BEIJING (ANP) - Novak Djokovic heeft dinsdag voor de zevende keer de China Open gewonnen. De 39-jarige Serviër zag zijn Australische tegenstander Alex De Minaur aan het begin van de tweede set opgeven. Djokovic stond met 7-6 (3) 0-1 voor.
Djokovic won het toernooi bij al zijn zes eerdere deelnames tussen 2009 en 2015. Djokovic is de huidige nummer 11 van de wereldranglijst.
LONDEN (ANP) - De Britse politie heeft een nieuwe verdachte aangehouden in verband met de verdachte busjes bij de luchtmachtbasis RAF Fairford. Het gaat om een 22-jarige Brit, meldt de antiterreurpolitie. Hij wordt verdacht van het voorbereiden van terreurdaden. Eerder werden zes anderen aangehouden. Zij zijn op borgtocht vrijgelaten.
De 22-jarige man is volgens de politie deze dinsdag opgepakt in de deelgemeente Westminster, waar ook het bestuurlijke en politieke centrum van Londen ligt. Er is een doorzoeking geweest in "hetzelfde gebied".
Wie de verdachte is of wat hij gedaan zou hebben, vermeldt de politie niet. "Dit blijft een lopend onderzoek en onze teams van specialisten blijven verschillende onderzoekslijnen naar de omstandigheden rond de gebeurtenissen bij RAF Fairford uitzoeken", zegt Vicki Evans van de politie-eenheid. Over het incident is nog veel onduidelijk.
Vijf Britten werden op 27 september opgepakt bij de basis. Een zesde Brits-Iraanse man enkele dagen later.
AMSTERDAM (ANP) - In de eregalerij van het Rijksmuseum in Amsterdam zijn van 9 oktober tot en met 17 januari twee topstukken te zien van Willem de Kooning. Woman I (1950-1952) en Woman and Bicycle (1952-1953) hangen daar in een eigen kabinet, vlak naast Rembrandts Nachtwacht. De werken zijn een extra eerbetoon naast de overzichtstentoonstelling die het museum wijdt aan de Nederlands-Amerikaanse schilder.
In de eregalerij hangen de grote meesters van de Nederlandse schilderkunst. De Kooning past daar uitstekend tussen, zegt museumdirecteur Taco Dibbits. "De Kooning is van Nederlandse afkomst en staat in een lange traditie van Hollandse meesters."
De tentoonstelling heet Willem de Kooning at work. Daarmee presenteert het Rijksmuseum voor het eerst in Nederland een groot overzicht van De Koonings getekende oeuvre en een aantal van zijn beroemdste schilderijen en sculpturen. Er zijn meer dan 120 werken te zien.
PC, PS5, Switch 2; Wych Elm Games, Team 17
Abandoned shops, ruined apartment buildings and rotting sewer networks make up a dark landscape in which you play a private eye searching for a missing singer-songwriter
In a weird deserted town miles from anywhere, a troubled detective searches for a missing musician and the girl he may or may not have murdered. It could be a Silent Hill game or a lost David Lynch movie from the 1990s – in fact, it’s neither. And also both. If that whets your appetite, stick around, there’s plenty more to come.
Developed by Scandinavian studio Wych Elm Games, Silver Pines is a dark Metroidvania-style adventure, where you play as shambling private eye, Red Walker, exploring a 2D universe of abandoned shops, ruined apartment buildings and rotting sewer networks. Officially, everyone has left because of an incoming storm, but very quickly you learn that something much darker is afoot. Someone has hired you to find singer-songwriter Eddie Velvet, but you don’t know why; your only contact with your client is via the payphones dotted around town, where you can also save your progress – as long as you have a dollar to pay for the call. Each location is filled with clues and puzzles – a weird newspaper story pinned to the wall, a strange statue that needs a missing piece – and through these artefacts you unlock new rooms and descend further into the mystery.
Continue reading...What, exactly, about the drink is so distracting? The viral debate raises bigger questions about who defines ‘professionalism’
The great iced coffee debate of 2026 is the latest submission to the young-people-just-don’t-get-it discourse and, of course, it’s as polarizing as ever.
Recruiters say you shouldn’t bring iced coffee to interviews, while young people are (rightly) asking: what’s the big deal? It’s one of those conversations that makes me cringe, given just how eagerly it springs up from the generational divide plaguing mainstream culture. And as usual, gen Z are cast as the entitled morons who want to live life with no rules or responsibilities, all to the detriment of the millennials and gen X-ers who have to deal with them.
Tayo Bero is a Guardian US columnist
Continue reading...Firms working on reproducing compounds without need for repeated harvesting but conservationists are sceptical
Many of the world’s most expensive perfumes begin with a wounded tree. When some Aquilaria trees are damaged, they produce a dark, fragrant resin that becomes agarwood, or oudh – an ingredient so valuable that wild trees have been illegally felled in its pursuit.
The result has devastated wild Aquilaria populations. But what if perfumers could create the smell without cutting down the tree?
Continue reading...Metal band Gwar host this instalment of the horror series, which serves up darkly humorous movie morsels that would struggle to frighten a toddler
The latest in the long-running horror-feature series is, as per usual, a decidedly diverse ragbag of shorts, strung together with the thinnest of connective tissue. The theme this go-round seems to be music and sound, so it sort of makes sense that hosting duties for the interstitial bits fall to the goofy metal band Gwar, its assorted members met here cracking Halloween dad jokes in their trademark extravagant outfits.
The five mini movies vary significantly in length as well as quality. Flying Lotus’s stop-motion exercise Another Cabin posits a young boy in a rural cabin living with a mean old grannie who tries to push him forward when a tentacled demon tears the roof of the house in search of a snack. The characters’ resemblance to the cast of early 2000s series The PJs is slightly jarring, given this is such a different register, but the brevity works in its favour. In contrast Renee Zhan’s Dance, Dance, Dance, Dance, the opener, drags on a bit, but has a reasonable gags-to-gore ratio in its tale of murderous puppets taking revenge on visiting studio execs who would dare to “reimagine” some ageing IP best left dormant. The funniest gag is the bright major-scale title song the puppets (designed by Jim Henson’s Creature Shop) sing about how all things must die.
Continue reading...Counter-terrorism policing says 22-year-old detained in London on suspicion of terrorism offences
A seventh man has been arrested in London on suspicion of terrorism offences related to the suspected RAF Fairford terrorism plot, police have said.
The 22-year-old British national was arrested in Westminster, central London, on suspicion of preparation of terrorist acts under section 5 of the Terrorism Act 2006, counter-terrorism policing said.
Continue reading...Students, staff and parents march in cities including Marseille and Lyon, while up to 40,000 expected in Paris
Nearly 90,000 students, staff and parents have taken to the streets in cities across France as protesters blockaded hundreds of high schools in a nationwide day of action against long hours, missing teachers and crumbling classrooms.
The French interior ministry said 86,000 people took part in marches in cities including Marseille, Nantes and Lyon on Tuesday morning, with up to 40,000 more expected to join the largest demonstration, in Paris, later in the day.
Continue reading...The Guardian’s picture editors select photographs from around the world
Continue reading...World Health Organization detects no sign of further outbreak since Darya Shipilova died last week
The World Health Organization has said the risk of an epidemic in Russia is lowafter the sudden death of a lab technician who worked at a plague research institute in Siberia.
Darya Shipilova, who was 28, died last week, two days after falling ill. Russian media reports suggested she may have become infected after an accident at her workplace, where dangerous pathogens are kept and studied.
Continue reading...
In publieke situaties zijn mensen minder geneigd zich op een niet-talige manier te uiten. Zuchten en kreunen worden niet gewaardeerd. En kokhalzen al helemaal niet.
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Voedselzekerheid gaat verder dan een noodpakket voor acht dagen. Kijk naar het „talent” van een gebied, en pas daar je productie op aan, zegt Jannemarie de Jonge. „Meer plantaardig en minder dieren is een no brainer”.
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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.
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 to 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 of 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/
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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/
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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
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Voting only gets you so far https://www.garbageday.email/p/voting-only-gets-you-so-far
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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
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
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"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).
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"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).
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"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).
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"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).
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"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.
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"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
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"Unauthorized Bread": a middle-grades graphic novel adapted from my novella about refugees, toasters and DRM, FirstSecond, April 20, 2027
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"Enshittification, Why Everything Suddenly Got Worse and What to Do About It" (the graphic novel), Firstsecond, 2027
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"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: 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.
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A Little Brother short story about DIY insulin PLANNING
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