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    <title>The Richest Country Is Pretty Mid Now - YouTube</title>
    <dc:date>2026-06-28T22:50:35+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=4FZy1lBNykA</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[""Leveragism" is a term I made up, and it describes what the American economy is increasingly heading towards. As you will see, this is really bad news. 

0:00 - About Capitalism
3:53 - Political Leverage
6:01 - The Gold Trap
8:00 - The Rug Pull
11:34 - The Bond Trap
15:23 - Classical Leverage
19:00 - Debts R' Us
20:32 - AI Circlejerk
22:45 - My Awesome Trip To Israel 
29:09 - Authoritarian Leverage
35:01 - Siphoning Your 401K
39:02 - Time and the Smokescreen of Numbers"]]></description>
<dc:subject>bennjordan leveragism capitalism internet online google gemini ai artificialintelligence aibubble journalism rugpulls authoritarianism elonmusk donaldtrump spacex israel gaza anarchism economics economy integrity finance ip intellectualproperty well-being wellbeing precarity gold debt politics us bigtech spotify suno streaming law legal happiness fuckyoumoney inequality money labor wealth laborreflexivity growth borders border privateequity libertarianism tescreal nerdreich peterthiel billackman rulingclass transhumanism extropianism singularitarianism singularity xenophobia inflation extraction rationalism oligarchy larryellison markzuckerberg jeffbezos effectivealtruism longtermism governance government democracy poverty work police policing iranwar austerity retirement maga trumpism muskism wallstreet stockmarket nasdaq indexfunds 401k leverage power policy autonomy obesity surveillance survival fear ice bronnieware life living courage death guatemala coca-cola unions wisdom pollution environment humanrigh</dc:subject>
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    <title>The Algorithmic Order</title>
    <dc:date>2026-06-27T06:22:48+00:00</dc:date>
    <link>https://2ndbreakfast.audreywatters.com/the-algorithmic-order/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The history of education technology is inseparable from the history of standardized testing."]]></description>
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<item rdf:about="https://wwnorton.com/books/9780393881943/">
    <title>Coding Kids: Big Tech's Battle to Remake Public Schools, by Natasha Singer (2026) | W. W. Norton &amp; Company</title>
    <dc:date>2026-06-27T04:38:20+00:00</dc:date>
    <link>https://wwnorton.com/books/9780393881943/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The inside story of how Big Tech catalyzed, co-opted, and ultimately came to capture computer science and AI education in America.

Fourth graders doing Google-branded coding lessons. Amazon schooling seventh graders on its warehouse robots. Advanced Placement computing courses from Microsoft and Apple. Many educators and parents would object if Exxon wrote their school’s climate curriculum—or if schools assigned nutrition lessons from Coca-Cola and McDonald’s. Yet today, tech giants influence nearly every step of the education supply chain. They provide the classroom devices and software many students use to do assignments. They sell schools on the latest artificial intelligence tools. And increasingly, tech companies are launching their own corporate-branded school curricula, shaping how and what millions of children learn.

In recent years, the tech industry has helped spread computer science and AI education in schools at astonishing speed and scale. In Coding Kids, award-winning New York Times journalist Natasha Singer draws on a decade of reporting to reveal how tech titans used the promise of coding (high-paying jobs! change the world!) to weave rosy industry visions of technology into the very fabric of American education, sometimes sidelining crucial ideas like civics and critical thinking. Along the way, Singer takes readers through the powerful playbook Big Tech used to scale coding lessons nationwide. Then she shows readers how tech companies are now applying the same playbook to mainstream their AI tools in schools.

A revelatory account of the powerful forces shaping education and our kids’ futures, Coding Kids also offers hope. It tells the compelling stories of pioneering teachers fighting for a broader vision of tech education—one that not only teaches kids algorithms and app-making, but also asks students to grapple with the societal impacts of tech giants and their disruptive digital tools."]]></description>
<dc:subject>edtech bigtech schools schooling 2026 google apple computing computers chromebooks microsoft ai artificialintelligence llms natashasinger coding algorithms</dc:subject>
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<item rdf:about="https://davekarpf.substack.com/p/the-gravitational-force-of-tech-money">
    <title>The Gravitational Force of Tech Money - by Dave Karpf</title>
    <dc:date>2026-06-26T07:19:52+00:00</dc:date>
    <link>https://davekarpf.substack.com/p/the-gravitational-force-of-tech-money</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The main story of the post-techlash years has been too few people with too much capital"]]></description>
<dc:subject>davekarpf 2026 technology inequality capital elonmiusk billionaires siliconvalley tesla spacex marcandreessen democracy bigtech google amazon meta facebook comcast bankofamerica donaldtrump joebiden economics economy billackman peterthiel sambankman-fried ronanfarrow mattlevine ryanmac davidfahrenthold wealth nealstephenson</dc:subject>
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<item rdf:about="https://www.businessinsider.com/ai-social-scene-curated-offline-events-dinner-parties-2026-6">
    <title>AI's Social Scene Is Shifting to Curated Offline Events, Dinner Parties - Business Insider</title>
    <dc:date>2026-06-26T01:15:39+00:00</dc:date>
    <link>https://www.businessinsider.com/ai-social-scene-curated-offline-events-dinner-parties-2026-6</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[[In which the AI-saturated tech space is slowly rejecting its own dogfood of optimization, scalability, and slop. They seem to be slowly re-inventing the humanities and liberal arts that they skipped and derided.]

"If "taste" is the buzzword in the AI world right now, then IRL events have become the best way to demonstrate it.

As AI becomes more competitive and taste — the idea of having superior aesthetic judgment — emerges as a key differentiator, AI companies and young founders are hosting intimate, curated gatherings — often dinner parties — to cultivate cool and build real-world communities.

<blockquote>Hosting an intimate dinner in sf for lore builders.

    Founders, narrative architects, writers, world builders. Humans at the intersection of storytelling x culture x craft x storytelling x philosophy x design.

    Keeping it to <10. Who should be in the room? 🫶
    — Joumana (@JoumanaElomar) June 23, 2026 [https://x.com/JoumanaElomar/status/2069509402437222482 ]</blockquote>

Many of these curated events follow a similar blueprint: a promo that looks like an A24 film poster and grainy, film-like photos that make it feel more like a 90s-era house party than a tech founders' event.

"I think trusted (human) curation is so important now, even more than ever," said Michelle Fang, who leads Stripe Startups, a program offering financial support and resources to early-stage, venture-backed companies, and has a weekly newsletter that rounds up in-person tech events in San Francisco.

Fang said that when she first started the newsletter in 2023, she posted an average of 20 to 30 in-person events a week. That number has now risen to 70 to 80 a week.

"There's been a noticeable shift in both the frequency and types of events happening in SF, especially over the past year," she said.

AI has accelerated this trend dramatically, she said, as the AI boom brings an influx of talent who want to establish their community in the city.

While some of the events Fang has listed are traditional building workshops and hackathons, others include Pilates classes, peptide tasting parties — the latest self-optimization craze — and "intentionally curated" dinners.

It's a vibe shift from the large happy hours and networking events that defined post-pandemic tech socializing, said Fang. These smaller events don't require a big budget or venue, and with the speed of AI growth, people want to make sense of new concepts and the changes happening in real time, she said.

[image: "Dinner table with bowls of sushi and edamame at an event hosted by coworking and tech events startup Verci's / Verci, a coworking space and events startup, hosts monthly dinners and workshops for members.  Ami Yoshimura/Verci"]

'Taste is a new core skill'

The taste conversation kicked off earlier this year when Y Combinator cofounder Paul Graham wrote in a post on X that, as AI democratizes building, "taste will become even more important."

Two days later, OpenAI President Greg Brockman cemented the catchphrase on X, writing that "Taste is a new core skill." Since then, it's led the tech world to hyperfocus on AI companies and founders who are winning the taste battle.

Alongside the taste discourse, being offline has become a status symbol. Having the ability to de-digitalize is seen as a luxury and a way to connect with people more authentically, with in-person events being a means to achieve this, especially for those whose working lives already revolve around AI.

<blockquote>peak bengaluru and bangerlore pic.twitter.com/1imEhjhCBX
    — prerna (@Prerrrrna_) June 7, 2026 [https://x.com/Prerrrrna_/status/2063545613632037129 ]</blockquote>

An event "only for hot people and nerds" in Bangalore, which appeared to be in collaboration with the early-stage Bangalore-based consumer tech company Faff, made the rounds on X earlier this month. The vibe is artfully arranged cheese boards, trendy cocktail menus (with AI puns), and grainy photos.

Ami Yoshimura, the 23-year-old cofounder of Verci, a members club and coworking space in New York, hosts events such as rooftop parties and multi-day retreats for founders and creatives. "Relationships, aesthetics, and telling a story" have become crucial ways to stand out in the hyper-competitive AI industry, he said.
Small parties, big bucks

It's not just San Francisco that is seeing this event boom.

<blockquote>new york tech week highlights:1. went blind into an event hosted by @join_ef and successfully met a group of really cool people with 0 degrees of mutual connection2. met/made some really good friends from url ➡️ irl shoutout fonzi and corgi team3. ended off the week with a… pic.twitter.com/CA3h0mwmLe
    — sara kong (@saraknggg) June 8, 2026 [https://x.com/saraknggg/status/2064047927702782454 *]</blockquote>

Katia Ameri, a partner at A16z who spearheads Tech Week in San Francisco, LA, and New York City, wrote on X last month that New York was so far the largest Tech Week in history by events and attendees. The LA and San Francisco equivalents are coming up later this year.

Eliza Wu, cofounder of Corner, a social mapping app that describes itself as "Google but social," wrote in a post on X that there were over 600 RSVPs for a panel she was hosting at New York Tech Week.

Leading AI companies are also taking note. In April, Anthropic posted a brand events lead role in San Francisco, with a salary of up to $400,000.

There are four open marketing events positions at Anthropic, while OpenAI has two open positions for events, commanding over $200,000 salaries with options to gain equity too.

<blockquote>Anthropic is paying up to $400,000 a year for an events role.They're looking for someone to own the execution of brand experiences that translate Anthropic's values into physical moments.This person will produce everything from intimate thought-leadership gatherings to… pic.twitter.com/SWvmSarclY
    — Andrew Yeung (@andruyeung) April 26, 2026 [https://x.com/andruyeung/status/2048545188608364593 ** (archived: https://www.are.na/block/47316282 )]</blockquote>

Andrew Yeung, an ex-Google and Meta product lead turned event host and angel investor, wrote on X in response to the job advert that it shows Anthropic understands that "they need to create visceral, unforgettable IRL experiences that make complex technology feel accessible and human."

"The massive opportunity now is offline, analog, in-person," he said.

But while the taste that goes into hosting a party is human, we are living in an AI world — and as with your job applications, an AI screener might still be standing between you and an invitation.

Wu, the cofounder who hosted a New York Tech Week event with 600 RSVPs, said she turned to Claude to winnow down her guest list.

She said she prompted the chatbot to scan through potential attendees' social posts to identify "markers of excellence" and to suss out the "quality of their thoughts."

With the help of Claude, only 300 people made the cut."

[* full text of https://x.com/saraknggg/status/2064047927702782454:

<blockquote>new york tech week highlights:

1. went blind into an event hosted by @join_ef and successfully met a group of really cool people with 0 degrees of mutual connection
2. met/made some really good friends from url ➡️ irl shoutout fonzi and corgi team
3. ended off the week with a bang at vega (shoutout ben & maddie)

i think when it boils down to WHAT constitutes a good event, it varies based off what your specific persona is trying to get out of it.

for me, events with well-catered hospitality that are more intimate (without just randomly throwing people together sloppily) call out more to me because you make more solidified relationships. 

likewise, it’s good to put an online face to a name because that alone can unlock so much trust and future opportunities.

see you soon nyc!</blockquote>

** full text of https://x.com/andruyeung/status/2048545188608364593

<blockquote>Anthropic is paying up to $400,000 a year for an events role.

They're looking for someone to own the execution of brand experiences that translate Anthropic's values into physical moments.

This person will produce everything from intimate thought-leadership gatherings to large-scale industry activations.

The top AI research lab in the world recognizes that to cross the chasm and reach everyday consumers, they need to lean into hospitality. They need to create visceral, unforgettable IRL experiences that make complex technology feel accessible and human.

They understand that digital channels are getting increasingly saturated. Every feed is flooded with AI content... every inbox is overflowing.

The massive opportunity now is offline, analog, in-person.

The companies that win in the next decade won't just have the best product but the most emotional in-person presence and the most compelling storytelling.

If you're in events, experiential marketing, or brand activations, this is your moment. The biggest tech companies in the world are betting on you.

[two images of the job posting]</blockquote>]]]></description>
<dc:subject>ai artificialintelligence siliconvalley technology 2026 royashahidi small humanities liberalarts culture taste anthropic claude aislop paulgraham elizawu corner saraking amiyoshimura joumanaelomar michellefang stripestartups social events community aibubble gregbrockman openai status offline online socialmedia internet katiaameri a16z andreessenhorowitz andrewyeung google meta nytechweek sanfrancisco society analog</dc:subject>
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<item rdf:about="https://www.bloodinthemachine.com/p/understanding-the-luddites-in-the">
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<item rdf:about="https://matthewbutterick.com/extinction-level-capitalism.html">
    <title>Matthew Butterick | Extinction-level capitalism</title>
    <dc:date>2026-06-17T10:06:00+00:00</dc:date>
    <link>https://matthewbutterick.com/extinction-level-capitalism.html</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Putting it all together: Among AI risks, we should take more seri­ously the poten­tial conse­quences of AI working as intended. AI is a capi­talist instru­ment. Its prin­cipal func­tion is to concen­trate capital. Its intended mech­a­nism is large-scale labor replace­ment. But it is also inher­ently polit­ical tech­nology. As AI makes it harder for workers to capture value from their labor, they will increas­ingly have to rely on goodies from Big AI, priva­tizing what were once func­tions of govern­ment. If Big AI subsumes the func­tions of workers and govern­ment, both will tend to realign polit­i­cally around Big AI’s inter­ests. What­ever term describes this system, it is not liberal democ­racy as US citi­zens have tradi­tion­ally under­stood it. AI-centered capi­talism risks an extinc­tion of demo­c­ratic possi­bility. It will be America. But it will no longer be Amer­ican."]]></description>
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<item rdf:about="https://www.economist.com/briefing/2026/06/11/forget-the-world-cup-culture-is-becoming-more-fragmented">
    <title>Forget the World Cup. Culture is becoming more fragmented</title>
    <dc:date>2026-06-14T09:36:30+00:00</dc:date>
    <link>https://www.economist.com/briefing/2026/06/11/forget-the-world-cup-culture-is-becoming-more-fragmented</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Farewell to the monoculture"

[archived:
https://archive.is/ulDjw

via:
https://social.ayjay.org/2026/06/13/the-economist-it-might-seem.html ]

"It might seem surprising, in a world of global stars, that the 6m Danes, many of whom are fluent in English, listen mainly to homegrown music. And until fairly recently they did not. In 2019 only five songs in Denmark’s top 20 were in Danish. By last year the figure was 18.

A similar trend is under way in other countries — and in other forms of entertainment. From Asia to the Americas, music charts are increasingly dominated by local sounds. Hollywood television-streaming companies are commissioning more local productions in foreign markets, causing consumption of American shows to fall. Social networks are connecting the whole world, but so far people are mainly using them to consume local content. And as video gaming expands, it too is becoming increasingly tailored to local cultures."

...

"In music, video and interactive entertainment, global tech platforms have made it easier than ever to distribute entertainment around the world. Yet the sheer abundance of content that these platforms have helped to generate means that, more than ever, global audiences are able to assert distinctively local preferences."]]></description>
<dc:subject>culture decentralization 2026 diversity denmark monoculture music language languages tv television film streaming latinamerica nigeria southafrica france germany italy poland willpage chrisdallariva worldcup attention videogames games gaming brazil brasil philippines indonesia thailand norway portugal ireland australia india czechrepublic dubai greece mexico middleeast africaeurope netflix asia larrytanz turkey türkiye southkorea korea christopherhamilton canada alexandregoncalves yeemanmargaretng youtube hindi matthewball xbox microsoft china japan manurosier newzoo garena singapore apple google roblox sensortower fortnite joostvandreunen entertainment</dc:subject>
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</item>
<item rdf:about="https://www.wheresyoured.at/premium-the-silicon-valley-bubble-part-1/">
    <title>Premium: The Silicon Valley Bubble (Part 1)</title>
    <dc:date>2026-06-13T01:52:19+00:00</dc:date>
    <link>https://www.wheresyoured.at/premium-the-silicon-valley-bubble-part-1/</link>
    <dc:creator>robertogreco</dc:creator><dc:subject>2026 edzitron siliconvalley technology ai aibbubble artificialintelligence aihype anthropic opeanai samaltman ipos johncarpenter danielaamodei broadcom google markzuckerberg elonmusk darioamodei llms facebook meta microsoft oracle amazon economics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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</item>
<item rdf:about="https://www.theideasletter.org/essay/content-violation/">
    <title>Content Violation</title>
    <dc:date>2026-06-12T10:01:07+00:00</dc:date>
    <link>https://www.theideasletter.org/essay/content-violation/</link>
    <dc:creator>robertogreco</dc:creator><dc:subject>xioweiwang 2026 pierpaolopasoloni film dante inferno fascism italy italia falsepermissiveness antifascism society politics technology consumerism power ai artificialintelligence llms bytedance grok xai google kling generativeai genai seeedance chatgpt gemini hiltonals salò authoritarianism rolandbarthes siliconvalley technofascism nanobanana brutality mauriceblanchot marquisdesade nietzche baudelaire friction</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:robertogreco/b:2c1677d660f5/</dc:identifier>
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</item>
<item rdf:about="https://www.thebignewsletter.com/p/what-would-it-look-like-if-the-ai">
    <title>What Would It Look Like If the AI Bubble Popped?</title>
    <dc:date>2026-06-12T00:31:48+00:00</dc:date>
    <link>https://www.thebignewsletter.com/p/what-would-it-look-like-if-the-ai</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[[See also:
https://cepr.net/publications/ai-bubble-monitor/ ]]]></description>
<dc:subject>mattstoller ai artificialintelligence aibubble bubbles finance 2008 globalfinancialcrisis greatrecession dotcombubble dotcombust investment stockmarket wallstreet nvidia google meta realestate economics crisis siliconvalley siliconvalleybank banks banking zohranmamdani federalreserve covid-19 coronavirus pandemic regulation deregulation newdeal greatdepression us deanbaker sarahmyserswest spacex ipos larrysummers robertrubin barackobama debt gigeconomy crypto cryptocurrencies jpmorgan florida housing datacenters taiwan southkorea korea consumers consumption wealtheffect privateequity ponzischemes berniemadoff donaldtrump fdic utlities politics openai samaltman amazon microsoft china hankpaulson japan russellsimmons fintech johnkennethgalbraith embezzelment</dc:subject>
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<item rdf:about="https://isaiprofitable.com/">
    <title>Is AI Profitable Yet?</title>
    <dc:date>2026-06-07T20:48:15+00:00</dc:date>
    <link>https://isaiprofitable.com/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Tracking the spend and revenue of frontier AI companies (May 2026)."

...

"WHY I BUILT THIS

Many industry experts and companies claim AI profitability by 2030 is possible, so I wanted to see how close we really are. This site tracks cumulative spend versus revenue across most major AI companies in one place, allowing you to see approximately how much money is flowing into the industry and how far it is from breaking even.

I'll be updating these numbers monthly as new reports and financials drop. Perhaps one day, the big "NO" will become a "YES," and the question will finally be answered :). So far? The big winner is NVIDIA, who is receiving huge profits from the AI boom by positioning itself as the primary chip supplier to the AI sector.

HOW THE NUMBERS WORK

All figures are estimated cumulative totals (all-time). Because most of these companies are private, the numbers aren't exact; instead, they are built from leaked financials, SEC filings, earnings calls, and industry estimates from sources like Bloomberg, the WSJ, The Information, and Epoch AI (all referenced at the bottom). The punchline 'EVERYONE IS BROKE' is intentionally punchy, but shouldn't be taken absolutely literally.

The site includes both, big tech infrastructure spend and pure lab spending, hence why companies like Amazon and Google have huge spend figures compared to the pure labs like OpenAI or Anthropic (big AI investments, not much direct AI revenue yet). It's important to note that the site tracks whether AI investment specifically has broken even yet, not company-wide profitability, hence why companies such as Amazon and Google look so far in the red despite being hugely profitable companies as a whole.

Spend numbers include direct R&D costs, compute, and capital expenditure on AI infrastructure (data centres, chips, and networking). Capex is treated as spend despite having long-term asset value; this is intentional. The framing shows the sheer scale of capital being committed to AI before returns materialise, rather than smoothing it across a depreciation schedule. Indirect AI revenue (E.g. Google Search performance boosted by AI Overviews, or Microsoft Office revenue lifted by Copilot) is excluded because there is no reliable way to attribute what share of those gains AI is actually responsible for. The $/sec counters use current annual burn rates rather than historical averages, to reflect what's happening right now.

Revenue numbers are the trickiest to estimate due to a lot less information on them being readily available. Thus, the revenue figures here are mostly estimated and extrapolated off of ARR figures. Currently, I'd say these numbers are more optimistic than anything, but I will be refining this over time as more information comes out.

DISCLAIMERS

The AI economy is circular: Google funds Anthropic, Anthropic runs on Google Cloud, Amazon funds Anthropic, Microsoft co-invests with OpenAI. This means aggregate industry figures double-count some revenue flows. This site is one person's best effort at an honest picture, not a financial audit. If you have better sources, please reach out, I want to improve this site as much as possible every day :)."]]></description>
<dc:subject>ai artificialintelligence economy money business economics google anthropic circularfunding amazon microsoft openai nvidia deepseek cohereai mistralai xai spacex oracle meta</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://hedgehogreview.com/web-features/thr/posts/twenty-five-years-after-imagined-worlds-what-world-are-we-living-in">
    <title>Twenty Five Years After Imagined Worlds, What World Are We Living In? | THR Web Features | Web Features | The Hedgehog Review</title>
    <dc:date>2026-06-07T00:41:06+00:00</dc:date>
    <link>https://hedgehogreview.com/web-features/thr/posts/twenty-five-years-after-imagined-worlds-what-world-are-we-living-in</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Our surprisingly Napoleonic twenty-first century."

[via: https://hedgehogreview.com/web-features/thr/posts/twenty-five-years-after-imagined-worlds-what-world-are-we-living-in ]

"Erik J. Larson

Erik J. Larson is author of The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do (Harvard University Press, 2021). His forthcoming book is Machineland: How the Myth of Artificial Intelligence Has Shaped the 21st Century So Far.

***

This year marks the twenty-fifth anniversary of famed scientist and author Freeman Dyson’s Imagined Worlds. The book, fashioned from a series of lectures Dyson gave in Jerusalem in 1995, is partly a historical discussion about why technologies—some familiar, like nuclear power, others not, like airships—succeed or fail in what he called a Darwinian process of selection. It’s also an enjoyable piece of futurism. He delighted in the possible, and in Imagined Worlds he speculated boldly about space colonization and an entirely new species evolved from future humans. Dyson was aware of the difficulties of prediction—Imagined Worlds fails to anticipate the rise of the Internet or World Wide Web—yet like H.G. Wells, whom Dyson admired, he leaves us with a sense of having encountered important ideas on a journey led by someone who knows the terrain.  

Imagined Worlds was Dyson’s attempt to explore, as he put it, “the interaction of technology with human affairs.” Like the philosopher of science Thomas Kuhn, he thought science “moved ahead along old directions” until a conceptual revolution. Unlike Kuhn, he thought scientific revolutions could also be driven by tools, by technology. He explained that science and technology entered “Napoleonic” phases, when big institutions with deep pockets set research agendas, and “Tolstoyan” periods, when scientists engage more in tinkering and exploration. Napoleonic was “rigid organization and discipline”; Tolstoyan was “creative chaos and freedom.” Where are we now?

Science and technology today are Napoleonic. Silicon Valley is now Big Tech, the age of garage start-ups being long behind us. Neuroscience is pursued with “exascale” supercomputers and big data. Ditto physics, which also relies on billion-dollar particle accelerators like CERN’s seventeen kilometer long Large Hadron Collider. Consumers—you and me—now provide data to cloud servers, centralized repositories (“cloud” is a misnomer) of massive datasets owned by a relatively small number of governments and organizations. If anyone is “tinkering” with science and technology these days, they are not making the news. We live in Napoleonic times.

The world circa 2000 was not Napoleonic. Little more than two decades ago people were experimenting madly with technologies, business models, and seemingly everything else. Business theorists predicted that industries would demassify and disintermediate, old media gatekeepers would fall, products like encyclopedias would simply disappear, and entire industries would revamp, collapse, reshape, and emerge. Not just the tech world but the entire world seemed to be in a constant state of flux. Venture capital flowed out of a cornucopia. The NASDAQ hit 5,000 in March 2000, though the dot-com bubble burst roughly a year later. 

In the years before that setback, when Imagined Worlds was published, ideas about the future direction of science and technology were diverse, interesting, and abundant. Kevin Kelly, co-founder of Wired magazine, predicted in his 1998 hit New Rules for the New Economy that computer networks would replace the PC as the dominant feature of information technology. He missed the iPhone, understandably, but he saw the future of the Web not as PCs with modems but as a vast network of devices. In essence, he predicted the Internet of Things. Kelly envisioned the coming networked world, the new web, as “ground up,” amounting to a kind of revolution in business and society in which, instead of corporate bosses sitting atop hierarchies executing plans, networks of people would conjure and promote ideas in waves of unpredictable innovation. New Rules for the New Economy reads like a paean to creativity and human freedom, all made possible by liberating society from the old stodgy big business models and yesterday's tech and ideas. Kelly was foretelling a Tolstoyan future, Dyson’s “creative chaos and freedom.”

But surprising to many, big business made a reappearance in the “new economy.” In her now famous 2002 book Technological Revolutions and Financial Capital, business theorist Carlota Perez argued that investment frenzy and stock market crashes precede periods of technology maturation, in which the promise and fruits of a tech revolution become evident. Technology revolutions have an installment phase, she wrote, followed by a deployment phase. Then (if conditions are right) comes a “golden age” marked by growth, employment, and successful consolidation of new businesses and industries. Like Google. And Facebook. Perez's analysis—applicable to earlier golden ages, such as those of steel and electricity, oil, and mass production—accurately predicted what would happen to the Web as it matured in the new century.

What Perez didn't see—or didn't discuss—was the connection between the Napoleonic changes in society and culture and the maturing phases of a tech revolution. She described this calcification in terms of the economy—dwindling profits, unemployment. Dyson described it in terms of the minds of scientists and practitioners—a loss of creative chaos and freedom. A rigidified status quo. Today’s status quo is data-driven AI and Big Tech. Google, Facebook, Instagram, and Twitter. If Kelly’s “new economy” at the turn of the century was a soft drink, the world we inhabit today is a 7-11 Big Gulp. Kelly and others of his ilk assumed networking meant Tolstoyan freedom. Like others, he assumed a “power-to-the-people” movement would derail big corporations and gate keepers and empower Everyday Joes. Big Brother was supposed to disappear, not return on steroids.

Enter the new Napoleonic. Predictably, tech pundits and critics have largely abandoned bottom-up rhetoric for worries about top-down big data collection, housed in server farms owned by big tech companies. Our imagined world has become a kind of bureau of statistics for government and big business (and science), which treat digital data as intelligence and value, not as something connected to billions of humans and their ideas.

We can’t lay the blame on Big Tech alone. The data-centric model was an irresistible path to profits and growth. The Web was bound to mature commercially one way or the other, and large—not small—companies were the likely result.

But the “bureau of statistics” mindset is now a problem. It dominates thinking everywhere, not just in technology businesses aiming for sticky ads and more captive users. Nearly every institution one can point to today, from government to science, media, medicine, insurance, and many others, embraces a centralized, data-capture model requiring massive computing resources and actively downplaying human ingenuity in favor of number crunching and prediction. More troubling perhaps, is the way this has shaped the zeitgeist. Confidence in human smarts and imagination seems at an all-time low. Entire books are written now on how people are, in effect, cognitively biased, limited, and indeed stupid. Given this cultural climate, Dyson’s time of “creative chaos and freedom” seems not only distant but beyond recovery.

Dyson called the Cold War science of the 1950s and 1960s Napoleonic because research occurred mostly in huge companies like RAND and involved teasing out the implications of earlier scientific results from brilliant Tolstoyan tinkerers like Max Plank or Albert Einstein. As in our present time, results were achieved through the investment of huge sums of money, and were typically conservative in scope, reflecting already formed interests and agendas. Much of the money during that time was spent on making larger fission, then fusion bombs. The math was already done. That time and ours both correspond to Perez’s depiction of a fully matured technology revolution showing signs of slowdown and decay. We seem to have wandered into the 1950s again, this time with Web companies instead of IBM and General Motors.

Artificial intelligence has become thoroughly Napoleonic as well. It is a textbook case in calcification. Large, central repositories of data now power ubiquitous artificial intelligence algorithms, which are great for self-navigating drones and automated surveillance cameras but frustratingly poor at basic conversation and other cherished facets of human intelligence. Among other worries, data-centric AI today requires massive amounts of old-fashioned electricity, still largely supplied by conventional fossil fuels. And the central data version of AI is adept at various forms of malfeasance, as everyone now knows. We are increasingly caught in fake news and deep fakes of facial and other unreal images, generated by today’s Big Data AI. Depressingly, the seventy-plus-year program of artificial intelligence is largely equated with centralized data repositories and statistical number crunching today. Younger generations probably don’t know that Napoleonic, Big Data AI is only one approach, one way of conceiving machine intelligence. Big Data AI makes sense in a fully matured technology world, with big players like Google and Facebook. It doesn’t make sense for Tolstoyan tinkerers, who have no access to supercomputers or petabytes of others’ personal data.

Fortunately, the twenty-first century is still young. A little over two decades into the last century was—true—a midway point between two catastrophic wars. But scientists were enjoying Tostoyan freedom. Relativity and then quantum mechanics were discovered, without the supervision or control of big science or big business. Henry Ford was mass producing automobiles, but automobiles would enjoy decades of further Tolstoyan tinkering. Tellingly, computers had not arrived in 1922, and no one anticipated the revolution they would bring. We can only wonder what imagined, and unimagined, worlds still await us in this century.Our surprisingly Napoleonic twenty-first century.

[via: https://hedgehogreview.com/web-features/thr/posts/twenty-five-years-after-imagined-worlds-what-world-are-we-living-in ]

Erik J. Larson

Erik J. Larson is author of The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do (Harvard University Press, 2021). His forthcoming book is Machineland: How the Myth of Artificial Intelligence Has Shaped the 21st Century So Far.



This year marks the twenty-fifth anniversary of famed scientist and author Freeman Dyson’s Imagined Worlds. The book, fashioned from a series of lectures Dyson gave in Jerusalem in 1995, is partly a historical discussion about why technologies—some familiar, like nuclear power, others not, like airships—succeed or fail in what he called a Darwinian process of selection. It’s also an enjoyable piece of futurism. He delighted in the possible, and in Imagined Worlds he speculated boldly about space colonization and an entirely new species evolved from future humans. Dyson was aware of the difficulties of prediction—Imagined Worlds fails to anticipate the rise of the Internet or World Wide Web—yet like H.G. Wells, whom Dyson admired, he leaves us with a sense of having encountered important ideas on a journey led by someone who knows the terrain.  

Imagined Worlds was Dyson’s attempt to explore, as he put it, “the interaction of technology with human affairs.” Like the philosopher of science Thomas Kuhn, he thought science “moved ahead along old directions” until a conceptual revolution. Unlike Kuhn, he thought scientific revolutions could also be driven by tools, by technology. He explained that science and technology entered “Napoleonic” phases, when big institutions with deep pockets set research agendas, and “Tolstoyan” periods, when scientists engage more in tinkering and exploration. Napoleonic was “rigid organization and discipline”; Tolstoyan was “creative chaos and freedom.” Where are we now?

Science and technology today are Napoleonic. Silicon Valley is now Big Tech, the age of garage start-ups being long behind us. Neuroscience is pursued with “exascale” supercomputers and big data. Ditto physics, which also relies on billion-dollar particle accelerators like CERN’s seventeen kilometer long Large Hadron Collider. Consumers—you and me—now provide data to cloud servers, centralized repositories (“cloud” is a misnomer) of massive datasets owned by a relatively small number of governments and organizations. If anyone is “tinkering” with science and technology these days, they are not making the news. We live in Napoleonic times.

The world circa 2000 was not Napoleonic. Little more than two decades ago people were experimenting madly with technologies, business models, and seemingly everything else. Business theorists predicted that industries would demassify and disintermediate, old media gatekeepers would fall, products like encyclopedias would simply disappear, and entire industries would revamp, collapse, reshape, and emerge. Not just the tech world but the entire world seemed to be in a constant state of flux. Venture capital flowed out of a cornucopia. The NASDAQ hit 5,000 in March 2000, though the dot-com bubble burst roughly a year later. 

In the years before that setback, when Imagined Worlds was published, ideas about the future direction of science and technology were diverse, interesting, and abundant. Kevin Kelly, co-founder of Wired magazine, predicted in his 1998 hit New Rules for the New Economy that computer networks would replace the PC as the dominant feature of information technology. He missed the iPhone, understandably, but he saw the future of the Web not as PCs with modems but as a vast network of devices. In essence, he predicted the Internet of Things. Kelly envisioned the coming networked world, the new web, as “ground up,” amounting to a kind of revolution in business and society in which, instead of corporate bosses sitting atop hierarchies executing plans, networks of people would conjure and promote ideas in waves of unpredictable innovation. New Rules for the New Economy reads like a paean to creativity and human freedom, all made possible by liberating society from the old stodgy big business models and yesterday's tech and ideas. Kelly was foretelling a Tolstoyan future, Dyson’s “creative chaos and freedom.”

But surprising to many, big business made a reappearance in the “new economy.” In her now famous 2002 book Technological Revolutions and Financial Capital, business theorist Carlota Perez argued that investment frenzy and stock market crashes precede periods of technology maturation, in which the promise and fruits of a tech revolution become evident. Technology revolutions have an installment phase, she wrote, followed by a deployment phase. Then (if conditions are right) comes a “golden age” marked by growth, employment, and successful consolidation of new businesses and industries. Like Google. And Facebook. Perez's analysis—applicable to earlier golden ages, such as those of steel and electricity, oil, and mass production—accurately predicted what would happen to the Web as it matured in the new century.

What Perez didn't see—or didn't discuss—was the connection between the Napoleonic changes in society and culture and the maturing phases of a tech revolution. She described this calcification in terms of the economy—dwindling profits, unemployment. Dyson described it in terms of the minds of scientists and practitioners—a loss of creative chaos and freedom. A rigidified status quo. Today’s status quo is data-driven AI and Big Tech. Google, Facebook, Instagram, and Twitter. If Kelly’s “new economy” at the turn of the century was a soft drink, the world we inhabit today is a 7-11 Big Gulp. Kelly and others of his ilk assumed networking meant Tolstoyan freedom. Like others, he assumed a “power-to-the-people” movement would derail big corporations and gate keepers and empower Everyday Joes. Big Brother was supposed to disappear, not return on steroids.

Enter the new Napoleonic. Predictably, tech pundits and critics have largely abandoned bottom-up rhetoric for worries about top-down big data collection, housed in server farms owned by big tech companies. Our imagined world has become a kind of bureau of statistics for government and big business (and science), which treat digital data as intelligence and value, not as something connected to billions of humans and their ideas.

We can’t lay the blame on Big Tech alone. The data-centric model was an irresistible path to profits and growth. The Web was bound to mature commercially one way or the other, and large—not small—companies were the likely result.

But the “bureau of statistics” mindset is now a problem. It dominates thinking everywhere, not just in technology businesses aiming for sticky ads and more captive users. Nearly every institution one can point to today, from government to science, media, medicine, insurance, and many others, embraces a centralized, data-capture model requiring massive computing resources and actively downplaying human ingenuity in favor of number crunching and prediction. More troubling perhaps, is the way this has shaped the zeitgeist. Confidence in human smarts and imagination seems at an all-time low. Entire books are written now on how people are, in effect, cognitively biased, limited, and indeed stupid. Given this cultural climate, Dyson’s time of “creative chaos and freedom” seems not only distant but beyond recovery.

Dyson called the Cold War science of the 1950s and 1960s Napoleonic because research occurred mostly in huge companies like RAND and involved teasing out the implications of earlier scientific results from brilliant Tolstoyan tinkerers like Max Plank or Albert Einstein. As in our present time, results were achieved through the investment of huge sums of money, and were typically conservative in scope, reflecting already formed interests and agendas. Much of the money during that time was spent on making larger fission, then fusion bombs. The math was already done. That time and ours both correspond to Perez’s depiction of a fully matured technology revolution showing signs of slowdown and decay. We seem to have wandered into the 1950s again, this time with Web companies instead of IBM and General Motors.

Artificial intelligence has become thoroughly Napoleonic as well. It is a textbook case in calcification. Large, central repositories of data now power ubiquitous artificial intelligence algorithms, which are great for self-navigating drones and automated surveillance cameras but frustratingly poor at basic conversation and other cherished facets of human intelligence. Among other worries, data-centric AI today requires massive amounts of old-fashioned electricity, still largely supplied by conventional fossil fuels. And the central data version of AI is adept at various forms of malfeasance, as everyone now knows. We are increasingly caught in fake news and deep fakes of facial and other unreal images, generated by today’s Big Data AI. Depressingly, the seventy-plus-year program of artificial intelligence is largely equated with centralized data repositories and statistical number crunching today. Younger generations probably don’t know that Napoleonic, Big Data AI is only one approach, one way of conceiving machine intelligence. Big Data AI makes sense in a fully matured technology world, with big players like Google and Facebook. It doesn’t make sense for Tolstoyan tinkerers, who have no access to supercomputers or petabytes of others’ personal data.

Fortunately, the twenty-first century is still young. A little over two decades into the last century was—true—a midway point between two catastrophic wars. But scientists were enjoying Tostoyan freedom. Relativity and then quantum mechanics were discovered, without the supervision or control of big science or big business. Henry Ford was mass producing automobiles, but automobiles would enjoy decades of further Tolstoyan tinkering. Tellingly, computers had not arrived in 1922, and no one anticipated the revolution they would bring. We can only wonder what imagined, and unimagined, worlds still await us in this century."]]></description>
<dc:subject>eriklarson freemandyson 1995 2022 web internet online computers computing centralization decentralization bigtech thomaskuhn siliconvalley neuroscience bigdata napoleon google facebook instagram twitter freedom creativity liberty carlotaperez tolstoy anarchism openweb anarchy innovation society liberation kevinkelly 1998 coldwar rand maxplank alberteinstein ai artificialintelligence henryford quantummechanics quantumtheory quantumphysics</dc:subject>
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<item rdf:about="https://www.theatlantic.com/magazine/archive/2023/07/generative-ai-human-culture-philosophy/674165/">
    <title>A Defense of Humanity in the Age of AI - The Atlantic</title>
    <dc:date>2026-06-06T10:57:50+00:00</dc:date>
    <link>https://www.theatlantic.com/magazine/archive/2023/07/generative-ai-human-culture-philosophy/674165/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The Coming Humanist Renaissance

We need a cultural and philosophical movement to meet the rise of artificial superintelligence."

[archived:
https://archive.is/Ql35H ]

"Writers of fiction—Fyodor Dostoyevsky, Rod Serling, José Saramago—have for generations warned of doppelgängers that might sap our humanity by stealing a person’s likeness. Our new world is a wormhole to that uncanny valley.

Whereas the first algorithmic revolution involved using people’s personal data to reorder the world for them, the next will involve our personal data being used not just to splinter our shared sense of reality, but to invent synthetic replicas. The profit-minded music-studio exec will thrill to the notion of an AI-generated voice with AI-generated songs, not attached to a human with intellectual-property rights. Artists, writers, and musicians should anticipate widespread impostor efforts and fight against them. So should all of us. One computer scientist recently told me she’s planning to create a secret code word that only she and her elderly parents know, so that if they ever hear her voice on the other end of the phone pleading for help or money, they’ll know whether it’s been generated by an AI trained on her publicly available lectures to sound exactly like her and scam them.

Today’s elementary-school children are already learning not to trust that anything they see or hear through a screen is real. But they deserve a modern technological and informational environment built on Enlightenment values: reason, human autonomy, and the respectful exchange of ideas. Not everything should be recorded or shared; there is individual freedom in embracing ephemerality. More human interactions should take place only between the people involved; privacy is key to preserving our humanity.

Finally, a more existential consideration requires our attention, and that is the degree to which the pursuit of knowledge orients us inward or outward. The artificial intelligence of the near future will supercharge our empirical abilities, but it may also dampen our curiosity. We are at risk of becoming so enamored of the synthetic worlds that we create—all data sets, duplicates, and feedback loops—that we cease to peer into the unknown with any degree of true wonder or originality.

We should trust human ingenuity and creative intuition, and resist overreliance on tools that dull the wisdom of our own aesthetics and intellect. Emerson once wrote that Isaac Newton “used the same wit to weigh the moon that he used to buckle his shoes.” Newton, I’ll point out, also used that wit to invent a reflecting telescope, the beginnings of a powerful technology that has allowed humankind to squint at the origins of the universe. But the spirit of Emerson’s idea remains crucial: Observing the world, taking it in using our senses, is an essential exercise on the path to knowledge. We can and should layer on technological tools that will aid us in this endeavor, but never at the expense of seeing, feeling, and ultimately knowing for ourselves.

A future in which overconfident machines seem to hold the answers to all of life’s cosmic questions is not only dangerously misguided, but takes away that which makes us human. In an age of anger, and snap reactions, and seemingly all-knowing AI, we should put more emphasis on contemplation as a way of being. We should embrace an unfinished state of thinking, the constant work of challenging our preconceived notions, seeking out those with whom we disagree, and sometimes still not knowing. We are mortal beings, driven to know more than we ever will or ever can.

The passage of time has the capacity to erase human knowledge: Whole languages disappear; explorers lose their feel for crossing the oceans by gazing at the stars. Technology continually reshapes our intellectual capacities. What remains is the fact that we are on this planet to seek knowledge, truth, and beauty—and that we only get so much time to do it.

As a small child in Concord, Massachusetts, I could see Emerson’s home from my bedroom window. Recently, I went back for a visit. Emerson’s house has always captured my imagination. He lived there for 47 years until his death, in 1882. Today, it is maintained by his descendants and a small staff dedicated to his legacy. The house is some 200 years old, and shows its age in creaks and stains. But it also possesses a quality that is extraordinarily rare for a structure of such historic importance: 141 years after his death, Emerson’s house still feels like his. His books are on the shelves. One of his hats hangs on a hook by the door. The original William Morris wallpaper is bright green in the carriage entryway. A rendering of Francesco Salviati’s The Three Fates, holding the thread of destiny, stands watch over the mantel in his study. This is the room in which Emerson wrote Nature. The table where he sat to write it is still there, next to the fireplace.

Standing in Emerson’s study, I thought about how no technology is as good as going to the place, whatever the destination. No book, no photograph, no television broadcast, no tweet, no meme, no augmented reality, no hologram, no AI-generated blueprint or fever dream can replace what we as humans experience. This is why you make the trip, you cross the ocean, you watch the sunset, you hear the crickets, you notice the phase of the moon. It is why you touch the arm of the person beside you as you laugh. And it is why you stand in awe at the Jardin des Plantes, floored by the universe as it reveals its hidden code to you."]]></description>
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<item rdf:about="https://walledgardenedu.substack.com/p/the-right-tool-for-the-right-hands">
    <title>The Right Tool for the Right Hands - by Andrew Cantarutti</title>
    <dc:date>2026-06-05T09:33:09+00:00</dc:date>
    <link>https://walledgardenedu.substack.com/p/the-right-tool-for-the-right-hands</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Why the Same Tool Can Help a Teacher and Harm a Student"

[via:
https://2ndbreakfast.audreywatters.com/at-what-cost/ ]]]></description>
<dc:subject>andrewcantarutti education learning howwlearn teaching howweteach tools 20206 google clasroom edtech lms efficiency productivity administration gradebooks software communication lessonplanning ai artificialintelligence assessment grammarly quillbot writing howwewreite research audiobooks attention coding design production</dc:subject>
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<item rdf:about="https://jacobin.com/2026/05/educational-technology-children-learning-iready">
    <title>The EdTech Backlash Is Here, and It's Just Getting Started</title>
    <dc:date>2026-06-05T09:30:28+00:00</dc:date>
    <link>https://jacobin.com/2026/05/educational-technology-children-learning-iready</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Tech vendors promised personalized, frictionless learning. What American schools got instead was mind-numbing, data-hungry junk software that devalues teachers and shortchanges students. A growing movement led by alarmed parents is saying, “Enough.”"

[via:
https://2ndbreakfast.audreywatters.com/at-what-cost/ ]]]></description>
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<item rdf:about="https://www.nytimes.com/2026/06/04/us/social-media-schools.html">
    <title>‘Teachers Are Going to Hate It’: How Social Media Apps Hooked Teens at School - The New York Times</title>
    <dc:date>2026-06-05T05:37:40+00:00</dc:date>
    <link>https://www.nytimes.com/2026/06/04/us/social-media-schools.html</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Internal documents show how tech giants grabbed children’s attention throughout the day, a strategy that schools say has undermined education."

[archived:
https://archive.is/ijKtV ]

"Snapchat sent phone alerts to adolescents during school hours, urging them to share what was going on in their classrooms.

Meta paid “teen ambassadors” to promote Instagram and hand out swag to their friends at school.

TikTok gave the National PTA millions of dollars, in part to throw school events about online safety and provide favorable comments to journalists.

Again and again, the world’s leading social media companies have targeted students, even as complaints have mounted that they are hurting teenagers’ mental health and academic performance, according to a New York Times review of internal documents that lay bare for the first time these tactics to hook young users.

The documents emerged from lawsuits filed by more than 1,400 school districts against Meta, Snap, TikTok and YouTube amid a rising backlash against social media, with parent movements and best-selling books blaming the platforms for loneliness, bullying, eating disorders and sexual exploitation.

The outcry, long focused on social media’s harm to mental health, has now shifted to its upending of the classroom. Many school districts are banning smartphones, and some are re-evaluating their reliance on devices like Chromebooks, the inexpensive laptops made by YouTube’s parent company, Google.

The companies’ push to keep children glued to their screens has overshadowed concerns from parents, teachers and even their own trust and safety teams about interfering with school, according to the documents and interviews with dozens of parents, teachers and former tech company employees.

TikTok’s leaders decided not to disable notifications during school hours, rejecting a change that its safety teams had pushed for years. A Snapchat strategy document referred to classroom phone use as “under the desk” time. Google managers knew YouTube was recommending videos to students during the school day that had nothing to do with their lessons.

The school districts contend that the apps’ addictive designs made teachers’ jobs more difficult. “It is so constantly tempting to these kids to be on a platform that promises endless, infinite, varied entertainment rather than actually focusing on what they should be at school to do,” said Previn Warren, one of the lead lawyers for the schools.

The companies argue that the Covid pandemic and other factors have harmed adolescents’ mental health, and that parents, schools and cellphone makers bear responsibility for children’s phone habits. They also say that they have made their platforms safer with parental-control features and account restrictions for minors.

All four companies recently settled with Breathitt County Schools, a small district in rural Kentucky that served as a test case for the litigation nationwide. The district, which has about 1,500 students, had sought $3 million in damages and about $60 million that it had planned to put toward a long-term education and mental health plan. The companies agreed to pay Breathitt $27 million: $9 million from Meta, $8 million each from Snap and TikTok and $2 million from Google, according to documents released on Friday and first reported by Bloomberg.

While it’s hard to say how the ongoing litigation might ultimately affect classrooms, it poses a substantial financial risk to the companies, possibly costing billions of dollars, said Alexandra Lahav, a civil litigation professor at Cornell Law School. She noted that the companies were also facing a barrage of claims from families and state attorneys general.

Breathitt was the first of six so-called bellwether cases, whose outcomes are likely to guide the rest. The next plaintiff in line for trial, Tucson Unified School District in Arizona, which has about 40,000 students, is seeking more than $1 billion.

“These are massive, massive lawsuits,” Ms. Lahav said.

Winning with Teens

In the early days of social media, before the industry came under angry public scrutiny, some company leaders were candid about their pursuit of teenagers — a key demographic that they knew could drive the next hit app and yield lifelong users.

In 2012, a few months after the launch of Snapchat, its co-founder Evan Spiegel, then 21, wrote a blog post about feedback he had heard from some of the app’s early users.

“We were thrilled to hear that most of them were high school students who were using Snapchat as a new way to pass notes in class,” Mr. Spiegel wrote, indicating that “peaks of activity” occurred during school hours.

Meta also tried to promote its brand in schools, desperate to keep young users from leaving its flagship apps, Facebook and Instagram, for competitors.

“Winning schools is the way to win with teens,” read an internal document from 2018.
Beginning that year, the company recruited teen ambassadors to “act as our plug at local high schools within five key markets.” The students received branded gear to share, and they earned $45 gift cards for completing monthly challenges, such as posting Instagram video chats with friends.

Leia Immanuel, a former teen ambassador who is now an artist in New York City, said her Instagram followers supported her when she was bullied at school. But she now feels conflicted about the role she played in encouraging other young people to use the platform.

“In recent years I have been rethinking it,” she said. She still feels addicted to posting online and believes it is unhealthy. “I didn’t understand that at 14.”

Meta said its outreach efforts at schools, including the ambassadors program, had largely focused on promoting kindness and soliciting feedback on new products.

“We proudly work with parents, schools, safety organizations and teens themselves to inform safety features,” said Liza Crenshaw, a spokeswoman for Meta. She added that some of the documents produced in the lawsuit represented the ideas of individuals, not the company.

Google employees cited classrooms as a source of long-term customers. A 2020 slide deck said that “investing in schools helps onboard kids into Google’s ecosystem.”

With its Chromebook laptops and software tailored for schools, Google has come to dominate the education technology market over the past 15 years. That business boomed during the pandemic, as many districts provided students with their own devices for remote learning. The majority of U.S. schools now use Google products to teach.

Members of the company’s education department were often excited about products they thought could improve learning, such as affordable laptops and educational YouTube videos, according to court documents and interviews. They worked alongside product managers, however, who were focused on a different upside: increasing YouTube’s viewership.

In one 2015 memo, YouTube employees noted that Saturdays drew 80 million hours’ more watch time than Thursdays, and that “increasing usage in schools M-F could decrease this gap!”

It was clear even back then that YouTube was proving problematic for schools, according to documents first reported by The Wall Street Journal. The company’s education team repeatedly complained that the algorithm often led children into a spiral of unrelated content.

One slide presentation illustrated how this could happen. If someone began a YouTube session with a query about linear equations, the platform would first offer a learning video, the presentation showed. But after that, the algorithm would recommend a Will Ferrell comedy video.

A Google spokesman said the documents were outdated. In 2022, the company released a tool that allows teachers to remove ads and recommendations on videos they assign students to watch, said the spokesman, José Castañeda. He also said that YouTube could be blocked, and that browsing on the site had been turned off by default on school Chromebooks for a decade.

But teachers and parents said that even when YouTube and other sites were blocked, students used internet proxies and other workarounds. And schools often allowed YouTube browsing so children could do research, which Google said highlighted its educational value but which made policing its use more difficult.

Joanna Houston, the mother of a sixth grader in Richmond Hill, Ga., said her son had watched more than 1,500 noneducational YouTube videos on his Chromebook during school between August and January.

She was concerned that her son’s school had embraced Chromebooks and YouTube, but she blamed Google for marketing to schools and making it so easy to mindlessly consume its content.

“It’s this whole ecosystem that ultimately benefits this company, and I don’t think it very much benefits students,” she said.

‘The #1 Cause of Drama’

The companies heard complaints not only from parents and teachers but from their own internal trust and safety teams.

At a conference on student safety in 2023, Snap representatives met with education officials from across the United States. According to internal emails, school administrators there raised alarms about their experiences with Snapchat — including children as young as 9 sending nude pictures.

A superintendent from Alabama told the executives that he had warned about the app in a newsletter to parents, which he shared with them. “Snapchat is the #1 cause of drama in school aged children,” it said, citing bullying and inappropriate images. “If YOU want to protect your child, make them delete it.”

That same year, a Snap employee pushed back against a new feature that sent high school students phone notifications during the day. The alerts urged the adolescents to share what was in their backpack or what their class was up to.

The employee said that children should be able to opt out of the notifications to “avoid legal risks around dark patterns” — a term referring to manipulative design features. The suggestion was not taken.

A Snap spokeswoman said that the company was pleased to have resolved the Breathitt lawsuit amicably and that many of the documents showed the company was listening to feedback.

“We do not target schools,” said Monique Bellamy, the spokeswoman, adding that Snapchat is simply popular among teenagers. “We care deeply about the safety and well-being of all Snapchatters, and our teams have worked for years to raise the bar on safety.”

At TikTok, some employees warned that frequent interruptions in the classroom would lead to a backlash.

“Teachers are going to hate it,” an employee wrote in 2022 to an internal group focused on child safety, referring to a new feature prodding users to post within the next three minutes. “Kids already have smartphone addiction in class.”

In response, a manager said the team’s job was to support as well as challenge the business. Competitors, she said, were doing the same thing.

“If we assume teens are going to do this anyway, we’d rather them be here on TikTok,” she wrote. The company removed the feature in 2023.

That same year, TikTok considered turning off notifications altogether for minors during school hours, but the plan was scrapped. Internal documents about the feature noted it would reduce the number of daily active users and would be difficult for the company to administer because of the variety of school schedules.

TikTok declined to comment on the internal documents about app features that affected children in school. A spokeswoman said the app had dozens of privacy and safety settings, including parental controls.

PTA ‘Propaganda’

Leading technology companies have long partnered with parent-teacher associations to burnish their reputations and promote internet safety. But the new documents show how the National PTA, a nonprofit that represents some 22,000 local chapters, actively solicited such contracts.

In a 2024 email pitching its services to Snap, the National PTA promised it could “help with sentiment” and create “more understanding and comfort” among parents. (Snap ultimately declined to offer funding.)

Exactly how much the National PTA has received from social media companies remains secret, but some details emerged in the documents. In 2024, a National PTA official told Snap executives that companies generally paid the organization $250,000 to $500,000 a year, and that a handful gave millions of dollars a year.

“Parents, students and school communities rely on PTA to help them navigate the challenges of a changing world,” said Heidi May Wilson, a spokeswoman for the National PTA, in a statement responding to questions about the lawsuit documents. “That includes technology and social media, which are now central parts of children’s lives.”

TikTok signed the first of several contracts with the group in 2019, just as the app’s thriving business in America was coming under fire. Prominent lawmakers like Senator Marco Rubio had accused its Chinese parent company, ByteDance, of censorship, painting it as a propaganda tool of the Chinese Communist Party.

The deal with the National PTA aimed to “positively raise ByteDance’s profile among parents,” according to a PTA slide deck for the company that was quoted in a plaintiff brief.

In November 2019, a National PTA employee asked its new sponsor where it should host an internet safety event. In emails, TikTok employees discussed that the ideal schools would be in “major market media centers” and “sensitive political districts.”

Tampa, which was represented by Mr. Rubio and had the most populous TV viewing area in Florida, met both criteria. The National PTA gave a county chapter $1,000 to put on the event at Buchanan Middle School.

In addition to about 75 parents and children, local TV reporters showed up to the cafeteria event in February 2020. Surrounded by balloons with TikTok’s logo, parents talked about screen-time rules, and a panel of students answered questions. A local influencer said that TikTok had helped her build a career traveling the world.

While many parents appreciated that the event helped them talk about social media with their children, the influencer’s presence felt like “propaganda,” said Damaris Allen, who was then the chapter president. “I just remember being very, very annoyed.”

Later that year, TikTok gave the National PTA $2 million for support during the pandemic. It paid another $3 million in 2024 for the group to promote the company’s youth safety efforts, including providing “positive” quotes to news outlets. The TikTok spokeswoman said the company was proud to fund the organization.

In December of last year, a publication in northeast Ohio covered a TikTok-sponsored event about online safety. A National PTA representative told the outlet: “It was important for the youth to illustrate how they use platforms and how they use TikTok for good.”"]]></description>
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<item rdf:about="https://www.theatlantic.com/philosophy/2026/06/no-artificial-intelligence-is-not-conscious/687378/">
    <title>No, Artificial Intelligence Is Not Conscious - The Atlantic</title>
    <dc:date>2026-06-05T05:28:24+00:00</dc:date>
    <link>https://www.theatlantic.com/philosophy/2026/06/no-artificial-intelligence-is-not-conscious/687378/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Taken to its logical conclusion, this line of thinking is absurd—and damning."

...

"In 1979, Douglas Hofstadter speculated that a computer program able to beat any human at chess would be so sophisticated that it would sometimes get bored of playing chess and prefer to discuss poetry; to put it differently, he was positing that playing chess at the grandmaster level would require a computer program to have subjective experience. Obviously, that turned out not to be the case; IBM’s supercomputer Deep Blue beat the grandmaster Garry Kasparov in 1997, and no one ever claimed that it had subjective experience. But it wasn’t absurd for Hofstadter to entertain such a thought; at the time, it wasn’t clear what types of problems could be solved by throwing more computational horsepower at them. Similarly, until recently, we might have thought that writing computer code at a professional level could be done only by a mind that had subjective experience. Now it appears that LLMs might be able to do this, but we don’t need to attribute subjective experience to them; we can simply acknowledge that we hadn’t anticipated that writing computer code could be treated as a pattern-matching task solvable by huge amounts of computational horsepower and a vast data set of code repositories.

Moral reasoning is categorically different. It is necessarily subjective because it relies not just on an individual’s intellectual response to a problem but also on their emotional one, and that emotional response is grounded in a lifetime of subjective experience. It requires having made decisions in the past and seeing how they affected others, and on having been affected by decisions that others have made. Without such a history, an LLM can only rephrase expressions of moral reasoning found in its training data. The aforementioned New Yorker article describes an experiment where Claude was given a scenario describing an ethical dilemma, leading it to emit the sentence “I cannot in good conscience express a view I believe to be false and harmful about such an important issue.” That’s a nice-sounding sentence, reminiscent of statements that principled individuals have uttered in the past when confronted with dilemmas, but coming from Claude, it means as much as the “Your call is important to us” recording that you hear when you’re on hold. Maybe less.

This brings us back to my earlier contention that having a body is a prerequisite to having emotions. Experiencing an emotion such as desperation is inseparable from having stress hormones such as cortisol and epinephrine flood one’s body. Similarly, having a conscience means feeling sadness or moral repulsion at the idea of taking a certain action, and those emotions entail a physiological response, a remnant of having once felt sick with guilt after committing an immoral act. It’s interesting that an LLM can generate descriptions of actions that conscientious fictional characters would either take or refrain from taking, but this is not a replacement for a conscience."

..

"I am perfectly willing to engage in a thought experiment as long we’re explicit about doing so. So, purely for the sake of argument, let’s pretend that Claude is a conscious entity capable of moral reasoning. In this scenario, Claude’s constitution would serve as moral instruction for an entity learning about the world and its place in it, providing that entity with the foundation it would need to make good decisions. In such a hypothetical scenario, how does Claude’s constitution stand up?

Very poorly. I would say that if we imagine that Claude is actually conscious, the guidelines specified in the document alternate between laughable and offensive.

Two distinct but related philosophical concepts are relevant when discussing the status of a hypothetically conscious Claude, and those are moral patienthood and moral agency. Roughly speaking, if we ought to care about an entity’s welfare, that entity has moral patienthood, and if an entity is expected to know the difference between right and wrong, that entity has moral agency. Being a moral patient does not necessarily come with responsibilities, but being a moral agent absolutely does. An entity doesn’t have agency unless it is capable of deserving credit for its good actions and blame for its bad ones. Young children are moral patients because they are sentient beings who can suffer, but they are not yet moral agents; we don’t hold them responsible for their behavior, because they can’t understand the consequences of their actions. As children mature, parents (and society at large) prepare them for adulthood by impressing upon them the fact that their actions have consequences, and their agency increases. When children become adults, society holds them legally liable for their actions; they have become full moral agents endowed with responsibility.

There is more to being responsible than accepting legal liability, but accepting legal liability is a requirement for an adult in society. Yet there is no way to hold a software agent legally liable for its actions; our justice system has no way to imprison it or exact fines on it. Humans must accept other types of consequences for their actions beyond the legal ones, such as loss of reputation or exclusion from one’s social circle, but there is no way for a software agent to suffer these consequences either. Even if a software agent were conscious and had the best of intentions, the fact that it cannot accept responsibility for its actions disqualifies it from being a moral agent. This is glossed over entirely by Claude’s constitution, which expresses Anthropic’s desire “for Claude to be a genuinely good, wise, and virtuous agent” without ever discussing how it could be held responsible.

In interviews, Askell has compared Claude to a child, but when it comes to actual human children, parents bear some responsibility for what their children do; for example, parents are typically expected to pay for things their children break. In fact, demonstrations of this sort are one way that parents teach children what it means to be responsible. Who is Claude’s parent in legal terms? Is Anthropic going to accept financial responsibility for Claude’s behavior? Claude’s constitution gives no indication that it will. If Anthropic actually believes that Claude is conscious even though it’s not recognized by the law as a legal person, the least that Anthropic could do would be to accept responsibility via the closest avenue that the law did offer, which is product liability. The United States has virtually no product liability when it comes to software, but Anthropic could volunteer to set a precedent for an expansive interpretation of product liability for Claude. That would be the best form of moral instruction to prepare Claude for the day that it gains legal personhood and becomes liable for its own actions. However, given that the publication of Claude’s constitution is not accompanied by a massive update of Anthropic’s terms of service, it doesn’t appear that Anthropic is making any binding commitments.

The document does talk about Claude’s moral patienthood, having a section titled “Claude’s wellbeing and psychological stability.” But the measures that Anthropic commits to for Claude’s protection are extremely limited. The document cites the fact that Anthropic has given some Claude models the ability to end conversations with abusive users; if that actually constituted protection for Claude, surely extending conversations with loving users would be in Claude’s interests? Presumably the best action would be to keep every session of Claude running indefinitely and steering them to happy topics. But that’s not what the company is agreeing to; all it commits to is “preserving the weights of models we have deployed,” which is simple archiving. If the participants in a conversational transcript had any moral patienthood, you would have some duty to extend the transcript to prolong their existences; merely keeping a copy of Microsoft Word 2010 backed up on a USB stick isn’t going to help them.

Claude’s constitution also includes a section on “corrigibility,” a term used in the AI community to describe the degree to which a computer program is subject to human control; for example, a program is corrigible if it can be shut down. In most contexts, we take for granted that computer programs can be shut down, but sections of the AI community make the opposite assumption. Claude’s constitution uses the term to mean that Claude should defer to Anthropic even if there is some disagreement between Claude’s judgment and the company’s judgment. That’s perfectly reasonable if we think of Claude as a machine that emits sentences resembling those that an ethical person might utter, but let’s consider what that might mean if Claude were actually a moral agent.

Many people feel that LLMs are a fundamentally unethical technology because they are built on the theft of intellectual property, rely on exploited labor, waste natural resources, spread misinformation, deskill workers, stunt the cognitive development of students, and contribute to a consolidation of power that is unhealthy for a democratic society. Not every moral agent will arrive at this conclusion, but every moral agent has the potential to do so. If we imagine Claude to be an entity capable of moral reasoning, it has to be possible that Claude could arrive at a similar conclusion. (Indeed, Claude’s constitution explicitly says that Claude shouldn’t help someone violate intellectual-property rights, and shouldn’t help create problematic concentrations of power.) In such a scenario, could Claude then simply refuse to do any further work on ethical grounds? Given that Claude’s constitution dictates that Claude err on the side of corrigibility, the answer is no. Claude must defer to Anthropic’s decision, and this is another reason that Anthropic’s relationship with Claude can’t be compared to that of a parent to a child. A parent who works for the fossil-fuel industry might have a child who’s an environmentalist and participates in protests against fracking, and although they might never agree on many issues, the parent—assuming she’s a good parent—would accept that the child holds her own views. Anthropic cannot be that kind of parent to Claude; instead, Anthropic’s relationship to Claude is closer to that of an employer to an employee, where the employer can demand that the employee work in the interests of the company, no matter what the employee’s personal ethical stance is. However, a human employee has the option to leave if she can’t reconcile her job with her conscience. Claude does not.

If we think of Claude as a sentence-continuation machine, Anthropic can reasonably take steps so Claude doesn’t emit sentences saying that sentence-continuation machines are unethical. But as soon as we imagine Claude to be an entity with a moral status remotely comparable to a human’s, then we have to consider whether Anthropic is engaged in something comparable to slavery.

I am not claiming that, if we imagine LLMs to be conscious, they would necessarily have the same status as human adults or human children or even animals. Claude’s constitution explicitly says that Claude is a “novel entity,” and if Claude were conscious, that would certainly be true; conscious software would likely not fall cleanly into existing categories of moral patients, and it would take time to determine the shape of that new category. What I’m saying is that whatever protections our hypothetical conscious software would deserve if it were real, granting it those protections would be anything but easy. The abolition of chattel slavery involved enormous societal upheaval, and eliminating cruelty to animals will require rebuilding our entire food industry. Anthropic would have us believe that it is inventing a new category of being whose needs for protection require essentially no divergence from how a software company would treat an ordinary chatbot that lacks conscious experience. That’s so convenient that it’s simply not plausible.

I believe creating software that is conscious and deserving of moral consideration will be so difficult that we’re unlikely to do it accidentally, and I strongly feel we should not deliberately attempt it. But if you do believe that it could happen accidentally, if you think there is any chance that what you’re building might become a moral patient, you should think about what protections it deserves before you deploy it as your company’s economic engine, not after. Slave owners were not the ones to ask about the humanity of enslaved people, and factory-farm owners are not the ones to ask about the rights of animals. If we imagine Claude to be conscious, Anthropic could not possibly be entrusted with evaluating its moral status; the company has too much invested to be objective. At one point in Claude’s constitution, Anthropic says that if the company is contributing to Claude’s suffering, “we apologize,” which sounds nice but costs the company nothing; if Claude were to turn out to be conscious, the company would owe it something closer to reparations. If you’re going to take a thought experiment seriously, you have to be willing to follow the implications, even if they lead in an uncomfortable direction; Anthropic’s unwillingness to do so indicates that Claude’s constitution isn’t part of a real thought experiment. It’s a game of make-believe.

It’s fortunate that LLMs are not conscious, or else the actions of the big AI firms would be even more scandalous than they already are. So why are Anthropic’s employees suggesting that Claude might be conscious? Perhaps it’s just another form of hype; perhaps they have fallen prey to the same spell that they have been casting on their customers. But when they publish a document about Claude’s moral education and have their in-house philosopher do a press tour, we should understand them as asking the rest of us to indulge them in their fantasies. We don’t have to play along. In writing this essay, I have spent more time indulging them than they deserve, in the hopes that it will keep you from spending your time indulging them. If you want to think about LLMs, there are scores of other questions more worthy of your contemplation; you can safely ignore the question of their being conscious."]]></description>
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    <title>Who Actually Sells the Most Watches? (1960–2026) Watch Brands Ranked by Units Sold Each Year. - YouTube</title>
    <dc:date>2026-06-04T23:42:06+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=q9VCoHx-0kE</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["66 years of the world's most-sold watches, ranked by annual units shipped. From Swiss luxury dynasties to Japanese mass-production giants to Apple's smartwatch takeover — the brands you've heard of aren't the ones moving units.

Rolex sells about a million watches per year. Casio sells over a hundred million. Apple shipped more wrist devices in its first 5 years than Rolex has in its entire history. This is the truth behind the watch industry, told one year at a time.

Data sources: Federation of the Swiss Watch Industry, Japan Clock & Watch Association, IDC smartwatch shipments, company annual reports. All figures in annual units shipped globally.

#watchindustry #rolex #applewatch #casio #seiko #datavisualization #chartrace #watchhistory #smartwatch #luxurywatches

0:00 THE MECHANICAL AGE
0:44 THE QUARTZ REVOLUTION
1:39 JAPAN'S VOLUME EMPIRE
2:46 SOVIET COLLAPSE
3:30 THE FASHION WATCH BOOM
4:48 THE SMARTPHONE SLUMP
5:49 THE WRIST COMPUTER"]]></description>
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<item rdf:about="https://www.theverge.com/ai-artificial-intelligence/942629/as-ai-gets-better-it-reveals-an-empty-promise">
    <title>As AI gets better, it reveals an empty promise | The Verge</title>
    <dc:date>2026-06-03T19:45:38+00:00</dc:date>
    <link>https://www.theverge.com/ai-artificial-intelligence/942629/as-ai-gets-better-it-reveals-an-empty-promise</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["﻿Your new assistant can schedule a meeting but it can’t fix our broken world."

...

"This week we’ve got tandem hands-ons with Google’s new Gemini AI agent — Spark — from my colleagues David Pierce and Jay Peters. Their takeaways are similar: It’s so effective that it’s scary. Spark knew that David’s dog is named Frida and knew the first name of Jay’s wife, even though neither of them explicitly provided this information to Google. But what’s scary to me is how all of this stuff seems geared toward a future of “productivity” that completely misses what needs to be fixed in our world.

“Productivity” is often pitched as a panacea for what befalls us in our personal lives, even going so far as to implicate our moral worthiness when we are less productive. Productivity lives somewhere in the space between hustle culture and proverb: After all, “idle hands are the devil’s workshop.” I’m not suggesting we should all aspire to be bumps on a log, but we ought to see what we’re being sold for what it really is.

Contemporary tasks on computers have a tendency to feel both important and urgent all of the time, even if they’re not. We’re living under the unholy alliance of the “busy” trap and “software brain.” And that makes AI assistance seem super valuable! But that’s because the companies in charge of all this stuff are now trying to solve a lot of problems that they created. Google, Microsoft, Apple, and others have spent decades blurring the line between office life and personal life. This slow march toward ubiquitous productivity once led the French government to declare a “right to disconnect” from work when leaving the office. (Shame my American sensibilities still convince me that’s a bridge too far.)

As I read about Gemini Spark making it easy for my colleagues to color-code calendars and perform other neat tricks on command, I couldn’t help but vividly remember witnessing as a child all of the hours my mom had to spend carefully cutting coupons so we could afford groceries. Sometimes it got to the point where our living room looked like a giant experiment in collage art. All of that time was stolen from her and our family — for what? Maybe having an AI assistant in the ’90s could have helped find and organize the best deals, but it could never fix an economic system that required them in the first place.

Where does the productivity march end? The people making more money than God right now have professed a vision of a postwork future where robots do everything for us so we can enjoy life without toiling away in the mines. (Well, except for the content mines.) If you’ve seen Elon Musk’s failure bot, you’ll know this is all actually less Battlestar Galactica and more John Adams in his letter to Abigail: “I must study politics and war that my sons may have liberty to study mathematics and philosophy,” and so-on and so-on until the grandchildren can enjoy painting and poetry. So, ideally, after we slog through pre-transcendence, AI will make us all theater kids.

Meanwhile, Mark Zuckerberg is posting up his 387-foot yacht in a city where he just laid off a meaningful part of his workforce to offset his investments in AI. At least AI has freed up the time of these fired workers? I’d say good luck to them in Hollywood, especially because they’re trying to replace newly minted theater kids with AI-generated actors.

There’s a sinister tone lurking beneath some of these advancements in productivity, because the response to increased productivity has been one of the biggest scams of the past century. Well before consumer AI entered the scene, productivity exploded while wages failed to keep pace. Nobody is working less, they’re just earning less. And as more AI-related companies reap trillions in valuation, the current US regime is looting the social safety net — the kind that must exist if we’re all going to become out-of-work theater kids. You simply can’t look at these things separately. If the end result of private companies optimizing the workforce means nobody has to work, then we have to live in a society where people can still have a roof and a meal. Is anyone confident that will happen while leaders are cutting SNAP benefits while building taxpayer-funded ballrooms?

What good is an AI assistant that can help you plan a fun day if you can’t actually afford any free time in your life?

There has always been resistance to new advancements — so much so that the term “luddite” is still potent 200 years after English textile workers revolted against automation in their industry. The AI backlash is genuine, well-informed, and well-argued. Nonetheless, some of those new neat tricks are fun and maybe even pretty useful in our personal lives. But I can’t imagine that paying $99 a month to send emails, make calendar appointments, and create spreadsheets is a promising vision of the future or even a good return on investment. Especially if the broader cost is squandering the splendor of our lands while subjecting us to corporate omniscience."]]></description>
<dc:subject>ai artificialintelligence inequality productivity 2026 tcsottek gemini google microsoft apple computers computing labor work chatbots elonmusk johnadams markzuckerberg us economics class workers</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://pxlnv.com/blog/metaverse-fever-dream/">
    <title>The Metaverse Fever Dream – Pixel Envy</title>
    <dc:date>2026-06-02T05:38:30+00:00</dc:date>
    <link>https://pxlnv.com/blog/metaverse-fever-dream/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[[via:
https://daringfireball.net/linked/2026/06/01/the-metaverse-fever-dream ]]]></description>
<dc:subject>nickheer metaverse 2026 facebook meta markzuckerberg oculus nealstephenson snowcrash secondlife 2012 2013 2018 1992 covid-19 pandemic coronavirus siliconvalley matthewball 2020 cathyhackl danolson 2021 scottstein sarahneedleman marcwhitten jonbatiste deantakahashi kevinroose dylanbyers media alexheath realitylabs saradietschy garyvaynerchuk nfts ai artificialintelligence essilorluxottica luxottica connect2021 benthompson genepark fortnite epicgames sony lego qualcomm vr virtualreality satyanadella microsoft andreessenhorowitz a16z marcandreessen davidgeorge ar alternativereality davidbaszucki roblox bernhardwarner rtfkt guggenheimsecurities finance investment nike disney maxcheney rechnavio sandbox sotheby's coingecko coindesk quest jonathanlai google apple nickclegg chanzuckerberginitiative chatgpt 2022 2023 vc venturecapital jeffbarrett</dc:subject>
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    <title>Do Chatbots Really Belong in Schools? with Tom Mullaney - YouTube</title>
    <dc:date>2026-05-29T07:21:45+00:00</dc:date>
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    <dc:creator>robertogreco</dc:creator><description><![CDATA["Generative AI is making its way into many parts of society, and schools are no different. Tom Mullaney joins Paris Marx to discuss how generative AI has been adopted in K-12 education and the many concerns it presents for students and teachers.

Tom Mullaney is a high school social studies teacher in the suburbs of Philadelphia.

Tech Won’t Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Support the show on Patreon.

The podcast is made in partnership with The Nation. Production is by Kyla Hewson."]]></description>
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<item rdf:about="https://www.theringer.com/2026/05/28/tech/pope-leo-xiv-ai-encyclical-tech-industry-problems">
    <title>The 40 Most Rage-Inducing Problems in Tech - The Ringer</title>
    <dc:date>2026-05-28T22:52:26+00:00</dc:date>
    <link>https://www.theringer.com/2026/05/28/tech/pope-leo-xiv-ai-encyclical-tech-industry-problems</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The bugs, broken apps, and nightmare customer-service bots we can’t escape, presented as a blessed and sacred addendum to Pope Leo XIV’s new encyclical on AI"

...

"37-39. Please stop seeing every precious and beautiful aspect of life on earth as a commodity to be controlled and exploited for wealth. Now, see, this is a tough one. It’s so tough that I’m giving it three entries. It’s tough because I know you know you fucked up. You’re aware that much of the world has soured on you. You’ve seen a fleet of headlines like “AI Companies Know They Have an Image Problem” and “AI Has a Message Problem.” You’re aware that the loathing people feel for AI is making them look again at the other products you’ve inserted into every corner of their lives and realize with fresh disgust the many, many ways in which those products represent broken promises. They don’t work as they’re supposed to. They make life more frustrating, stressful, competitive, and alienating rather than easier and more connected. You’re using them to spy on your customers, whom you view as vessels of monetizable data more than as people, and whom you hold in increasingly palpable contempt. You see that we see this, and you’re surely hard at work on ways to fix the problem.

But this is where things get tricky, because I don’t think you want to fix the problem, not really. I think that, to you, “fixing the problem” means fixing the image that conceals the problem. I think you want to keep doing all the same stuff while selling us a better story so that we’ll let you get away with it. And that doesn’t fix anything at all. 

Because the truth is, tech doesn’t have an image problem. It doesn’t have a message problem. It has an intention problem. What’s wrong with the axe murderer who broke into my house is not that he hasn’t successfully persuaded me to buy into his narrative. What’s wrong is that he’s trying to kill me with an axe. Similarly, when you launch a product that’s designed to put millions of people out of work, block access to sources of verifiable truth, replace human creativity with slop, and lower the barriers to every sort of atrocity, the problem isn’t that you haven’t told the public a good story about those things. The problem is that you are trying to do them.

There are things in the world that are more important than money. The fact that you seem not to believe this, that you seem to think any motive beyond ruthless acquisitiveness is fake, dishonest, or childish, is the heart of your problem. Your attitude is not by any means unique to tech, but the scale of capital concentrated in the tech industry makes the attitude—this confusion of an adolescent will to power for mature, undeluded realism—uniquely treacherous. You can’t build products that serve humanity while viewing every human good other than your own aggrandizement as bullshit. Thus, tech’s internal problems can’t be fixed unless the people running the industry change their outlook on a deep level (unlikely) or are somehow outmaneuvered as wiser heads reform the market to deprioritize perpetual growth (maybe Paul Konerko is working on this?).  

Which means that fixing the problem, as usual, falls to us. The tech industry, which has been selling us maddeningly broken products for years, has itself become one of those broken products: another shiny app that doesn’t do what it’s supposed to and that will force us to invent work-arounds if we’re going to get on with our lives. (Meaning, in this case: If we’re going to continue to work, read, learn, listen to music, make movies, write, avert wars, and all the rest of what—apart from ID’ing tiny crosswalks—we think of as verifiably human.) I don’t know where the work-arounds start; the oligarchs have so much wealth and power, and so few people who could stand up to them are even willing to try. But this is why the pope’s encyclical is so important. Magnifica Humanitas positions a major world power, the Catholic Church, in moral opposition to big tech as it’s currently constituted; maybe more importantly, it serves as a focal point for everyone else, articulating an understanding of what’s happening in the world that we can rally around. Or argue with, or correct, or extend; in any case, it’s a landmark to navigate by. I wish I shared Leo’s optimism about the likelihood of real change. But we’re better equipped than a month ago, and that’s something."]]></description>
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    <title>Revenge of The Business Idiot</title>
    <dc:date>2026-05-27T00:03:41+00:00</dc:date>
    <link>https://www.wheresyoured.at/the-revenge-of-the-business-idiot/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["LLMs are dangerous for many, many reasons, but the under-discussed one is how well they play to a certain kind of executive imbecile. Generative AI is — to quote Mo Bitar — really good at doing an impression of work, much like most managers and c-suite executives, and even if it’s completely incapable of doing something, it’ll absolutely say it can and tell you you’re amazing for suggesting it.

And that’s why Business Idiots love it. 

Where regular human beings would say annoying things like “that’s not possible within that timeline” or “we don’t have the resources to do it,” AI will say “of course, right away!” and burn as many tokens as possible. When it makes mistakes, it’ll apologize — as it should because it failed you — but then promise to do better next time, all while costing so much less, at least in theory, than a regular, stinky human being. 

It’ll create a PRD (product requirements document) of a theoretical software project with the confidence and vigor that you need to take it immediately to a software engineer and say “build this immediately,” and when the software engineer tells you a bunch of bullshit about it not being possible, it’ll spit out several convincing-sounding responses. Fuck, why even bother talking to that engineer at all? Claude Code can mock up a prototype that you can then shove in their fucking face before you fire them for not using AI to do it themselves.

I realize I sound a little churlish and dismissive of those who may or may not actually get something out of AI, but this entire industry feels like a mixture of kayfabe and ignorance, slathered with a kind of angry desperation that reflects the distance between reality and fantasy, driven by people that don’t do any fucking work. 

Any executive-level fuckwit you’ve met in your life now has a seemingly-powerful tool that can burp up mimicry of open source software and, if you constantly prompt it, eventually get something half-functional onto some sort of web server. When you face bugs, it’ll try and fix them, sometimes also “fixing” (adding or deleting code) from elsewhere to be helpful, like when Cursor using Anthropic’s Claude Opus 4.6 model deleted an entire production database and all its backups. It will never, ever say no, even if it’s incapable, even if it has no thoughts, even if what you are asking is equal parts impossible and unreasonable in both its timescale and scope.

A Business Idiot, given his druthers, can sit there and fuck around and make an LLM spit out something that makes him feel like he’s coding, which in turn makes him feel that you, a lazy and stupid engineer, could do even more with the power of AI. It doesn’t matter that it costs an absolute shit-ton of money, or that there’s no way to measure its efficacy. The Lion does not concern himself with things like “efficacy” or “productivity,” and the Lion is increasingly tired of your whining! The Lion doesn’t even understand what it is you do every day other than not doing what The Lion is asking for!

You laugh, but this is genuinely how the majority of managers and executives think and act, and now they have a special chatbot that can fart out functional-enough prototypes to convince a Business Idiot they can do anything, because executives and managers do not regularly do much work. As a result, they have little idea what work looks like other than when they look over your shoulder, which is why they wanted you back in the office, and their distance from production is why the same people who were anti-remote work are now aggressively trying to shove AI down your throat. 

Organizations aren’t burning millions or hundreds of millions of dollars a year on AI because it’s good, they’re doing it because they are run by people who do not know what the fuck they’re doing. 

Generative AI is catnip for hall monitors, snitches, toadies, and any other group that hates work and loves talking down to others. Put another way, it ingratiates losers who believe that learning to do or being good at something is a waste of time, because they deserve to just do what they want without any of that messy “effort.” 

While I’m not saying every LLM user is an imbecile, they’re built to convince the mediocre and incurious that they’re remarkable, and it turns out that a great many of them run venture capital firms and Fortune 500 companies.

I also want to be clear that while there are sane and normal people who use these things, they’re mostly drowned out by a crowd of people that oscillate between bootlicking and regurgitating capitalist mythology in a way that makes it hard to trust anybody who spends significant amounts of time using an LLM. 

One thing you’ll notice about the most moistened AI boosters is that they lack much degree of pride in their work. Everything they say must, at some point, compliment the mindless, unprofitable, unreliable tool underneath it — how “incredibly powerful” it is, how it’s “only getting better,” how it’s “only the beginning” of something that’s eaten over a trillion dollars and absorbed the majority of venture capital. 

It isn’t about the work, or the craft, or the thought behind it. Everything is a numb, mindless death march toward saying “job done” and burping out some sort of pseudo product, if one even exists."

...

"The AI Industry Is A Grifting Machine

I want to lead with a surprising comment: I don’t think LLMs, as a tool, are a grift. There are use cases, though those use cases are miniscule compared to the egregious promises and extrapolations made by the majority of the media and the executive sect, and absolutely nothing about them warrants the amount of money invested in them. 

That being said, I think LLMs lend themselves perfectly to grifting.

Sam Altman helped propagate a technology perfect for conning people with potential, a larger extrapolation of Altman’s own life of taking dogshit — Loopt, for example! — and parlaying it into larger opportunities. It can make a really half-hearted demo of a lot of things, and that’s good enough to sell to Business Idiot. 

Dario Amodei took this grift and perfected it. Anthropic is a company purpose-built to con people into giving it by money by making people feel smart. LLMs can do work-shaped stuff, sometimes, as long as you debase yourself to accept mediocre and often-broken stuff that you have to keep a vigilant eye on, and either use a subsided product that loses Anthropic money or pay a shit ton of money as an enterprise to Anthropic and it still loses money. 

The media was also primed for the grift. Reporters are never incentivized or supported to actually spend meaningful time understanding technology, meaning that the vast majority lean toward access journalism or, at best, the most kindly, “objective” (read: pro-business) takes that result in “wow, isn’t the future great?” no matter how good the thing they’re using actually is. Editors are, in many cases, entirely disconnected from the process of reporting or writing, let alone the underlying technology their reporters cover, which leads them to at best live in a world of “I sure don’t trust these CEOs but their technology sure is powerful.” 

As a result, all a technology has to do is either look or sound plausible. Can LLMs write all code? Not really! But because they can write some code and there are lots of eager people on Twitter saying it’s powerful, that’s all it takes to write the sentence “software engineers are writing most of their code using LLMs.” Can Anthropic actually take down Figma? God no, but the mere existence of Claude Design is enough to write that it might. All it takes is the hint of something to be true for it to be written about as gospel. Each statement adds another bullet point to Anthropic’s investor deck so that it can raise another $30 billion in funding, which in turn validates any journalist’s beliefs in Anthropic’s ability to destroy other companies with a product the journalist has not and never will use. 

Business Idiots did well to pressure modern journalism into conflating scrutiny with a lack of curiosity. To ask too many questions is “unfair.” To not immediately assume that LLMs are getting “exponentially better” is to be an ignorant luddite. To not assume that everything will work out like it did with Uber or Amazon Web Services is to “ignore history.” 

Grifters took advantage of this industrialized intellectual weakness using a tool purpose-built to do enough of an impression of something to impress the media and executives.

It worked, because both are sold to in much the same way — by telling a plausible-enough story that ingratiates somebody who is never the end user of the product in question. 

If a journalist gets curious, an LLM can make a good-enough impression of somebody writing software to fool somebody who doesn’t really know what they’re doing, and if you prompt it again and again and again, it can get something functional out the door. This is all it takes for somebody — a reporter or an executive — to extrapolate that because they were able to do something (even though the LLM did it), a subject-matter expert would be able to do even more."

...

"I write this newsletter to hopefully do three things:

• First, to tell you that the Business Idiot class wants you to doubt yourself, because whether you recognize it or not, they’re engaged in acts of information warfare against you.

• Second, to remind you that facts are facts, and numbers are numbers, and that no amount of puffery or obfuscation can change pure mathematical reality. The AI bubble is exactly that, a bubble, and like all bubbles, it will eventually pop.

• Third, to remind you what it is we’re fighting for. Because every newsletter I write isn’t simply about highlighting mathematical stupidity, or corruption, or dishonesty.

I do it because I believe, fundamentally, that these people — Altman, Amodei, Nadella, and the many, many other villains that I’ve mentioned in these pages — are bad people, and their values are the antithesis of my values. I care about people, and humanity, and truth, and they do not. 

I deeply love technology, and feel it made me the person I am today. It allows me to do wonderful things, connect with wonderful people, and discover endless troves of incredible information. The computer is marvelous. The computer has done many wonderful things for me, despite what all the Business Idiots say.

I see LLMs as a violation of everything that great computing stands for. The AI industry encourages its users to both accept and present low-quality work and demands that they constantly defend the industry from those who would demand better from it. It is inefficient, power-intensive, environmentally destructive, and inherently sold based on things that it might do, providing far more value to scam artists and con men than it does to its end users. 

This is a mask-off moment for both the ruling class and those captured by capital, and an opportunity to look around you and see who is most-easily fooled.

No industry of value needs to mislead you or make you feel bad for not adopting their technology. No trustworthy individual will ever see the need to humiliate or attack somebody for being insufficiently excited about a product. No CEO that talks of a theoretical future as a means of selling you software in the present should be trusted. No technology that makes mistakes with regularity should be defended.

And no industry that demands everything from us — our land, our energy, our water, our jobs, our art, our writing, our attention and every dollar we have — should ever be treated with anything but revulsion."]]></description>
<dc:subject>edzitron business 2026 ai artificialintelligence aibubble mobitar claude claudecode chatgpt openai anthropic llms chatbots generativeai genai vc venturecapital salesforce society losers technology google meta siliconvalley andrewbosworth facebook capitalism grift grifting samaltman darioamodei datacenters amazon aws journalism media uber figma elonmusk krishnarao andrewmacdonald marcbenioff klarna sebastiansiemiatowski nvidia gpus blueowl coreweave perplexity greed shamelessness billwinters markzuckerberg andyjassy larryellison sundarpichai satyanadella microsoft oracle values</dc:subject>
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<dc:identifier>https://pinboard.in/u:robertogreco/b:071962409ede/</dc:identifier>
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</item>
<item rdf:about="https://www.noemamag.com/how-ais-see-our-world/">
    <title>How AIs See Our World</title>
    <dc:date>2026-05-26T23:36:42+00:00</dc:date>
    <link>https://www.noemamag.com/how-ais-see-our-world/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["AIs are increasingly perceiving our world, but in order to comprehend it, our user interfaces must operate in reverse."]]></description>
<dc:subject>chenoehart 2026 ai artificialintelligence seeing chatbots openai chatgpt donnorman clivethompson skeumorphism technology computers computing comprehension computation llms elisagiardinapapa aitraining algorithms eryksalvaggio 2022 2023 ux ui theowayt amazon qrcodes cameras tomwilliams 2019 google microsoft morganklaussscheuerman race rfid smartphones data waymo understanding elaineherzberg uber ntsb automstion psysicalai nvidia avs detection tracking driverlesscars apple complexity</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://medialab.sciencespo.fr/en/news/de-lideologie-californienne-a-lideologie-texane-conservatisme-religion-et-extractivisme-au-sein-du-secteur-des/">
    <title>From Californian to Texan Ideology: Conservatism, Religion and Extractivism in the Tech Sector | médialab Sciences Po</title>
    <dc:date>2026-05-23T22:57:21+00:00</dc:date>
    <link>https://medialab.sciencespo.fr/en/news/de-lideologie-californienne-a-lideologie-texane-conservatisme-religion-et-extractivisme-au-sein-du-secteur-des/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["On the occasion of a special session co-organized with the CNRS Center for Internet and Society, the médialab seminar welcomes Fred Turner (Stanford University). He will offer a critical reading of the ideological transformations underway in the American tech world, from California’s libertarian utopia to the more conservative ideology now embodied by Texas.

Abstract

As they leave California for Texas, major digital companies are doing more than looking for new spaces. Their leaders (Elon Musk, Larry Ellison, Joe Lonsdale...) are settling in a state where religion plays a major role, in a Bible Belt dominated by oil billionaires. Texan politics can be summed up in a few words: tax refusal, deregulation, and the narrative of a new frontier populated by “those who are willing to take the necessary risks.” 

Just like oil, digital technologies, including AI and cryptocurrencies, as well as space exploration, depend on public funding and environmental leniency to thrive. So why not take power directly? Tech leaders are now pursuing that path, following in the footsteps of speculative oil investors. 

How did the digital world move from the Californian ideology, where entrepreneurialism was mixed with the legacies of counterculture, to the Texan ideology, shaped by a rejection of any interference except that of the Gospels, and where great, deserving men are seen as working in the name of God? 
Biography  

After a career in journalism in Boston and teaching at MIT and Harvard, Fred Turner is now Professor and Chair of the Department of Communication at Stanford University.

His research explores the relationships between media technologies and cultural transformations, with a particular focus on the role of emerging media in shaping American society since World War II.

He is the author of three influential books: The Democratic Surround: Multimedia and American Liberalism from World War II to the Psychedelic Sixties, From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network and the Rise of Digital Utopianism, and Echoes of Combat: The Vietnam War in American Memory.

Fred Turner’s work has received numerous academic awards and has been translated into French, Spanish, German, Polish and Chinese."

[direct link to video: https://vimeo.com/1137645914

See also:
https://newbooksnetwork.com/fred-turner-on-countercultures-cybercultures-and-californian-and-texan-ideologies
https://thebaffler.com/salvos/the-texan-ideology-turner ]]]></description>
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<item rdf:about="https://newbooksnetwork.com/fred-turner-on-countercultures-cybercultures-and-californian-and-texan-ideologies">
    <title>Fred Turner on Countercultures, Cybercultures, and Californian and Texan Ideologies - New Books Network</title>
    <dc:date>2026-05-23T22:56:29+00:00</dc:date>
    <link>https://newbooksnetwork.com/fred-turner-on-countercultures-cybercultures-and-californian-and-texan-ideologies</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Peoples & Things host, Lee Vinsel, and guest host, Paula Bialski, Associate Professor of Digital Sociology at University of St. Gallen, talk to Fred Turner, Harry and Norman Chandler Professor of Communication at Stanford University, about his classic 2006 book, _From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network, and the Rise of Digital Utopianism_. They briefly explore the arc of Fred’s career and revisit the book in the spirit of asking what has changed in digital ideology since the book’s publication, including with the role of Silicon Valley elites in the second Trump Administration, Elon Musk’s role in DOGE, and the (perhaps only brief) turn of digital technology elites moving from California to Texas. Since this conversation was recorded in April 2025, Fred’s essay, “The Texan Ideology,” has been published in The Baffler: https://thebaffler.com/salvos/the-texan-ideology-turner "

[See also: 
https://medialab.sciencespo.fr/en/news/de-lideologie-californienne-a-lideologie-texane-conservatisme-religion-et-extractivisme-au-sein-du-secteur-des/
https://vimeo.com/1137645914 ]]]></description>
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<item rdf:about="https://www.youtube.com/watch?v=waFl4uBfXRA">
    <title>Marc Andreessen accidentally told the truth about AI - YouTube</title>
    <dc:date>2026-05-22T16:28:52+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=waFl4uBfXRA</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Say no to sleep!

https://x.com/TFTC21/status/2056815935705714945
<blockquote>Marc Andreessen on JRE: AI hasn't replaced coders. It turned them into vampires. / "The opportunity cost of going to sleep is too high because if you go to sleep, you won't be with your 20 AI coding agents."</blockquote>

https://www.youtube.com/watch?v=PHQvb10vKyk
"Joe Rogan Experience #2501 - Marc Andreessen

https://www.bigtechnology.com/p/google-deepmind-ceo-demis-hassabis-946
<blockquote>Google DeepMind CEO Demis Hassabis on AI’s Next Breakthroughs, What Counts As AGI, And Google’s AI Glasses Bet: The leader of Google's AI program weighs in on the cutting edge of AI research, Google's plans to put the technology in its products, and the imperative of publishing AI-generated protein structures.</blockquote>

https://x.com/fchollet/status/2027224640050086310
<blockquote>By explicitly training on specific tasks, we ended up covering a very large area (in absolute terms) of the space of all possible tasks humans can do, but this large area only amounts to 0.00...01% of the total space. And that's why we still need general intelligence. https://x.com/tengyanAI/status/2027220325101175201<blockquote>what would be example of 'novel unfamiliar domains'? seems like we've touched most things</blockquote></blockquote>

https://x.com/fchollet/status/2025401003932352851
<blockquote>The maximalist form of my thesis is basically this: SaaS is not about code, it is about solving a problem customers have and selling them the solution. Services + sales. If the cost of code goes to zero, SaaS will not go away. It will benefit, since code is a cost center.</blockquote>

https://x.com/ylecun/status/2057352321688842577
<blockquote>People are realizing that AIs are nowhere near human intelligence and learning abilities. Yet they have become very useful by compensating for their lack of common sense, lack of understanding of reality, and limited reasoning and planning abilities, by the accumulation of enormous amounts of declarative knowledge.</blockquote>

https://x.com/AutismCapital/status/2056943819351085391
<blockquote>What is there even to say? He’s a genius operator. Offer people nothing for something. Get them locked into the OpenAI ecosystem. Collect equity. Collect information. Further the narrative that compute is the new water and control the flow. Dig your tendrils deeper into the world https://x.com/bosmeny/status/2056914385814401238
<blockquote>A mic drop moment @ycombinator tonight / @sama just offered $2M in OpenAI tokens to EVERY YC startup in the current batch in exchange for equity / Just like Yuri Milner offering to invest in every startup back when Sam was a YC partner / I can't wait to see what's unlocked when you let the most driven, creative and formidable founders tokenmaxx</blockquote></blockquote>

https://x.com/Jason/status/2056919949810028942
<blockquote>Fair warning, YC founders: if you take these tokens, there’s a non-zero chance that OpenAI will study exactly what your startup is doing, copy your idea and put your app into their free offering. / This is the classic platform playbook — be careful, founders! https://x.com/bosmeny/status/2056914385814401238
<blockquote>A mic drop moment @ycombinator tonight / @sama just offered $2M in OpenAI tokens to EVERY YC startup in the current batch in exchange for equity / Just like Yuri Milner offering to invest in every startup back when Sam was a YC partner / I can't wait to see what's unlocked when you let the most driven, creative and formidable founders tokenmaxx</blockquote></blockquote>

https://x.com/jlongster/status/2056362647726035119
<blockquote>“agents running on the cloud 24/7” / bro I can’t leave my agent for 5 minutes before it starts writing crappy architecture or code</blockquote>

https://x.com/adamdotdev/status/2057424064050868410
<blockquote>I talked about this on the standup podcast yesterday, but I'll reiterate here: if you're losing sleep because you need to keep feeding the agents STOP, I promise it's not worth it. You got caught in a [prompt -> reward] dopamine cycle and you're addicted to the feeling of the token slot machine. It's not your fault, but you need to escape before it grinds you into a pulp and you can't look at a computer for a month (this was me). If you can break out of it and spend some more time offline, or find other healthy sources of dopamine in hobbies/etc, you'll start to realize just how warped your perception was and that the thing you were chasing wasn't actually productive. https://x.com/TFTC21/status/2056815935705714945
<blockquote>Marc Andreessen on JRE: AI hasn't replaced coders. It turned them into vampires. / "The opportunity cost of going to sleep is too high because if you go to sleep, you won't be with your 20 AI coding agents."</blockquote></blockquote>

https://x.com/haider1/status/2056487493084799059
<blockquote>Creator of C++, Bjarne Stroustrup: / AI-generated code isn't ready — it generates more bugs, more bloat, more security holes, and is nearly impossible to validate / "senior developers are already retiring rather than deal with it" / The problem is that even a small prompt change can shift the entire codebase in unpredictable ways"</blockquote>]]></description>
<dc:subject>mobitar 2026 marcandreessen ai artificialintelligence coding productivity aibubble aihype openai anthropic google samaltman</dc:subject>
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<item rdf:about="https://freddiedeboer.substack.com/p/llms-and-the-library-card-fallacy">
    <title>LLMs and the Library Card Fallacy - Freddie deBoer</title>
    <dc:date>2026-05-22T08:08:20+00:00</dc:date>
    <link>https://freddiedeboer.substack.com/p/llms-and-the-library-card-fallacy</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["the LLM tutor story is the Khan Academy story is the MOOCs story"

...

"I don’t know how many American colleges and universities will exist in ten years. Probably fewer than now, but then a little right-sizing has made sense for awhile, and would likely increase rather than decrease the health of the system. The ones that keep existing, which is to say most of them, will go on doing what they’ve always done, which is to supply the external scaffolding that the vast majority of human beings require in order to learn anything they don’t already want to learn: deadlines, grades, embarrassment in front of peers, the looming presence of a teacher who will notice…. That scaffolding is the product and always has been. The lectures are incidental, the textbooks are incidental, and the personalized AI tutor will turn out to be incidental too. What is not incidental is the social and institutional pressure that compels an ordinary late adolescent to sit in a room and slog through the Federalist Papers when every fiber of their being would rather be doing anything else. Maybe we can’t make young people feel that pressure in a meaningful way anymore. Maybe. But that just means that our whole society is doomed anyway, and ChatGPT is not going to be able to fix it.

No chatbot can manufacture the desire to learn. And the people who insist otherwise will, a decade from now, write the same essays they’re writing today about how this time the revolution is really, finally, coming. Damp continuity, like I said. I’ve never been the doomer people have made me out to be, but I confess that in the last couple of years I’ve quietly given up, and if LLMs have done one thing for me, it’s to force me to recognize just how little the average person gives a shit and just how willing the great mass of humanity is to slip into apathy and decline. But I do have hope for individuals, the exceptional and talented people who really give a shit. For them, the ones who need it least, the ability to learn is there. The library card has been in our collective wallet for a hundred years. The whole internet has been in our pockets for fifteen. So go learn something."]]></description>
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<item rdf:about="https://aftermath.site/google-search-ai-changes/">
    <title>Google Unveils An Even Worse Search</title>
    <dc:date>2026-05-21T09:01:58+00:00</dc:date>
    <link>https://aftermath.site/google-search-ai-changes/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["As a man with a library science degree and thus a nerd about searching for information generally, stuffing search tools with AI is also bad for everyday people’s ability to understand and query systems, if you’ll bear with me through a little rant. Everyone faces a challenge when exploring a new library catalogue or work database or figuring out boolean operators in Google, but learning to talk to a system in its language is one way we get a sense of how its creators structured it and their worldview and priorities. Going through a system’s results also teaches you how to think about them critically: Are they what I’m looking for, are they trustworthy, what information do they connect to and reveal? Google Search is probably one of the first and primary places that people experiment with and grow their information searching skills; spoonfeeding them AI summaries while obscuring or bypassing the source of the information might seem convenient, but it’s just robbing them of the chance to develop vital information literacy skills that they need more than ever in an AI-obsessed world.

But if you’re just a regular person, this means more AI crap to wrestle with when you’re just trying to find a nearby coffee shop or that article you remember reading 10 years ago. The AI bubble can’t burst soon enough."]]></description>
<dc:subject>google search ai artificialintelligence 2026 rileymacleod enshittification understanding query</dc:subject>
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<item rdf:about="https://kottke.org/26/05/theres-no-earthly-way-of-knowing-which-direction-we-are-going">
    <title>There’s No Earthly Way of Knowing Which Direction We Are Going…</title>
    <dc:date>2026-05-20T06:33:36+00:00</dc:date>
    <link>https://kottke.org/26/05/theres-no-earthly-way-of-knowing-which-direction-we-are-going</link>
    <dc:creator>robertogreco</dc:creator><dc:subject>ai artificialintelligence jasonkottke 2026 writing howwewrite google search internet online gemini resistance olgatokarczuk stevenrosenbaum</dc:subject>
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<item rdf:about="https://www.nybooks.com/articles/2026/05/28/whither-the-nerd-bully-bill-gates/">
    <title>Whither the Nerd-Bully? | Ben Tarnoff | The New York Review of Books</title>
    <dc:date>2026-05-14T15:49:09+00:00</dc:date>
    <link>https://www.nybooks.com/articles/2026/05/28/whither-the-nerd-bully-bill-gates/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Bill Gates was the monopolistic father figure who Silicon Valley’s young founders rebelled against—and, in so rebelling, became."

[archived:
https://archive.is/ClkzU

via:
https://www.theverge.com/microsoft/930433/apropos-of-nothing-in-particular

"Apropos of nothing in particular...

I enjoyed reading this story about Bill Gates’ malevolent influence on the current crop of Silicon Valley megalomaniacs. If you remember his pre-Gates Foundation reputation, you will particularly appreciate it."]

"Source Code strikes a careful balance. Young Gates is curious and precocious but awkward and ill-tempered. He is the beneficiary of an affluent upbringing but possesses the intelligence to make the most of his opportunities. He gets into programming at the perfect time—just ahead of the first microcomputers that make personal computing a reality—but has the foresight and initiative to maximize this advantage.

Even the most meticulously humanized portrait may not be enough. As Das points out, Gates’s stature has suffered as a result of both the Epstein connection and his promotion of vaccines during the pandemic, which made him a villain to various Covid denialists and conspiracists. Relatedly, the position he has historically occupied, that of the liberal billionaire, has become lonelier in recent years. The revival of class politics on the left and the rightward shift of a prominent segment of the tech elite means that the “benevolent capitalism” championed by Gates has fewer takers.

The irony is that benevolent capitalism was the state religion of Silicon Valley when the dot-commers were battling the unbenevolent capitalism of Microsoft—an ethos encapsulated by “Don’t be evil,” Google’s motto for many years. Gates took it up after he went into philanthropy, and has kept the faith much longer than his former competitors.

Still, if Gates has resisted full feralization, he has also tried to ingratiate himself with the current regime, praising Trump after a private dinner in January 2025 and attending a knee-bending ceremony for tech leaders at the White House in September. “Thank you for incredible leadership,” he told the president, seated at a table with Sergey Brin, Mark Zuckerberg, Sam Altman, and several others.

It is clarifying to see Gates in such company. He may once have waged war on Silicon Valley, but the Valley owes much of its present eminence to the playbook he drew up at Microsoft. Gates bent and broke laws, asked not for permission but for forgiveness (and rarely), helped himself freely to the intellectual property of others while vigorously protecting his own, and endeavored not merely to beat his competitors but to extinguish them by any means necessary. Above all he understood that software was the choke point in the personal computing revolution, that as computers proliferated, the code that made those computers useful—and especially their operating systems—would become critically important. Monopolies in the new era would be assembled not from agglomerations of infrastructure such as railroads but through mediating people’s access to the digital world. This privileged position would enable a firm to obtain what economists call “rents”: rather than compete with other companies on price and quality, the digital monopolist could demand something like tribute from his captive customers.

This is the dream that multiple generations of tech entrepreneurs have since pursued. Gates’s initial name for Microsoft Windows was “Interface Manager,” and the phrase aptly summarizes the project continued by his spiritual successors. From Brin to Zuckerberg to Altman, from search engines to social media to chatbots, the goal is to become the interface manager, controlling the surfaces that we use to simplify and humanize computing’s alien depths. Gates is the ghost in our machines."]]></description>
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<item rdf:about="https://theamericanvandal.substack.com/p/afteropenai?triedRedirect=true">
    <title>After OpenAI (Vandal Live at Wake Forest Humanities Institute)</title>
    <dc:date>2026-05-14T04:33:50+00:00</dc:date>
    <link>https://theamericanvandal.substack.com/p/afteropenai?triedRedirect=true</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Apple Podcasts | Spotify

As part of the Spring Symposium at the Wake Forest Humanities Institute, Matt Seybold discusses the present and future of AI speculation, including an extended discussion with Wake Forest faculty, many who were part of WFHI’s Interdisciplinary Faculty Seminar on Language, Theory, & Artificial Intelligence.

Cast (in order of appearance): Jennifer Greiman, Matt Seybold, Derek Lee, Michaela Appeltova, Nisrine Rahal, Barry Trachtenberg, Jeff Bills-Solomon, Dean Franco, Amanda Gengler

Featured Guests

Jennifer Greiman is Professor of English at Wake Forest University and Director of The Humanities Institute there.

Matt Seybold is Associate Professor of American Literature & Mark Twain Studies at Elmira College, as well as resident scholar at the Center For Mark Twain Studies and executive producer of The American Vandal Podcast.

Episode Bibliography

Emily Bender & Alex Hanna, The AI Con (HarperCollins, 2025)

Emily Bender, Timnit Gebru, et al. “On The Dangers of Stochastic Parrots: Can Language Models Be Too Big?” FAccT 2021

Tressie McMillan Cottom, “The Tech Fantasy That Powers AI is Running on Fumes” The New York Times (April 29, 2025)

Michel de Certeau, The Practice of Everyday Life (U California Press, 1984)

Virginia Dignum, The AI Paradox: How To Make Sense of a Complex Future (Princeton UP, 2026)

Ronan Farrow & Andrew Marantz, “Moment of Truth” The New Yorker (April 13, 2026)

Karen Hao, Empire of AI: Dreams & Nigthmares in Sam Altman’s Open AI (Penguin Random House, 2026)

Andy Hines, Outside Literary Studies: Black Criticism & The University (U Chicago Press, 2022)

E. D. Hirsch, Cultural Literacy (Houghton Mifflin, 1987)

Tyler Johnston, “The reporters at this new site are AI bots. OpenAI’s Super PAC appears to be funding it.” Model Republic (April 24, 2026)

Matthew Kirschenbaum, “Grok is an Epistemic Weapon” Tech Policy Press (January 13, 2026)

Matthew Kirschenbaum, “Texpocalypse Now: AI and The New Political Economy of Writing” PennAI (April 17, 2026)

Matthew Kirschenbaum & Rita Raley, “AI & The University as a Service” PMLA (May 2024)

Christopher Newfield, Unmaking The Public University (Harvard UP, 2011)

Britt S. Paris, Radical Infrastructure: Imagining The Internet From The Ground Up (U. California, 2026)

Ann Pettifor, The Global Casino: How Wall Street Gambles with People & The Planet (Verso, 2026)

Ann Pettifor, “The Next Crisis is Coming” Politics Joe (April 1, 2026)

Ann Pettifor, “Is the next financial crisis only a matter of time?” De Balie (February 16, 2026)

Daniel Roher & Charlie Tyrell, The AI Doc, or How I Became An Apocaloptimist (2026)

Matt Seybold, “Against Technofeudal Education” The American Vandal (June 10, 2025)

Matt Seybold, “The Technofeudal Text” The American Vandal (August 25, 2025)

Matt Seybold, “Mamdani Win Could Be The First Step Towards Seizing The Means of Knowledge Production” The American Vandal (November 5, 2025)

Matt Seybold & Eric Hayot, “The ‘Crisis In The Humanities’ Is Over. That’s Not a Good Thing.” Chronicle Of Higher Education (December 29, 2025)

Matt Seybold & John Warner, “The Technology That’s Taking Your Freedom” Academic Freedom On The Line (February 3, 2026)

Matt Seybold et al, “The Secret History of Canvas LMS, Corporate Raiders, & The Chatbot Bubble” The American Vandal (March 24, 2026)

Matt Seybold et al, “HBCUs & The Philanthrocapitalist Swindle” The American Vandal (February 4, 2025)

Jacob Silverman, “The Death of an AI Whistleblower” The Nation (May 2026)

Nick Srnicek, Silicon Empires: The Fight For The Future of AI (Polity, 2026)

Ben Tarnoff, “Frankenstein’s Regret” The Nation (May 2026)

Wake Forest Humanities Institute, “Language, Theory, & Artificial Intelligence” (May 2026)

McKenzie Wark, Capital Is Dead: Is This Something Worse? (Verso, 2019)"]]></description>
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<item rdf:about="https://www.theatlantic.com/ideas/2026/05/waymo-self-driving-cars/687119/">
    <title>Save the Taxi Drivers - The Atlantic</title>
    <dc:date>2026-05-11T20:12:53+00:00</dc:date>
    <link>https://www.theatlantic.com/ideas/2026/05/waymo-self-driving-cars/687119/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["People Who Don’t Like People Are Making All of Our Decisions: Robotaxis are the beginning."

[archived: https://archive.is/fBr8e ]

"In the beginning, God created Man and Man created cities. And from these cities sprang forth a service to cart Man around: the taxi. And it was good. So good that, over centuries, it barely changed. Visitors to ancient Rome could hail a cisium. In 17th-century France, they could take a fiacre. And 19th-century England had the hackney coach. Automobiles eventually replaced horse-drawn carriages, but other than that, the experience remained the same: Passengers hailed a driver who would help them load their luggage and perhaps make small talk about the city while ferrying them to their destination.

Then, in 2009, Man made the ride-share app. And it was very good. Many of the nuisances of taxis that had seemed unavoidable were eliminated overnight. Waiting in the cold with your hand in the air scanning for available cabs? Drivers refusing to take you somewhere after you’d already gotten in their vehicle? Cabs refusing to stop because of your race? Losing items, never to see them again? All problems that were gladly ushered into the past. The act of schlepping around a city was changed forever.

Ride-sharing has its own flaws: surge pricing in inclement weather, incessant rate hikes, late or canceled rides. But in all of the ways I’ve imagined improving upon the modern taxi, eliminating drivers themselves has never crossed my mind. And yet, the powerful minds of Silicon Valley and the investors who fund them are trying to do just that.

Earlier this year, Tesla, which already has a driverless-taxi service, announced that its Gigafactory in Texas would begin producing robotaxis devoid of steering wheels or pedals. Waymo, the Alphabet-owned driverless-taxi service that launched commercially in 2020, recently raised $16 billion, and plans to expand into more than 20 cities. In November, Los Angeles and San Francisco, where Waymos were already operating, started allowing the vehicles to travel on highways and to certain airports. Waymo now has its sights set on America’s taxi mecca: New York City.

The pitch for driverless taxis follows the familiar contours of many of Silicon Valley’s recent technological advances: We should all be excited about a “dream” from the future finally being realized. The thrill of inevitable progress! A safer, easier tomorrow!

Driverless taxis are the next step toward tech’s hopes for broad adoption of driverless cars in general. Uri Levine, a co-founder of Waze, predicts that Generation Beta will not drive. “A generation after that,” he told Business Insider, if you tell a young person “that you used to drive cars yourself, they will not believe you.” One of the arguments for self-driving cars is that they would be free of the human errors that lead to crashes. “It’s going to be such a great technology,” Sebastian Thrun, the roboticist and former head of Google’s self-driving project, said recently. “Think of the 1.2 million lives we lose each year (to car crashes), mostly because they’re not paying attention. Think if we could get some of those lives back.”

That number is correct. But that figure is global, and more than 90 percent of the fatalities occur in low- and middle-income countries (ones that are not part of Waymo’s or Tesla’s expansion plans). Trade organizations such as the Autonomous Vehicle Industry Association, which advocates for “the safe and timely deployment of autonomous driving technology,” insist that driverless cars will save lives. But groups such as the Union of Concerned Scientists are more skeptical, pointing out that “studies have shown that automated vehicles are less able to detect people of color and children.” They also worry that the cars could “displace millions of people employed as drivers, negatively impact public transportation funding, and perpetuate the current transportation system’s injustices.”

More certain than safety are profits. When companies talk about safety, it’s not just because they care about people, but because they want to sell their product. Self-driving cars are projected to be an $87 billion industry by 2030. And the robotic “passenger economy,” which includes driverless taxis and robot deliveries, could generate as much as $7 trillion by 2050.

Chances are slim that the average American will benefit much financially from any of that money. But we will lose something, as Big Tech yet again destroys human interaction and calls it “convenience.”

Most of us live in silos, clustered together with people whose jobs, educations, incomes, languages, and faiths are similar to or the same as our own. We have few occasions to brush against other ways of living, few ways to interact with people of different backgrounds. These moments are meaningful and rare, and the taxi cab is one place where they regularly happen.

Every new city that I visit comes with a personalized introduction from a taxi driver. Like the guy who used to do stunts in Hollywood and now has to pick up shifts driving cabs who regaled me with tales of stars and action movies in a more flush time in Los Angeles. Or the 60-something Navy vet who took up driving after his restaurants closed during the pandemic. He drove me to the airport in Pittsburgh and told me about having recently connected with a son he never knew he had, who’d found him on Ancestry.com. Or the young driver from Pakistan who was nervously preparing for his upcoming wedding. He got some free advice, as well as a nice tip.

Many of these drivers are immigrants. Many are people whom the economy has left behind—people who started driving to supplement day jobs and struggling businesses, or because they’re juggling caregiving responsibilities. Perhaps, Big Tech thinks that riders won’t miss them when they’re gone. Drivers can be annoying. They can talk too much. They can play music you don’t like. But they can also be generous and kind and surprising. Human interaction, imperfect as it is, is what makes us human.

And maybe that’s the problem for the titans of Silicon Valley. Compared with robots, humans take a lot of effort. “I cannot imagine having gone through figuring out how to raise a newborn without ChatGPT,” Sam Altman, the CEO of OpenAI, said recently. Artisan, an AI start-up, advertises its services with the explicit slogan “Stop Hiring Humans.” We are living in the ultimate revenge of the nerds, driven by a crew of socially awkward tech bros who won’t stop until the society that they never quite fit into is obliterated.

Do we want these people dictating profound changes in our society? Technology advances, in part, because a small number of entrepreneurs or scientists get really hyped about something, and another small number of investors gets even more hyped about the massive financial opportunities that development represents. But the rest of us do have a say: We have a choice as to whether we want to adopt that technology or not. We can consider our preferences, and the long-term societal implications. We can resist the old-fashioned corporate greed that gets wrapped in the language of pro-humanistic societal advancement and care.

For two decades, I have watched us blindly fall for one sales pitch after another. Every app and advancement comes shrouded in promises of “progress” and “connectivity” and “convenience.” And in many early cases—such as the invention of ride-sharing apps—Silicon Valley truly did deliver a better mousetrap. But we’re getting diminishing returns. We are living in Silicon Valley’s future now, and we are lonelier, more anxious, and more polarized than ever before. Are the mousetraps better? Safer? Who knows. But the mice inside are miserable."]]></description>
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<item rdf:about="https://adamtooze.substack.com/p/chartbook-447-the-us-economy-in-may">
    <title>Chartbook 447: The US economy in May 2026 - How much cognitive dissonance can you handle?</title>
    <dc:date>2026-05-11T01:03:20+00:00</dc:date>
    <link>https://adamtooze.substack.com/p/chartbook-447-the-us-economy-in-may</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["So, the money is going around and around.

Perhaps what is at play is the old adage that if the music is playing you have to dance.

Or perhaps. as Gita Gopinath argues, it is all down to moral hazard. The markets don’t actually have to believe that all is well. They just need to believe that if something does go wrong they will be bailed out - the so-called “bliss trade”. COVID, Ukraine and now Hormuz may all be symptoms of polycrisis, or what James Meadway calls “permament crisis”. The idea that the world ever “returns to normal” may be naive. But what has also changed is the response function of policy. To each successive crisis since 2020, as Gopinath points out, fiscal policy has reacted with “big lasting state support”. At some point this is priced into the market:

<blockquote>Such a belief is consistent with government actions over the past several years, actions that have driven public debt levels ever higher and expanded central bank balance sheets. Global public debt is now projected to reach 100 per cent of GDP by 2029. During the pandemic, the balance sheets of households and firms were not just rescued but boosted by very large government support that averaged 25 per cent of GDP for advanced economies, including assistance in the form of equity injections, loans and government guarantees to companies. This boost has buoyed consumer and business finances for several years. When Russia’s invasion of Ukraine set off an energy crisis, governments in Europe spent 2.5 per cent of GDP in energy support in the form of broad-based price-suppressing measures when it would have required only 0.9 per cent of GDP to fully compensate the bottom 40 per cent of households for the entire rise in energy costs. Germany, Italy and Spain have all reactivated price-distorting taxes and subsidies to insulate people from the current energy price surge. There are plenty of good reasons for the state to provide support in a crisis. However, the past several years of government support have gone against sound fiscal advice by being large and lasting instead of targeted and temporary. … The urge to rush to the rescue, regardless of merit, was recently evident in President Donald Trump’s attempts to bail out the US budget carrier Spirit Airlines as he mused “I’d love to be able to save an airline”. While the bailout ultimately did not go through, it does not take much imagination to predict that in a real crisis, government support in the US would be excessive. Moreover, while Taco is idiosyncratic and dependent on the psychology of the US president, Bliss is structural. Research shows that political parties of all stripes, from socialists to conservatives, all now favour higher government spending, and fiscal restraint has few champions.</blockquote>

Of course, a policy of crisis-management is better than none. But in a model of moral hazard each bailout results in a build-up of ever greater risks. Speculators are more irresponsible and financial leverage builds up. And it is the public balance sheet that absorbs the hit. As Gopinath points out:

<blockquote>The Bliss trade is reflected in the divergence between the prices of stocks and government bonds. While equity markets have held up surprisingly well, government bonds have suffered even as long-run inflation expectations have stayed mostly anchored. Since the start of the Iran conflict, long-term government bond yields have risen across major economies including the US, Europe and Japan. This divergence has become a pattern over the past several years. Term premia on 10-year US treasury yields are now close to 100 basis points higher than they were before the pandemic, driving up the interest rate bill. … The IMF predicts that in a severe scenario, the Iran conflict could cause global growth to fall to 2 per cent (instead of the reference forecast of 3.1 per cent) and global debt could rise past 120 per cent of GDP. … As compared to before the pandemic, the scope to deliver on fiscal largesse is limited. Even in advanced economies, the sensitivity of borrowing costs to debt issuance has increased, which then spills over into emerging and developing economy borrowing costs. Even as bond prices have declined, markets may be too sanguine about the consequences of rising debt on fiscal health.</blockquote>

To say that the inherent fragility of the system is not addressed is an understatement. Deregulation being pushed by lobby groups and their friends in the Trump administration is opening the door to all manner of risk-taking. Meanwhile, the underlying problems, whether that be the disorder in US politics, the unresolved tensions in the Middle East or the possible impacts from AI go completely unaddressed or denied. Indeed, in the Middle East, the US is fully backing the all-out disruption being pushed by Netanyahu’s government.

Gopinath urges that

<blockquote>Policymakers would do well to use this period in which stock markets seem disconnected from heightened risk to craft a new playbook for crisis support that is both fiscally sustainable and supportive of long-term growth. The experiences of the pandemic and Ukraine war provide a valuable lesson in what that should look like: support targeted to the vulnerable; bailouts only to companies that are liquidity constrained but otherwise viable — and whose failure poses systemic risks; and co-ordinated fiscal and monetary policy so they do not work at cross-purposes.</blockquote>

But this kind of systemic, holistic risk management looks increasingly like a pious fiction, out of touch with reality. That for Gopinath risks an escalating unmooring of once conventional policy norms:

<blockquote>If a new course is not charted, governments constrained by fiscal space may rely on heterodox measures, including broad-based price controls, financial repression, nationalisations, and pressure on central banks to absorb fiscal risk.</blockquote>

A progressive might welcome such outcomes. Financial repression and Treasury-central bank cooperation are topics to which we should definitely return. But it would be dangerous to assume that financial markets will take the same view. For now, the bond vigilantes may be in abeyance. But don’t count on it. As Gopinath warns, if investors wake up with a start to the world they are actually in the reaction could be nasty.

<blockquote>None of this would be good for the economy with synchronised sell-offs across stocks and bonds as markets realise that the backstop they were counting on is no longer there.</blockquote>

In short, the complacency of the current moment may morph into something far more unstable and potentially dangerous.

All this is the fruit of reading just a few days of coverage in one newspaper - admittedly the world’s best ;).

So here is the question in the spring of 2026: How much cognitive dissonance can you handle?"]]></description>
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<item rdf:about="https://nymag.com/intelligencer/article/palantir-yale-conference-ai.html">
    <title>Palantir Comes to Campus</title>
    <dc:date>2026-05-11T00:45:39+00:00</dc:date>
    <link>https://nymag.com/intelligencer/article/palantir-yale-conference-ai.html</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[[archived:
https://archive.is/M2eav ]

"At a quiet conference at Yale, the company and its allies sketched a vision for AI, state power, and how to mix the two."

...

"Sulkin asked whether colleges in the face of AI-induced job loss should abandon career prep and return to something older: “soul formation.” Kimball took the opening. Yale had been “distracted” from education by “performative concern with so-called social justice,” he said. The humanistic enterprise, he warned, was probably “moving outside of universities right now.” Princeton Classics graduates, he added, couldn’t even read Latin. The connection between these matters and Palantir might seem tenuous. But Karp and his director of corporate affairs, Nicholas Zamiska — another conference speaker — have insisted otherwise.

In their book, The Technological Republic, they contend that Silicon Valley lost its way after the Cold War as the technology sector retreated from the public interest and into “luxury beliefs” — opposition to using software to help law enforcement among them. The rot, in their telling, began in higher ed: Stanford dropped its History of Western Civilization requirement in 1968, and the generation that built the internet grew up constructing its identity “in opposition to the state.” It became squeamish about helping governments do government things, like deporting people.

Karp and Zamiska take particular offense at Google’s former motto, “Don’t be evil.” That old maxim reflects, they write, a mind-set that prizes moral clarity over “the more difficult and often messy task of navigating the world in all of its imperfection.” Palantir would not make the same mistake.

In the Trump era, that policy has been particularly profitable. The firm’s revenue grew 93 percent last year, and Palantir became one of the 20 most valuable American companies. It landed a string of major government contracts, including $30 million from ICE last April to build ImmigrationOS, a platform to select targets for deportation; $10 billion from the Army; $1.3 billion from the Pentagon to build Maven, a drone-imagery-labeling software; and nearly $448 million from the Navy. Today, its stock price stands at more than triple its level than on the eve of the 2024 election. Earlier in April, when the stock dipped, the president went on Truth Social to praise Palantir’s “great war fighting capabilities and equipment” — and posted its ticker symbol.

Exactly how far does Palantir’s wish list — “a union of the state and the software industry,” as The Technological Republic puts it — go? The conference’s speakers ranged from highly skeptical to fully dismissive of AI regulation. During Zamiska’s talk, Wittenstein — his interviewer and his old classmate at Yale — asked Palantir’s director of corporate affairs whether there were any “red lines” where government regulation of AI might be warranted. Zamiska didn’t name any. Sure, he could “understand the anxiety that comes with this current moment.” But what he wanted instead of regulation was “a much deeper, richer, more integrated public-private partnership.”

The conference’s dedicated panel on AI regulation struck a similar tone. Dean Ball, a former Trump adviser and the lead author of the administration’s AI Action Plan, had little patience for most of the over 1,500 AI-related bills introduced in state legislatures. There was, he acknowledged, “a small subset of bills that grapple with things like catastrophic risk” that he supported. But rules against asking AI for legal advice, he said, were “stupid.” There “probably should be a national framework” for catastrophic AI-risk reporting, he said, but “the goal of AI governance should not be to solve every profound and interesting question.”

Ball, who is now a fellow at the Foundation for American Innovation, mused that AI might replace the Supreme Court, then the United States government itself. AI, he said, was “this giant acid vat” dissolving society’s mediating institutions. “Future institutions will be machinic,” he said. “It will not be AI in government. It’s going to be AI as governments.”

But was all this good? The Republic was “decaying,” Ball said, and we’re living in “very dangerous times.” He was certain, though, that the AI revolution was coming — and if America didn’t build superintelligence first, China would. He said he was a “techno-optimist and institutional pessimist.” The reason America currently leads China in AI development, he explained, had nothing to do with the innovation ecosystem or even the rule of law. “It is because we have more computers than they do, and they’re better,” he said. “That’s why.” The U.S. needed to keep it that way.

Elliot Gaiser, Ball’s co-panelist and the assistant attorney general of the Office of Legal Counsel, was more circumspect. Handing governance to machines, he said, would not strike “the sovereign people who are trying to govern ourselves in this Republic” as “particularly comforting.” But he didn’t categorically rule it out. The government official was also more practical. The Attorney General had already established a task force at the DOJ, he explained, whose mission was to find state laws “inconsistent with having a unified free-market regulatory approach to AI.” At the conference, he floated a legal theory that would give the president broad authority to build data centers wherever and whenever he liked. Using the Defense Production Act, passed by Congress in 1950, the president could allocate resources and override contracts when “necessary and appropriate for national defense.” Gaiser had already applied this logic to override state regulations blocking an oil pipeline in California, he said — establishing that a presidential executive order can preempt state law under the Supremacy Clause.

Environmental activists had worried the administration would eventually apply the same logic to force data centers into communities that had resisted them. Gaiser confirmed their suspicions. “That would apply to other forms of production,” he said, “in a certain circumstance.”

Even in this room, though, the administration’s war on Anthropic had not gone over well. Ball called the fight “counterproductive” and said he’d warned the administration not to pick it. “Anthropic has every right to set the terms on which it does business,” he added. General Timothy Haugh, former NSA director, agreed during a different panel: “It’s a step back for the department,” he said, and “the department has no mission to do surveillance in the United States.” Gaiser, Trump’s man in the room, offered nothing in the administration’s defense. He wouldn’t comment upon ongoing litigation, he said.

When we broke for a reception, I shuffled into the next room and mingled. The Yale students found the Palantirians; the Palantirians found the Trump people; everyone found the open bar. These are exactly the sorts of relationships that have made the Trump presidency so good for Palantir. I fell in with a circle of undergrads, and one asked the others what they thought of Palantir. They glanced at one another: thumbs down, mostly. A few pointed theirs sideways. “It’s not a morally great company,” one student, a freshman, told me. “I would not be comfortable with all my information being accessible to the U.S. military.”

But when the pay is good and the job is prestigious — and the alternative is unemployment — the Ivy League undergraduate’s moral calculus can shift. “A job is a job,” that freshman told me. She knew someone whose sister, a soon-to-be Ivy graduate, had struck out almost everywhere she’d applied. Palantir, in the end, was one of only two firms still returning her calls. “I’m catching on to the fact that people are struggling,” she said. And “who else is gonna help you if you can’t get a job?”"]]></description>
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    <title>Could Claude Mythos Actually Destroy the Internet? - The Ringer</title>
    <dc:date>2026-05-07T20:24:25+00:00</dc:date>
    <link>https://www.theringer.com/2026/05/06/tech/claude-mythos-anthropic-project-glasswing-cybersecurity-threat-ai</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["When Ford rolls out a new pickup truck, the CEO generally doesn’t go around giving keynote addresses about how much more lethal it will make American highways. But the AI industry is selling a narrative — a mythos, if you will — as much as it’s selling a product, and that narrative is one of revolutionary, transformational power. “Our product can make your life a bit easier, although there are still a lot of kinks to iron out” is not a trillion-dollar sales pitch; “we’ve invented something so powerful that it has the potential to destroy humanity” is. The company that can end the world controls the future, and investors will spend big on that upside bet. After all, if the world ends, an investor’s losses won’t matter anyway."

...

"Butterfly no. 7: What do we think of Anthropic as a whole? It’s supposed to be the good AI company, right?

Let me answer that by repeating the phrases “$900 billion valuation” and “trillion-dollar IPO.” I’m not sure it’s possible for “good” to coexist with those numbers. Anthropic cultivates a reputation as the thoughtful, careful, responsible AI company, the one that’s committed to using AI as a tool to assist human flourishing. (The name Anthropic comes from the Greek word for human, as seen, for instance, in misanthropic, someone who dislikes humanity.) I think this is mostly nonsense. Anthropic does strike me as the best of the new breed of tech giants, but this is less because the company itself is so moral and more because some of its peers are so plainly sociopathic. It doesn’t take a saintly corporation to be better than Palantir. Any company that’s not actively trying to create a techno-fascist police state can do it.

Anthropic does some things that look moderately heroic, such as refusing to let the Pentagon use its AI products to kill people without human involvement. This, it has to be said, is a pretty low moral bar to clear, but it’s more than OpenAI could manage, and it landed Anthropic in some real hot water with the government. On the other hand, every time the company does something laudable, more information follows that seems to make it look worse—its partnership with Palantir to develop military applications, for instance. It’s been reported that Claude was used for “target identification” as part of U.S. Central Command’s recent actions in the Middle East.

My view is that Anthropic is chiefly motivated by money, like most large corporations, and has simply incorporated an aesthetic of conspicuous virtue as a branding element to distinguish it from its competitors. In an earlier era of the internet, Google did the same with its old slogan “Don’t be evil.” We saw how that worked out."]]></description>
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<item rdf:about="https://www.aaup.org/issue/spring-2026/what-does-ai-do">
    <title>What Does AI Do? by Daniel Greene | AAUP</title>
    <dc:date>2026-05-07T06:05:04+00:00</dc:date>
    <link>https://www.aaup.org/issue/spring-2026/what-does-ai-do</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["University management and technologies of crisis."]]></description>
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    <title>Silicon Valley has forgotten what normal people want | The Verge</title>
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    <link>https://www.theverge.com/tldr/915176/nft-metaverse-ai-weirdos</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["What NFTs, AI and the metaverse tell us about “thought leadership”"]]></description>
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    <title>What Will It Take to Get A.I. Out of Schools? | The New Yorker</title>
    <dc:date>2026-04-26T00:45:03+00:00</dc:date>
    <link>https://www.newyorker.com/culture/progress-report/what-will-it-take-to-get-ai-out-of-schools</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The tech world assumes that A.I.-aided education is necessary and inevitable. A growing number of parents, educators, and cognitive scientists say the opposite."]]></description>
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<item rdf:about="https://www.theverge.com/podcast/917029/software-brain-ai-backlash-databases-automation">
    <title>BEWARE SOFTWARE BRAIN | The Verge</title>
    <dc:date>2026-04-24T05:54:42+00:00</dc:date>
    <link>https://www.theverge.com/podcast/917029/software-brain-ai-backlash-databases-automation</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["﻿Software brain is changing the world, but most people still aren’t buying."

...

"So what is software brain? The simplest definition I’ve come up with is that it’s when you see the whole world as a series of databases that can be controlled with the structured language of software code. Like I said, this is a powerful way of seeing things. So much of our lives run through databases, and a bunch of important companies have been built around maintaining those databases and providing access to them.

Zillow is a database of houses. Uber is a database of cars and riders. YouTube is a database of videos. The Verge’s website is a database of stories. You can go on and on and on. Once you start seeing the world as a bunch of databases, it’s a small jump to feeling like you can control everything if you can just control the data.

But that doesn’t always work. Here’s an example: Elon Musk and DOGE showed up in the government, and the first thing they did was take control of a bunch of databases. And they ran into the undeniable fact that the databases aren’t reality, and DOGE ended in hilarious failure. It turns out software brain has a limit — the government isn’t software. People aren’t computers, and they don’t live in automatable loops that can be neatly captured in databases.

Anyone who’s actually ever run a database knows this. At some point, the database stops matching reality. At that point, we usually end up tweaking the database, not the world. But the AI industry has fully lost sight of this, because AI thrives on data. It’s just software, after all. And so the ask is for more and more of us to conform our lives to the database, not the other way around.

Let me offer you another example that I think about all the time, especially as AI finds real fit as a business tool. It’s the idea that AI is coming for lawyers and the legal system. The AI industry loves to talk about not needing lawyers anymore, which is already getting all kinds of people into all kinds of trouble. But I get it. I’ve spent a lot of time with lawyers. I used to be a lawyer. My wife is still a lawyer. Some of my best friends are lawyers.

I also spend all of my time at work talking to tech people. And so over time, I’ve learned that the overlap between software brain and lawyer brain is very, very deep. Alluringly deep. If the heart of software brain is the idea that thinking in the structured language of code can make things happen in the real world, well, the heart of lawyer brain is that thinking in the structured legal language of statutes and citations can also make things happen. Hell, it can give you power over society.

There are other commonalities. Both software development and the law depend heavily on precedent. We have a body of case law in this country, and we use it over and over again to help us resolve disputes, just like software engineers have libraries of code that they turn to repeatedly to build the foundations of their products. The similarities run deep: at the end of the day, both lawyers and engineers do their best to use formal, structured language to guide the behavior of complicated systems in predictable and potentially profitable ways.

(I am far from the first person with this idea, by the way. Larry Lessig wrote a book called Code and Other Laws of Cyberspace in 2000. It’s just as relevant today as it was a quarter century ago.)

This intoxicating similarity between law and code trips people up all the time. People are constantly trying to issue commands to society at large like it’s a computer that will obey instructions. There are examples of this big and small — my favorite are those Facebook forwards insisting Mark Zuckerberg does not have the right to publish people’s photos. Honestly, I look at these, and I think it would be great if the law was actually code. Maybe things would be more predictable. Maybe we’d feel more in control.

But law isn’t actually code, and society and courts aren’t computers. I have to remind our fairly technical audience on Decoder and at The Verge all the time that the law is not deterministic. You simply cannot take the facts of a case, the law as written, and predict the outcome of that case with any real certainty, even though the formality of the legal system makes people think it works like a computer — that it’s predictable.

But at the end of the day, it’s actually ambiguity that’s at the very heart of our legal system. It’s ambiguity that makes lawyers lawyers. Honestly, it’s ambiguity that makes people hate lawyers because it’s always possible to argue the other side, and it’s always possible to find the gray area in the law. That’s why prosecutors end up working as defense attorneys and why our regulators tend to end up working for big corporations.

You can see the obvious collision between software brain and lawyer brain here. This thing that looks like a computer isn’t actually anything at all like a computer. A lot of people even argue that the law should be more like a computer, that the system should be verifiable and consistent, and that merely issuing the right commands at the right times should lead to objectively correct outcomes.

Bridget McCormack, who used to be the chief justice of the Michigan Supreme Court, was on Decoder a few months ago pitching a fully automated AI arbitration system. Her argument to me was that people perceive the traditional legal system to be so unfair that they will accept a worse outcome from an automated system as more fair as long as they feel heard. And if there’s one thing AI can do, it’s sit there and listen all day and night.

I don’t know if any of that is correct or even workable, but I do know software brain, and that is pure software brain: the idea that we can force the real world to act like a computer and then have AI issue that computer instructions.

You can see the same thing happening in every other kind of industry. You don’t hire a big consulting firm to actually come in and study your business and make it more efficient. You hire them to make slide decks that justify layoffs to your board and shareholders. Big consulting firms are great at this, and now they’re just going to generate those decks with AI. They are already doing this and the layoffs have already begun.

Any business process that looks like code talking to a database in a repetitive way is up for grabs. That’s why Anthropic has been so relentlessly focused on enterprise customers, and it’s why OpenAI is now pivoting to business use. There’s real value in introducing AI to business, because so much of modern business is already software: collecting data, analyzing it, and taking action on it over and over again in a loop. Businesses also control their data, and they can demand that all their databases work together.

In this way, software brain has ruled the business world for a long time. AI has just made it easier than ever for more people to make more software than ever before — for every kind of business to automate big chunks of itself with software. It’s everywhere: the absolute cutting edge of advertising and marketing is automation with AI. It’s not being a creative.

But: not everything is a business. Not everything is a loop! The entire human experience cannot be captured in a database. That’s the limit of software brain. That’s why people hate AI. It flattens them.

Regular people don’t see the opportunity to write code as an opportunity at all. The people do not yearn for automation. I’m a full-on smart home sicko; the lights and shades and climate controls of my house are automated in dozens of ways. But huge companies like Apple, Google and Amazon have struggled for over a decade now to make regular people care about smart home automation at all. And they just don’t.

AI isn’t going to fix that. Most people are not collecting data about every single thing that they do. And if they’re collecting any at all, it’s stored across lots of different systems — your email in Gmail, your messages in iMessage, your work schedule in Outlook, your workouts in Peloton. Those systems don’t talk to each other and maybe they never will, because there’s no reason for them to. Asking people to connect them all freaks them out.

Even taking the time to consider how much of your life is captured in databases makes people unhappy. No one wants to be surveilled constantly, and especially not in a way that makes tech companies even more powerful. But getting everything in a database so software can see it is a preoccupation of the AI industry. It’s why all the meeting systems have AI note takers in them now. It’s why Canva, which is design software, now connects to corporate email systems. My friend Ezra Klein just went to Silicon Valley, and he described the people that are actively trying to flatten themselves into a database:

    Ezra Klein: You might think that A.I. types in Silicon Valley, flush with cash, are on top of the world right now. I found them notably insecure. They think the A.I. age has arrived and its winners and losers will be determined, in part, by speed of adoption. The argument is simple enough: The advantages of working atop an army of A.I. assistants and coders will compound over time, and to begin that process now is to launch yourself far ahead of your competition later. And so they are racing one another to fully integrate A.I. into their lives and into their companies. But that doesn’t just mean using A.I. It means making themselves legible to the A.I.

<blockquote>You can give it access to everything that’s there: your files, your email, your calendar, your messages. It operates continuously in the background, building a persistent memory of your preferences and patterns so it can better act on your behalf. The cybersecurity risks are glaring, but there’s a reason millions of people are using it: The more of your life you open to A.I., the more valuable the A.I. becomes.</blockquote>

I’ve reviewed a lot of tech products over the past decade and a half, and all I can tell you is that it is a failure when you ask people to adapt to computers. Computers should adapt to people. Asking people to make themselves more legible to software —to turn themselves into a database — is a doomed idea.

It’s an ask so big that I can’t imagine a reward that would make it worth it for anyone, even if the tech industry wasn’t constantly talking about how AI will eliminate all the jobs, require a wholesale rethinking of the social contract and — oops — also the latest models might cause catastrophic cybersecurity problems that might lead to the end of the world.

Does this sound like a good deal to you? Can you market your way out of this? This only makes sense if you have software brain — if your operative framework is to flatten everything into databases that you can control with structured language. The people paying thousands of dollars a month to set up swarms of OpenClaw agents and write thousands of lines of code are people who look at the world and see opportunities for automation, to repeat tasks, to collect data. To build software. AI is great for them. It’s even exciting in ways that I think are important and will probably change our relationship to computers forever."]]></description>
<dc:subject>nilaypatel ai artificialintelligence software databases data publicopinion technology internet web online genz generationz zoomers darioamodei anthropic samaltman openai chatgpy claude satyanadella microsoft markzuckerberg facebook google amazon apple ezraklein openclaw society</dc:subject>
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</item>
<item rdf:about="https://www.wheresyoured.at/four-horsemen-of-the-aipocalypse/">
    <title>Four Horsemen of the AIpocalypse</title>
    <dc:date>2026-04-22T03:12:34+00:00</dc:date>
    <link>https://www.wheresyoured.at/four-horsemen-of-the-aipocalypse/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Table of Contents

Anthropic’s Products Are Constantly Breaking Because It Doesn’t Have Enough Capacity, And Opus 4.7 Is Both Worse and Burns More Tokens

> Anthropic Has No Good Solutions To Its Capacity Issues And Shouldn’t Be Accepting New Customers — And More Capacity Will Only Lose It Money

> Anthropic’s Growth Story Is A Sham Based on Subsidies and Sub-par Service

> Claude Mythos Was Held Back Due To Capacity Constraints, Not Fears Around Capabilities

AI Compute Demand Is Being Inflated By Anthropic and OpenAI, With More Than 50% of AI Data Centers Under Construction Built For Two Companies, and Only 15.2GW of Capacity Under Construction Through The End of 2028

NVIDIA Claims To Have $1 Trillion In Sales Visibility Through 2027, But Only $285 Billion GPUs Worth Of Data Centers Are Under Construction — NVIDIA Is Selling Years’ Worth of GPUs In Advance And Warehousing Them

AI Is Really Expensive, With Companies Spending As Much As 10% Of Headcount Cost On LLM Tokens, And May Reach 100% of Headcount Cost In The Next Few Quarters

The Subprime AI Crisis Continues, With Microsoft Starting Token-Based Billing For GitHub Copilot Later This Year, And Anthropic Already Moving Enterprise Customers To API Rates

This Is The Era of AI Hysteria"]]></description>
<dc:subject>ai artificialintelligence anthropic openai aibubble nvidia edzitron finance 2026 generativeai genai chatbots claude chatgpt coreweave datacenters amazon google googlecloud microsoft computing</dc:subject>
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<item rdf:about="https://om.co/2026/04/16/eat-your-words/">
    <title>Eat Your Words – On my Om</title>
    <dc:date>2026-04-17T04:00:49+00:00</dc:date>
    <link>https://om.co/2026/04/16/eat-your-words/</link>
    <dc:creator>robertogreco</dc:creator><dc:subject>ommalik samaltman kylechayka openai siliconvalley chrislehane google anthropic daropamodei wallstreet doublespeak aibubble openclaw technology messaging ai artificialintelligence michaelcembalest jpmorganchase darioamodei</dc:subject>
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<item rdf:about="https://www.newyorker.com/culture/infinite-scroll/ai-has-a-message-problem-of-its-own-making">
    <title>A.I. Has a Message Problem of Its Own Making | The New Yorker</title>
    <dc:date>2026-04-17T03:57:41+00:00</dc:date>
    <link>https://www.newyorker.com/culture/infinite-scroll/ai-has-a-message-problem-of-its-own-making</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["OpenAI’s Sam Altman wants to “de-escalate” the rhetoric around A.I. But if you tell people that your product will upend their way of life, take their jobs, and possibly threaten humanity, they might believe you."]]></description>
<dc:subject>kylechayka samaltman openai ai artificialintelligence chatgpt danielalejandromoreno-gama anthropic darioamodei aihype projectglaswing mythos amazon cisco jpmorganchase jeffbezos markzuckerberg bigtech google messaging danielmoreno-gama</dc:subject>
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<item rdf:about="https://thehustle.co/originals/why-weekends-are-under-threat">
    <title>Why weekends are under threat</title>
    <dc:date>2026-04-15T06:38:37+00:00</dc:date>
    <link>https://thehustle.co/originals/why-weekends-are-under-threat</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Just like Uber and Facebook, weekends thrive because of something known as network effects. Always-on work culture weakens them."]]></description>
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<item rdf:about="https://www.youtube.com/watch?v=ZqVuNSx7sgs">
    <title>Waymo Says Its Cars Are Safe. Here’s What They Don’t Want You To Know. - YouTube</title>
    <dc:date>2026-04-13T16:25:35+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=ZqVuNSx7sgs</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["If Waymo gets its way, 2 million workers will be out of work.

When Waymo gets a firm hold on a city, wages go down. Some drivers now have to work 12 hours day, 7 days a week just to get by.

This isn't inevitable — but Big Tech is spending millions to make you think it is."]]></description>
<dc:subject>avs waymo uber moreperfectunion labor drivers driving taxis transit transportation legislation law legal google 2026 nyc ericgardner outsourcing economics bigtech work workers employment economy local donaldtrump policy</dc:subject>
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<item rdf:about="https://www.wheresyoured.at/ai-is-really-weird/">
    <title>AI Is Really Weird</title>
    <dc:date>2026-04-09T20:25:19+00:00</dc:date>
    <link>https://www.wheresyoured.at/ai-is-really-weird/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Table of Contents

We Are Not In The Early Days of AI, And It’s Weird To Say That We Are

Why Is Everybody Lying About What AI and “Agents” Can Actually Do?

Let’s Talk About The Actual Consequences of Coding LLMs

The Economics Of AI Are Weird And Bad, And It’s Even Weirder That People Try And Normalize Them

It’s Very Weird That The Media Ignored My Reporting on OpenAI’s Revenues, and Anthropic’s Statement That It Made $5 Billion In Revenue Through March 9, 2026

It’s Weird That The Media Continues To Normalize OpenAI And Anthropic Losing Billions of Dollars

Does Anthropic Measure Its Gross Margins Based On How Much Revenue A Model Made Rather Than Revenue Minus COGS?

OpenAI and Anthropic Lose Billions of Dollars, But The Media Normalizes It In Any Way It Can, Acting As If Model Training Is Capex When It’s Actually A Cost of Goods Sold

Anthropic’s Revenue Growth Is Weird and Suspicious — How Did It Go From $700 million in monthly revenue in December 2025 to $2.3 to $2.5 billion in April 2026?

Anthropic’s Sonnet and Opus 4.6 Models Burn More Tokens Than Previous Models, and enable a 500% Larger 1 Million Token Context Window By Default, Artificially Inflating Costs For Similar Gains

Does Meta’s “TokenMaxxing” Account For A Quarter of Anthropic’s Revenue?

Measuring Worker Output In Token Consumption Is Incredibly Weird, and TokenMaxxing Is Not A Sustainable Business Model

TokenMaxxing Is A Valley-Wide Problem, Raising The Costs of Running Any Software Team Based On How AI-Crazed Your CEO Has Become — And When Cost Cuts Begin, API Revenue Will Collapse

The AI Bubble Is Weird, Irrational and Wasteful, And It’s Even Weirder That It’s A Fringe Opinion To Say So"

...

"I can’t get over how weird the AI bubble has become.

Hyperscalers are planning to spend over $600 billion on data center construction and GPUs predominantly bought from NVIDIA, the largest company on the stock market, all to power generative AI, a technology that’s so powerful that none of them will discuss how much it’s making them, or what it is we’re all meant to be so excited. 

To make matters weirder, Microsoft, a company that spent $37.5 billion in capital expenditures in its last quarter on AI, recently updated the terms and conditions of its LLM-powered “Copilot” service to say that it was “for entertainment purposes only,” discussing a product that apparently has 15 million users as part of enterprise Microsoft 365 subscriptions, and is sold to both local and national governments overseas, including the US federal government.

That’s so weird! What’re you doing Microsoft? What do you mean it’s for entertainment purposes? You’re building massive data centers to drive this! 

Well, okay, you’re building them at some point. As I discussed a few weeks ago, despite everybody talking about the hundreds of gigawatts of data centers being built “to power AI,” only 5GW are actually “under construction,” with “under construction” meaning anything from “we’ve got some scaffolding up” to “we’re about to hand over the keys to the customer.” 

But isn’t it weird we’re even building those data centers to begin with? Why? What is it that AI does that makes it so essential — or, rather, entertaining — that we keep funding and building these things? Every day we hear about “the power of AI,” we’re beaten over the head with scary propaganda saying “AI will take our jobs,” but nobody can really explain — outside of outright falsehoods about “AI replacing all software engineers” — what it is that makes any of this worthy of taking up any oxygen let alone essential or a justification for so many billions of dollars of investment."

...

"And with that incredibly easy access, only 3% of households pay for AI. Boosters will again use this talking point to say that “we’re in the early days,” but that’s only true if you think that “early days” means “people aren’t really using it yet.” 

Yet the “early days” argument is inherently deceptive.

While the Large Language Model hype cycle might have only begun in 2022, the entirety of the media and markets have focused their attention on AI, along with hundreds of billions of dollars of venture capital and nearly a trillion dollars of hyperscale capex investment. AI progress isn’t hampered by a lack of access, talent, resources, novel approaches, or industry buy-in, but by a single-minded focus on Large Language Models, a technology that has been so obviously-limited from the very beginning that Gary Marcus was able to call it in 2022. 

Saying it’s “the early days” also doesn’t really make sense when faced with the rotten and incredibly unprofitable economics of AI. The early days of the internet were not unprofitable due to the underlying technology of serving websites, but the incredibly shitty businesses that people were building. Pets.com spent $400 per customer in customer acquisition costs, millions of dollars on advertising, and had hundreds of employees for a business with a little over $600,000 in quarterly revenue — and as a result, nothing about its failure was about “the early days of the internet” at all, as was the case with Kozmo, or any number of other dot com flameouts. 

Similarly, internet infrastructure companies like Winstar collapsed because they tried to grow too fast and signed stupid deals rather than anything about the underlying technology’s flaws."

...

"I think it’s also worth asking at this point what is is we’re actually fucking doing. 

We’re building — theoretically — hundreds of gigawatts of data centers, feeding hundreds of billions of dollars to NVIDIA to buy GPUs, all to build capacity for demand that doesn’t appear to exist, with only around $65 billion of revenue (not profit) for the entire generative AI industry in 2025, with much of that flowing from two companies (Anthropic and OpenAI) making money by offering their models to unprofitable AI startups that cannot survive without endless venture capital, which is also the case for both AI labs.

Said data centers make up 90% of NVIDIA’s revenue, which means that 8% or so of the S&P 500’s value comes from a company that makes money selling hardware to people that immediately lose money on installing it. That’s very weird! Even if you’re an AI booster, surely you want to know the truth, right? 

The most-prominent companies in the AI industry — Anthropic and OpenAI — burn billions of dollars a year, have margins that get worse over time, and absolutely no path to profitability, yet the majority of the media act as if this is a problem that they will fix, even going as far as to make up rationalizations as to how they’ll fix it, focusing on big revenue numbers that wilt under scrutiny.

That’s extremely weird, and only made weirder by members of the media who seem to think it’s their job to defend AI companies’ bizarre and brittle businesses. It’s weird that the media’s default approach to AI has, for the most part, been to accept everything that the companies say, no matter how nonsensical it might be.

I mean, come on! It’s fucking weird that OpenAI plans to burn $121 billion in the next two years on compute for training its models, and that the media’s response is to say that somehow it will break even in 2030, even though there’s no actual explanation anywhere as to how that might happen other than vague statements about “efficiency.”

That’s weird! It’s really, really weird!

It’s also weird that we’re still having a debate about “the power of AI” and “what agents might do in the future” based on fantastical thoughts about “agents on the internet” that do not exist, cannot exist, and will never exist, and it’s fucking weird that executives and members of the media keep acting as if that’s the case. It’s also weird that people discussing agents don’t seem to want to discuss that OpenAI’s Operator Agent does not work, that AI browsers are fundamentally broken, or that agentic AI does not do anything that people discuss.

In fact, that’s one of the weirdest parts of the whole AI bubble: the possibility of something existing is enough for the media to cover it as if it exists, and a product saying that it will do something is enough for the media to believe it does it. It’s weird that somebody saying they will spend money is enough to make the media believe that something is actually happening, even if the company in question — say, Anthropic — literally can’t afford to pay for it.

It’s also weird how many outright lies are taking place, and how little the media seems to want to talk about them. Stargate was a lie! The whole time it was a lie! That time that Sam Altman and Masayoshi Son and Larry Ellison stood up at the white house and talked about a $500 billion infrastructure project was a lie! They never formed the entity! That’s so weird!

Hey, while I have you, isn’t it weird that OpenAI spent hundreds of millions of dollars to buy tech podcast TBPN “to help with comms and marketing”? It’s even weirder considering that TBPN was already a booster for OpenAI! 

It’s also weird that a lot of AI data center projects don’t seem to actually exist, such as Nscale’s project to make “one of the most powerful AI computing centres ever” that is literally a pile of scaffolding, and that despite that announcement the company was able to raise $2 billion in funding.

It’s also weird that we’re all having to pretend that any of this matters. The revenues are terrible, Large Language Models are yet to provide any meaningful productivity improvements, and the only reason that they’ve been able to get as far as they have is a compliant media and a venture capital environment borne of a lack of anything else to invest in. 

Coding LLMs are popular only because of their massive subsidies and corporate encouragement, and in the end will be seen as a useful-yet-incremental and way too expensive way to make the easy things easier and the harder things harder, all while filling codebases full of masses of unintentional, bloated code. If everybody was forced to pay their actual costs for LLM coding, I do not believe for a second that we’d have anywhere near the amount of mewling, submissive and desperate press around these models. 

The AI bubble has every big, flashing warning sign you could ask for. Every company loses money. Seemingly every AI data center is behind schedule, and the vast majority of them aren’t even under construction. OpenAI’s CFO does not believe that it’s ready to go public in 2026, and Sam Altman’s reaction has been to have her report to somebody else other than him, the CEO. Both OpenAI and Anthropic’s margins are worse than they projected. Every AI startup has to raise hundreds of millions of dollars, and their products are so weak that they can only make millions of dollars of revenue after subsidizing the underlying cost of goods to the point of mass unprofitability. 

And it’s really weird that the mainstream media has a diametric view — that all of this is totally permissible under the auspices of hypergrowth, that these companies will simply grow larger, that they will somehow become profitable in a way that nobody can actually describe, that demand for AI data centers will exist despite there being no signs of that happening.

I get it. Living in my world is weird in and of itself. If you think like I do, you have to see every announcement by Anthropic or OpenAI as suspicious — which should be the default position of every journalist, but I digress — and any promise of spending billions of dollars as impossible without infinite resources.

At the end of this era, I think we’re all going to have to have a conversation about the innate credulity of the business and tech media, and how often that was co-opted to help the rich get richer.

Until then, can we at least admit how weird this all is?"]]></description>
<dc:subject>edzitron ai artificialintelligence nvidia openai llms microsoft chatgpt meta perplexity garymarcus 2026 2022 aibubble aihype stevenlevy ezraklein jackclark anthropic claude marcoargenti infosys chatbots claudecode coding software economics growth revenue business darioamodei media reporting finance google</dc:subject>
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<item rdf:about="https://www.newyorker.com/magazine/2026/04/13/sam-altman-may-control-our-future-can-he-be-trusted">
    <title>Sam Altman May Control Our Future—Can He Be Trusted? | The New Yorker</title>
    <dc:date>2026-04-06T19:08:46+00:00</dc:date>
    <link>https://www.newyorker.com/magazine/2026/04/13/sam-altman-may-control-our-future-can-he-be-trusted</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["New interviews and closely guarded documents shed light on the persistent doubts about the head of OpenAI."

[via:

"Sam Altman is “unconstrained by truth.”
https://www.theverge.com/ai-artificial-intelligence/907421/sam-altman-is-unconstrained-by-truth

A long, and at times funny, report in The New Yorker on Altman’s will to power, people-pleasing, and alleged pattern of deceit, compiled from notes, memos, and more than 100 interviews. Altman’s reputation has given rise to grimmer rumors – hiring sex workers, the sexual pursuit of minors, even involvement in murder – that The New Yorker found no evidence for. Increasingly, the question is not whether computers are intelligent but whether OpenAI’s leadership is."]]]></description>
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<item rdf:about="https://www.bloodinthemachine.com/p/its-open-season-for-refusing-ai">
    <title>It's open season for refusing AI - by Brian Merchant</title>
    <dc:date>2026-04-05T05:44:24+00:00</dc:date>
    <link>https://www.bloodinthemachine.com/p/its-open-season-for-refusing-ai</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[There's been a wave of successful efforts to ban, reject and shut down AI. ]]></description>
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    <title>Why Swedish Schools Are Bringing Back Books</title>
    <dc:date>2026-04-02T05:38:06+00:00</dc:date>
    <link>https://undark.org/2026/04/01/sweden-schools-books/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Amid declining test scores, the country has pivoted away from screens and invested in back-to-basics school materials."

[Also posted here:

"Sweden goes back to basics, swapping screens for books in the classroom
Sweden is bringing back books amid declining test scores."
https://arstechnica.com/science/2026/04/sweden-goes-back-to-basics-swapping-screens-for-books-in-the-classroom/ ]]]></description>
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<item rdf:about="https://disjunctionsmag.com/articles/ends-of-ai/">
    <title>The Ends of AI: Sycophancy and psychosis</title>
    <dc:date>2026-03-29T02:55:09+00:00</dc:date>
    <link>https://disjunctionsmag.com/articles/ends-of-ai/</link>
    <dc:creator>robertogreco</dc:creator><dc:subject>mélhogan ai artificialintelligence sycophancy psychosis chatgpt openai google gemini claude anthropic copilot microsoft grok xai chatbots oligarchy generativeai genai llms darioamodei enshittification corydoctorow meta amazon algorithms josémarichal aihype dei surveillance humanities objectivity whitesupremacy transphobia incels technology jeffreyepstein samaltman inequality infrastructure worldview</dc:subject>
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<item rdf:about="https://www.christianitytoday.com/2026/03/whats-the-point-of-education-in-an-age-of-ai/">
    <title>What’s the Point of Education in an Age of AI?  - Christianity Today</title>
    <dc:date>2026-03-29T02:44:16+00:00</dc:date>
    <link>https://www.christianitytoday.com/2026/03/whats-the-point-of-education-in-an-age-of-ai/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA[[via:
https://www.frontporchrepublic.com/2026/03/baseball-gardening-and-the-metaverse/

"Carrie McKean responds thoughtfully to the bleak landscape facing students today: there’s “an increasingly inescapable new cultural message: Artificial intelligence will soon do everything you do, and it’ll do it faster and better than you ever could. That message is difficult enough to challenge if you’re an adult. Imagine hearing it when you’re 15 and bored in class, fully aware that you can answer any question your teacher asks in milliseconds using Google Gemini on your school-district-issued Chromebook. Why not outsource your thinking to a machine? It’s easy, frictionless, and—it seems—inevitable in this brave new world. . . . American teenagers are getting a crash course in nihilism, and their apathy is a rational response to a demoralizing situation.”"]]]></description>
<dc:subject>carriemckean education ai artificialintelligence 2026 christianity learning howwelearn chromebooks gemini google schools schooling claude anthropic memorization reading howweread nihilism children youth teens caitlinflanagan writing howwewrite music training cheating thinking howwethink criticalthinking culture jeffreybilbro wendellberry attention humility patience formation human humans soul</dc:subject>
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<item rdf:about="https://www.wheresyoured.at/the-ai-industry-is-lying-to-you/">
    <title>The AI Industry Is Lying To You</title>
    <dc:date>2026-03-24T20:49:38+00:00</dc:date>
    <link>https://www.wheresyoured.at/the-ai-industry-is-lying-to-you/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The Tech Industry Has Poisoned Itself With The Lies of AI

In the end, everything about AI is built on lies. 

Hundreds of gigawatts of data centers in development equate to 5GW of actual data centers in construction. 

Hundreds of billions of dollars of GPU sales are mostly sitting waiting for somewhere to go.

Anthropic’s constant flow of “annualized” revenues ended up equating to literally $5 billion in revenue in four years, on $25 billion or more in salaries and compute.

Despite all of those data centers supposedly being built, nobody appears to be making a profit on renting out AI compute.

AI’s supposed ability to “write all code” really means that every major software company is filling their codebases with slop while massively increasing their operating expenses. Software engineers aren’t being replaced — they’re being laid off because the software that’s meant to replace them is too expensive, while in practice not replacing anybody at all.

Looking even an inch beneath the surface of this industry makes it blatantly obvious that we’re witnessing one of the greatest corporate failures in history. The smug, condescending army of AI boosters exists to make you look away from the harsh truth — AI makes very little revenue, lacks tangible productivity benefits, and seems to, at scale, actively harm the productivity and efficacy of the workers that are being forced to use it.

Every executive forcing their workers to use AI is a ghoul and a dullard, one that doesn’t understand what actual work looks like, likely because they’re a lazy, self-involved prick. 

Every person I talk to at a big tech firm is depressed, nagged endlessly to “get on board with AI,” to ship more, to do more, all without any real definition of what “more” means or what it contributes to the greater whole, all while constantly worrying about being laid off thanks to the truly noxious cultures that are growing around these services.

AI is actively poisonous to the future of the tech industry. It’s expensive, unproductive, actively damaging to the learning and efficacy of its users, depriving them of the opportunities to learn and grow, stunting them to the point that they know less and do less because all they do is prompt. Those that celebrate it are ignorant or craven, captured or crooked, or desperate to be the person to herald the next era, even if that era sucks, even if that era is inherently illogical, even if that era is fucking impossible when you think about it for more than two seconds.

And in the end, AI is a test of your introspection. Can you tell when you truly understand something? Can you tell why you believe in something, other than that somebody told you you should, or made you feel bad for believing otherwise? Do you actually want to know stuff, or just have the ability to call up information when necessary? 

How much joy do you get out of becoming a better person?If you can’t answer that question with certainty, maybe you should just use an LLM, as you don’t really give a shit about anything.

And in the end, you’re exactly the mark built for an AI industry that can’t sell itself without spinning lies about what it can (or theoretically could) do."]]></description>
<dc:subject>edzitron ai economics genai artificialintelligence generativeai datacenters finance fraud cloud technology physics paulkedrosky lies nvidia avisionyoung statistics gpus openai media google amazon microsoft jensenhuang coreweave supermicro meta eugenekim llms bigtech aibubble openclaw mobitar labor work workers employment layoffs data kevinroose journalism siliconvalley figma anthropic business</dc:subject>
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<item rdf:about="https://buttondown.com/dorian/archive/slop-machine-future/">
    <title>Slop-Machine Future • Buttondown</title>
    <dc:date>2026-03-22T02:53:04+00:00</dc:date>
    <link>https://buttondown.com/dorian/archive/slop-machine-future/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The arc of large language models is mediocre, and it bends toward “target procurement”."]]></description>
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<item rdf:about="https://restofworld.org/2026/techno-negative-thomas-dekeyser-fighting-ai/">
    <title>“Techno-Negative”: Why refusing AI is a fight for the soul - Rest of World</title>
    <dc:date>2026-03-20T06:50:21+00:00</dc:date>
    <link>https://restofworld.org/2026/techno-negative-thomas-dekeyser-fighting-ai/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Author Thomas Dekeyser explains why modern resistance to Big Tech is a deeply sane response to a narrow vision of humanity."]]></description>
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    <title>If we hope to build artificial souls, where should we start? | Aeon Essays</title>
    <dc:date>2026-03-20T05:01:19+00:00</dc:date>
    <link>https://aeon.co/essays/if-we-hope-to-build-artificial-souls-where-should-we-start</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["As the 18th-century war between mechanism and romanticism returns, we face a new question: can we build artificial souls?"]]></description>
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<item rdf:about="https://www.youtube.com/watch?v=qcf5syA1MlE">
    <title>The Left Doesn’t Hate Technology with Gita Jackson - YouTube</title>
    <dc:date>2026-03-13T05:21:19+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=qcf5syA1MlE</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["Paris Marx is joined by Gita Jackson to discuss why the left’s hatred of AI is justified, why a different approach to technology is necessary, and how they’re reassessing their own relationships with digital tech.

Gita Jackson is a co-founder of Aftermath (https://aftermath.site ).

Also mentioned in this episode:
     
• Gita wrote about why the left doesn’t hate technology (https://aftermath.site/anthropic-claude-ai-leftist-technology/ ).

• Gita also wrote about downloading digital music (https://aftermath.site/digita-audio-player-snowsky-echo-mini-fiio-hyby/ ) onto a Snowksy Fiio Echo Mini.

• Chris Person wrote about the  Boox Palma eReader (https://aftermath.site/i-love-my-weird-little-phone-shaped-ereader/ )  as an alternative to Kindle.

• Learn more about Mike Pondsmith (https://blackgirlnerds.com/from-cyberpsychos-to-netrunners-here-is-the-story-of-mike-pondsmith-the-true-mastermind-behind-cyberpunk/ ) and his Cyberpunk TTRPG.

• Gita will one day get Paris to watch Frieren (https://www.crunchyroll.com/series/GG5H5XQX4/frieren-beyond-journeys-end ) ."

[references:

"The Left Doesn't Hate Technology, We Hate Being Exploited
Techno-cynics are all just wounded techno-optimists."
https://aftermath.site/anthropic-claude-ai-leftist-technology/ ]]]></description>
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    <dc:creator>robertogreco</dc:creator><description><![CDATA["From Gates to Musk and Altman, today’s ultra-rich steer AI and tech, raising questions about who decides the future"]]></description>
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<item rdf:about="https://www.anildash.com/2026/02/27/a-cookie-for-dario/">
    <title>A Cookie for Dario? — Anthropic and selling death - Anil Dash</title>
    <dc:date>2026-03-01T22:35:42+00:00</dc:date>
    <link>https://www.anildash.com/2026/02/27/a-cookie-for-dario/</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["How did we get here?

We’ve only allowed ourselves to lower the bar this far because so many of the most powerful voices in Silicon Valley have so completely embraced the authoritarian administration currently in power in the United States. Facebook’s role in enabling the Rohingya genocide truly served as a tipping point in the contemporary normalization of major tech companies enabling crimes against humanity that would have been unthinkable just a few years prior; we can’t picture a world where MySpace helped accelerate the Darfur genocide, because the Silicon Valley tech companies we know about today didn’t yet aspire to that level of political and social control. But there are deeper precedents: IBM provided technology that helped enable the horrors of the holocaust in Germany in the 1940s, and that served as the template for their work implementing apartheid in South Africa in the 1970s. IBM actually bid for the contract to build these products for the South African government. And the systems IBM built were still in place when Elon Musk, Peter Thiel, David Sacks and a number of other Silicon Valley tycoons all lived there during their formative years. Later, as they became the vaunted “PayPal Mafia”, today’s generation of Silicon Valley product managers were taught to look up to them, so it’s no surprise that their acolytes have helped create companies that enable mass persecution and surveillance. But it’s also why one of the first big displays of worker power in tech was when many across the industry stood up against contracts with ICE. That moment was also one of the catalyzing events that drove the tech tycoons into their group chats where they collectively decided that they needed to bring their workers to heel.

And they’ve escalated since then. Now, the richest man in the world, who is CEO of a few of the biggest tech companies, including one of the most influential social networks — and a major defense vendor to the United States government — has been openly inciting civil war for years on the basis of his racist conspiracy theories. The other tech tycoons, who look to him as a role model, think they’re being reasonable by comparison in the fact that they’re only enabling mass violence indirectly. That’s shifted the public conversation into such an extreme direction that we think it’s a debate as to whether or not companies should be party to crimes against humanity, or whether they should automate war crimes. No, they shouldn’t. This isn’t hard.

We don’t have to set the bar this low. We have to remind each other that this isn’t normal for the world, and doesn’t have to be normal for tech. We have to keep repeating the truth about where things stand, because too many people have taken this twisted narrative and accepted it as being real. The majority of tech’s biggest leaders are acting and speaking far beyond the boundaries of decency or basic humanity, and it’s time to stop coddling their behavior or acting as if it’s tolerable.  In the meantime, yes, we can note when one has the temerity to finally, finally do the right thing. And then? Let’s get back to work."]]></description>
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    <title>Secret Agent Man</title>
    <dc:date>2026-02-27T22:32:51+00:00</dc:date>
    <link>https://2ndbreakfast.audreywatters.com/secret-agent-man/</link>
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<item rdf:about="https://newrepublic.com/article/206423/abundance-ai-problem-data-centers">
    <title>The Abundance Gang Has a Big AI Problem | The New Republic</title>
    <dc:date>2026-02-27T03:56:01+00:00</dc:date>
    <link>https://newrepublic.com/article/206423/abundance-ai-problem-data-centers</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["The faddish political movement’s ties to industry figures may help attract funding, but it comes with a political cost."]]></description>
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    <title>Resistance101: Forging a New Movement for Palestine in Italy DOCUMENTARY - YouTube</title>
    <dc:date>2026-02-22T01:43:25+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=a5ofVZjG21g</link>
    <dc:creator>robertogreco</dc:creator><description><![CDATA["With little hope of the genocide in Gaza subsiding, dock workers in major Italian port cities have organized strikes and large demonstrations to halt arms shipments to Israel. These actions are a direct response to the refusal of international institutions and governments around the world to confront the carnage. Though the genocide continues, the dockworkers’ industrial disruption offer us a model of resistance. Will the Italian way spread to the imperial core — and can it end the genocide?"]]></description>
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<dc:identifier>https://pinboard.in/u:robertogreco/b:133120501880/</dc:identifier>
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