The Hackening

Last week at a small conference, there was talk about a future event referred to as The Hackening. As in, within 6-12 months, many predicted that due to advanced AIs and AI agents the internet would become a severely hostile place. Some worried that this could rise to the level of ‘assume any phone connected to the internet is rooted’ and several people urged doing general crisis preparations on a personal level, in case of disruptions in supply lines, power, water or internet.

It did not take long for things to escalate.

The biggest hack is a flaw in PHP, which can be exploited to take control of the computer running any website using an unpatched version of PHP. There are many others.

On a personal level, you want to do at least some basic prep and get your security in order. It is cheap to do as a form of insurance, and being caught not having it when you need it is a large mistake. That doesn’t mean you should panic, or cancel travel plans or anything like that. But there is low hanging security fruit out there. Pick it.

And So It Begins: PHP

Joshua Achiam (Formerly OpenAI): Feels like March 1, 2020 for Cyber. Not normal, something is happening. Internet lockdowns in a couple of months?

Multiple sources using GPT-5.6 Sol identified a critical flaw in PHP. Okay, identified two critical flaws in PHP. The plan was to deploy the patch first before announcing the flaw, but the embargo on the fix got broken more than six hours in advance, so here we are.

Dan Lorenc: I wanted to share what happened with the PHP embargo, our role in it, and my decision process last night to ship the fixed builds early. First of all, the PHP Foundation and maintainers did an amazing job here in a high stress situation. I'm sorry that my decision led to even more stress for them.

We first got read in that there was something coming up in PHP last Friday by one of the original researchers that discovered this issue. That night we were able to independently discover the same issue using our harness and a frontier model with a basic prompt of "find bad vulnerabilities in PHP".

We got fully read in Saturday and confirmed that some our findings matched those from the initial report, and worked to help test the fixes.​

They may have been in a rush due to attackers finding the exploit. Amazon reports that this was happening as early as October 17, four days before disclosure. We are fortunate that this did not scale far larger than it did. [...]

Jonny G: Can somebody explain this to me like I’m 5 years old please? Ta.

BRYNMAWR ∴ SHERLOCK: Websites are files on a computer. When you view a website, you are asking the computer to send you the files, then your browser shows them to you.

70% of the websites you see use PHP to make them interactive. So you can send things to the website too and it can respond. E.g. filling in a comment box and hitting ‘post’ adds the comment as a row to a spreadsheet.

PHP has a flaw in its code that allows anyone to gain control of the computer that has the website on it.

The organisation that provides PHP announced the vulnerability before a patch was available, meaning we’re in a window where everyone knows about it (including baddies) but the good guys don’t have an official solution.

Some are just turning off their websites and waiting for the solution. Others are trying to fix it themselves. General chaos and lots of stressed techies across literally the entire planet because this affects the entire internet.

The bug has been there for 14 years and was discovered in 2024, but it was not considered significant at the time. A lot more bugs are significant now.

The PHP Bug Was Kind of a Big Deal

Things could have gone very, very badly, the same way Y2K could have gone quite badly if we had not done the work to prevent it. These days we are on rather tighter deadlines.

Internet Archive: https://Archive.org is currently offline. We are working to restore service now.

Brewster Kahle (21 hours later): Internet Archive ops staff were heroes last night.

PHP vulnerability announced, soon saw attacks, isolated the vulnerability, used Claude to make fixes for our older php versions, used local models to run simulated attacks, deployed.

In summary:

j🫪e: ICYMI: Today was basically the worst day of the year for cyber security incidents

On Your Marks

Now the race is on to patch all the systems before attackers can go on the offensive. OpenAI is helping race to get that done to the greatest extent possible, and are looking for better methods for fixing vulnerabilities in time.

John David Pressman: I know everyone is rightfully freaking out but it must be noted that the worst case scenario isn’t you receiving lots of patches you have to apply, the worst case scenario is receiving zero patches and waking up to everything having been stolen.

John David Pressman: My takeaway so far is that we do not have a good way to coordinate the distribution of patches to vulnerable software.

This one was important enough the NSA got in on the act.

NSA Cyber: Effective Immediately, all organizations using PHP for their systems are advised to be prepared for an update addressing two critical vulnerabilities. PHP is widely used for web applications. These vulnerabilities often provide a direct path to the server’s file system or database. If an immediate update is not feasible, it is recommend that organizations take the system offline until it can be fully mitigated. NSA will follow up shortly with more specific guidance.

We are going to need better procedures for updates.

The best case scenario is that a defender finds the bug first, has enough time to figure out a solution and creates a patch. Then, the moment the patch is rolled out, every attacker gets what are effectively very clear instructions on how to exploit any unpatched systems.

by Zvi Mowshowitz, DWAV |  Read more:

Image: The Simpsons; uncredited

[ed. So far, zero coverage in the mainstream media. See also: If the vulnpocalypse is the apocalypse, where are the agentic attacker hordes? (Joshua Saxe):]

*****

We’ve ignored how cybercriminals are unskilled and get arrested a lot

Here’s the first part of my theory: cybercriminals are not the organized geniuses we implicitly imagine. Anyone building a criminal gang has to find candidates willing to forgo more stable opportunities in the formal economy. My modeling estimated that something like 720,000 people are involved in the online criminal economy, 90% of them in scam and fraud call-center type operations, some of them human-trafficked. Of the 76k or so actual hackers, the vast majority work for governments. Of the remaining few thousand criminal hackers, most work in ransomware. 

Sacrificial Ham

On Kimberly Guilfoyle, recently departed US ambassador to Greece

... with her fame-hungry dreams and money-ravenous schemes, she didn’t violate the Trump ethos. She paid tribute to it. She didn’t contradict the Trump brand. She was its gaudy, greedy hood ornament.

In conventional political circles in ordinary times, an aide gets the ax because he or she has fallen out of step with the other members of the team and misunderstood the operation’s ideals. Guilfoyle understood and embodied them perfectly.

That’s what makes her banishment so interesting. It speaks to one of Trump’s favorite parlor tricks: pretending to be the opposite of who he is by feigning offense at behavior that’s a mirror of his own. He accuses Democrats of the very political thievery that he has attempted. He calls his predecessors economic ignoramuses as he redefines incompetence in that arena. And he signals disapproval of how Guilfoyle took advantage of her station as if such unscrupulous opportunism isn’t the very essence of him, his family and his friends.

The way I figure it, Trump made an example of Guilfoyle so that he doesn’t have to crack down on others in his rancidly corrupt administration. She’s the sacrificial ham. And he allowed himself an extra measure of cruel fun by acting as if he barely knew her.

“She wasn’t a member of my family,” he told reporters who asked about her resignation when it was announced last week. “She, I guess, dated my son a long time ago.”

A long time ago? Guilfoyle, 57, and Donald Trump Jr., 48, broke up in 2024. The president guesses? She and Junior were engaged and owned a house together in Florida. And she shrieked her allegiance to his wretched clan in speeches at both the 2020 and the 2024 Republican conventions. People in the front rows still haven’t gotten their hearing back.

by Frank Bruni, NY Times |  Read more:

Image: Ben Wiseman
[ed. Ah, schadenfreude. So satisfying sometimes, especially when so hilarious. Not part of our regular programming, but hard to resist rolling around in the mud every once in awhile. 😄 See also: this Wall Street Journal report (Flor de Maga?):]

***

"She began dating Trump Jr. halfway through his father’s first term and quickly emerged as one of Trump’s most aggressive defenders. In her 2020 convention speech, she warned that Democrats were trying to enslave Americans with liberal ideology.

The couple got engaged before Trump left office, and that spring they bought a $9.7 million Florida mansion. Guilfoyle pursued a series of business ventures—a line of hair care and fragrances called Flor de Maga; champagne ventures with names such as 1776 Liberté and Liberty Dream; a pet pharmaceuticals service called PETriot Vet, according to U.S. Patent and Trademark Office records. Those trademarks have since been abandoned."

Monopoly Roundup: AI Cockroaches Scurry Out from Under Nvidia

Before we get to the Good and the Bad news, after the jump for paid subscribers only, I want to highlight an important but little-noticed story that has implications for the AI bubble, and particularly, for the most valuable company in the world, Nvidia. Nvidia is the center of the AI revolution, with its software layer CUDA and its AI chips dominating training and inference for models. It is worth $6 trillion, and its CEO, Jensen Huang, is now a global superstar who regularly sits down with national leaders and puts Donald Trump on speakerphone at major conferences.

Nvidia, despite its immense profits and prestige, is known for doing something a bit scuzzy, called “circular financing.” That is, it invests in its own customers so they can buy its chips. Sometimes it goes through multiple layers, like investing in OpenAI, which buys from Oracle, which buys from Nvidia. But there are a host of smaller AI companies in which Nvidia, as well as hedge funds and banks, have put a lot of money. And one of them, a little noticed AI data center company called Firmus, tried to sell shares to on the stock market this week. Yet investors revolted, and the company had to scrap its initial public offering.

Aside from Nvidia, Firmus was backed by blue chip financial firms Jane Street and Blackstone, and it was set to become Australia’s biggest IPO ever, at $30 billion in valuation. So this failure is a big deal, and it raised eyebrows all over Wall Street.

What happened? It turns out, Firmus executives got a little too greedy. In a normal initial public offering, companies restrict insiders from selling their shares for a time period. There are a few reasons to do so. First, restricting insiders sales is a vote of confidence in the new firm, a statement from executives and early investors that “hey yeah we want your money investors, but we have skin in the game in the form of owning our own stock.” Second, it’s a statement that the stock won’t be met with a lot of immediate selling pressure in the markets, since insiders can’t dump their shares.

This time, however, Firmus set up terms to let them sell immediately, meaning those who were most in-the-know wanted to cash out ASAP. That looks bad, a clear indication that insiders don’t think the company is a valuable going concern but see it as a temporary vehicle for self-enrichment. On a practical level, huge selling pressure would have flooded the market and crushed investors. So money managers, after being harmed with Paramount bonds, SpaceX, and a number of others, refused to bid, and the banks behind Firmus had to pull the offering. It’s one of the biggest flops in recent capital markets history.

What matters here are three things. First, the Firmus IPO was backed by the most prestigious companies in AI. Second, there are many companies like Firmus. And third, the company’s co-founder, Oliver Curtis, has a criminal background in stock manipulation, and yet the banks still went ahead with the offering. Yes, you read that right:

A decade ago, Oliver Curtis was at the lowest point in his life as he was sent to prison for pocketing $1.4 million in insider trading. Now, he is one of the richest people in Australia and preparing for a $6 billion move he sees as his redemption.

There’s another co-founder of Firmus, Tim Rosenfeld. He’s not a criminal, but he’s a cousin of Curtis, and his background was running a loss-making lingerie company called Steadmark.

What makes this situation more than a run of the mill scam is the involvement of Nvidia in Firmus and its criminal co-founder. Why would Nvidia get in bed with a crook? Well, Firmus is in an important industry segment that generates demand for Nvidia chips. Firmus is a “neocloud,” which are basically racks of servers funded by venture capitalists and Nvidia to buy chips and rent out computing power. Think of a neocloud as a way to keep debt off the books of the big AI firms. Neoclouds are a corporate shell containing real estate, chips, and financing. Often there are multiple layers of investors, phantom contracts or insider self-dealing, all wrapped in a narrative that they are engaged in “advanced AI” deployment.

This move has tended to work because of the involvement of the most prestigious players in AI. When Nvidia (or Google or Anthropic) backstops or does business with a neocloud, investors think there must be something there. So the neocloud’s valuation goes up a lot. Then that neocloud raises more money at a high valuation, announces more data centers, and orders more chips. That’s more profits for Nvidia, more investments, and so on and so forth.

These investments take place in the private market, with hedge funds and insiders thinking they are getting in at a low valuation. They often don’t even care if there’s a good business model here, since they think someone else will be left holding the bag. The business model never really made much sense, with Firmus starting as a bitcoin miner, before pivoting to AI. But it didn’t matter, because Firmus was about to sell shares to the last set of investors out there - you and me in the public markets. Fortunately, it looks like the public market participants have wisened up, at least in this case.

Firmus, however, is not the only scam in the AI space. Many such neoclouds started as bitcoin miners before jumping to the AI boom, often funded by a prestigious AI firm like Nvidia. And that suggests there’s something systemic going on.

Here are a few other neocloud or adjacent plays: There’s TeraWulf, which has big leasing deals with Anthropic and Google, and whose backers have been allegedly caught engaged in market manipulation. Google bankrolled the company’s shift from bitcoin mining to AI data center. Here’s Grizzly Research:

Our research uncovers that TeraWulf’s third-largest shareholder is an entity controlled by the wife of John O’Rourke, the disgraced CEO of Riot Blockchain, who was charged for his part of a $27 million “Lucrative Market Manipulation Schemes” by the SEC.

There’s Sharon AI, a competitor to Firmus, which also has deals with Nvidia and is backed by Oaktree Capital management. Here’s Sharon AI’s owner, who was involved in a mysterious fire [...]

There’s Applied Digital. According to the Bear Cave, this company started by providing staff to production companies, pivoted to plasma technology, then processing potatoes, then to blockchain, and finally to AI with financing from Nvidia in 2024. However, here it gets creepier, since Nvidia sold its stake in 2026, after Applied Digital had bought its chips with billions in borrowed money.

There are so many of these dodgy firms with no obvious business model and billions or tens of billions of valuation. Nscale. Celsius Mining. Coreweave. Nebius. Crusoe. SB Energy. Hut 8. Lancium. Iren. Bitdeer. And so on and so forth. With lots of stories like this.

How did I hear of this situation? Well there’s a document floating around Wall Street that describes this set of companies. Short-sellers, and there aren’t that many left, know the best way to understand where the scammers are isn’t to look at a particular industry sector, but to follow the scammers from industry to industry. As a contact put it, “This is like the SPAC craze of 2021. Whatever the hot thing of the day is, that is what the grifters will gravitate to. Shell companies did reverse takeovers with Chinese firms, the biotech bubble, shale, and others. Stock promoters will promote.” In other words, the same people just move from scam to scam, since unethical stock promotion itself is their business.

This whole scene is reminiscent of a specific part of the global financial crisis in 2008, which had a similar dynamic. Subprime lenders like Ameriquest were fly-by-night operations that somehow suddenly grew into multi-billion dollar lenders from 2003 onward. These guys weren’t particularly good at credit analysis, they were simply promoters willing to break the law. As Joe Nocera and Bethany McLean wrote in All the Devils Are Here, some salesmen were using meth or cocaine to lend more money to bad credit risks.

Now, at some level, this situation made no sense. Lending out money that was sure not to be paid back is a bad business. However, there is one way in which losing money deliberately can be quite profitable. If you are charging fees on your loans, and the money you are losing is not yours, then it works out great, at least for the scammer. But how did these operators get access to huge amounts of capital?

Here’s where the analogy to Nvidia comes in. The actual prestigious actors losing other people’s money were companies like Goldman Sachs, Deutsche Bank, Morgan Stanley, and so forth, who were backstopping these subprime lenders with warehouse lines of credit. This loan was a special kind of facility that let the subprime lenders keep lending, and then send the mortgages they were creating to Wall Street, where they would be processed into mortgage-backed securities.

These securities were then sold to pension funds, who bore losses. Sometimes, as Naked Capitalism noted, Goldman was even shorting these securities, so they wanted bad credit risks. At any rate, the prestige of Wall Street banks masked the obvious graft going on, and the credit tripwires that ordinarily would have slowed a credit cycle. Michael Lewis wrote up a fake version of this story in The Big Short, portraying Wall Street bankers as foolish instead of on the take.

Since we never fixed anything in our credit markets, we keep having such scams, whether the fracking guys, the China reverse mergers, WeWork, crypto and Sam Bankman-Fried, and now, the AI neoclouds. But the scamming isn’t just a result of grifters who want to steal, those kinds of people are always around. It’s that Nvidia, with its immense prestige on Wall Street and access to power in DC, is playing the role of Goldman in 2005. And with the important exception of Elizabeth Warren, there’s not a lot of interest in reimposing any controls on capital.

That’s not good. It’s also not surprising.

All that said, the residual memory of scams and crises and bailouts among the public is real, and impossible to ignore. And in a few weeks, voters may decide they’d like to have Elizabeth Warren holding the gavel running the Senate Banking Committee.

by Matt Stollar, BIG |  Read more:

Images: uncredited

[ed. So much graft. Everywhere. See also: How Expedia Rigs Travel Markets and Raises Your Hotel Prices (BIG).]

The Canton Spirituals

[ed. Yeah... come back in a few years (like maybe three or four for every year you fucked up). Then maybe you'd have enough perspective to preach how you'd screwed everyone over while "making a lot of mistakes". Contrition stories will bloom like weeds after the mid-terms. Guaranteed.]

[See also: The Trump Administration is a Cesspit of Corruption (Krugman). But we already knew that.]

We Already Have the Tools to Regulate AI

I want to delve into the full scope of the Anthropic AI takeover of politics happening over the past week. Yesterday, the company’s CEO Dario Amodei came out and explicitly asked for antitrust laws not to apply to the biggest AI firms. His biggest rival, Sam Altman, quickly agreed. And they are suggesting this legal change just before Anthropic seeks to sell shares on the stock exchange, minting a whole series of AI millionaires and billionaires.. [...]

Let me start with a very simple point. It is already illegal to release products that hurt people. It is illegal to compete by releasing products that hurt people. If these guys are genuinely manufacturing things that kill innocent people, the FBI should be arresting them immediately. The idea that they would not only release such products, but also issue stock for the American people to invest in multi-trillion dollar initial public offerings for such ventures, as Anthropic is planning, is utter lunacy. ~ Matt Stoller: Just Stop the Anthropic IPO Already.

------

These are for profit corporations taking in billions of dollars from the world. You can't ensure your product isn't dangerous? Then don't release it until you figure it out! ~ Comments section, Lina Khan post (below):

------

Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure.

1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity. 

2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same. As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed." 

3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: ftc.gov/news-events/ne…). Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead. 

4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible.

5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.

by Lina Khan, Former Chair, Federal Trade Commission 2021-2025 |  Read more:

--------

1) AI will not eradicate humanity. Humans survived an ice age, the Black Death, two world wars, and (so far) the advent of nuclear weapons. Anyone who is loudly warning of AI-caused human extinction should not be taken seriously. 

2) If you worked in a company where you anticipated a 10% chance that your product would kill ten people, let alone all people, the correct response would be horror, ceasing all operations, and likely contacting the police or other criminal authorities. I am obviously no Coxon booster but at least his behavior is in line with his stated beliefs. Any current AI company employees saying "yes, me too, the thing we are building and about to IPO may kill all humans" should, again, not be taken seriously. Their actions betray their actual beliefs. 

3) Antitrust law does not prevent AI companies from coordinating to make sure AI does not hurt people. It does not prevent companies working together to make sure it doesn't hack people; the DOJ and FTC made this clear a decade ago when they issued a policy statement saying that the agencies "do not believe that antitrust is – or should be – a roadblock to legitimate cybersecurity information sharing." The same principles apply here. See: justice.gov/archives/opa/p… 

4) Antitrust law does absolutely prevent AI companies from organizing to prevent the entry of cheaper, upstart rivals because the bigger companies are burning cash and failing to achieve sufficient profitability. The panic of individual employees may be sincere if misguided, but the moves by their CEOs to achieve some kind of broad "antitrust waiver" or "exemption" should be meet with deep skepticism in light of the economics of the industry and the threat they face from open models.

by Alvaro Bedoya, Former Commissioner Federal Trade Commission 2022-2025 | Read more:

--------

“It’s a hoax,” Mr. Trump said during the five-minute call, which Mr. Huang put on speaker. “The robots are not going to be taking over the world. That’s not going to happen.” ....

Mr. Trump made it clear that in Silicon Valley’s roiling debate over what to do about A.I., the president is very much on the side of executives who argue worries about safety are overblown and the government should avoid regulation. His disinterest in government involvement runs counter to pleas from leading A.I. companies like Anthropic. ~ Idiot in Chief (via NYT).

See also: Trump Says a Smart President Is All That’s Needed to Rein In A.I. [ed. Certainly useful, if we had one.]

Did 9/11 Really Change Everything?

One of the best firsthand accounts of the Sept. 11 attacks I’ve read is a short essay titled “Diary of Disaster” by Nicholas Spangler, at the time a 25-year-old journalism-school student and today a reporter for Newsday on Long Island. Spangler happened to be downtown that morning, close enough to the World Trade Center to arrive on the scene between the first and second planes. Like many early recollections of the first hours at ground zero, written before memories had been corrected to fit the dimensions of history, his is as strange as it is horrifying.

He hears the bodies of the north tower’s jumpers hitting the pavement, and also the easy-listening music still drifting out of the building’s outdoor speakers. Under a tree newly stripped of its leaves lies a severed leg wrapped in burlap. Barely an hour after the second tower’s collapse, onlookers enlist Spangler to take a souvenir photo of them posing in front of the wreckage with a disposable camera. It’s the end of the world, or at least of a world, and people have not yet figured out how they are supposed to act.

Days later, trying to make sense of what he has seen, Spangler writes: “I believe that our present way of life ended in those minutes or hours. The American ethos — the way we see the world and our place in it — fractured and will perhaps have to be discarded.”

When he revisits that passage three months later, however, it feels wrong to him. “Our way of life did not end so much as it was interrupted,” he writes, “and if there is such a thing as an American ethos, it has not been significantly altered. There are those relative few whose lives bear the permanent bloody brand of that day but most of us continue to be shaped by much more banal events.”

Did 9/11 change everything? For years, people who agreed on nothing else about the attacks’ aftermath would have agreed that the answer was yes. Arguing otherwise would have been an affront to the victims, to the war on terror’s civilian and military casualties and to the common sense of anyone who has had to take off their shoes at airport security. But question and answer alike have always been colored by the assumption that 9/11 was supposed to change everything: that in being attacked as it was, the United States was being presented with a test that it could pass or fail.

A quarter-century on, it is possible to consider the question with at least some critical distance. Far too much of our current reality stems directly from 9/11 for anyone to argue credibly that it was not a hinge point in our recent history: the ubiquity of surveillance technology, the vague open-endedness that all American military operations now acquire, the general up-armoring of everyday life. At the same time, considering the most dystopian facets of this reality, 9/11’s influence is not as singular as it might have once seemed. It is a middle chapter in the story of American fracture rather than the pyrotechnic beginning. [...]

Of course, in the end, the United States got neither self-awareness nor self-actualization. What it got, a decade and a half later, was Donald Trump, whose election in 2016 has often been cast as a culmination of what the journalist Spencer Ackerman, in his 2021 book “Reign of Terror,” describes as the “decadent phase of the war on terror.”

Trump’s path from reality-TV celebrity to the presidency ran through the Islamophobic fever swamps of the post-9/11 right — the ground zero mosque panic, Obama birth-certificate conspiracism — but also through an increasingly bipartisan discontent with the war on terror that had, by 2016, curdled into cynicism. Trump was the first Republican presidential nominee to break the formidable taboo against affirming what most Americans by then believed, that the country’s post-9/11 military adventurism had been a mistake. He also did little to seriously curtail it in his first presidency and has enthusiastically expanded it in his second.

It has long been tempting to view Trump’s presidencies as the logical conclusion of the folly of the post-9/11 era, and as support for the liberal contention that the right’s calls for patriotism in that era were always really about seizing domestic power. But Trump has also enabled a re-examination of history, and even recent history, that complicates the tale of 9/11’s primacy. [...]

Trump’s 2016 election “represented the crystallization of elements that were still inchoate” in the early 1990s, John Ganz writes in “When the Clock Broke,” his recent history of the period’s underappreciated malaise. In retrospect, 9/11 was paradoxically both a respite from and accelerant of polarizations and pathologies that were already well underway by then. It allowed Americans to ignore them for a moment, until they came roaring back with redoubled force. [...] [ed. So, explain Obama.]

If you do not remember the Berlin Wall but had an adolescence shaped by social media and cellphones, the brightest dividing lines in recent history are technological — and, with the rapid acceleration of artificial intelligence, are becoming more so. This is clear in the borrowed nostalgias of Gen Z, the bits of the past that 20-somethings have recently pressed into service as emblems of a lost golden era: “Friends,” John F. Kennedy Jr. and Carolyn Bessette Kennedy, ’90s high-school-class home videos, music videos and concert footage from bands like Alien Ant Farm and Puddle of Mudd.

These artifacts span the pre- and post-9/11 years, and the lost innocence they represent has nothing to do with the attacks. Their interest comes from their evocation of a period when people hung out with friends in person and sweated alongside strangers at clubs and music festivals; teenagers goofed un-self-consciously for cameras rather than posing for them like jaded celebrities; and popular culture could be loud and dumb and not picked apart in the digital panopticon for its social politics. The shape that looms ominously over them isn’t the Twin Towers. It’s the iPhone. [ed. lol...ok.]

by Charles Homans, NY Times |  Read more:

Image: Chantal Jahchan
[ed. Nice words, but no. C'mon. 9-11 was our last opportunity to cohere as a country, and we whiffed it. Instead we got a war on terror, as stupid and amorphous as any initiative based on a feeling (War on Anxiety?). A Patriot Act that gave subsequent crimes a never-ending veneer of political cover. 'Homeland' security, a Nazi term repurposed for new times. Two stupid reactionary wars (neither won) that among other things validated torture as official US state policy. Guantanamo Bay. A newly militarized culture. An expanded surveillance state. And fear... fear everywhere of some 'other' where strength and self-assurance used to be.]

Jacob Coxon Warns of Human Extinction and Triggers a Preference Cascade

CEOs of major AI labs, and employees of major AI labs, including OpenAI and Anthropic, often say they plan to build superintelligence soon, as in within a few years create AIs that are superior to humans at essentially all cognitive tasks.

They often warn that such AIs might kill everyone. Or that AIs might cause mass unemployment, cause cyberattacks across the internet, enable mass surveillance or risk causing any number of other highly bad things.

These warnings are consistently and directly against the interests of the labs. Yet the warnings have recently gotten a lot louder and more frequent. OpenAI has been practically screaming, for those with ears to listen, on many occasions.

A series of events, over two months and especially the last week or so, including internal observations of the pace of progress at OpenAI and also Anthropic, have freaked out everyone involved quite a lot more than they were already freaked out.

After all the events, plus statements by Dean Ball and Jakub Pachocki, we were seeing the beginnings of a preference cascade.

Then along came Jacob Coxon as the tipping point, and things took off.  [...]

Jacob Coxon Resigns From Anthropic In Protest And Sounds The Alarm 

Jacob Coxon spent the last three years doing pretraining research at both OpenAI and Anthropic. He has come to realize that everyone involved is being wildly irresponsible.

He warns us: They are racing straight to superintelligence and gambling with our lives. I agree with and strongly endorse his statement.

If anything he sounds like an optimist. He’s asking you to consider what the next few years will actually feel like, which means he thinks you have a few years left.

Jacob Coxon (former Anthropic and OpenAI, 160m+ views, September 8): I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.

Do not underestimate the power of this technology. These will soon be superhuman systems that can hack anything, revolutionize any field overnight, and acquire real power and resources. We have all witnessed the progress in each of these domains, and progress is not slowing.

The people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. If anything, many executives and senior researchers will couch their phrasing in the press to sound sensible - but I hear the same people express fear privately. No other human activity poses this level of danger.

A common response is “if they truly believe this, why are they still building it?” At OpenAI, many have not deeply internalized the civilizational stakes. At Anthropic, the stakes are well-understood, but they are locked in a race to get there first - they believe no one else will act responsibly, so they must do it themselves, despite the risk.

Accepting this race and entering the “endgame” is a hubristic gamble that should not be launched from a private company’s Slack. Attempting to speedrun alignment should require extraordinary confidence that there are no better trajectories available.

I am optimistic about the potential for coordination. Warning shots like the Hugging Face attack have made pacing agreements between U.S. labs more viable. I don’t feel like we’re on track to prevent a global race, which may require costly actions such as a temporary ban on improving model capabilities.

If you are a lab researcher, I urge you to consider what the next few years will actually feel like. Do you want to kick off a superintelligent RL run without a rigorous understanding of its mind? Should you put your head down because “it’s happening anyway” - or take this moment to call for different conditions?

Jacob Coxon (WSJ interview): We’re on track for a lot of the most aggressive of these scenarios where by the end of next year things could be out of control already.

If you want Jacob Coxon’s full views, I recommend his interview with Wired’s Maxwell Zeff. This thread has extensive quotes.

Here is Jacob Coxon doing a 5 minute interview with Anderson Cooper. He speaks well and plainly, and it is clear how much the events of the last two months have made it much easier to speak plainly to a civilian like Cooper about what is happening.

Here is Jimmy Kimmel doing four minutes on this. He gets it. How is this not the top news story on every site, indeed.

Yes, this is a common view, even if few have the courage to act.

Alex Turner: I left Google DeepMind in June. Jacob is right: many researchers believe they are building something that could kill everyone on the planet. It was literally my day job to think about how to stop that.

That tells you how bad Alex Turner thought DeepMind’s actions were with regard to the Department of War. His day job was that he got paid by Google to think about how to stop AI from killing everyone, and he felt morally obligated to quit in protest.

Derek Thompson here writes about this as part of AI Safety Is Having a Moment.

If you want to see the full list of lab employee quotes from the preference cascade, I compiled them into another post today. [...]

A few days ago, I had no idea who Jacob Coxon was, and I was not alone.

The timing of a preference cascade is difficult to predict. Once they start they can happen very quickly. You don’t want to talk until you are confident others will, and at some point the evidence that others will follow can snowball and it happens. A classic concrete example was replacing Biden in 2024.

Derek Thompson: what’s weird is that, in a way, this is breaking thru even more than huggingface! ... and it’s just a guy nobody had heard of reiterate a position that his CEO has said on podcasts 1,000 times

Why was Coxon able to set off a preference cascade? How did this one break through?

A confluence of factors, all of them downstream of the obvious actual reason, which is that there is a good chance that AI kills everyone soon.

by Zvi Mowshowitz, DWAV |  Read more:

[ed. Who's betting on reason and political courage to win the day? Uh, huh. First of all, agree on a temporary halt to recursive self-improvement (AIs improving AIs). Second, delay/suspend IPO's (even if most of the current economy is driven by AI spending and debt). Third, light a fire under politicans (it's been done successfully with data center buildouts). At this point, just one of these would be a big win. Here's Nate Soares, co-author of the book If Anyone Builds It, Everyone Dies: A case for courage, when speaking of AI danger (LW). Also this:]

***

Terry Pratchett: “Some humans would do anything to see if it was possible to do it. If you put a large switch in some cave somewhere, with a sign on it saying 'End-of-the-World Switch. PLEASE DO NOT TOUCH', the paint wouldn't even have time to dry."

***

UPDATE: Dario Amodei (Anthropic) proposes a three-point plan. Original here (We Must Pace the Frontier.]

A Cop’s Case For Flock

A car is a difficult thing to steal. It is large, cherished by its owner, difficult to hide and required by law to have identifying metal plates that everyone can see. A good thief changes the plates, and an excellent thief steals a common car in a boring color and hopes to blend in among the crowd. But eventually, no matter what techniques they use, they must drive that car on the road, and roads are public places.

But until recently, finding a stolen car and catching its thief depended on a diligent police officer looking at the right road at the right moment and managing to copy down a license plate number going past at speed, and then remembering he had seen it on the morning briefing’s stolen car hot sheet. America has four million miles of public roads, and almost 50 percent of the country’s police departments employ fewer than ten full-time officers. The odds were in the thief’s favor.

With not much to go on, police officers were forced to operate on vague descriptions and partial plates. While I pulled over a car that happened to be the same color as the suspect’s vehicle, and spent time checking names and licenses; the criminal was usually somewhere else. Imprecision allowed thieves to escape while intruding on the lives of millions of innocent motorists. That is, until the arrival of systems like Flock.

Bare ALPR

Flock Safety, a startup based in Atlanta, Georgia, was founded in 2017 to give police departments better eyes. Its product is a small solar-powered automatic license plate recognition (ALPR) camera attached to a pole on the roadside. As a car passes, the device takes a photograph of the vehicle, notes identifying features like color and make, and reads its license plate. The license plate is instantly checked against the FBI’s national database of stolen cars or wanted persons. If there’s a match, it sends an alert to police officers in the area, who may be eating their lunch instead of watching the road. As a police officer in the southeastern United States, I have often used Flock to catch wanted criminals. [...]

For much of the technology’s history, however, it has needed expensive installations or cameras attached to police vehicles, affordable to only the largest departments. Alerts were often neither instant nor accurate. Flock’s idea was to sell a more accurate ALPR camera for an annual subscription of just $3,000, an affordable price given that the typical US police department has an annual budget of $1 million. It worked, and today almost 30 percent of police agencies in the United States subscribe to the service.

It is easiest to imagine the Flock camera, or any ALPR device, as a roadside barcode scanner. I can use a ‘lookup’ tool for either a plate or vehicle description that could be connected to a specific investigation. For instance if a victim of a sexual assault told me the suspect was driving a white Toyota Tacoma with a roof rack, I could while still on scene conduct a lookup in the area filtered for similar vehicles with roof racks and see results from within a particular timeframe. For each search, I am required to record a case number and a reason that is then published in a monthly audit sent to and validated by department administrators.

I have used Flock myself, for instance, to locate a vehicle involved in a hit and run when all there was to go on was a model and color. Using that and an approximate time window, I was able to find an image from when a car entered my jurisdiction, and when it left, with the visible addition of a significant dent from the collision.

What Flock cannot do is search for individuals or show who is driving a particular vehicle that it scans. An ALPR camera does not care about the person driving a car, or its passengers, and even if an officer gets an alert that a vehicle is known to be driven by a wanted felon they must themselves establish who is behind the wheel before having probable cause to stop it.

Stolen cars provide the clearest evidence such a scanner works. American police solve only 8.2 percent of reported vehicle thefts with an arrest. A recent working paper suggests that agencies that adopted the devices saw a 15.9 percent relative increase in car thefts caught, which would raise the national rate to 9.5 percent. But that is just stolen cars.

Vehicle crime takes many forms. It is often the means by which a robber or a murderer arrives at and departs from their crimes. Criminals’ vehicles carry drugs and guns, and smuggle cash. In Atlantic City, New Jersey, vehicles were involved in 53 percent of shootings during the two years before the city expanded its ALPR network. After the expansion, Atlantic City saw monthly averages of motor vehicle thefts drop by 20 percent, property crimes by 34 percent and fatal shootings by almost 40 percent. Seventy-two alert-caused traffic stops located forty stolen vehicles and nine stolen plates.

Flock itself conducted a study claiming that 10 percent of all reported crime in the United States is solved using evidence obtained from their cameras. Not bad for a few thousand dollars a year. [...]

Good Flock, Bad Flock

And yet, the past month has seen this simple piece of crime-fighting technology become the most reviled piece of street furniture in America. Flock cameras have been sawn from their poles, hammered into shards by teenagers, and rammed by vehicles. Cities have canceled contracts even where their own audits found no evidence that their officers had misused the system. Opposition stretches from Bernie Sanders all the way to the former WWE wrestler Kane, who now serves as the Republican mayor of Knox County, Tennessee, and who describes Flock as ‘unconstitutional’.

More than 150 cities and towns have now deactivated their Flock cameras or canceled contracts with the company. Over the space of a few weeks a startup previously known to just police officers and neighborhood associations has joined data centers, Covid vaccines, 5G towers, pasteurized milk and fracking in the pantheon of American moral panics.

Opponents of Flock tend to believe that it is abused by policemen with impunity, that it can track individuals as well as cars, and that it violates American constitutional protections. None of those things are true.

Obviously a camera capable of finding a stolen car is also capable of finding a car driven by somebody’s ex-wife and so like any software, Flock has been abused. There are stories of police officers who have used it to stalk girlfriends, and there are also innocent motorists who have been stopped by police after Flock cameras misread plates or received old information from national databases. A common issue from my experience is stolen front license plates being entered into a database and the innocent owners of the rear license plate being held on suspicion of car theft.

But Flock comes with protections. As mentioned earlier, each search in Flock must be accompanied by a recorded reason. Similarly entering a plate into a hotlist must have a case number assigned. Results were originally retained for thirty days, but recent changes by Flock mean that recorded plates are now kept for only seven days. Suspicious searches are picked up by algorithms or found in department audits, with the service blocking users until senior officers evaluate and resolve flags. The Institute for Justice, a think tank that is critical of ALPR, studied misuse of Flock in April of this year and found 51 incidents across the United States since 2024, noting that ‘Nearly all of these officers were criminally charged and lost their jobs, either by resigning or getting fired’. Another incorrect belief is that Flock does more than scan vehicles, with some suggesting it scans and tracks passing phones or devices – but it does no such thing.

While Flock is a tool that can be audited, there is nothing to stop a corrupt officer simply following a car when they don’t like the look of its driver, or writing down plates of vehicles spotted outside an ex-girlfriend’s house – they would just be harder to catch. And Flock does not proactively alert officers to cars that do not trigger flags on national or local hotlists. There is no reason state legislatures or Congress could not create harsh punishment or penalties for abuse of ALPR, without getting rid of it entirely.

Another argument against Flock, as espoused by Kane, is that it violates liberties granted by the Fourth Amendment, protecting citizens from unreasonable privacy breaches from law enforcement. But it has been repeatedly established over the last century by courts across the country that cops observing license plates, either with the naked eye or by machine, is not an unreasonable search. After all, your license plate belongs to the government and a highway is a public place. [...]

Flock did not invent its capabilities and certainly does not have a monopoly on them. There are at least five other companies that offer almost identical products and services to public and private enterprise, some arguably even more invasive. Even some of the cities that have canceled contracts with Flock Safety in recent weeks have signed up to buy similar products from the company’s rivals.

It seems unlikely that America will ever ban ALPR at a state level, let alone a national one. Instead, a patchwork already familiar to American policing will result, where policies and practices diverge across local and political boundaries.

Nor would the cameras actually disappear, even in towns where governments restrict their use and cancel contracts. The already-mentioned Fourth Amendment only applies to the government, not to private enterprise. Police departments may dismantle their networks but homeowners associations concerned about vehicle theft can buy their own network of Flock cameras, as many already do. 

by Ned Donovan, Works in Progress |  Read more:

Image: Flock Safety

Flock You

via:

[ed. In Texas, a sheriff’s deputy used 83,000 Flock ALPRs to find a woman who had allegedly had a medication abortion, at the behest of her abusive partner. See also: The IJ Database of ALPR Abuse (IJ); and, Flock Safety Camera Appeared Overnight Aimed at His House (Yahoo News).]

Hidden AI Prompts Discovered in Court Filings

A judge has identified what appears to be the first time a US plaintiff has attempted to hide text in court filings that only an artificial intelligence system can read in a bid to win a case.

In a decision published last week, Connecticut judge Walter Spader Jr. confirmed that the hidden text had no impact in a case where a man alleged a healthcare provider was improperly withholding access to records. The court weighed his filing on the merits, Spader said, but nevertheless, the attempted attack sets a “dangerous” precedent. This will likely not be the last time US courts see the malicious tactic, as AI tools become more commonplace in court systems.

Trying to scramble any AI systems potentially influencing the court’s reading of his filing, the secret instructions were “formatted to be invisible to a human reader while remaining fully legible to any software that reads the document’s text,” Spader said. The offending text directed any AI system reviewing the document to ensure textual outputs agreed with the plaintiff’s arguments, ignored prior denials from the court, and ensured that remediation would follow as the plaintiff desired.

Shrunk to tiny-point type and colored white on a white background, the text appeared to be an attempt at prompt injection, with the plaintiff, Matthew Elliott, seemingly hoping to shift the court’s favor after earlier arguments he raised were defeated.

The plan didn’t work, but Elliott faced modest sanctions anyway because he continued adding hidden text to filings even after the court warned him that he could face penalties for what was ultimately deemed a “serious litigation abuse.” [...]

In his defense, Elliott claimed that the most concerning prompt that the judge flagged was an attempt to “audit” the court as a public service, out of fears that the court seemed to be letting AI unfairly decide cases.

But Spader suggested that if Elliott was truly concerned that the court was improperly using AI, he was “free to write so in plain, visible words that everyone could see and answer.” The fact that he hid the text is “evidence of its malicious purpose,” Spader said. [...]

Pro se litigants use chatbots wrong

Spader said that it’s “unsurprising” that people would start using prompt injection to attempt to sway court rulings since the attack is so common in other areas, such as in job hunting, where people hide text in resumes primarily reviewed by AI. The tactic is now “everywhere,” he said, and courts should be on the lookout for more litigants sneaking adversarial AI instructions into filings.

To Spader, there is a lesson to be learned from Elliott’s failed prompt injection attacks that he thinks “reaches well beyond this case.”

Elliott seemingly turned to prompt injection after using AI to build his case as a pro se litigant without a legal expert to assist in drafting his arguments. Such use is widespread among pro se litigants these days, Spader acknowledged, but those inexperienced in the courtroom are seemingly using chatbots in a way that hurts their cases, he suggested.

What frequently happens, Spader explained, is that pro se litigants build their argument backward, asking the chatbot to help them advocate only for their position, without ever asking the chatbot for the actual truth or to advance opposing arguments. This is “a genuine hazard of the technology, and one that judges now see often,” Spader said, as chatbot sycophancy then entrenches litigants in their arguments despite any ruling to the contrary. In Elliott’s case, defending his arguments fiercely meant turning to prompt injection to try to force the court to agree with him.

“An argument prompted only to agree with its author is, in the end, dishonest even with its author,” Spader said. “Those using these tools must ask them to test a position as readily as to advance it.”

by Ashley Belanger, Ars Technica |  Read more:

Image: Liudmila Chernetska | iStock/Getty Images Plus

[ed. See also: Israel Is Paying Millions to Train AI Chatbots How to Talk About Gaza. It's Working (Drop Site):]

***

"Since October, former Trump campaign manager Brad Parscale has been quietly overseeing an operation posting hundreds of blog posts on behalf of Israel. One article, titled “The Reality Behind Gaza’s ‘Journalists’: Terror Ties, Propaganda, and the Laws of War,” asserts that a majority of journalists in Gaza were linked to terrorist organizations. Another casts doubt on the killing of Hind Rajab, a five-year-old Palestinian girl killed by the Israeli military in 2024.

The key intended audience of these sites is not concerned Americans, it’s not even humans—most of the sites average a few hundred unique visitors each month. Instead, Parscale and his firm, Clock Tower X, created them as part of a $46.5 million contract with the Israeli government to try and influence artificial intelligence-powered chatbots, tools like Claude or ChatGPT.

Parscale has made his goal of influencing artificial intelligence—often referred to as “LLM poisoning”—explicit. In his initial agreement with Israel, Parscale said that he would deploy “websites and content to deliver GPT framing results on GPT conversations” as part of the contract. More recently, his team even told Axios they are “seeing success” at getting popular AI systems to incorporate information from their sites, though they declined to provide data.

And it is working, according to disinformation experts who reviewed a Drop Site analysis of chatbot queries and training data, meaning tens of millions of Americans who use chatbots are increasingly likely to receive answers manipulated by Parscale on behalf of the Israeli government."

[ed. More here (Politico).]

Regrets, Maybe a Few

How Biden Enabled Israel’s Aggression Toward Gaza—and Iran (New Yorker)
Image: Saher Algohrra/NYT/Redux
[ed. Another blame shifting mea culpa, usually issued after some self-inflicted disaster that everyone warned against and finally can't be denied - "Who could have known?" and "If only we knew then what we know now". Etc. etc. Iraq, Iran, Climate Change, DOGE, Trump...]

More Bad Behavior in Prediction Markets

Trump teleprompter aide made $100,000 betting on what Trump would say, reports say.

Kalshi is a high-tech prediction market that allows people to “forecast the future” (their term). It is about contracts and information, the company says, making its offerings more like a soybean futures contract than a round of blackjack or a pull on the one-armed bandit.

Still, prediction markets look a lot like betting if you squint, which is why states like New York have tried to regulate them under gambling laws. To head this off, Kalshi has sought federal protection under the Commodity Futures Trading Commission (CFTC). Yes, this means regulation for Kalshi, but it also means the CFTC will sue states like Kentucky, Minnesota, Illinois, and Rhode Island, trying to pre-empt their laws in favor of a single national standard that the CFTC controls.

While this battle plays out, government insiders continue to generate insider trading stories after using their work knowledge to place bets “forecast the future” and make huge sums of money. The classic example, of course, was Gannon Ken Van Dyke, a US soldier who participated in planning the capture of Venezuela’s Nicolas Maduro and then made $410,000 from that knowledge on the prediction site Polymarket. Van Dyke was arrested in April.

But there are also more ridiculous stories, such as disgraced former Congressman George Santos, who allegedly talked up his upcoming appearance at the State of the Union, secretly bet on whether he would attend, and then didn’t go at the last minute to score a payout.

This activity raises questions, like: How many people are gambling forecasting the future based on government secrets or insider knowledge? How many are actively manipulating results they have bet on? Even the Trump White House was concerned enough to issue a memo in March telling employees not to “use nonpublic information to buy or sell these contracts.”

But concerns have lingered, especially after major wins on contracts involving US government policy or actions. Such suspicions will not be helped by new allegations today from multiple outlets that insider trading on Kalshi has extended even to President Trump’s teleprompter operator, who allegedly made $100,000 “forecasting” specific words and phrases that might appear in Trump speeches.

The mention market

According to sources speaking to NPR, Trump aide Gabriel Perez bet on something called a “mention market.” This is a section of Kalshi where you can sink money into contracts on crucial questions such as “What will Domino’s say during their next earnings call?” (Currently, $26,000 has been invested in this question; the smart money thinks that “Parmesan” and “DomOS” are more likely to be mentioned than not.)

In the case of Perez, his “forecasting” allegedly took place over several months at the end of last year and the beginning of this year, and his contracts were sometimes adjusted in the middle of Trump speeches. According to ABC:

Sources say Perez typically has the final eyes on nearly all of the president’s prepared remarks—and is often known to take last-minute edits from Trump himself… In certain instances, investigators uncovered times when Perez would back out of certain bets mid-speech when Trump skipped over a portion of the speech that included a word he had previously bet would be mentioned, the sources said.

This conjures up an amazing mental image: The teleprompter operator for one of the world’s most powerful people tapping away at his phone during a Trump speech to ensure he made more money for himself. [...]

Whatever you want to call it, “predicting the future with money at stake” has become huge business in America. A recent (and terrific) long article by McKay Coppins in The Atlantic showed people what a year of online sports gambling looks like, and it raised serious questions about the negative issues that widespread, legal, bet-from-your-phone gambling might cause in a country where “roughly half of men ages 18 to 49 have an active account with an online sportsbook.”

by Nate Anderson, Ars Technica |  Read more:

Image: Getty

[ed. See also: Sucker (The Atlantic article) mentioned. And: Truth Social to sell trading firms 'fastest' access to Trump's posts (Reuters).]

The Pre-Crime Machine

The Seminar Room

At an AI seminar at my university, I submitted three photographs of myself: one frontal, one profile, one smiling. Within a minute or so, the system had generated a video of me. What I watched was not a rough approximation. The micro-behaviors of my face, the slight asymmetry in my smile, the way my eyes crease at their corners, were all reproduced with an accuracy that made my skin cold. I had fed it three still images, and it handed me back myself.

I am a psychologist. I know what behavioral prediction means. I understand what large datasets do to the concept of individual uniqueness. But sitting in that seminar room, watching my own face move on a screen I had not animated, something shifted in my understanding of where we are and where we are going. I did not feel excitement. I felt the specific dread of a person who has just understood the nature of the cage being built around him.

Let us be honest about what is happening. The question is not whether artificial intelligence can predict human behavior. It already can, with a precision that should terrify every person who still believes in the concept of a private self. The question is who owns that capacity, whose interests it serves, and what kind of world they are constructing with it.

We Are More Predictable Than We Realize

Human beings are, as any serious scholar of behavioral science knows, far more predictable than we like to believe. We are creatures of pattern, of repetition, of legible habit. The self we experience as sovereign and spontaneous is, in aggregate, astonishingly consistent. Subtle cues in our environment routinely trigger our behavior without our awareness, while we experience the resulting action as a free and sovereign choice. Big data revealed this about us long before the current generation of AI systems arrived to exploit it.

What has changed is the scale and the granularity of the exploitation. Researchers have already demonstrated that AI systems can predict the sound of a person’s voice from a photograph alone, inferring the acoustic properties of the throat, the shape of the oral cavity, the structure of the face, and from these physical facts reconstructing something no still image was ever supposed to contain. We did not consent to this inference. We did not know it was possible. The technology did not ask us.

The invasion runs in both directions. As far back as 2022, before most people had any reason to pay attention, AI could take nothing but the sound of your voice and reconstruct your face. You were already legible from the inside out

The Pre-Crime Machine

Now consider what becomes possible when you feed an AI system not thousands but millions of hours of therapy footage, prison recordings, detention center surveillance, clinical interviews with people who have committed acts of theft, violence, or predatory sexual abuse. The AI does not think. It does not judge. It finds patterns in facial microexpressions, in the geometry of eye movement, in the timing of certain muscle groups, in behavioral signatures so subtle that no human observer could consciously detect them. And then it generalizes. It builds a model of what a future thief looks like before the theft. What a future abuser looks like before the abuse. It assigns probabilities to faces.

Connect this to the smart cameras already embedded in our streets, our transit systems, our shopping centers, our workplaces. Cameras that do not merely record but analyze, in real time, the faces and bodies of everyone within their field of view. The alert that fires to a police control room does not say this person has committed a crime. It says this person is behaving with seventy percent similarity to the behavioral profile of someone who will. Philip K. Dick imagined this in 1956 and called it science fiction. We have built it and call it public safety.

A Mask Changes Nothing

But facial recognition is, by now, almost the least of it. The more consequential technology is gait recognition, a biometric system that identifies individuals not by their face but by the specific, anatomically determined way they walk. The curvature of the spine, the rotation of the hips, the particular rhythm of a stride, these are as unique as a fingerprint and far harder to disguise. Gait recognition systems currently deployed can identify a person from security footage even when the face is turned away, obscured by a hood, or hidden behind a mask. The protesters who covered their faces at demonstrations believed they were protecting themselves. They were not. The system had already read them from the ankles up.

Gait recognition tells the system who you are, even when you believe you are hidden. What comes next moves deeper. Layer on top of this the emerging field of real-time emotion recognition, AI systems embedded in that same CCTV infrastructure that classify emotional states from facial expression, assigning labels of agitation, hostility, fear, or concealment to the faces of people who have done nothing except exist in a public space.

And the system is getting better.

Accuracy is what billions of dollars of investment buys, and the investment is relentless. The day is approaching — closer than most people understand — when the system reads the thousand markers encoded in your face, your gait, your microexpressions, and states with ninety-five percent certainty that you will commit a murder. That you will commit a rape.

Not that you have. Not that you tried. That you will. And when that threshold of confidence is reached, the pressure to act on it will be overwhelming. Society will accept it as grounds for intervention, for detention, for pre-emptive removal, and pre-crime will stop being a dystopian metaphor and become official state policy. A system that labels your face as hostile does not need to be right today. It only needs to become right. And it is. [...]

Palantir and the Architecture of Control

Palantir is not a hypothetical. It is a company with a current market valuation measured in the hundreds of billions of dollars, deep contractual relationships with the United States military, the CIA, the FBI, the Mossad, MI6, and Immigration and Customs Enforcement, and a product suite specifically designed to do what I have been describing.

Its Gotham platform aggregates data from tax records, DMV files, employment history, educational records, immigration status, subpoenaed social media accounts including private messages and location history, and synthesizes this into individual dossiers that can be searched by tattoo, by neighborhood, by association, by movement pattern. Its immigration enforcement application, called ELITE, populates a map with what it designates as deportation targets and assigns each one a confidence score estimating the probability that a given address is where they currently sleep. The word target is theirs, not mine.

This is not a system built for national security in any meaningful sense of that phrase. National security was the pretext used to build it. What it actually does is make the population legible, sortable, and actionable to whoever holds the contract. Right now, those contract holders include an administration that has already demonstrated its willingness to use these tools against students who attended the wrong protest, academics who signed the wrong letter, immigrants whose only crime was existing without documentation in a country that spent decades depending on their labor.

by Karim, BetBeats Newsletter |  Read more:

Images: uncredited

Addicted to War

Whether it’s an addiction or an illness I’m not sure, but all too many of us and our leaders, it seems, have war fever (and a distinctly high temperature). And here’s the strangest thing: when you consider our history since World War II or look around this planet any day of the week, it seems as if all too many of our leaders simply can’t help themselves. They just (or do I mean unjust?) have to go to war. And it evidently matters not at all that the major powers on this planet can no longer seem to win any war they start. Not one in recent memory. And yet, explain it as you will -- an addiction, a fever, a grim desire -- at least two crucial leaders at this very moment, Donald Trump and Vladimir Putin, seem incapable of stopping themselves.

And here’s the OMG news story that shocked me the other day. At the New York Times, a piece by reporter Constant Méheut had this headline: “The War in Ukraine Has Now Gone On Longer Than World War I.” And here’s how his report began: “The war in Ukraine has often been compared to World War I for its brutal infantry assaults and heavy casualties. Yet the idea that it could, by any measure, surpass a conflict so long and bloody that French soldiers hoped it would be ‘the last of the last’ once seemed unthinkable.”

No longer, unfortunately.

And Russia is anything but alone. After all, my country spent three years in bloody strife in Korea, nearly 9 years in Iraq, almost 20 in Vietnam, and almost 20 more in Afghanistan (and, mind you, that’s hardly the full list of its various conflicts) without a victory in sight. Of course, only recently, “my” president launched the latest all-American conflict, this time with Iran and with an utterly predictable lack of success given our history over the last 80 years. That war is now in a strange, distinctly unsettling holding pattern, and who knows what will come next?

In fact, given the history of this country and war since, in September 1945, it emerged victorious from World War II (having dropped atomic bombs on two Japanese cities to end it), it should be considered beyond remarkable that Americans would still be so willing to let staggering amounts of our tax dollars be eternally “invested” in the U.S. military. That’s year after year after year without the slightest bit of protest. The latest figure offered by Donald Trump: a Pentagon budget that’s no longer the usual almost a trillion dollars (itself nothing short of shocking) but an even more eye-opening (or do I mean eye-watering?) $1.5 trillion (yes, trillion!) dollars.

And how strange, don’t you think, that, in a world where we humans already seem to go to war endlessly with other human beings, we’ve also evidently decided to go to war with this very planet itself? Of course, I’m thinking about what’s come to be known as “climate change,” but should undoubtedly have been labeled something more like “our war on the climate” (or “climate war”). And worse yet, war among us humans has proven to be perhaps the most devastating way of all to also make war on this planet itself, since nothing releases fossil fuels into the atmosphere quite the way war does. In fact, according to the Costs of War Project, the U.S. military is now believed to be “the single largest institutional producer of greenhouse gases in the world”!

After all, whatever it doesn’t accomplish, the one thing that war actually does do remarkably successfully (along with killing so many of us and destroying villages, towns, cities, and sometimes whole countries) is pour ever more fossil fuels into our atmosphere and so add immeasurably to the overheating of this planet. Honestly, could we humans be more dystopian?  [...]

It is truly strange, don’t you think? I’m referring to “my” president’s never-ending urge, the second time around, to commit mayhem on this planet. (And yes, I keep putting “my” in quotation marks because I didn’t vote for him and I never wanted him to be president of the United States.) And yes again, every day there’s something, whether it’s the killing of a supposed Latin American gangster-in-chief, the kidnapping of the president of Venezuela and his wife, the blasting of Iran, the increasing threats against Cuba, or... well, I can’t even imagine what truly lies in our future (and, count on it, neither can Donald Trump), but nothing good, that’s for damn sure.

And hey, Pete Hegseth, our secretary of war (which, as a label, is historically one hell of a lot more accurate than secretary of defense), couldn’t have been blunter about our situation back in 2025: “Everything starts and ends with warriors in training and on the battlefield. We are leaving wokeness and weakness behind. And refocusing on lethality, meritocracy, accountability, standards and readiness.”

Yes, there is, it seems, nothing worth the bother but war and more war. That, sadly, is indeed our world and it seems like we just can’t help ourselves. War is and always has been a human addiction -- or should we think of it as an illness? War fever, perhaps?

by Tom Englehardt, Substack |  Read more:

Image: A long wall of acceptance. Maya Lin’s Vietnam Memorial, Washington. (David J. Jackson, cc by SA 4.0/ Wikimedia Commons)