get some use out of ChatGPT."
This shear ("AI is changing everything"/"Well, OK, we're not using AI for anything") is so extreme that Suresh once met an exec who confessed to crafting an AI-centered AI strategy for a $2b/year business, even though that exec "had never even used ChatGPT or any AI tool in their life."
Some people have privately admitted to Suresh that they've embraced AI in order to earn a career-boosting corporate reputation for "thought leadership." But many other people (especially nontechnical people) sincerely believe that AI is about to "change everything." As Suresh says, if you're in business with a liar, you might be able to reason with them in private – but you can't reason with a true believer.
The true believers are in charge. Suresh points out that it would be very weird for the CEO of an engineering firm or a hospital to mandate "specific procedures or building techniques without explicit agreement from the professionals on staff." But when it comes to AI, business leaders will confidently demand that the skilled professionals who perform the business's core functions use AI, even if those professionals don't think it will help.
As an aside: I remember the dotcom era, when the business press was full of articles about the conflict between CEOs and a new workforce that demanded the right to use the web on the job. Today, the business press is full of articles about the conflict between the workforce and CEOs who demand that they use AI.
Suresh describes workers who feel they have to "AI wash" their work: "They just do the work, the same way they have for decades, and say Claude did it." To add verisimilitude to this sham, they write circular processes in which one chatbot prompts another, and then the process repeats itself in reverse, for the sole purpose of consuming AI tokens to score a high rank on corporate "token leaderboards."
How to account for this wildly, expensively irrational corporate leadership? Suresh places the blame in the hypnotizing, mesmerizing power of the AI demo. For example: Hermit Tech is often engaged to set up a database product called Snowflake for its customers. Snowflake has a useless, expensive AI bolt-on called Cortex, that Snowflake itself describes as being 92% accurate under ideal circumstances (that is, at least 8% of the time, it will mislead you, perhaps very badly).
Suresh describes sales meetings with execs who were lukewarm on the idea of retooling with Snowflake, but who were very interested in Cortex. Against their better judgment, Suresh and his team provided them with a Cortex demo, carefully explaining that this AI tool could not satisfy their requirements. Without fail, this resulted in the previously lukewarm customers insisting that they be allowed to purchase Cortex immediately. Sales prospects who'd been unmoved by a pitch for new technology that would result in millions in savings were hypnotized by demos of a product that was described as unsuitable and unreliable.
To their credit, Hermit Tech refused to sell these customers Cortex, and stopped doing Cortex demos altogether. Suresh describes the experience of "the total 180°, that shift from ice-cold to red-hot buying frenzy" as "deeply unsettling." What's more, the Cortex demos that Suresh and co performed were, by his account, pretty uninspiring. The thing that these demos had going for them is that they showed AI actually doing something marginally useful, to execs who'd already spent millions on AI without having anything to show for their money. The spectacle of AI that does something galvanizes corporate leaders who feel like they're the only bosses who can't find a revolutionary use for AI in their businesses.
This is the situation up and down the corporate org-chart. Suresh has a reader whose title is "Head of AI" at a billion-dollar firm who tells him "their job is totally fraudulent but it was the only promotion pathway remaining at the organisation." This exec is hardly alone. They're part of a cohort of executives at companies that have publicly announced "100x" productivity gains, but who confessed to Suresh that nothing of the sort has happened.
Why did these companies make these claims? Because their customers were making the claims. How could you hope to sell to a company that had 100x'ed its productivity with AI unless you, too had 100x'ed your productivity? If, as a vendor, you walked into a boardroom and said that this wasn't a plausible claim, you'd be calling your sales prospect a liar, with real consequences: "getting enterprise contracts cancelled because you wanted to opine on something that doesn’t really matter to your organisation’s mission is a great way to get fired."
With the state of the industry dominated by froth, lies and mutual destruction pacts, it's no wonder that companies are deploying "totally gameable metrics such as 'money spent on AI'" as a means of evaluating employees and divisions.
Between true believers and people who must find ways to plausibly tout their AI usage, there is now a gigantic market for "AI solutions." At best these are just traditional tech consulting contracts, like migrating a database from Oracle to Snowflake, with some kind of ornamental AI usage around the edges so that the person who commissions the work can claim to be "procuring AI-enabled services" for the business.
This isn't a harmless frippery: contracts are delayed and work is put off until the work can be made "sufficiently AI" to attain the minimum degree of buzzword compliance. Worse: every fake AI project that produces real results (because it's not really AI) adds credibility to the AI true believers, who view these projects as proof that AI can do anything, and therefore demand to know why everything isn't being done by AI.
Suresh ends his essay with a long section on how to "navigate AI mania" – advice for how to smile and nod politely when you're confronted with AI bullshit, while steering clear of the worst consequences and avoiding needless fights. This looks like very sound advice for anyone in a corporate environment, but thankfully, that isn't me.
Rather than summarize that advice, I want to reflect a little on two questions that Suresh's essay raises but doesn't answer. The first is why? Why are people in power such easy converts to this religious mania?
I have my own theory. The most important discomfort that powerful people experience is having ego-shattering conflicts with subordinates who know how to do things they do not know how to do. The fact that you're "in charge" is hard to reconcile with the fact that the people you're nominally in charge of tell you that all your ideas are impossible, illegal, immoral, or lethal:
Take that Cortex demo. Sure, Cortex is an expensive, unreliable way to address a Snowflake database. But (unlike Snowflake) Cortex is controlled via conversational, plain-language commands. With Cortex, a boss doesn't need to ask an underling to retrieve information from the company Snowflake system, an interaction that might come with unsolicited feedback about the technical or commercial incoherence of the boss's request. Cortex is the underling, except that unlike a human underling, Cortex never back-sasses you about your foolish questions. The fact that it grossly misleads you 8% of the time is a small price to pay for a life untroubled by uppity pismires who insist that your ideas be connected to base reality as they understand it.
The other question Suresh implicitly raises is, "How can you reconcile the failure of AI in the enterprise with the individual claims of skilled technologists who insist that AI is helping them do great work?" The answer is that these AI users are "centaurs" – experienced workers who are assisted by automation on terms that they set for themselves:
Thanks to their skill and experience, these workers possess discernment, the ability to tell good code from bad, and (more importantly) good uses of code-generation tools from bad. They demonstrate the adage that worker-driven automation improves quality, while capital-driven automation improves throughput:
An automation technique that requires close supervision by skilled and experienced workers isn't going to be a raw productivity powerhouse. You don't "100x" your code this way, at least, not in the sense of firing 99 of your coders and having the remaining programmer pick up all their work. Rather, an automation tool that requires the continuous and conscientious exercise of discernment will let individual practitioners improve their work in extremely satisfying and useful ways. It's a way to spend more on operations in order to produce better outputs. It's not a way to cut your workforce, realize a gigantic savings, and still produce comparable goods and services at a far lower cost.
That is why some individual coders report such delight with their AI tools. They engage with those tools on their own terms, to improve their work in the ways that they, in their expert judgment, consider beneficial. No one ranks them on a "token-maximization" scoreboard. No one tells them they can't do a project if it isn't "sufficiently AI." When they set out to do a project, no one makes them prove that it couldn't be "done by AI."
As ever, the most important fact about a given technology isn't "what it does," but "who it does it for" and "who it does it to."
All the pathologies Suresh observes and documents so well in this piece are hypertrophied versions of the buzzword-compliance dysfunctions from previous bubbles, but at a scale never before seen. Quantity has a quality all its own. These businesses aren't just wasting billions – they're replacing skilled workers with defective chatbots. As I've written before, AI is the asbestos we're shoveling into the walls of our technological society. Our descendants will spend generations digging it out again, and the longer the bubble goes on without popping, the longer it will take to repair the damage.
In other words, corporate leadership is starting from the premise that AI has (or will) radically change the business, and they're working backwards from that premise to find the evidence to support this article of faith.
I've seen this happening and it is terrifying. Being told that the organization you work for has made a huge investment in AI, and that your opportunities for advancement (or even getting to keep the job you have) are contingent on finding a way to use that AI....What are those workers realistically supposed to do? Stand up for accuracy and get fired? Point out the ecological and ethical impacts of increasing AI use and hope the executive who made the AI investment doesn't decide to save money by terminating the squeaky wheels? Try to unionize and get fired? They're too scared to do anything but comply.
And that enhanced tendency toward compliance is a big part of the appeal of AI, as mentioned above. AI doesn't talk back, which business leaders LOVE. So human workers are learning to also not talk back, because they can tell it's dangerous to their jobs to do so. No one will say that the emperor has no clothes when the AI is confidently describing the clothes (and being so complimentary about the emperor's taste in fabric!). If you can't see the clothes, then that's a defect in you; nothing else could possibly explain it.
The funniest thing about the old "emperor's new clothes" story is the part where no one in that story stopped to think about the logical conclusion according to the described properties of that magical fabric.
Some nonzero number of people were going to perceive the emperor as naked.
They were so worried about personally being thought simple, or unsuited for their own job, that no one stopped to think about the people who really were unsuited for their jobs. And anyone who lives in a society knows we've got a fair number of those.
By the description originally given, anyone who was incompetent at their job would get an eyeful of bare emperor, because the cloth would be rendered invisible. Who would choose to dress in something like that? Who would risk parading through the street, appearing to be naked to people who were bad at their jobs?
And we're all just staring in confusion and disbelief at these naked C-suiters, as they proudly slap each other on their (naked) backs, congratulating each other on their masterful implementation of AI.
It feels as if we're having to choose between having a roof over our heads versus using our principles to keep the rain off of us. I can't really blame front line workers for choosing to stay housed.
Without naming any names, about a year ago one of the mega companies behind one of the big AI things informed its marketing and advertising partners to stop asking for actual internal data for use cases to build commercials and campaigns around. Turns out their own internal research showed that inside their own company, no one used it, no one wanted to use it, and the people who were forced to use it were less productive and very upset about it. Legal wouldn't let them pretend otherwise publicly; too much documentation. All their spots are now aspirational and very vague.
One of the few aspects of this AI bullshit where it's clear the emperor has no clothes: lawyers insulating their clients against specific claims and liability over what the AI things can actually do.
Turns out their own internal research showed that inside their own company, no one used it, no one wanted to use it, and the people who were forced to use it were less productive and very upset about it.
So the Sillycunt Valley corporations made themselves hostages to their own bullshit to sell something that's unreliable, fully centralized and thus insanely expensive to maintain, impossible to customize by the client and raising a whole host of privacy and data security issues.
The business model for that is coming apart: it rides on bullshit of the highest order, desperately trying to nickel and dime the customer while even bigger amounts of money are blown on the hardware backend that somehow can't get operational if it gets built in the first place.
Also, let me get this straight: are we talking about "what things the AI can actually do" as a promise or as a threat?
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