University of Michigan spinout Laplace Intelligence uses AI agents and interactive simulation to stress-test robots and self-driving vehicles before deployment. The profitable startup is competing in Startup Battlefield at TechCrunch Disrupt, October 13-15 in San Francisco.

If you've been engaging with the American job market lately, first of all, I'm so sorry. Second of all, you've probably run into an AI-powered "automated recruitment agent": in other words, an AI bot that the company makes you do a one-sided interview with as part of the extended humiliation ritual that is landing a job. — Read the rest

The post Messing with AI interviewers is cathartic appeared first on Boing Boing.

Last week, a clone of Adobe's Creative Suite appeared, said to be reverse-engineered and recreated using AI. Adobe's bad reputation made it easy for the internet to take perverse joy in its misfortune. Out with Adobe's surveillance technology, in with a fast and efficient replacement! — Read the rest

The post "Terrible games" made with AI appeared first on Boing Boing.

Anthropic updated its usage policy to protect Claude from bullies. Along with clarifications on child sexual abuse material and weapons development, the 2026 Usage Policy update prohibits users from "Engag[ing] in sustained and needless abusive or cruel behavior toward our models"

The update published yesterday, and effective in November, along with sections titled "Do Not Undermine Democratic Processes" and "Do Not Generate Sexually Explicit Content" is a section called "Do Not Engage in Cruel, Abusive, or Psychologically Harmful Conduct." — Read the rest

The post Anthropic wants people to stop being mean to Claude appeared first on Boing Boing.

In the 1987 Nintendo game “Zelda II: The Adventure of Link,” there is a village you can visit and a home you can enter and a man in a purple shirt you can speak with. But the only thing he says is “I am Error.” I was unexpectedly delighted by this dialogue when I first encountered it on a Gamecube emulator in 2009 (I’m not that old). It felt both meta and existential, or just an amusing bug. It turned out that Error was actually the character’s name, a sort of in-joke slash translation mistake that has since become a meme akin to “Your princess is in another castle” or “It’s dangerous to go alone! Take this” from the original “Legend of Zelda.”

Error is a non-player character (NPC), meaning one that the player can’t control but is usually more than just video game wallpaper. Nearly 40 years later, NPCs have come a long way, with increasingly complex behaviors and conversational dialogue that span far more than just three words. The upcoming game “Grand Theft Auto VI” is rumored to feature unprecedented complex NPCs with rich, fleshed-out personalities and backstories, while video game companies explore using artificial intelligence to let players train NPCs as they interact.

In many ways, NPCs are how many people were first introduced to AI, although in a relatively simplistic form compared to the chatbots and massive data center hogs that we have come to either love or loathe, with little room in between. Years ago, NPCs became an insult spun out of 4Chan, the anonymous online forum, to describe real people who don’t think for themselves and follow a set of cultural programming, usually illustrated by an expressionless gray cartoon avatar. The meme became popularized by chronically online cohorts of Donald Trump supporters during his first presidential term, adjacent to the idea of “Trump derangement syndrome,” both implying that people oppose the MAGA movement out of reflexive mindlessness and not, you know, because they’d looked under the hood and seen it for what it is.

It might just sound like a new way to call someone an idiot, but the NPC label has much deeper, scarier implications. On the surface, it seems like harmless video game humor, and I’m sure we’ve all had encounters with actual humans that resembled interacting with tautological machines programmed with limited responses. “There is weather today. Did you hear about celebrity? Sports.” And certainly social media, now overrun by bots, increasingly feels as if every conversation is between different viruses. These realities don’t map to every experience yet following the NPC slander to its logical conclusion can be dangerous: declaring that a person’s alleged lack of inner thinking is justification for dismissing their humanity. After all, they’re just mindless characters in a video game (and maybe reality is just The Matrix, so whatever), so it’s fine to ignore them, disenfranchise them or abandon them to a grim fate.

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Solipsism, the philosophical position that you can only experience your own consciousness, and therefore other people might not exist or have souls, is not a new idea. René Descartes believed animals were soulless, unthinking automatons, though modern neuroscience has repeatedly disproven that one. (On some level, “I am Error” echoes Descartes’ famous quip about thinking and therefore am-ing.) But now that complex AI has spilled from video games into the mainstream, it’s especially dangerous to see the NPC label has become embedded in mainstream politics, whether explicitly or not.

All this is rooted in Donald Trump’s recent campaign to rebrand artificial intelligence as “super intelligence” via executive order, posting on social media Thursday that “The White House considers anyone that uses the term, ‘Artificial Intelligence,’ as opposed to the highly accepted new and more accurate term, ‘Super Intelligence,’ THE ENEMY!” The idea has quickly been embraced by tech leaders, with SpaceX CEO Elon Musk saying this week that AI is “no more” and promising to change the name of his AI company, SpaceXAI, a subsidiary of SpaceX, to SpaceXSI. More recently, Amazon founder Jeff Bezos shared his approval in a Wednesday interview with Fox News. “I do like SI, because ‘artificial’ is not a very flattering thing. Like, nobody wants an artificial sweetener, artificial flavoring,” Bezos said. “Artificial sort of means fake.”

Yeah, most of us are going to roll our eyes hard at AI being “super,” but if these attempts at normalization gain ground and get pushed to their absurd conclusion, it might end in providing AI more rights than humans. (It’s worth noting Musk invokes the NPC meme often.) It’s right there in the name: “Super intelligence” is better than the old, human kind, so why shouldn’t we give these computer programs rights and defend them from regulation? That’s why stories about AI bots being put into virtual torture chambers aren’t just silly, but foregrounds the false notion that AI is capable of suffering. (Maybe don’t put bots in rooms like that anyway — at the very least, it’s a waste of energy.)

After all, AI will either become the savior of humanity or make humans obsolete, depending on what day of the week it is. Sure, this technology is nifty, even as it comes with an enormous environmental destruction. But we are still a long way from elevating the technology above regular human intelligence. But as in a two-for-one, if you can be sold on the myth that AI is superhuman, it travels along with the idea that regular humans are disposable. In other words, the tech bros are trying to turn us all into NPCs, into Errors, not least through the mass surveillance programs being used to hunt migrants and spy on protesters.

Yes, thankfully, granting above-human rights to supposedly sentient AI sentience is still a fringe idea, but we can see that changing before our eyes, not to mention we already kind of did that with corporations. Recently, OpenAI CEO Sam Altman told POLITICO that the “world should accept some bad things happening for the benefits of this technology and people having the agency.” To further consolidate its power — or at least keep the economy from crashing — Silicon Valley wants us to believe their latest technological invention can think, reason and moralize. It’s no surprise that tech bros were recently exposed trying to convince none other than the pope that AI is conscious, but to his credit, Leo XIV has rejected this idea, saying “Algorithms lack the spark of humanity” and elsewhere warning against “losing our humanity amid a ‘paradise of machines.’”

Spending time with large language models like ChatGPT and knowing a little about how they work, it becomes clear that it’s just a really good computer program that can mirror human expression, sometimes terribly and sometimes surprisingly well. There remains zero hard evidence that AI algorithms are sentient.

Yet an increasing number of people are convinced otherwise, as seen in the controversial AI psychosis phenomenon, which makes me wonder how so many people have persuaded themselves a souped-up version of “I am Error” is a conscious being. It can feel like human interaction typing back and forth with these things, but there are always gaps where you can sense the uncanny valley, where you know it’s just a lot of math and nothing more. Perhaps, if you want to be really cynical about it, you could boil down all of human nature and biology and the emergence of consciousness into “a lot of math” as well. But our brains aren’t computers and physics has yet to fully explain consciousness — that’s why they call it a hard problem. Instead of stewing in this mystery, tech bros have gotten the metaphor backward, assigning personhood to bots while denying it to living humans. Talk about soulless.

The post Billionaires love Trump’s AI rebrand appeared first on Salon.com.

A few years ago, an experimental McDonald’s drive-thru system became convinced that two customers needed an almost ceremonial quantity of chicken McNuggets. As a video of the exchange showed, the number kept climbing: 240, 250, 260. The customers shouted for it to stop. The machine, unmoved, continued adding nuggets.

The clip went viral, in part because the mistake was so specifically inhuman. Someone wearing a headset might mishear an order for 26 nuggets. But one imagines that, somewhere between the second and third hundred, a person would pause to ask, “You sure you want 260 nuggets, hon?” The machine had no such reservations.

McDonald’s eventually ended that IBM pilot in 2024, after testing automated order-taking at more than 100 restaurants. Now, it’s trying again.

The company’s new voice assistant, Archy, is part of its Google-powered ArchIQ system and can take drive-thru orders in English and Spanish. McDonald’s says its early tests have topped 90% accuracy, with plans to expand the technology as part of a sweeping modernization initiative. The pitch is familiar: Faster service, fewer mistakes and less repetitive work for employees, who will theoretically be freed to concentrate on something more important.

Hospitality.

But another chicken chain is drawing a line. Chick-fil-A CEO Andrew Cathy recently told CNBC that his company has no plans to replace drive-thru order takers with AI, even as it explores ways to use the technology elsewhere. The reason, he explained, is that the chain wants its hospitality to remain “human to human.”

At first glance, this sounds like a disagreement over whether a computer can be trusted to hear “no onions” rather than “more onions.” But underneath that technical question is a more consequential one: Which parts of hospitality do restaurants think are automatable — and which are worth keeping human?

There is, of course, a genuine appeal to frictionlessness.

Sometimes you’re tired, antisocial or running spectacularly late. Sometimes you want to make a substitution to an order without worrying whether it will get lost between the person wearing the headset and the person assembling your food. Sometimes you just want to tell a box that you need fries and trust that fries will appear.

I understand this instinct completely. I’ve walked into plenty of busy restaurants where the prevailing atmosphere suggested human error was the expectation rather than the exception, and a kiosk felt like a little gift.

Nor is there anything inherently noble about making employees spend eight hours deciphering orders shouted through crackling speakers while the ice-cream machine is down and a small diplomatic crisis is unfolding in the PlayPlace. Taking orders is part of the job, certainly; trying to do it while the rest of the restaurant threatens to unravel is another matter.

The optimistic version of AI-assisted service makes some sense: Let the machine handle routine tasks. Give employees more time to solve problems, help customers and perhaps make their shifts a little less frantic.

The less optimistic version is that companies will realize they can run the same restaurant with fewer people.

McDonald’s own financial projections offer some reason to examine that distinction carefully. In its September presentation of the company’s broader “> NEXT” strategy, the chain said Archy could free at least 50 labor hours per week as the technology scales. It also projected that its larger package of restaurant improvements could generate approximately $100,000 in annual gross cash-flow benefits for an average U.S. restaurant, with most of those gains eventually benefiting the bottom line.

Neither figure tells us precisely what happens to the employees who would otherwise be working those hours. But it does reveal how closely the language of hospitality is intertwined with the language of efficiency.

And McDonald’s has experimented with this vision before. In late 2022, the company unveiled a smaller-format restaurant outside Fort Worth, Texas, designed around customers ordering ahead through an app and collecting their food from a conveyor system. Employees still prepared the meals, but the design dramatically reduced the need for face-to-face interaction.

The concept was presented as a more convenient way to get food into customers’ hands. Fair enough. But if the great promise of automation is that it gives employees more opportunities to practice hospitality, it’s worth asking what that hospitality looks like when customers scarcely encounter those employees in the first place.

Chick-fil-A, meanwhile, has made a rather different calculation.

The company has always been unusually explicit about its values, which are rooted in the religious principles of founder S. Truett Cathy. Its restaurants remain closed on Sundays, including locations where that choice may seem commercially inconvenient like airports and college campuses. Its employees are famous for responding to customers with the relentlessly chipper “My pleasure!” The brand talks about service not merely as a function of getting food to customers, but as an expression of care.

That self-image is not without complications. Chick-fil-A has faced years of criticism over its charitable foundation’s past donations to organizations with anti-LGBTQ positions, which it said it would stop funding in 2019. Its public vision of care has not always been received as universally inclusive.

Still, the consistency with which the chain has made personal hospitality part of its identity is instructive.

And it’s not as though Chick-fil-A is technologically timid. At a Georgia location opened in 2024, food travels from an elevated kitchen to employees below on a conveyor system designed to deliver a meal every six seconds. Customers can order ahead digitally or place orders with workers in the drive-thru. The technology is decidedly futuristic, but the company has deliberately preserved a person at the point of service.

That distinction strikes me as meaningful.

Technology can expedite a restaurant’s work without necessarily becoming the face — or voice — of the restaurant itself.

Of course, a scripted “My pleasure!” isn’t necessarily more authentic than a cheerful voice generated by a computer. And anybody who has ever worked in a customer-facing job knows that hospitality, particularly of the relentlessly sunny variety, can involve a tremendous amount of emotional labor.

Employees shouldn’t have to manufacture delight on demand while working short-staffed shifts for inadequate pay, fielding customer complaints about things outside their control. A good restaurant culture takes more than telling workers to smile. It requires adequate staffing, good managers, training, compensation and enough breathing room for employees to exercise judgment.

But I think there’s a difference between demanding that employees perform warmth and creating an environment where warmth has room to develop.

Disney World, for example, has practically made an industry out of carefully cultivated hospitality. The entire experience is choreographed, from the language employees use to the way they interact with guests. Yet some of the most memorable moments happen when an employee notices something unexpected and responds in kind: A bus driver making a tired child laugh, or a character performer taking an extra moment with someone who’s been waiting all morning.

The environment is engineered. The little spark between two people isn’t.

And that’s what makes this debate about AI ordering feel more consequential than the technology itself might initially suggest.

Because hospitality isn’t entirely something a restaurant provides. It’s also something customers participate in.

Recently, I was ordering coffee at a neighborhood café, one location of a regional chain. A woman ahead of me, well-dressed and perhaps in her early 30s, was asked by the barista what she’d like. Instead of answering, she wordlessly handed over her phone. The barista looked confused. The woman sighed, tapped her screen with a fingernail and said, “It’s right there.”

It was a small moment, over almost as soon as it began. Nobody yelled. Nobody demanded a manager. But something about the exchange bothered me. The barista had asked a perfectly ordinary question. The customer seemed irritated that the answer required any effort on her part. The information existed on a screen. Why should she have to communicate it?

We’ve spent years teaching machines to understand human behavior. I wonder whether we’ve also begun expecting humans to behave more like machines.

It’s difficult to shake the feeling that something has frayed in our public interactions since the pandemic. We got used to contactless delivery, app-based ordering, packages appearing at our doors and transactions completed without speaking to anyone. Those conveniences were useful, sometimes essential. Many remain genuinely wonderful.

But I’ve also noticed more impatience. Less eye contact. An increasingly common expectation that the person behind the counter should function as an extension of whatever digital system we’ve already been using.

And perhaps there’s an uncomfortable lesson here for customers, too. We demand personalized service, but don’t always seem particularly interested in the people providing it. We want our preferences remembered, our mistakes corrected and our food ready precisely when promised. We don’t necessarily want to offer much patience, curiosity or goodwill in return.

Service workers have always dealt with difficult customers, of course. There’s no reason to romanticize some vanished golden age of American politeness. But the incremental disappearance of ordinary interactions raises a question worth considering: What happens when convenience becomes the organizing principle of our public lives?

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I keep thinking about the spaceship in Pixar’s “WALL-E,” the Axiom, where every human need has been anticipated and met. Passengers float around in automated chairs, surrounded by screens, food and entertainment. They are comfortable, in the technical sense. They are also profoundly disconnected from one another and from the world around them.

The unsettling thing about the Axiom isn’t that its passengers are miserable. It’s that they don’t seem to notice everything they’re missing.

No one individual convenience creates that kind of world. But taken together, thousands of decisions to eliminate small inconveniences can also eliminate opportunities for connection. And those encounters, however insignificant they seem, are part of how we learn to share space with other people.

A few months ago, I was shopping at Trader Joe’s when I noticed the cashier’s earrings. They looked like tiny illustrations of fish pulled from the label of a particularly fancy tin of sardines, with hooks attached. I told her I loved them. “Shrinky Dinks!” she replied.

It turned out she was a crafter. She pulled out her phone to show me some of her work, which included garments she’d fashioned out of Trader Joe’s tote bags. There were pants. Actual pants, made from the grocery store’s reusable bags.

I was delighted. Here was this woman who liked her job, or at least the store where she worked, and liked making things, and had found a wonderfully weird way to combine those interests. For a minute or two, the checkout lane became something other than a place where groceries changed hands.

It wasn’t a life-changing encounter. I don’t know the woman’s full name; her name tag simply said MB. I couldn’t tell you what I bought that day. But I remember her earrings, and the pants, and how much fun it was to meet someone who was so enthusiastic about something so delightfully specific. I wouldn’t have had that interaction if I’d been scanning my own groceries. And, importantly, I wouldn’t have had it if I hadn’t noticed the earrings and said something.

Neither of us was obligated to participate. That’s part of what made it lovely.

This is the problem with imagining hospitality as another task that can be optimized. The value of an interaction isn’t always apparent in advance, and the most meaningful parts of it often have little to do with completing the transaction.

A machine might eventually take my order perfectly. It might remember my favorite coffee, anticipate the substitution I’m about to request and move me through the line several seconds faster. On certain mornings, I’d welcome every bit of that.

But it cannot offer the particular surprise of encountering another person who has decided, for no reason other than the pleasure of it, to show me something strange and wonderful.

The real danger of automating our ordinary encounters isn’t that we’ll suddenly forget what human connection feels like. It’s that we’ll gradually make fewer opportunities for it, until its absence begins to feel normal.

Communities are shaped by the ways we participate in them. Even at a coffee counter. Even through a drive-thru window.

Sometimes that participation amounts to nothing more than a little patience, an unexpected compliment or somebody asking, Wait, is that really what you meant?

And sometimes that’s where the magic happens.

The post The AI drive-thru wars aren’t really about your order appeared first on Salon.com.

Audiophiles following the news cycle know by now that after seven years, AudioQuest has released a new DragonFly USB DAC. The DragonFly Copper (US$250, CAD$345) was spoken of at High End Vienna 2026 and started shipping in September, replacing the Cobalt at the flagship. As usual with a new Dragonfly, the forums and review sites lit up within days of the announcement (see sites like this, or this

If people don’t widely embrace artificial intelligence out of fear or a godlike savior complex, AI’s biggest champions will try something else: labeling critics “the enemy.” That’s precisely how President Donald Trump described people who don’t like his rebrand via executive order of AI to “super intelligence,” posting on social media Thursday that “The White House considers anyone that uses the term, ‘Artificial Intelligence,’ as opposed to the highly accepted new and more accurate term, ‘Super Intelligence,’ THE ENEMY!” 

As noted by Axios, the White House still uses the term “AI” including on websites like ai.gov, though that website was updated Thursday with “SI.gov” in massive text. “The URL is still ‘AI.gov,’ though, with ‘SI.gov’ leading to an error page,” Axios reported, which Salon confirmed.

Tech billionaires are already embracing the term super intelligence. This week, SpaceX CEO Elon Musk said AI is “no more” and promised to change the name of his AI company, SpaceXAI, a subsidiary of SpaceX, to SpaceXSI. More recently, Amazon founder Jeff Bezos shared his approval in a Wednesday interview with Fox News. “I do like SI, because ‘artificial’ is not a very flattering thing. Like, nobody wants an artificial sweetener, artificial flavoring,” Bezos said. “Artificial sort of means fake.”

Peter Thiel, founder of the tech company Palantir that aggregates data used in federal mass surveillance and deportation programs, has gone as far to describe AI’s critics as “the Antichrist.” Apocalyptic eschatology has long been an interest of Thiel’s, who has made the Antichrist a central topic of secretive lectures he’s given behind closed doors. Thiel doesn’t seem to believe in an Antichrist like in the “Book of Revelation,” but rather as a force that imposes a one-world government and stifles technological development.

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In leaked recordings obtained by Politico’s Decoded of Thiel’s speeches in Nashville in late September and published Thursday, the tech mogul claimed former President Barack Obama and Pope Leo XIV only oppose AI to boost their popularity, which is apparently something they would need.

“Many people know that AI is politically unpopular, and want to leverage that to boost their own popularity,” Thiel said. “Both Obama and the pope fall into this category. Obama knows the Democrats have no ideas, but they can at least oppose AI,” adding “AI is the threat über alles of late modernity. The pope knows it. That’s why he wrote his first encyclical … he needed something politically popular to distract from the church’s child sex abuse scandals, and he found it in AI.”

Obama recently called for public oversight of AI while the pope’s first encyclical focuses on “safeguarding the human person in the time of artificial intelligence.”

The post Tech leaders embrace Trump’s “super intelligence” as he calls critics “the enemy” appeared first on Salon.com.

Yet another update on the running AI discussion.

Here’s an interview Ezra Klein did with a guy named David Robinson. And that interview is about a piece Robinson, a member of the Open AI safety and safety documentation team, wrote in The Atlantic announcing his resignation from OpenAI — a decision and announcement he is self-aware enough to note has become something of a cliche. I found the interview interesting and edifying, largely on the front I mentioned earlier about finding reliable narrators.

Robinson isn’t a data scientist or a programmer. His role at OpenAI was essentially being the conduit between the teams building the LLMs and the knowledgable and interested public, specifically the people who write the documentation — what does this model do, how does it work, what are the possible safety risks. As is usually the case in any highly technical space, the people doing the work aren’t going to be writers and they’re usually not going to speak a language outsiders can necessarily understand. So you have people who are close enough to the work and the workers to understand what is happening and also able to speak human so they can communicate it to everyone else. Robinson led the team that served in that role.

Today's links

• Disloyalty: Air Canada's frequent flier fuckery.
• Hey look at this: Delights to delectate.
• Object permanence: Indie booksellers v internet; Coke pays dieticians to astroturf soda taxes; Voting in a voter-suppression state; Facebook v your use of Facebook.
• Upcoming appearances: Hudson, Calgary, Winnipeg, Paris, Vancouver, Victoria, Ottawa, Kilkenny, Sheffield, Oxford, Montreal.
• Recent appearances: Where I've been.
• Latest books: You keep readin' em, I'll keep writin' 'em.
• Upcoming books: Like I said, I'll keep writin' 'em.
• Colophon: All the rest.

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Disloyalty (permalink)

Up until very recently indeed, airlines were the only businesses that I dealt with regularly that practiced "price discrimination," charging different customers different prices for the same seats.

Economists broadly like this "second-order" price discrimination, where a company charges customers different prices based on the circumstances of the purchase, such as a bakery discounting bread at the end of the day. When an airline cranks up the price of an itinerary that doesn't include a Saturday stay, they're using that fact as a proxy for "price-insensitive" business travelers whose bosses can afford to pay more for a ticket, rather than paying a worker overtime to spend a weekend away from home after a meeting.

Despite the arguments about "efficiency," it's safe to say that *fliers* hate this. The airlines' pricing algorithms are so opaque and capricious that anyone who buys a ticket at *any* price inevitably feels like they got a bad deal. This situation is only exacerbated by the airlines' extreme and aggressive secrecy over their pricing strategies, which includes lawsuits against websites that use historical pricing data to predict when a plane ticket will be the cheapest to buy:

https://www.eff.org/document/preliminary-injunction-american-airlines-v-farechase-inc

When a company wants the government to intervene to prohibit third parties from publishing factual information about its prices, that's a bad look. Hard to believe that they're so sure that you, the customer, will be delighted by these pricing tactics that they can't bear to have these third parties ruin the surprise.

But this second-order discrimination is *so* 20th century. Here in the 21st century, we have *first-order* price discrimination, in which AI-powered pricing algorithms use commercial surveillance data about *you*, personally, to predict the highest price you're willing to pay. In this world of "surveillance pricing," every traveler (or customer) sees a different price, in a kind of cod-Marxist dystopia whose motto is "from each according to their ability (to pay), to each according to their (desperate) needs":

https://pluralistic.net/2025/01/11/socialism-for-the-wealthy/#rugged-individualism-for-the-poor

Airlines *love* this kind of pricing, and they have means, motive and opportunity to practice it. All over the world, airlines have acquired or entered into joint ventures with surveillance pricing companies. These deals put the airlines on the horns of a dilemma: they love to boast to their shareholders about the way that surveillance pricing will let them gouge fliers, but inevitably the public finds out about these investor calls and breaks out the pitchforks and torches.

This triggers embarrassing climbdowns, like Delta's fiasco of summer 2025, when CEO Ed Bastian bragged to shareholders that his deal with the Israeli surveillance pricing company Fetcherr would boost profits by 50% (!) by figuring out which customers could be safely gouged. When fliers, civil society groups and members of Congress got wind of this and raised a ruckus, Fetcherr publicly disavowed Bastian's remarks, insisting that it wasn't even capable of the kind of price-fixing he'd promised. Then Delta launched a smear campaign against its critics, claiming that Bastian never said the thing he *absolutely said* and accusing surveillance pricing activists of peddling "misinformation":

https://groundworkcollaborative.org/news/amid-deltas-ai-pricing-scheme-groundwork-applauds-congressional-action-to-crack-down-on-surveillance-pricing-schemes/

Meanwhile, airlines all over the world have quietly switched their frequent flier reward programs from "mileage-based" rewards to "revenue-based" rewards. That means that you get points and status based on how much you spend on your ticket, not how far you fly. What may not be obvious from this move is that it forces frequent fliers to buy their tickets directly from the airlines, who claim that they can't tell how much you've spent on your ticket otherwise.

So tickets bought on sites like Expedia or through travel agents often qualify for insultingly small points awards, or no points at all. For example, British Airways once gave me *12 points* on a $2,000 Alaska Air ticket because I didn't buy it through British Airways' site (attaining BA's gold status requires *50,000* points).

Forcing frequent fliers to buy their tickets directly from the airline's website sets things up beautifully for surveillance-driven, first-order price discrimination. Airlines you do business with regularly can augment the personal information you provide to them and the data they collect from you with sensitive information purchased from the unregulated data-broker industry, which will cheerfully disclose your salary, credit card debts, or even if you've recently lost a parent and might be flying out for a funeral.

The airlines strenuously deny that they're doing this, of course, but they continue to make investor-facing announcements about their exciting deals with surveillance pricing companies…and things are getting *weird* for frequent travelers.

Thanks to a lot of book-related travel over the past couple of years, I have "Elite" status with Air Canada. Yesterday, I needed to book a last-minute, one-way fare on a route that is only serviced by Air Canada (AC enjoys a monopoly over many Canadian routes, even between major Canadian cities). I checked it out on Google Flights and found a fare for the eye-watering sum of USD829.73.

Now, my normal daily-use browser is Firefox, but I know from long experience that I can't log in to my Air Canada frequent flier account on any browser except Chromium, which I keep installed on my system for just this kind of hostile garbage website. So I tabbed over to Chromium and pasted the Google Flights outbound link that would take me to a pre-populated reservation form on aircanada.com. To my amazement, that same flight was showing as a USD1200 fare!

These were identical trips, loaded via identical referrer URLs. The difference was that in the browser where Air Canada knew that I was an extremely loyal and prolific customer, they had whacked me with a *44.8% premium* to punish me for my loyalty!

I couldn't believe it. I actually called Air Canada's customer service line for "Elite" fliers, and the customer service rep was at a loss for an explanation and could only apologise and suggest that I write a letter to the company.

I'm publishing this instead, because a) this will do more to punish Air Canada for trying to screw me over; and b) this can help you book your tickets in the future.

Yesterday, I finished buying the ticket in my logged-out Firefox window (Air Canada's website will work with Firefox to buy tickets provided you don't try to log in to your Aeroplan account first), paying $829. Then I flipped back to Chromium, where I was still logged into my Air Canada Aeroplan account, located the reservation, and added my frequent flier number to it.

I guess this is how I'm buying my plane tickets from now on.

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Hey look at this (permalink)

* PM Mark Carney pledged to ‘Buy Canadian.’ Since then, $7.8 billion in contracts went to American corporations https://archive.is/zDBfX#selection-3576.0-3576.3

* Tracing the rogue ideology of the frontier labs to their product choices https://buttondown.com/apperceptive/archive/tracing-the-rogue-ideology-of-the-frontier-labs/

* Have you heard of the term "enshittification?" https://www.youtube.com/watch?v=nJ5V3pk6PEA&t=1220s

* Window display at TYPE Books Toronto to honour David Byrne’s new book https://stopmakingsense.info/window-display-at-type-books-toronto-to-honour-david-byrnes-new-book/

* Red Vienna Is Still Alive https://www.thenation.com/article/society/vienna-public-housing-urban-cities/

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Object permanence (permalink)

#20yrsago Indie booksellers in the age of the Internet https://web.archive.org/web/20061026112859/https://www.wired.com/news/wireservice/1,71924-0.html

#10yrsago Wells Fargo whistleblower describes bank’s culture of blackballing threats and coerced corruption https://www.npr.org/sections/money/2016/10/07/497084491/episode-728-the-wells-fargo-hustle

#10yrsago Coca-Cola is paying dietitians to tweet scare-stories about soda taxes https://medium.com/cokeleak/is-coke-paying-dietitians-to-tweet-against-soda-tax-12d130d73b9a#.dw8udqccy

#10yrsago What it’s like to register to vote in states with voter suppression law https://www.bbc.com/news/election-us-2016-37569855

#5yrsago Facebook shouldn't be in charge of how you use Facebook https://pluralistic.net/2021/10/08/unfollow-everything/#shut-the-zuck-up

---

Upcoming appearances (permalink)

* Hudson, OH: Hudson Library, Oct 7
https://engagedpatrons.org/EventsExtended.cfm?SiteID=3850&EventID=596952&PK=

* Calgary: Wordfest, Oct 8
https://wordfest.com/2026/show/wordfest-presents-cory-doctorow-2026/

* Winnipeg: McNally Robinson, Oct 9
https://www.mcnallyrobinson.com/event-18991/An-Evening-with-Cory-Doctorow

* Paris: Slow Tech Summit, Oct 15
https://slowtechsummit.com/

* Vancouver: Read, Resist, Repair, Rejoice (Vancouver Writers Festival), Oct 19
https://writersfest.bc.ca/festival-event-2026/01

* Victoria: Munro's Books, Oct 20
https://www.munrobooks.com/events/6113620261020

* Vancouver: Life After AI (Vancouver Writers Festival), Oct 22
https://writersfest.bc.ca/festival-event-2026/46

* Ottawa: Life After AI (Ottawa Writers Festival), Oct 24
https://writersfestival.org/event/life-after-ai

* Kilkenny (Kilkenomics), Nov 6-8
https://kilkenomics.com/

* Vancouver: Enshittification (Sid Williams Theatre Society), Nov 10
https://www.sidwilliamstheatre.com/events/cory-doctorow-talks-enshittification/

* Vancouver: BC Policy Solutions Gala, Nov 12
https://bcpolicy.ca/gala/

* Sheffield: Reverse Centaur at Juno Books, Nov 25
https://www.outsavvy.com/event/40274/cory-doctorow-in-conversation

* Oxford: Bennett Oxford Symposium on Open Code in Science, Dec 9
https://www.bennett.ox.ac.uk/events/2026-bennett-institute-symposium/

* Montreal: World Science Fiction Convention, Sep 2-6
https://montreal2027.ca/en

---

Recent appearances (permalink)

* Terms of Service with Clare Duffy (CNN)
https://www.cnn.com/audio/podcasts/terms-of-service-with-clare-duffy/episodes/458ce968-af5d-11f0-b539-13ed2afe25f8

* AI, Work, and Power (Software Engineering Daily)
AI, Work, and Power https://softwareengineeringdaily.com/podcasts/cory-doctorow-on-ai-work-and-power/

* AI, Corporate Power, and the Fight for Worker Control (Plutopia)
https://plutopia.io/cory-doctorow-ai-corporate-power-and-the-fight-for-worker-control/

* How to Think About AI—Before It’s Too Late (Daniel Solove)
https://www.youtube.com/watch?v=_0xR3uEgGcc

* Could Tech Bosses Destroy Life As We Know It? (Politics JOE)
https://www.youtube.com/watch?v=PL4VktU0SgY

---

Latest books (permalink)

* "The Reverse-Centaur's Guide to AI," a short book about being a better AI critic, Farrar, Straus and Giroux, June 2026
https://us.macmillan.com/books/9780374621568/thereversecentaursguidetolifeafterai/

* "Canny Valley": A limited edition collection of the collages I create for Pluralistic, self-published, September 2025 https://pluralistic.net/2025/09/04/illustrious/#chairman-bruce

* "Enshittification: Why Everything Suddenly Got Worse and What to Do About It," Farrar, Straus, Giroux, October 7 2025
https://us.macmillan.com/books/9780374619329/enshittification/

* "Picks and Shovels": a sequel to "Red Team Blues," about the heroic era of the PC, Tor Books (US), Head of Zeus (UK), February 2025 (https://us.macmillan.com/books/9781250865908/picksandshovels).

* "The Bezzle": a sequel to "Red Team Blues," about prison-tech and other grifts, Tor Books (US), Head of Zeus (UK), February 2024 (thebezzle.org).

* "The Lost Cause:" a solarpunk novel of hope in the climate emergency, Tor Books (US), Head of Zeus (UK), November 2023 (http://lost-cause.org).

* "The Internet Con": A nonfiction book about interoperability and Big Tech (Verso) September 2023 (http://seizethemeansofcomputation.org). Signed copies at Book Soup (https://www.booksoup.com/book/9781804291245).

* "Red Team Blues": "A grabby, compulsive thriller that will leave you knowing more about how the world works than you did before." Tor Books http://redteamblues.com.

* "Chokepoint Capitalism: How to Beat Big Tech, Tame Big Content, and Get Artists Paid, with Rebecca Giblin", on how to unrig the markets for creative labor, Beacon Press/Scribe 2022 https://chokepointcapitalism.com

---

Upcoming books (permalink)

* "The Post-American Internet," a geopolitical sequel of sorts to *Enshittification*, Farrar, Straus and Giroux, 2027

* "Unauthorized Bread": a middle-grades graphic novel adapted from my novella about refugees, toasters and DRM, FirstSecond, April 20, 2027

* "Enshittification, Why Everything Suddenly Got Worse and What to Do About It" (the graphic novel), Firstsecond, 2027

* "The Memex Method," Farrar, Straus, Giroux, 2027

---

Colophon (permalink)

Today's top sources:

Currently writing:

* “Once Is Enemy Action,” a science fiction novel about the origins of modern technofascism. Today's words: 529 (22924 total).

* "The Post-American Internet," a sequel to "Enshittification," about the better world the rest of us get to have now that Trump has torched America. Fourth draft completed. Submitted to editor.

* A Little Brother short story about DIY insulin PLANNING

---

This work – excluding any serialized fiction – is licensed under a Creative Commons Attribution 4.0 license. That means you can use it any way you like, including commercially, provided that you attribute it to me, Cory Doctorow, and include a link to pluralistic.net.

https://creativecommons.org/licenses/by/4.0/

Quotations and images are not included in this license; they are included either under a limitation or exception to copyright, or on the basis of a separate license. Please exercise caution.

---

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"When life gives you SARS, you make sarsaparilla" -Joey "Accordion Guy" DeVilla

READ CAREFULLY: By reading this, you agree, on behalf of your employer, to release me from all obligations and waivers arising from any and all NON-NEGOTIATED agreements, licenses, terms-of-service, shrinkwrap, clickwrap, browsewrap, confidentiality, non-disclosure, non-compete and acceptable use policies ("BOGUS AGREEMENTS") that I have entered into with your employer, its partners, licensors, agents and assigns, in perpetuity, without prejudice to my ongoing rights and privileges. You further represent that you have the authority to release me from any BOGUS AGREEMENTS on behalf of your employer.

ISSN: 3066-764X

For years, and especially in the last month or so, we’ve been collectively inundated with an AI industry which, uncannily and bizarrely, tells us simultaneously that AI is essential, inevitable and runs a significant chance of exterminating all of us in as few as two or three years. If you’ve dipped into this debate at all, you’ve quickly come upon discussions of so-called “rationalists” or “long-termists” or supporters of “effective altruism” who are simultaneously ubiquitous among those developing AI and in the AI safety (i.e., the folks sounding the alarm) community as well. (For the sake of simplicity and brevity, I’ll refer to these folks as the “REL nexus”: rationalists, effective altruists and long-termists. This is my coinage since I don’t know a better one.) I’ve spent a fair amount of time familiarizing myself with this world and how it relates to current debates about AI. So I wanted to share my basic impressions.

Today's links

• Swapping money for expertise: Money can't buy me love.
• Hey look at this: Delights to delectate.
• Object permanence: "Tempo"; Yahoo censors MEP's torture debate video; Scotland's money-laundry; A textbook scam; DOS the IRS then charge for access; Just trying to make a buck.
• Upcoming appearances: Virtual, South Bend, Hudson, Calgary, Winnipeg, Paris, Vancouver, Victoria, Ottawa, Kilkenny, Sheffield, Oxford, Montreal.
• Recent appearances: Where I've been.
• Latest books: You keep readin' em, I'll keep writin' 'em.
• Upcoming books: Like I said, I'll keep writin' 'em.
• Colophon: All the rest.

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Swapping money for expertise (permalink)

Since the mid-1950s, we have changed the thing that "AI" refers to every 5-10 years. The current thing we're calling "AI" is about a decade old, and all this label-switching leads to a lack of clarity as to what (this) "AI" is. Unless you know that, you can't understand AI's technical capabilities, limitations, and (most of all) its political economy.

The thing we now call "AI" is a lineal descendant of the thing we were calling "AI" immediately before the current "AI" emerged: that preceding AI is regular-degular "machine learning" (another flexible term, alas!). That slightly older AI was very similar to the current "AI", using comparable statistical techniques to analyze inputs and produce outputs. For example, the previous "AI" created the social media algorithms that have been the subject of so much discussion for 15+ years.

The difference is that this older AI was grounded in explicit, causal software models of the world. In the previous "AI" iteration, applying machine learning to playing chess required that a programmer first create a software model of a chess game, describing (in code) a chessboard, chess pieces, and the rules of chess. Then, the programmer fed a bunch of training data about chess games that had been played before to an "AI" system that analyzed their statistical relations and assayed chess moves.

The need to understand and describe a thing before you could apply "AI" to it is a bottleneck, because it requires programmers to understand how a thing works before they can incorporate it into an "AI" system. Lots of programmers know how to play chess, but far fewer understand the human pancreas, planetary weather systems, or patterns of mineral deposition in the Earth's crust.

For programmers to apply machine learning to these domains, they need to collaborate with experts who do understand them, who furthermore expect to be paid for this work. The need for expert input into this kind of "AI" represents a significant increase in the wage-bill paid by the programmer's employer: it means they have to pay for programmers and experts.

Even worse: this kind of "AI" can't be applied to systems we don't understand. We can observe far more causal relationships – instances in which A reliably causes B – in the universe than we can explain. There are lots of examples of us operationalizing these observations without understanding them. If you get sick today, your doctor might well prescribe one of the many medicines whose method of action is either incompletely understood or not understood at all. We know that molecule A reliably treats pathology B, but not why, and while that why is the subject of ongoing research, it's not necessary that the why be known before the molecule can be given to ailing patients.

But these mysterious phenomena are off-limits to "symbolic AI" (the previously ascendant kind of "AI," that was supplanted by today's "AI"). That kind of AI only really performs when it can operate over a model describing the theory of why A causes B (and not just the fact that A causes B for reasons unknown).

That's where the current kind of "AI" comes in. The major differentiator between the current "AI" and its immediate predecessor is that the current "AI" dispenses with models of reality. It is (in the jargon of the "Big Data" bubble that led to it) "theory-free."

In "theory-free AI," a programmer does not create a software model of reality and then ask a machine-learning system to use statistical insights from its training data to guess at how to operate over that model. Rather, the programmer shovels vastly more training data into the AI's inbox and uses titanic amounts of computing power to analyze that data and find statistical relationships without trying to explain them.

In other words, the current, "theory-free AI" finds all the instances in which A seems to cause B, but has no internal representation of why A causes B. This is true even when we know why A causes B! Purely theory-free chess programs don't operate with any conception of a board or pieces or rules – rather, they make guesses ("inferences" in AI-speak) about which chess move will be optimal based on vast, multi-dimensional arrays constructed by analyzing the statistical relationships between every chess move in their training data.

This yields a surprisingly good game of chess…until it doesn't. Because a theory-free statistical chess program doesn't "know" what a chessboard or a chess piece is and has no programmatic representation of the rules of chess, it will periodically move one of its pieces onto a square that is already occupied by another of its pieces.

When theory-free AI does this with language or image generation, we call it an "hallucination," but this is an extremely misleading metaphor. A biological "hallucination" involves some kind of misfire in your cognitive and/or sensory systems, often arising from chemical imbalances, intoxication, or neurological injury. When a theory-free AI puts a chess piece on a square where it already has a chess piece, that's because it's just extruding statistically founded guesses without any model or conception of what "chess" is. It's a feature, not a bug.

This is a very expensive way to make guesses! As far back as the 1950s, we were able to run conventional chess programs on computers built from vacuum tubes and electromechanical switches and these programs could play a valid game of chess without ever moving a chess piece to a square that one of its pieces already occupied. Modern theory-free AI that cannot manage this feat consumes heptillions of times more computing power.

That said, there's another case for theory-free AI: applying machine learning techniques to causal relationships we can observe but not explain. Remember, there are far more of these (as yet) unexplained causal relationships than there are perfectly understood ones. Theory-free AI can operate on these unexplained, observed phenomena in ways that the preceding (symbolic) AI can't. As anyone who's ever been successfully treated with a molecule whose method of action is partially or fully mysterious can attest, there's plenty of reasons to want to extract and operationalize these statistical relationships, even if we don't understand them.

The fact that theory-free AI can play chess but sometimes makes these weird errors makes it seem like a party-trick, but when you fold in the ability to operate on the (as yet) unexplained, you can see why people got interested in this about a decade ago.

What's more, the first bottleneck – the chess bottleneck – is most easily bypassed by adding the symbolic model back into the theory-free chess system. Today's "coding assistants" are hybridized in this way: they often integrate code interpreters or compilers that actually "know" what a computer program is and can head off many of these failure modes.

The introduction of these symbolic systems to theory-free systems is completely rational, and yet it represents an admission of a key limitation that theory-free AI cannot overcome. That limitation is both a technical fact, but even more importantly, it's a fact about theory-free AI's political economy: about the limitations of trading off expertise for money.

Because whatever else theory-free inference is, it is a way to swap the bottleneck of "before we can use a computer to help us do something, we need to find an expert who can explain how that thing works"; for a different bottleneck: "before we can use a computer to help us do something, we must spend an enormous amount of money on computing power to find statistical relationships between how things work."

Both money and expertise are scarce, but they are unevenly distributed. Expertise is almost entirely in the hands of people who aren't wealthy. However much money a billionaire has, they still have to hire people who have the "how to clean a toilet" or the "how to find seams of gold in quartz deposits" expertise. When that expertise is locally scarce (if there's only one person in town who know how to clean your toilet) or universally scarce (there's only one expert who can tell you which of your landholdings are likely to hold seams of gold) those experts have something that billionaires can't abide: power.

Our entire society is organized around converting money into power. Sometimes, that is overt, as when the wealthy can indenture or enslave a worker. Sometimes it is more indirect, as when the wealthy can enlist the state to limit union rights and enforce noncompete clauses in labor contracts. Sometimes it's so systemic as to be unremarkable and largely invisible, like the fact that the wealthy never have to work if they don't want to, but everyone else – no matter what expertise they hold – must work, usually for a wealthy person, lest they end up starving and homeless, with untreated medical conditions and no way to provide for their families.

Whenever a worker can say "no" to their boss, it's a sign that this system has broken down. This is where expertise comes in: a worker who has very scarce, in-demand expertise can say no to their boss all day long, because there are ten other bosses at the factory gates who'd like to offer them a job. This was the situation for many years among Silicon Valley engineers, who added an average of $1m/year to their bosses' turnover, and whose supply was very short of the demand for their rare expertise.

These engineers enjoyed all kinds of power. Not just power over their working conditions (free massages and kombucha and day care and dry cleaning), but also power over the company's products. This power crested in the late 2010s, when Google employees walked out en masse and forced the company to release them from binding arbitration waivers in their contracts, to crack down on sexual predators in the executive ranks, and to back out of billions of dollars in lethal drone projects for the Pentagon:

https://en.wikipedia.org/wiki/2018_Google_walkouts

The promise of theory-free inference isn't just about reducing the wage-bill associated with programmers: even more, it's about reducing their power. It's about removing their power to hold bosses to account for sexual assault and the power to withhold their labor from lethal military projects. In short, the power to thwart billionaires' desires.

AI is the money-losingest enterprise the human race has ever embarked upon. More than a trillion dollars has been spent this year to make a mere $50b in revenue. The technical excitement over AI's capabilities – from chess to gold-mining to treating pancreatic cancer – cannot be separated from the political excitement that billionaires (short on expertise, flush with cash) experience at the thought of swapping money for expertise and sidelining the only people in the world who can thwart their goals.

The fact that a theory-free AI might demand far more cash to accomplish a task (even a "solved" one like playing chess) than an expert would charge is beside the point. Billionaires have money, they don't have expertise. Theory-free inference is a bid to substitute one for the other: the beauty and terror of being able to manipulate the world without studying or understanding it is that it can be done with money alone. No experts needed.

In a world in thrall to financial power, expertise is the only substantial form of power that can reliably contest the power of wealth. Moreover, expertise is the foundation of other forms of power, such as labor power, which is what we call it when experts band together to combat financial power.

This is why AI bosses are so violently allergic to the idea of hybridizing AI with symbolic systems that operate on models of the world. These models of the world must be constructed by experts, and the power of expertise cannot be reliably commanded by the power of wealth.

This is even true when theory-free methods are applied to causal phenomena that we can observe without explaining. Sure, a pharma exec like Martin Shkreli or Arthur Sackler can command the production and sale of a molecule whose method of action isn't known but whose therapeutic value has been demonstrated. But to improve on that molecule, they must pay research scientists to study and unravel the method of action. Replace those experts with theory-free inference, and finance can emerge triumphant in the only forum in which it is routinely vanquished.

This is the political economy of theory-free AI. Without finance's infinite hostility to expertise, there would have been far less capital for theory-free AI. Experts who wanted to use theory-free AI to help them unravel and operationalize the causal universe could not have laid hands on the bales of $100 bills the industry is now shoveling into its money-furnaces at a rate never seen in human history.

Which is not to say that experts can't make good use of theory-free AI. Indeed, we frequently hear from skilled workers who are using "AI" to improve the quality of their outputs:

https://hrdag.org/tech-notes/large-language-models-IPNO.html

In automation parlance, these workers are "centaurs": workers who enlist technology to serve their needs. The centaur metaphor has the worker taking the role of the top half of the mythical man/horse, the half in which the judgment and decision-making takes place; while the bottom (horsey) half is given to the machine, providing strength, speed and stamina, but only at the direction of the human mind.

The unimaginable sums that oligarchs have committed to AI are mobilized in service to creating reverse centaurs: machines that enlist humans to serve them. If theory-free inference can substitute for expertise, then the humans the machines require to accomplish those tasks that elude computers will not have the power to set the pace of their work, insist upon humane working conditions, or reject work on unethical projects:

https://pluralistic.net/2025/12/05/pop-that-bubble/#u-washington

The joke's on the oligarchy, though. Because theory-free inference doesn't know about chessboards, chess pieces or the rules of chess, it can't be prevented from sometimes putting a chess piece on a square that's already occupied by one of its pieces. The "hallucinations" are intrinsic to and inextricable from theory-free inference, which means that the outputs of an "AI" can only be trusted if they can be evaluated by an expert, whose working tempo must be carefully modulated lest they fall prey to "automation blindness" (rapidly, repeatedly clicking "OK" until you lose the ability to spot mistakes):

https://pluralistic.net/2026/07/28/hitl-ers/#ai-ai-oh

Theory-free inference is technically and philosophically exciting: in their quest for a way to neutralize expertise with money, oligarchs inadvertently built a series of powerful scientific instruments that revealed a heretofore unsuspected degree of statistical regularity in the world:

https://pluralistic.net/2026/09/18/surprise/#wow-signal

But the remaining, stubbornly textured and rough edges of reality are where all the value is. The things we already understand about reality are, by definition, yesterday's news, and that's all a statistical model can do: project the past into the future. But everything exciting in the future is stuff we don't understand yet. The surprising functionality of theory-free AI is itself an example of this. The most interesting and valuable thing about theory-free AI isn't the things it can do, it's the systematic discovery and mapping of the statistically regular parts of reality, whose inverse provides a map of the irregular, surprising, poorly understood (and thus exciting and promising) phenomena in our universe.

Tomorrow's breakthroughs and fortunes lie not in merely operationalizing these causal relationships: they lie in understanding them. The point of theory-free inference is to give us the tools to replace that theory-freeness with testable, validated understanding.

---

Hey look at this (permalink)

• How the Courts Became a Safe Haven for Corporations https://prospect.org/2026/10/06/how-courts-became-safe-haven-for-corporations/

• Why Plain Text Is Still One of the Best Technologies We Have https://deadparrotbbs.com/why-plain-text-is-still-one-of-the-best-technologies-we-have/

• Exclusive: How did Rosalind Franklin miss the helix in her iconic DNA image? She didn’t https://www.science.org/content/article/how-did-rosalind-franklin-miss-helix-her-iconic-dna-image-she-didn-t

• Voting only gets you so far https://www.garbageday.email/p/voting-only-gets-you-so-far

• Career day https://www.dailykos.com/stories/2026/10/5/800105682/cartoon/career-day/

---

Object permanence (permalink)

#15yrsago Tempo: transformative, difficult look at advanced decision-making theory https://memex.craphound.com/2011/10/07/tempo-transformative-difficult-look-at-advanced-decision-making-theory/

#10yrsago Internet shutdowns cost the world at least $2.4 billion last year https://www.brookings.edu/articles/internet-shutdowns-cost-countries-2-4-billion-last-year/

#10yrsago Youtube took down MEP’s videos about torture debate https://web.archive.org/web/20160701000000*/https://marietjeschaake.eu/en/when-youtube-took-down-my-video

#10yrsago Yahoo didn’t install an NSA email scanner, it was a “buggy” NSA “rootkit” https://web.archive.org/web/20161007140143/https://motherboard.vice.com/read/yahoo-government-email-scanner-was-actually-a-secret-hacking-tool

#10yrsago The FCC helped create the Stingray problem, now it needs to fix it https://www.eff.org/deeplinks/2016/08/fcc-created-stingray-problem-now-it-needs-fix-it

#5yrsago Scottish Limited Partnerships are still laundering criminal millions https://pluralistic.net/2021/10/07/markets-in-everything/#if-its-not-scottish

#5yrsago "Inclusive Access" allows textbook monopolists to permanently consolidate their gains https://pluralistic.net/2021/10/07/markets-in-everything/#textbook-abuses

#5yrsago DoS a federal agency, then charge for access https://pluralistic.net/2021/10/07/markets-in-everything/#no-th-enq

#1yrago They're just trying to earn a buck https://pluralistic.net/2025/10/07/take-it-easy/#but-take-it

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Upcoming appearances (permalink)

• Virtual: How to govern technology in a multipolar digital world (Connecting Current), Oct 6
  https://connectingcurrent.tech/how-to-govern-technology-a-multipolar-digital-world/

• South Bend: An Evening With Cory Doctorow (Notre Dame), Oct 6
  https://franco.nd.edu/events/2026/10/06/an-evening-with-cory-doctorow/

• Hudson, OH: Hudson Library, Oct 7
  https://engagedpatrons.org/EventsExtended.cfm?SiteID=3850&EventID=596952&PK=

• Calgary: Wordfest, Oct 8
  https://wordfest.com/2026/show/wordfest-presents-cory-doctorow-2026/

• Winnipeg: McNally Robinson, Oct 9
  https://www.mcnallyrobinson.com/event-18991/An-Evening-with-Cory-Doctorow

• Paris: Slow Tech Summit, Oct 15
  https://slowtechsummit.com/

• Vancouver: Read, Resist, Repair, Rejoice (Vancouver Writers Festival), Oct 19
  https://writersfest.bc.ca/festival-event-2026/01

• Victoria: Munro's Books, Oct 20
  https://www.munrobooks.com/events/6113620261020

• Vancouver: Life After AI (Vancouver Writers Festival), Oct 22
  https://writersfest.bc.ca/festival-event-2026/46

• Ottawa: Life After AI (Ottawa Writers Festival), Oct 24
  https://writersfestival.org/event/life-after-ai

• Kilkenny (Kilkenomics), Nov 6-8
  https://kilkenomics.com/

• Vancouver: Enshittification (Sid Williams Theatre Society), Nov 10
  https://www.sidwilliamstheatre.com/events/cory-doctorow-talks-enshittification/

• Vancouver: BC Policy Solutions Gala, Nov 12
  https://bcpolicy.ca/gala/

• Sheffield: Reverse Centaur at Juno Books, Nov 25
  https://www.outsavvy.com/event/40274/cory-doctorow-in-conversation

• Oxford: Bennett Oxford Symposium on Open Code in Science, Dec 9
  https://www.bennett.ox.ac.uk/events/2026-bennett-institute-symposium/

• Montreal: World Science Fiction Convention, Sep 2-6
  https://montreal2027.ca/en

---

Recent appearances (permalink)

• Terms of Service with Clare Duffy (CNN)
  https://www.cnn.com/audio/podcasts/terms-of-service-with-clare-duffy/episodes/458ce968-af5d-11f0-b539-13ed2afe25f8

• AI, Work, and Power (Software Engineering Daily)
  AI, Work, and Power https://softwareengineeringdaily.com/podcasts/cory-doctorow-on-ai-work-and-power/

• AI, Corporate Power, and the Fight for Worker Control (Plutopia)
  https://plutopia.io/cory-doctorow-ai-corporate-power-and-the-fight-for-worker-control/

• How to Think About AI—Before It’s Too Late (Daniel Solove)
  https://www.youtube.com/watch?v=_0xR3uEgGcc

• Could Tech Bosses Destroy Life As We Know It? (Politics JOE)
  https://www.youtube.com/watch?v=PL4VktU0SgY

---

Latest books (permalink)

• "The Reverse-Centaur's Guide to AI," a short book about being a better AI critic, Farrar, Straus and Giroux, June 2026
  https://us.macmillan.com/books/9780374621568/thereversecentaursguidetolifeafterai/

• "Canny Valley": A limited edition collection of the collages I create for Pluralistic, self-published, September 2025 https://pluralistic.net/2025/09/04/illustrious/#chairman-bruce

• "Enshittification: Why Everything Suddenly Got Worse and What to Do About It," Farrar, Straus, Giroux, October 7 2025
  https://us.macmillan.com/books/9780374619329/enshittification/

• "Picks and Shovels": a sequel to "Red Team Blues," about the heroic era of the PC, Tor Books (US), Head of Zeus (UK), February 2025 (https://us.macmillan.com/books/9781250865908/picksandshovels).

• "The Bezzle": a sequel to "Red Team Blues," about prison-tech and other grifts, Tor Books (US), Head of Zeus (UK), February 2024 (thebezzle.org).

• "The Lost Cause:" a solarpunk novel of hope in the climate emergency, Tor Books (US), Head of Zeus (UK), November 2023 (http://lost-cause.org).

• "The Internet Con": A nonfiction book about interoperability and Big Tech (Verso) September 2023 (http://seizethemeansofcomputation.org). Signed copies at Book Soup (https://www.booksoup.com/book/9781804291245).

• "Red Team Blues": "A grabby, compulsive thriller that will leave you knowing more about how the world works than you did before." Tor Books http://redteamblues.com.

• "Chokepoint Capitalism: How to Beat Big Tech, Tame Big Content, and Get Artists Paid, with Rebecca Giblin", on how to unrig the markets for creative labor, Beacon Press/Scribe 2022 https://chokepointcapitalism.com

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Upcoming books (permalink)

• "The Post-American Internet," a geopolitical sequel of sorts to Enshittification, Farrar, Straus and Giroux, 2027

• "Unauthorized Bread": a middle-grades graphic novel adapted from my novella about refugees, toasters and DRM, FirstSecond, April 20, 2027

• "Enshittification, Why Everything Suddenly Got Worse and What to Do About It" (the graphic novel), Firstsecond, 2027

• "The Memex Method," Farrar, Straus, Giroux, 2027

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Colophon (permalink)

Today's top sources:

Currently writing:

• “Once Is Enemy Action,” a science fiction novel about the origins of modern technofascism. Today's words: 513 (22395 total).

• "The Post-American Internet," a sequel to "Enshittification," about the better world the rest of us get to have now that Trump has torched America. Fourth draft completed. Submitted to editor.

• A Little Brother short story about DIY insulin PLANNING

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The post We’ve tracked $80M of spending on almost 170 AI‑generated political ads this year – it’s weird appeared first on Salon.com.

We’ve been following this conversation here in The Editors’ Blog about what AI is, what it can do and whether it can possibly live up to its hype. It’s worth considering the question from what we might loosely call not only the supply side but also the demand side. From a very broad perspective, the history of the last three decades has been one defined by the fact that you have too much capital chasing too few productive investments. That’s the driver of the recent history of cycles of booms, bubbles, over-investment and busts: the Asian Financial Crisis, the Dot Com Bust, the Global Financial Crisis, perhaps soon the AI Bubble Collapse, along with many smaller of regional ones.

I couldn’t help but notice some people on social media dunking on a post from @nicksaraev, a self-described entrepreneur helper, who boldly proclaimed on X a few days ago: “I am not joking when I say this. Spotify, Apple Music, and streaming in general is over. AI music is now very, very good. You just don’t know yet because all AI music circulating today is from ~2-3 generations ago. Suno v6 pro et al has solved infinite personalized music.” He followed it up with “Yes, this probably hurts your feelings. It’s still going to happen.”

While my feelings are unhurt, and I don’t really know what “infinite personalized music” means or how it could be “solved,” at the same time, I can easily guess what is implied here and I don’t actually want to know more. As one Bluesky user observed, the inherent idea here comes “when you have no concept of how people engage with music.”

Nonetheless, we don’t seem able to escape this trend. I have a friend who has, on a few occasions, sent me AI-generated raps with his name or a joke inserted as the lyrics. They can be technically proficient, maybe even a little funny, but there is always an underlying cadence of the uncanny valley that I still doubt Suno v6 pro et al. or whatever has totally overcome. Please don’t send me examples; I actually don’t care. It’s not that I’m offended by the idea of generated art; it’s just that it bores me. I’m having plenty of fun engaging with music made with human ears, hands and minds.

Way back in the Bush II and Obama years, I volunteered at my college radio station in the Music Procurement Department or whatever it was called. Our job was to sort through the massive mailer box of padded envelopes and bubble mailers that came in from record labels, big, small and in-between. It was like Christmas every Wednesday afternoon as we shredded packages and stacked CDs, occasional stickers and vinyl, splitting the spoils and loading them into our computers — by hand even! We made notes about what should get added to the radio catalog as fodder for our aspiring DJs — and what should get chucked out or given away for free at radio events.

If we didn’t already know the band, the way we chose which albums to review was often based on cover art, the promo materials we skimmed, or a sticker on the front that read RIYL: Recommended If You Like. Almost every artist would put something like “RIYL: Jay-Z, Radiohead, The Beatles, Led Zeppelin, Talking Heads.” Sure, totally random indie label from Seattle, all of your bands sound exactly like Nirvana. It could be a pretty boring, sometimes horrifying process — I’ll never forget the thrash metal song we received about Shannen Doherty that sounded like it was recorded in a blender. I still can’t get over the inane lyrics: “Shannen Doherty, Shannen Doherty / You’re in my head. Shannen Doherty, Shannen Doherty / I like bread.” I wish I were making this up.

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But the crate digging, which I also did in physical record stores, was always worth it when you found your new favorite band or heard the summer’s hit track long before any of your friends. I was introduced to so many artists, many of whom I still turn to today. Hot Chip, Sea Wolf, Fleet Foxes, to name a few. It taught me to always give music a chance, no matter how ugly the art or how crusty the jewel case. Usually, you can listen to the song up to when the vocals kick in before giving up or listening longer. By then, you usually know if you’re gonna hate it or not.

I still devour new music this way, clocking a daily average of four hours of tunes familiar and novel. It helps me write and focus and relax and otherwise temper my mood throughout the day. I’m always looking for new artists to try. And I hope I always consume — I hate that word, but there it is — music this way, instead of becoming a curmudgeon who only appreciates the tunes from their youth and thinks anything modern is trash. If you think that, you aren’t digging deep enough. 

The only thing I can think of that’s worse than getting stuck on Greatest Hits or Top 40 is pushing a button and generating “infinite personalized music” with no human influence. It bores the sh*t out of me. It’s not just the lack of discovery, though that is critical, maybe because it scratches those deep primal hunter/gatherer itches. It’s more about the lack of anything personal behind the music. No history, no struggle, no catharsis, no exploration, no humanity. I listen to music because it’s flawed, raw and human, not just noise to fill my day. I have no doubt AI music will keep improving, at least to a point, but I predict few people who actually love music are going to listen that way because it has lost its essence.

 

Yes, I have streamed plenty of AI music on YouTube, often unintentionally when the vaporwave or atmospheric DnB mix I’m vibing to autoplays some slop channel. I can almost always tell when it’s generated. There’s a flatness, like an echo of a song you heard a long time ago, something better. It puts me to sleep and I inevitably switch it off. Maybe it’s gotten better lately. But I still think I’d notice. At any rate, I’d never seek it out.

As a child I was once gifted a “custom” cassette tape with songs “written for me.” Every single track on the album was centered around “Troy,” with my name mentioned as often as possible. I listened to that thing over and over again, until I spilled a bottle of soap in my tape deck and ruined it. But anyway, none of the songs were actually produced with me in mind. It was made by a company called Kidselebration that in 1986 made “personalized” cassette tapes like these for a whole boatload of names. The songs never changed, someone just dubbed in a different name into the song for Kyle, Sarah, Robert, etc. I can’t imagine how much friggin’ work this must have been before Pro Tools, but it was probably just the ‘80s equivalent of a lot of cut-and-paste.

You can listen to the one for “Jessica” here if you really want to. Every time they say “Insert Name,” it sounds totally awkward and weird. But even as a kid, I suspected on some level that this tape wasn’t really for me specifically. Something always felt off. If infinite personalized AI music doesn’t give people the same vibe, maybe they’re not listening hard enough. And please, don’t send me your robot music. Send me anything else.

The post Please don’t send me your robot music appeared first on Salon.com.

We created a list of the most notable AI agents that can live in your text messages, from general assistants to agents designed for families, travel, and work.

Recently, between medical appointments, I ended up at a grain-bowl-and-salad place in a suburban strip mall, the kind of sleek fast-casual restaurant that looks a little like an Apple Store decided to start serving brown rice and green goddess dressing. There were a few customers in scrubs and two self-order kiosks, both broken. The menu wasn’t posted anywhere else, except via a QR code printed on the back of several glossy takeout menus behind the register, which the cashier repeatedly warned us not to take because they only had a few.

The bowls themselves were fine. Watching them come together was more memorable: the cashier held each plastic container practically at arm’s length as he scooped, two vapes clacking around in his apron pocket, with the air of someone completing a task wholly unrelated to food. What arrived cost about $14 and tasted perfectly acceptable. It was also, somehow, shockingly anonymous.

There’s a word for this feeling now: slop. 

It describes several overlapping anxieties about modern restaurant food, but its prehistory belongs, at least partly, to the ghost kitchen.

In March 2020, as dining rooms shut down, Chuck E. Cheese launched Pasqually’s Pizza & Wings, a delivery-only brand operating out of its existing kitchens. The name was technically an Easter egg: Pasqually P. Pieplate is the chef in Chuck E. Cheese’s animatronic house band. 

To anyone not conversant in Chuck E. Cheese lore, though, Pasqually’s looked on Grubhub like a new pizza-and-wings joint. CEC maintained that the pizza itself was different — thicker crust, more sauce — but plenty of customers still felt tricked when they realized the restaurant at the address they’d ordered from was, in fact, Chuck E. Cheese.

The revelation inspired a small genre of internet consumer detective work. “Now I look up the addresses of places on delivery apps before I try something ‘new,’” one Reddit user wrote after discovering that an apparent new Indian restaurant was another business operating under a second name. Elsewhere, someone warned that “Pasquale’s Pizza and Wings on delivery is just Chucky Cheese.” In the same thread, though, came the rebuttal: there were good ghost kitchens. You were simply ordering from the lousy ones.

That argument feels almost quaint now. Ghost kitchens asked diners to accept a peculiar new distance between the restaurant being advertised and the human reality of the meal. What diners surrendered wasn’t necessarily quality so much as a little hospitality, a little transparency and, increasingly, the expectation that a restaurant represented somebody’s particular idea of what a restaurant should be.

From there, the abstraction moved onto the plate.

The “slop bowl” became internet shorthand for the familiar fast-casual mash-up — grains, greens, globally inspired protein, sauce, perhaps an avocado surcharge — assembled with the logic of a cafeteria line and an over-$10 price. The joke has always contained some affection; people like these bowls because they are easy, reliable and customizable. But the name also catches their underlying sameness. There is a reason so much online energy is devoted to “hacking” them: swapping sauces, doubling proteins, gaming the system in hopes of coaxing a little more pleasure from something designed, above all, to be frictionless.

And now the same aesthetic has escaped the bowl. AI slop has begun appearing on restaurant menus, signs and advertisements, offering food imagery that looks optimized for appetite without necessarily resembling anything a person could cook. My digital feed is littered with truly uncanny generated sandwiches, but I’ve only encountered a few in the wild: outside a cafe, a poster for a coffee drink topped with marshmallow “pearls” so perfectly round and iridescent that they looked less edible than cultured in a lab; on the train, hamburger ads where the meat resembled slabs of smooth, steak-rippled marble. The images have the visual grammar of food photography without much evidence that food has ever been involved.

Diners, meanwhile, are already expressing an aversion to the whole thing. Late last year, CNN’s Jordan Valinsky noted that Cava, Chipotle and Sweetgreen — “the big three slop slingers” — were all reporting softer business among younger customers, particularly those between 25 and 35. Some of that was straightforward economics. On Chipotle’s final earnings call of 2025, CEO Scott Boatwright said younger customers weren’t defecting to another chain so much as returning to the grocery store. “They feel the pinch,” he told analysts, “and we feel the pullback.”

Yet alongside that financial retreat, though, there is a more aesthetic refusal taking shape. In one food group I follow, posts about AI restaurant marketing increasingly read like miniature boycott pledges. “If you use AI to advertise your restaurant, market, or anything else,” one person wrote, “I will know that you don’t care about food or the planet and I will never ever patronize your business.” Another was more prescriptive: “Take pictures of your food. Spend a little time and effort to make your own flyer.” 

The complaint isn’t merely that the pictures are creepy. Diners are reading them as evidence: if a restaurant cannot be bothered to photograph its own food, hire an artist or make an ugly little flyer itself, what exactly is being communicated about the care happening elsewhere? 

That inference may not always be fair. Restaurant margins are brutal, and a generated image costs less than a photo shoot. But fairness is almost beside the point. Once diners begin treating evidence of human effort as part of the product, efficiency itself can start looking suspicious.

Which may explain the newest addition to the slop lexicon: PE, or private-equity, slop. The term is less a description of any particular food than a prediction about what happens when the people optimizing a restaurant become increasingly distant from the people cooking in it.

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Consider Los Tacos No. 1. The New York taco shop opened in 2013, earned a devoted following for its al pastor and handmade tortillas, and eventually grew to nine locations. As The Guardian reported, when it announced this September that it had taken an undisclosed investment from private-equity firm TSG Consumer to pursue what a press release called “thoughtful, founder-led growth,” customers immediately began writing its obituary. Social posts predicted “the beginning of the end,” along with smaller portions and worse food. The response became so intense that Los Tacos’ founders issued a reassurance that sounded almost like parody: “No, we’re not going to start charging extra for guac. We’re not switching to horse meat. And no, we’re definitely not messing with the tacos.”

The tacos had not, at that point, been messed with. That’s what makes the reaction interesting. “PE slop” names an anticipatory fear: that somewhere down the line, somebody who has never stood over the grill will notice that a particular ingredient costs slightly more, or a particular process takes slightly longer, and ask whether anyone would really notice if it disappeared.

My colleague Alex Galbraith recently argued that food may be where consumers most easily recognize the otherwise abstract mechanics of private equity. Newspapers can become thinner and health care more Byzantine in ways that are difficult to trace back to an investment firm. Lunch is more intimate. 

Galbraith points to a recent interview with comedian Stavros Halkias who summed it up like this: “Everybody understands that Wendy’s has gotten s**ttier. The spicy chicken sandwich now uses shredded lettuce. Right there, that is private equity. That is someone saying ‘We don’t want a fresh head of lettuce that costs more money. So, we’re going to give you bagged sh**ty lettuce. I know in the grand scheme of things it’s not a big deal, but people will notice.”

I don’t think all these things are “slop” because they’re necessarily bad. I think we’ve reached a point of saturation with food that feels devoid of human authorship. For years, restaurants have been encouraged to become frictionless, scalable, customizable and infinitely replicable. Now diners seem increasingly sensitive to the moment when all that optimization scrubs away specificity.

The opposite of slop isn’t necessarily handmade, independent, expensive or even particularly beautiful. A chain can have it; a bowl can have it; a restaurant backed by investors can have it. It’s simply the sense that something looks and tastes the way it does because somewhere along the line a person said, I like it this way, so I make it this way.

This isn’t an argument for turning every anonymous strip mall back into a village of idiosyncratic mom-and-pop shops. It’s something smaller, and probably more achievable. After years of food designed to work everywhere for everyone, diners may simply be hungry again for evidence that somebody meant it.

The post We’re over restaurant slop appeared first on Salon.com.

Last Wednesday, the head of an AI tech company casually announced, in a long-winded post on X, a discovery that, if true, would represent a major breakthrough in biomedical research. Dario Amodei, CEO of Anthropic, wrote that his company’s large language model Claude had found “a molecular machine that we suspect could represent a new gene editing mechanism.” 

So what does this “molecular machine” actually do? No one is entirely sure yet. But that hasn’t stopped tech bros from already upholding it as a new version of CRISPR, the enzyme-wielding tool that cuts up DNA like nobody’s business, sparking a revolution in ultra-precise genetic modification that has spanned research in everything from agriculture to cancer therapy. It’s no surprise its discoverers earned a Nobel Prize in Chemistry. If an AI program really just made a similar discovery, it would be big news.

Indeed, Amodei goes on to say that this finding could be a step toward developing cures for most diseases in five to 10 years. The company’s press release goes into more detail, but basically says that Claude was prompted to search through a massive database of DNA sequences for reverse transcriptases, enzymes that copy RNA into DNA. “After 21 hours spent searching this data by roughly 950 agents using 210 million tokens, one of the agents spotted something remarkable: a repeating pattern of DNA sequences that occurs next to the gene for an odd-looking RT,” the statement reads. Except that nothing about that is so “remarkable,” at least according to numerous people who study and work in this field.

“It is too soon to say that Claude — or the team of human researchers involved has discovered a ‘new CRISPR,’” Dimitri Perrin, an associate professor at the Queensland University of Technology, writes in The Conversation. He goes on to emphasize that what Claude found — a previously uncharacterized enzyme system found in viruses that infect bacteria — isn’t necessarily going to be useful. More research is needed, but Perrin explains that for now, the discovery is “CRISPR-like in its architecture, but there is no evidence that it is CRISPR-like in its function.”

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“Claude’s work isn’t even close to being in the same league as DeepMind’s AlphaFold system for predicting protein structure, which is proving to be truly transformative,” Michael Le Page, a senior reporter at New Scientist, wrote. Social media exploded with other examples of people dunking on Anthropic’s PR, with Simon Maechling, a PhD chemist, writing on X, “Claude discovered something in biology. Nobody knows what it does. But we already have the press release. … Finding something interesting isn’t the same as understanding it. Understanding it isn’t the same as showing it works. And showing it works isn’t the same as making it useful.”

Perhaps AI researcher Timnit Gebru summarized it best: “Please see what experts in this field are saying about this ‘discovery’ and not these scammers or press stenographers. This hype DDOS from them isn’t going to stop any time soon and we’ve seen how the mainstream media is doing press-release-as-a-service at this point.”

So it seems like Anthropic is making some pretty bold claims over something that is mildly cool and worth investigating, but at this point, also seems unlikely to revolutionize medicine or science. Why does this matter? A tech company making extreme claims is far from new. Big deal. But contrast all this hype (not to mention the energy spent debunking it) with the buzz just a few weeks ago about how, in just a few years, AI will supposedly gain sentience and kill off humanity. Consider how Anthropic CEO’s Amodei is among those pushing such a narrative, including warning that his company’s tools carry a risk of being used for cyberattacks or terrorism, including developing deadly viruses. Taken together, this presents a false dichotomy: AI will either end disease and suffering or inflict it in untold measure. Might there be a third option?

For anyone who buys the AI spiel, it’s a tool with boundless power. For now, however, the tech companies still rely on an old-fashioned kind of power offered by the state, which is precisely why other tech CEOs were seen sucking up to Chinese President Xi Jinping during his recent U.S. vacation. Amodei missed meeting Xi, for what it’s worth, but had a private dinner with President Donald Trump late Sunday night and later this week joined other tech leaders for a luncheon hosted by Trump and House Speaker Mike Johnson. There — joined by Nvidia CEO Jensen Huang, Tesla and SpaceX CEO Elon Musk, Meta’s Mark Zuckerberg and others — the president signed a “morally binding” artificial intelligence document, which sounds promising, until you hear Trump repeatedly tell reporters that tech companies can supervise themselves. “The self-regulation is very important,” Trump said. The document signed seems to have zero enforcement or legal mechanisms, so in this context, it appears “morally binding” just means “self-policing.” 

 

It’s no mystery why the president — heavily invested in the AI industry as he acridly dismisses any notion of regulation — is cozy with the idea of AI’s alleged abilities. In his latest effort to sell the American public on the coming “golden age” of AI (of course Trump would use that phrase), on Monday the Trump administration both launched America.gov, an AI chatbot powered by Google’s Gemini and Elon Musk’s Grok, and signed an executive order to rename AI “super intelligence.”

As Gebru observed, the grift has no end. All the more reason to pour cold water on outrageous claims about flagging little enzymes in huge databases. (Let’s avoid anthropomorphizing these programs by using the verb “discover.”) The goal of Anthropic’s AI propaganda — because that’s what it is — is to get most people skimming past the headlines to only catch “AI finds new CRISPR” and think a cure for cancer and world peace are right around the corner. All we have to do is hand the keys and all our money to Silicon Valley. Whether it’s utopia or dystopia, that’s the pitch: cede control of this tech to the billionaires in charge. In that sense, blindly swallowing AI’s positive hype can be as dangerous as its alleged existential risks.

The post AI hype promises miracles. That’s as risky as doomsday talk appeared first on Salon.com.

As I noted a week ago, we can’t know whether the current polls will be predictive of the November election results. But the polls themselves are at least speaking with a clear voice. I want to note two things that appear to be moving in unison: consumer confidence and the Republican position on the national generic ballot.

Here’s the trend line from Nate Silver’s Silver Bulletin …