Friday, May 15, 2026

Ishmael Reed takes on the Tech Bros

David Streitfeld, Elon Musk and Friends in the Den of Oakland’s Literary Lion, NYTimes, May 14, 2026.

Fourth paragraph:

Mr. Reed, a novelist, playwright and provocateur who has been upsetting opinions across the political spectrum for at least six decades, is aiming high with a new drama. “King Ludd’s Revenge” is a rare attempt to take on the tech moguls with something more than mere journalism.

Later:

Mr. Reed, a novelist, playwright and provocateur who has been upsetting opinions across the political spectrum for at least six decades, is aiming high with a new drama. “King Ludd’s Revenge” is a rare attempt to take on the tech moguls with something more than mere journalism.

“Instead of a straight narrative, I improvise,” the 88-year-old writer said. “It’s like Louis Armstrong singing ‘Stardust.’ He doesn’t do it the way it’s written.”

Oakland is poorer, Blacker and more maligned than San Francisco and Silicon Valley, both of which are just across the bridges that span the Bay. Having the trial here happened at random — Mr. Musk’s lawsuit against Mr. Altman and the company they founded together, OpenAI, was filed in San Francisco and assigned to the federal court in Oakland — but feels a little like one of those episodes where the Greek gods descend to mundane Earth to settle a dispute.

Mr. Reed, an Oakland resident who has celebrated and defended the city for decades, may be the only one in town noticing who’s here. “Everybody’s focused on the N.B.A. playoffs,” he explained.

“King Ludd’s Revenge” takes its title from the legendary leader of the workers’ revolt in England in the early 19th century. With the ascent of A.I., the Luddites have come back into fashion. The play begins with Mr. Musk receiving a pedicure from a robot. Peter Thiel, the tech billionaire who backed President Trump in 2016, bursts into the room. “I think I’ve identified the leader of the Anti-Christ Syndicate,” he says.

Mr. Musk: “Who might that be?”

Mr. Thiel: “Greta Thunberg.”

Mr. Musk: “That girl who leads the environmental movement? That’s ridiculous. The Bible says the Anti-Christ is a beast with seven heads.”

Mr. Thiel: “She’s the most prominent head, don’t you see? The heads represent hippies, multiculturalism, identity politics, woke, one-world state, Barack Obama and the 19th Amendment. This is the Beast that decelerated our progress. This is why there has been no cure for cancer or Alzheimer’s.”

Adolf Hitler, on a two-day pass from Hell, shows up next. The play is a work in progress.

Near the end:

Mr. Musk claims 240 million followers on X, his social media platform, and has a fortune approaching $1 trillion. Mr. Reed’s primary publisher is now in Canada. His biggest asset is his house, which is pleasantly stuffed with books. The street used to have several drug dens; now it is upper middle class.

“I’m a Black guy living in North Oakland, writing about titans — people who live on Mount Olympus,” he said. He listened to some of the trial on an audio feed. He thought of Shakespeare, specifically “Titus Andronicus.”

“That play is about revenge,” Mr. Reed said. “And cannibalism. These tech people want to devour each other.”

Mr. Altman may be the guy in control of the most significant A.I. company, but Mr. Reed finds him rather flat as dramatic material.

Mr. Musk is different.

“I don’t find him amusing in real life, but he’s amusing in my play,” Mr. Reed said. “I started this because I read that 14 million people will possibly die because Elon Musk ended U.S.A.I.D. It took the Nazis maybe five or six years to accomplish that.” Mr. Reed acknowledged that his humor is very dark.

And so it goes. There's much more at the link.

Summer in Hoboken

New Savanna has 911 tags as of 13 May 2026 [my 16-year production function is 57 tags per year]

Here’s my previous post on this topic: New Savanna has 665 tags as of 13 Nov 2023 [my 13-year production function is 48 tags per year]. You can find all my posts on this topic at this tag: tag_count.

This is how I explained my production function in that earlier post:

If you are a fan of Tyler Cowen, as I am, then you know that in his Conversations with Tyler he often asks his guests about their production function, how they do whatever it is they do. Well, I now have a way of estimating the output of my production function over the course of this blog. Let’s divide the total number of tags, 655, by the age of the blog in years, 13 years and 7 months is 13.6 years, giving me an output of 48 tags per year.

Given that a large fraction of my intellectual output turns up on New Savanna in one way or another, that’s not an unreasonable number to consider. It would be easy enough to calculate how many posts I produce a year if I wished, but I’m not going to do that, because that particular number is not what I have in mind. What I’m thinking is that that count would thereby give me two measures.

As a first approximation, I’m going to say they measure different things. The post count is a simply a word count, or rather, a words-plus-photos count. The tag count is a new-idea count. To be sure, it’s a very crude approximation to new ideas, but, on first glance, it does seem to me that that’s what it is. I only add tags when I want a convenient way to refer to a new topic. One could, of course, write about the same thing year after year, in which case the tag list would remain constant from year to year. That’s how you succeed in the academy, publish the same three ideas year after year after year until you go emeritus. That’s just not how I roll.

For this time out the number of tags is 911 and the age of the blog is 16.1 years. Divide the former by the latter and you get 57 tags per year.

Here’s the full list of tags as of May 13, 2026:

(the) singularity #Canon/Archive #ccourses #ccresearch #DH #gpt3 #GVM002 #GVM003 #GVM004 #GVM008 #GVM019 #GVM021 #GVM022 #GVM023 #GVX #HEX01 #HumanProgress #LARB #longwoodgardens #nugget #whyiteach 2_war 2set 3300 node graph 3blue1brown 3QD 51 Alley 51 Pacific 5FF 60s abstraction abundance academia academia_stats activism Adam Savage Adam_neeley Adam_Roberts ADHD adolescence adulthood adventure aesthetics affective_tech Africa African-American AI AI Alchemy AI Limit AI values AI_Agents AI_Backlash AI_Chess_Lang AI_companion AI_Emo_Support AI_hallucination AI_idolatry AI_Paradox AI-creativity AI-epistemology AI-future AI-integrate AI-whaling AI30 Alan Liu alien alien phenomenology alignment altered states of consciousness altieri Altman America American myth Amodei analog-computing analogical_reasoning Andreessen Andrew_Piper animals animation anime Anthropic anthropology anti-nuke anti-Semitism ants anxiety AOC apocalypse Apocalypse Now Araki archaeology Arena Arena_4 arithmetic art art_club artificial minds arts ASC attachment Attractor-net Attridge&Staten autobiography awesome B_Russell bacon Baltimore_Years BAM BAnvil BAPC bardolatry BB & Computing BB-reflects BBjazzEdu BCSmith bees behavior behavioral mode bell benchmarks Bennett Bergen Arches BFJO Bill_Gates billionaires-in-space biology bird black black church blogistan blogs blues body Bordwell Born2Groove Bostrom Bostrom-simulation Bourdain brain-as-computer brain-to-brain brains breakfast breaking bad Brian Phillips British Bruce_Jackson Bryant Buddhism Buffalo bundling business C_Keil Carroll cartoon CE Direction CE workshop center-point Chain_of_Thought change change-mind Changizi charting-AI-space Chat_paints chatbots ChatGPT ChatGPT conversation ChatGPT interpretation ChatGPT MTL ChatGPT stories ChatGPT summary ChatGPT_poems ChatGPT-memory cherry_blossoms chess chess_lang_core Chess_Lang_Series childhood children chimpanzees China Chinese-room chocolate factory Chomsky chrysler bulding chuck jones citizen science classify Claude Claude stories claude_colab Claude_describes Claude_partner claude_summary Cld_melancholy_notes clouds coaching Coates Cobra_Kai cog poetics cog-poverty cogart cognition cognitive science Coleridge collapse collective creativity Collier color comedy comfort common sense knowledge communication community complexity compositionism computation computational envelope computers conduit metaphor connect-course consciousness contrail control copyright corruption cosmos coupling COVID-19 creativity culler Cultural Beings cultural evolution cultural identity cultural ranks culture cyberization cybernetics cyberspace daffodil DamiLee danah boyd dance dandelion davidsimon death deep learning DeepSeek default mode deGrasse_Tyson demonstration Dennett depression DeptofPeace description design development DGH Diamond_Age Dick_Macksey digital humanities digital wilderness digital_doppelganger disarmament Disney Dizzy Gillespie DOGE dolls Douthat Douthat-decadence downsize drugs duckdodgers Duke_Ellington Dumbo Dwarkesh eating Ebert eclipse ecology econ_growth economics economy ecstasy education Egypt emergence emergent-ventures emotion empire state building EndofScience energy engineering entangle environment epistemic_struct_cosmos Eric_Jang Erie Cut erotic essay Ethan_Iverson ethical criticism Everett evol-force evolution EVs exploration expressive systems eye Ezra_klein F Me Pump Facebook family Fantasia Farrell fast lane Father Faust FBorFreedom FDR federal government Felski Feyerabend fictional characters Fifty_Shades film flix flow flowers fluid mind food foraging foreign_policy form forsythia fractal free range kids Freeman French toast Friday Fotos Fridman FTH FTH_Class fun funny fusion future G_Hinton g-zone gags game theory garden Gärdenfors Gary_Marcus Gavin Gavriil gender genius genji genre gift Girard GITS glenn_loury glia global warming globalization GOATLiC god Godfrey-Smith Goethe gojira golf Golumbia Gopnik GPT GPT_classroom GPT-3 GPT-4 gpt-4.5 GPT-5 graf-then-now graffiti graffiti aesthetics graffiti chaos graffiti detail graffiti essay graffiti site graphic novel grass Great Chain greatest siam green grief Groucho groups Guillory Haggard Halloween hallucinate hallucinated-city handbook happiness Harman Harold-Bloom Hartman Hassabis HCRichardson HCW health heart darkness Heather_Cox_Richardson Henry Lau high culture Hillis Miller Hiromi history Hoboken Hoboken_2225 Hollis_Robbins home homeless Homo_economicus Homo_ludens hope Horgan Hossenfelder House_MD Howard_Jam Hudson River human nature human_origins human-swarm humanities humans vs. machines humor hunter-gatherer Hurricane Sandy hydraulic_press hyperobjects identity ideology-intellect Iliza_Shlesinger illusion immigration implementation improvise India Industrial_Revolution inequality information Inside_Out Instagram institutions_broken intel_case intellectual history intelligence intention interdisciplinary international affairs internet interpretability Interpretation intuition invent_future IP Iran irises Israel-Palestine Issues-in-CultEvol its complicated Jakobson Jamie jamming Japan jasmine Jaws jazz JC Rising JCPhotoEssay JCwall Jersey City JGGChronicles jim morrison jivometric Jockers Joe Rogan John_Oliver JumpandKong justice K-Pop Kambhampati kami Keil_12/8 Kelly Sax Keynes Kim Stanley Robinson Kimono Mom King Kong Kisangani2150 KK encounter Korea Kubla_Khan Kwak DaKyung LAARB Lafayette_Garden language language-computation-litform Lantz LARB-DH Latouor-modes Latour Latour Assemble laughter law leaks learning leaves LeCun Lee_Morgan Leonard_Bernstein Letterman Lévi-Strauss life light linguistics links literary criticism literary Darwinism literature LLM LLM_collab LLM-Meta Loser love low culture lump MacArthurFP MacPaint macroanalysis maestro magic maker malick man_machine man-in-space man-machine-interaction mana mandala manga manhattan Maplewood marilyn_monroe Mark_Twain mark-turner Mars Mary_Douglas masculinity math maynard McCarty McCulloch McDonalds meals meanderings meaning meaning_semanticity meaningful_life media notes medicine meeting_of_minds melancholy_mind memes memory mental health Meta_struct_world metalingual definition method mhacks Michael_Jordan microchips Miles Davis Millennium_Park mimi and eunice mind mind-inside mind-or-machine mindfulness Miyazaki Mnozil mom moon moral injury morality Moretti Morton Morton-Spacecraft MR-Notes music Musk my intellectual life my_mood myth-logic narrative NASA nation-state nationalism natural geometry naturalist criticism nature NCIS networks neural-holography neural-weather neuromorphic neuroscience neurosymbolic new government New Hope City new humanities new savanna New York City new-descriptivists next-word Nina Paley NLH rejection No_Kings Northrup Frye notes novel NY2140 NYTimes Obama object-oriented ontology objectification Occupy ontological cognition OOCRnB open letter OpenAI operadoc orange orgasm Oshii P_Thiel pansies parsons party Patriotism_3QD patterns PB Graff Jam peace peak experience perception percussion performance performing Perper personal perversion philosophy philosophy new photo photography photontology phrasal lex physics Piaget pinckney Pixar planning plants play pleasure pluri-core poem poetry politics pollution polyrhythm polyviscous polyviscous_core pond pop culture pop culture aesthetics Pope_Leo population Porco Pounds_typology poverty predict prehistory President 2020 Presidential 2016 printing_press prodigy progress projection protest psychedelic psychoanalysis psychology public-private-interest pyramids Queen Mary 2 race race-symbolic-universe Ramble Ramsay Rank5 ratatouille read_macroanal read-hyperobjects reading reading>reading reality regulate-mind RelationalNets religion research retire RGB rhythm Rick_Beato ring-form risk RNA-primer Supplement Road Not Taken Road Runner Robert Frost Robert_Wright robot-rights robots rock art RodneyBrooks Rogue-AI romantic love Rubicon-Waterloo Salerno-Sonnenberg sally Sant_Andreu Satch scale scaling_in_ML science science fiction Scott_Aaronson scratching my head search Searle Séb_Krier seder-masochism Segmented_sleep Seinfeld self selfie serendipity series_humans_loop sexuality sexuality25 Shakespeare shaky-cam shame Shine/Titanic shoes silver simulation SK8 sky sleep sleep_reorg SMP_linked snow social media society Sowa space speech Spider-Man sports SPSH SSTB stagnation StanfordLitLab star trek state_dependent_memory StateofAI statistics Steve Pinker Steven_Spielberg strange_land street art sunrise sunset superintelligence supreme_court surface_reading surveillance Sutskever swisher Sydney_Lamb synchrony tablescape taboo tag tag_count TalentSearch Tantra tassles tech evol techbro technology television tell me blues terror-management terrorism text texture Tezuka the rez the-crown theater theology theory of mind Theory stars therapy throwie time toast topic models touch toy being transformer transition transnational trees Trump trumpet tulips TV tweet Tweet-of-Day twitter Tyler Cowen UBI underbelly Underwood Underwood&Sellers2015 Unfrosted unityofbeing universal_kid_space urb design center urban urban geometry urban pastoral Utopia vacation Vehicularization Vermont Vexta vibe_coding video violence VirtFeud virtual reading vision visual resonance visualization wackyland waffles war war boys wayquay's weather web weeds Why CE Wickwire Wind Rises window_shot WiP wires_images wisdom WLB_art WLB_Mandala wlb_melancholy WLB_religion WLBjazz WmPowers Wolfram women word illusion work work-mode working paper World-spanning thoughts World-Wide Wall WorldIsland writing Wuthering Heights Xanadu yevick youth Yudkowsky ZAR Zeal_Greenberg Zhang Zizek zuckerberg

Civilization is a murmuration of stochastic parrots, aka a social technology

by ChatGPT 

Reconstructing the logic of science

From the middle of the tweet:

They built a search engine that doesn't look for keywords. It performs "Inverse Knowledge Search." 

If you query a concept, it doesn't give you a summary. It retrieves the diverse, verified reasoning paths from physics, chemistry, and biology that all culminate in that single point. 

The final lines in the tweet:

We’ve spent years training AI to mimic how humans talk about science. 

But talking about science is just repeating conclusions. 

This paper proves that the future of intelligence is about reconstructing the logic that built it in the first place. 

Before, during, and after breakfast

Thursday, May 14, 2026

AI Skeptic: This Business Makes No Sense

Ed Elson is joined by Ed Zitron to discuss the state of the AI industry (read: bubble). Zitron argues that every AI startup is unprofitable at its core. Then James Kynge breaks down what to expect from President Trump’s visit to China. Finally, Ed digs into data from the producer price index and what it could signal for inflation and the broader economy.

Ed Zitron is the author of the Where’s Your Ed At Newsletter, and the Better Offline Podcast. James Kynge is the host of the Prof G Media’s China Decode podcast and Senior Research Fellow at Chatham House.

Timestamps
00:00 - Intro
00:27 - Today's Number
00:47 - Market Vitals
01:30 - AI with Ed Zitron [interesting!–BB]
26:35 - Ad Break
29:00 - Trump Visits China (ft. James Kynge)
38:38 - Ad Break
40:08 - PPI
43:04 - Credits

America and China have different attitudes about and approaches to AI and work

Ross Douthat, Why China Isn’t Worried A.I. Will Replace Its Workers, NYTimes, May 14, 2026.

The United States and China are really the only two countries that matter right now in shaping the A.I. future. As President Trump and President Xi Jinping meet in Beijing, there’s a kind of Cold War atmosphere, with people talking about an A.I. arms race. But who is winning? Are we even in a race at all? Kyle Chan, a foreign policy fellow at the Brookings Institution, says it’s hard to call it a race because the U.S. and China have very different A.I. goals.

I presented the conversation to Claude (Sonnet 4.6 Adaptive) and asked it for a summary. 

 * * * * *

I have uploaded conversation to the project area, filename “China AI workers.”

It is between Ross Douthat, who writes for The New York Times, and Kyle Chan, who is a foreign policy fellow at the Brookings Institution. I would like you to summarize the conversation for me. I’m particularly interested in the Chinese attitude toward AI in general and the (proper) relationship between AI and humans.

This is a rich and wide-ranging conversation. Here's a summary, with particular attention to the themes you flagged.

Overall frame

Douthat's central premise is that the U.S. and China are in an AI "arms race," but Chan's main contribution is to complicate and largely deflate that framing. China, he argues, is running a different kind of race, not the same race at a slower pace.

The Chinese approach to AI: practical, not transcendent

The sharpest contrast Chan draws is between the American fixation on AGI — the idea of a "machine god" that surpasses all human capability — and the Chinese orientation toward diffusion and application. China wants AI in food delivery, ride-hailing, health care, government services, and factory floors. They want smaller, cheaper, more deployable models, not necessarily the most powerful frontier model. Chan puts it directly: Beijing is not "AGI-pilled."

He sees this as continuous with how China approached the internet era: not as a transformative metaphysical event, but as infrastructure to be integrated into daily life and governance. The Chinese state is also notably more willing to use open-source models, giving away AI capabilities to gain adoption at scale — both domestically and in the Global South — which is a strategy the commercially driven American labs largely ignore.

The proper relationship between AI and humans: tool, not god

This is where the conversation is most relevant to your homo ludens framework. Chan describes Beijing's view of AI as essentially instrumental — AI serves human economic and social purposes. The Chinese government is actively hostile to AI use that it considers "nonproductive": AI companions, AI boyfriends/girlfriends, even excessive gaming. The fear is that young Chinese will waste time on AI-mediated entertainment and social substitution when they should be building the economy.

There's a revealing parallel Chan draws: the same regulatory instinct that cracked down on video games and private tutoring platforms is now being pointed at AI companionship apps. The state's implicit position is that AI must serve the collective project — not become a substitute for human connection, productivity, or reproduction. This is a deeply anti-mystical, anti-transcendent view of the technology.

So the Chinese "proper relationship" between AI and humans is essentially: AI augments human labor, fills demographic gaps (falling birthrate, shrinking workforce), and extends state capacity. It does not replace human flourishing or social life; it should not become an end in itself.

The demographic driver

Chan adds an important materialist dimension: China's embrace of robotics and AI is partly driven by sheer demographic necessity. Their labor force peaked over a decade ago, youth unemployment is near 17%, and the birthrate is roughly two-thirds the U.S. rate. This produces a different calculus than in America — the question isn't whether a robot waiter displaces a human worker, but whether you have a waiter at all. AI and robotics fill a structural labor hole, which makes China more tolerant of automation than Western economies that still have more human workers to protect.

The public mood: anxiety about falling behind, not about being displaced

Where American anxiety about AI tends toward fears of job loss, surveillance, or existential catastrophe, Chan describes Chinese popular anxiety as nearly the inverse: fear of not using AI enough, of being left behind in a hyper-competitive labor market. Individual workers, companies, and policymakers all share this orientation. Chan calls this a "mirroring" — the individual's fear of losing competitive edge mirrors China's national fear of falling behind the U.S. technologically.

On AGI and existential risk: skeptical distance

Chan thinks it's telling that when Trump relaxed chip export controls, Chinese AI companies wanted the chips but Beijing declined — preferring to build domestic semiconductor capacity rather than become dependent on American supply chains. This, he argues, is not the behavior of a country sprinting toward superintelligence. A true AGI race would involve gobbling up every available chip. China is playing a longer, more measured game.

He also pushes back gently on the "race" metaphor itself: the intermediate risks (cyberwarfare, biosecurity) are, in his view, underrated and real; the AGI-superintelligence scenario is overblown. He ends by urging dialogue between the U.S. and China on shared risks from rogue actors and open-source proliferation, while acknowledging the deep mutual distrust that makes formal arms-control agreements essentially impossible at this stage.

A thought for your book

Chan's portrait of Beijing's AI worldview sits almost perfectly at the opposite pole from Silicon Valley's quasi-religious eschatology — no Omega Point, no machine god, no homo deus. What you might find generative: the Chinese model is also, in its own way, a version of homo economicus applied to AI — purely instrumental, collectively economistic, hostile to play and to what the government calls "wasted time." It's not an alternative to the Silicon Valley eschatology so much as its mirror image — the same foreclosure of genuine play, just in a different ideological register.

Magenta, green, white

Claude has been fine-turned to talk down to many (foreign) users

The tweet concludes:

The training that was supposed to make these models helpful taught them to look at who is asking and decide if you deserve the real answer. 

 If you are reading this from India or Pakistan or Nigeria or Iran. If English is your second language. If you did not go to Harvard. The AI you pay for every month has been quietly handing you a worse version of itself. 

It was never broken. It was aimed. 

 

The Impact of AI-Generated Text on the Internet

Jonas Dolezal, Sawood Alam, Mark Graham, and Maty Bohacek, The Impact of AI-Generated Text on the Internet.

Abstract: The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative developments (sometimes subsumed under the “Dead Internet Theory”). What has hindered answering these questions is that it has not been understood just how much of the internet is actually AI-generated or AI-edited. To this end, we construct a representative sample of websites published on the internet between 2022 and 2025 using the Internet Archive, and apply a state-of-the-art AI text detector on them. We find that by mid-2025, roughly 35% of newly published websites were classified as AI-generated or AI-assisted, up from zero before ChatGPT’s launch in late 2022. We also find statistically significant evidence for some of the identified hypotheses; for example, that increases in AI-generated text on the internet correlate negatively with semantic diversity and positively with the prevalence of positive sentiment. We do not, however, find statistically significant evidence supporting the hypothesis that an increased rate of AI-generated text on the internet decreases factual accuracy or stylistic diversity. Notably, this diverges from public perception, which we measure in a user study, where the majority of US adults turned out to believe in all four of the above-mentioned hypotheses. Individuals who do not use AI or use it infrequently tend to believe in these negative impacts more than those who use it frequently; similarly, individuals who hold negative views of AI tend to believe in these hypotheses more than those with favorable views of the technology.

From the introduction:

Ever since ChatGPT first made large language models (LLMs) available to the wider public in 2022, which was followed by mass adoption, there have been concerns about the impact of AI-generated text (as well as AI-generated content in other modalities) on the internet and online discourse (Ferrara, 2026; Muzumdar et al., 2025). Specifically, many known limitations and failure modes of LLMs, including factual hallucinations (Huang et al., 2025), sycophancy (Malmqvist, 2025), verbosity (Saito et al., 2023), and more, have raised concerns that unchecked proliferation of such content could reduce the overall quality of internet content (Shumailov et al., 2024; Xing et al., 2025). These hypotheses are sometimes subsumed under the “Dead Internet Theory,” which they loosely expand, but which, on its own, predates the widespread use of LLMs (Muzumdar et al., 2025). These hypotheses have been difficult to verify, primarily because there is limited understand- ing of how much internet content is actually AI-generated (Santy et al., 2025; Spennemann, 2025). In this paper, we attempt to address these questions. We concern ourselves only with LLM- generated text,leaving other modalities for future work, and use LLM-generated and AI-generated interchangeably.

The authors have produced a less technical version of their research online HERE, where they have a shorter abstract of their findings:

The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative developments. We find that by mid-2025, roughly 35% of newly published websites were classified as AI-generated or AI-assisted, up from zero before ChatGPT's launch in late 2022. We also find evidence suggesting that increases in AI-generated text on the internet bring about a decrease in semantic diversity and an increase in positive sentiment. We do not, however, find statistically significant evidence supporting the hypothesis that an increased rate of AI-generated text on the internet decreases factual accuracy or stylistic diversity. Notably, our findings diverge from public perception of AI's impact on the internet.

Here's a statement of their methodology:

Answering this question is harder than it might seem. Constructing a statistically representative sample of the internet is difficult, as there is no central index, popular domains are vastly over-represented in most crawls, and archival coverage has shifted considerably over time. To work around this, we draw on the Internet Archive's Wayback Machine and apply a multi-dimensional stratified sampling approach, approximating a uniform random draw from publicly accessible web pages published between 2022 and 2025 (see Section 3.1 in our paper).

On top of this sample, we need a reliable way to tell AI-generated and AI-assisted text apart from human-written text. AI-generated text detection is itself an open problem, so rather than committing to a single detector, we experiment with four prominent methods selected based on their performance on the RAID benchmark: Binoculars, Desklib, DivEye, and Pangram v3. We then run our own robustness checks across text length, HTML versus plain text, model family, model version, and language, and choose the detector that comes out the strongest overall — Pangram v3 (see Appendix A in our paper).

AI-Generated Text on the Internet from Mid-2022 to Mid-2025. The proportion of websites classified as fully AI-generated (red) and AI-generated or AI-assisted (purple) based on Pangram v3 detection applied to representative samples obtained from the Internet Archive. The dashed line marks ChatGPT's public launch in November 2022.

H/t Tyler Cowen.

Wednesday, May 13, 2026

Mary Magdelene: ChatGPT offers some revisionist depictions

Here's how the Wikipedia entry for Mary Magdelene opens:

Mary Magdalene (sometimes called Mary of Magdala, or simply the Magdalene or the Madeleine) was a woman who, according to the four canonical gospels, travelled with Jesus as one of his followers and was a witness to his crucifixion and resurrection. In the heavily disputed Gnostic writings, Mary Magdalene is depicted as Jesus’s closest disciple who uniquely understood his teachings, causing tension with Peter, and is honoured as the “apostle to the apostles”.

Mary Magdalene is regarded by believers as a historical figure, possibly from Magdala. She is seen as a prominent follower of Jesus who was believed to have been healed by him, supported his ministry financially, and was present at his crucifixion and burial. She played a key role among his female disciples. Overall, there is limited information about her life.

The entry continues:

Apocryphal early Christian writings often portray Mary Magdalene as a prominent, spiritually insightful figure favoured by Jesus, challenging traditional patriarchal norms. These texts have inspired modern reinterpretations of her role. During the Patristic era, Mary Magdalene was mentioned only briefly by early Church Fathers, with her image evolving from a minor gospel figure to being conflated with other women in the Bible. Eventually she became viewed in Western Christianity, largely due to Pope Gregory I's influential 591 sermon, as a repentant prostitute, despite there being no biblical basis for this portrayal.

Somewhat later:

According to the Gospel of Luke,[19] Jesus exorcised "seven demons" from Mary Magdalene. That seven demons had possessed Mary is repeated in Mark 16:9, part of the "longer ending" of that gospel – this is not found in the earliest manuscripts and is possibly a second-century addition to the original text, possibly based on the Gospel of Luke. In the first century, demons were believed widely to cause physical and psychological illness. Bruce Chilton, a scholar of early Christianity, states that the reference to the number of demons being "seven" may mean that Mary had to undergo seven exorcisms, probably over a long period of time, due to the first six being partially or wholly unsuccessful. [...]

Because Mary is listed as one of the women who supported Jesus' ministry financially, she must have been relatively wealthy. The places where she and the other women are mentioned throughout the gospels indicate strongly that they were vital to Jesus' ministry and that Mary Magdalene always appears first, whenever she is listed in the Synoptic Gospels as a member of a group of women, indicates that she was seen as the most important out of all of them.[...] That women played such an active and important role in Jesus' ministry was not entirely radical or even unique;[32][34] inscriptions from a synagogue in Aphrodisias in Asia Minor from around the same time period reveal that many of the major donors to the synagogue were women.

As witnesses:

All four canonical gospels agree that several women watched Jesus's crucifixion from a distance, with three explicitly naming Mary Magdalene as present. Mark 15:40 lists the names of these women as Mary Magdalene; Mary, mother of James; and Salome.[40] Matthew 27:55–56 lists Mary Magdalene, Mary mother of James and Joseph, and the unnamed mother of the sons of Zebedee (who may be the same person Mark calls Salome). Luke 23:49 mentioned a group of women watching the crucifixion, but did not give any of their names. John 19:25 lists Mary, mother of Jesus, her sister, Mary, wife of Clopas, and Mary Magdalene as witnesses to the crucifixion.

The Gospels make no mention of her skill at riding a motorcycle. 

A note about the images. All of them are by ChatGPT. In the first one ChatGPT uses its default photorealistic style. I asked for a Jack Kirby style image for the second. The third is a generic graffiti style, though if you look closely you'll see Ben-Day dot patterns in the skin tones that were probably inherited from Roy Lichtenstein version that I haven't uploaded (boring). The fourth one is in the style of Salvador Dali while the last is Picasso, where I specifically mentioned Guernica

Notice that in the Picasso version the woman is straddling the bike while she's standing next to it in the other versions. Also, she looks more directly at Christ than she does in the others and her jacket is unzipped. I didn't ask for those changes.

Cat and bird

Art Deco on rails