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Received — 17 August 2026 ⏭ Activism

Pluralistic: Jennifer Jenkins' 'Music Copyright, Creativity, and Culture' (17 Aug 2026)

✇Pluralistic: Daily links from Cory Doctorow
By: Cory Doctorow
17 August 2026 at 09:00


Today's links

  • Jennifer Jenkins' 'Music Copyright, Creativity, and Culture': The definitive textbook (with comics!).
  • Hey look at this: Delights to delectate.
  • Object permanence: Hair-gel bombers v bras; Hair-gel bombers v chemistry; AOL digs for spammer's platinum; Stross on infosec in 2061; In-game Ponzi; Snowden on Shadow Brokers hack; Life v understanding advanced math; "Greatest of Marlys!"; Housing and precarity; LLMs as slot-machines for coders; Hypercard's backstory; Pirate Party; Fanbois' mental health v critics; Krugman calls for alien invasion; Trump x Serbian genocidaires; The last Sandman Slim; Muphry’s Law; NSA created the Shadow Brokers; DOJ kills private prisons; Walmart externalizes crime; "Sgt Augmento"; Zuckermuskian solipsism.
  • Upcoming appearances: Sydney, Melbourne, Brighton, London, South Bend.
  • Recent appearances: Where I've been.
  • Latest books: You keep readin' em, I'll keep writin' 'em.
  • Upcoming books: Like I said, I'll keep writin' 'em.
  • Colophon: All the rest.


The cover for the Oxford University Press edition of Jennifer Jenkins' 'Music Copyright, Creativity, and Culture.'

Jennifer Jenkins' 'Music Copyright, Creativity, and Culture' (permalink)

Nobody explains copyright like Jennifer Jenkins, the director of the Duke Center for the Public Domain, in which capacity she is responsible for the annual New Year's roundups of all the materials entering the public domain (a series that started in the decades during which the public domain was frozen by the Sonny Bono Copyright Act):

https://pluralistic.net/2023/12/20/em-oh-you-ess-ee/#sexytimes

Jenkins has a gift for making one of the most complicated, worst understood, most consequential areas of law not only comprehensible, but also fascinating. Her late 2023 explanation of what "Mickey Mouse's copyright is expiring" actually meant was the single best explainer on the subject, in a crowded field:

https://pluralistic.net/2023/12/15/mouse-liberation-front/#free-mickey

Small wonder that she's the go-to copyright and trademark expert for so many media outlets. Perhaps you heard her Planet Money segments on which superheroes are in the public domain:

https://www.npr.org/transcripts/969512231

Jenkins' flair for legal communications carries over to her scholarly work, of course, which is why her Open Copyright Casebook is a standard text for American law schools:

https://pluralistic.net/2024/07/30/open-and-shut-casebook/#stop-confusing-the-issue-with-relevant-facts

Jenkins co-wrote the Casebook with her husband, the equally erudite and expert James Boyle. It's just one of their many fruitful collaborations; they are also the writing team behind THEFT! A History of Music, the greatest graphic novel ever created about the history of music, music law, music censorship, and the music industry:

https://web.law.duke.edu/musiccomic/

Last year, Jenkins published Music Copyright, Creativity, and Culture, an Oxford University Press title that fuses her scholarly and popular work in a generalist textbook on the legal framework for music that will forever change how you think about music. Now, a second edition, with a lengthy section on new music litigation, AI copyright fights, and the issue of uncompensated labor is available as an open access download:

https://web.law.duke.edu/cspd/musiccopyright/

Music Copyright weaves together the economic, cultural, political and artistic history of music, pulling on historic threads ranging from antiquity to medieval Europe to the age of mechanical reproduction to describe changing views of musicians, their audiences, and religious and political leaders on what constituted music, who was allowed to make music, and what music was for. In so doing, she firmly establishes the extremely contingent nature of our present-day norms around music, showing that the "natural" present-day assumptions about who gets paid, who pays, and when payment (or permission) is required are anything but, and are always in flux.

For obvious reasons, much of Jenkins' text describes these changes in the context of the record, the radio, satellite transmission, P2P file-sharing, and digital sampling (along with a chapter on AI). These examples are liberally illustrated with links to musical excerpts that bring the subject to life (these are presented as hotlinks in the ebook; if you're reading the print edition, you can use the book's companion website:)

https://web.law.duke.edu/cspd/musiccopyright/

Interspersed with these histories and analysis are lengthy, extremely on-point excerpts from THEFT!, her graphic novel history of music. These enliven the text as much as the music samples, making this textbook as entertaining as it is informative.

Of especial interest – and importance – are the long sections on the courtroom battles of Ed Sheeran, Katy Perry, and Pharrell Williams over similar "grooves" and "vibes" to other songs, some of them well-known and some quite obscure:

https://pluralistic.net/2022/04/08/oh-why/#two-notes-and-running

These cases highlight the fundamental incoherence of music copyright, a system composed of improvised responses to new technologies, each layered atop the last in a messy pile that virtually no one understands.

Jenkins understands it, though. I've been reading, writing, and debating about this stuff since the late 1990s, and I learned something new on every page of this delightful book. This should be required reading for anyone who makes music, loves music, or cares about musicians and the arts more generally. It's a towering accomplishment and a brilliant read.

Hey look at this (permalink)


A shelf of leatherbound history books with a gilt-stamped series title, 'The World's Famous Events.'

Object permanence (permalink)

#25yrsago RIP, The Industry Standard, Palm buys BeOS https://web.archive.org/web/20010927192339/http://www.wired.com/news/business/0,1367,46113,00.html

#25yrsago Smart dust sensors https://web.archive.org/web/20011112010004/http://www.smalltimes.com/document_display.cfm?document_id=1935

#25yrsago Pentagon patents onion-routing https://web.archive.org/web/20010912222427/http://www.wired.com/news/politics/0,1283,46126,00.html

#25yrsago Coltan: the conflict mineral in our gadgets https://www.nytimes.com/2001/08/12/magazine/the-dirt-in-the-new-machine.html

#25yrsago Danny Goodman Talks About HyperCard https://web.archive.org/web/20011214114614/http://www.oreillynet.com/pub/a/mac/2001/08/17/goodman.html

#25yrsago Report an insecure website, win a visit from the FBI https://web.archive.org/web/20010820110330/http://www.linuxfreak.org/post.php/08/17/2001/134.html

#20yrsago Copyright wars: film-makers eats themselves https://web.archive.org/web/20070318010544/https://www.laweekly.com/film+tv/film/freedom-of-information/14244/

#20yrsago RyanAir to UK govt: ease off on security or we sue https://www.theguardian.com/business/2006/aug/18/theairlineindustry.terrorism

#20yrsago Federal court bans Bush’s warrantless spying on Americans https://edition.cnn.com/2006/POLITICS/08/17/domesticspying.lawsuit/index.html

#20yrsago Western millionaires plotted Equatorial Guinea coup as a game https://web.archive.org/web/20071114211448/https://www.salon.com/books/review/2006/08/17/roberts/index_np.html

#20yrsago Sweden’s Pirate Party – political arm of the pro-piracy groundswell https://web.archive.org/web/20060820093355/https://www.wired.com/news/technology/1,71544-0.html

#20yrsago Hair-Gel Bombers win war on bras https://www.huffingtonpost.co.uk/entry/us-authorities-leave-gel_n_27402

#20yrsago Would a hair-gel bomb actually work? https://seclists.org/interesting-people/2006/Aug/86

#20yrsago The Pirate Bay’s backstory https://web.archive.org/web/20060901180116/https://www.wired.com/news/technology/1,71543-0.html

#20yrsago AOL will dig for buried platinum and gold in spammer’s Mom’s yard https://www.nbcnews.com/id/wbna14365934

#15yrsago Charlie Stross on network security in 2061 https://www.antipope.org/charlie/blog-static/2011/08/usenix-2011-keynote-network-se.html

#15yrsago Damning 2007 letter asserts that phone hacking was an open practice at News of the World https://www.theguardian.com/media/2011/aug/16/phone-hacking-now-reporter-letter

#15yrsago In-game Ponzi nets US$50K https://web.archive.org/web/20110921052125/http://gamergaia.com/pc/1724-eve-online-space-heist-one-trillion-isk.html

#15yrsago Copyright troll handed ass (again), tries saddest trick ever to get out of paying its victim’s legal bills https://arstechnica.com/tech-policy/2011/08/righthaven-rocked-owes-34000-after-fair-use-loss/

#15yrsago English cops arrest man for planning water-fight via Blackberry Messenger https://www.theguardian.com/media/2011/aug/15/essex-water-fight-blackberry-messenger

#15yrsago Woman who recorded Massachusetts police beating charged with illegal wiretapping https://www.masslive.com/news/2011/08/videographer_of_alleged_melvin.html

#15yrsago Criticism of a brand lowers the self-esteem of its adherents https://arstechnica.com/science/2011/08/users-treat-criticism-of-favorite-brands-as-threat-to-self-image/

#15yrsago Homeopathy multinational sues blogger over statements that its mythological curative had “no active ingredient” https://web.archive.org/web/20110930131033/http://www.blogzero.it/contatti/prova/

#15yrsago Edinburgh Fringe show asks audience to shred banknotes https://www.theguardian.com/culture/2011/aug/16/crunch-edinburgh-festival-shred-cash

#15yrsago CCTV deterrence and the London uprising https://www.theguardian.com/technology/2011/aug/17/why-cctv-does-not-deter-crime

#15yrsago Paul Krugman: save the economy by staging an alien invasion hoax https://comicsalliance.com/watchmen-paul-krugman-alien-invasion/

#15yrsago Minecraft creator challenges trademark belligerents to winner-take-all Quake deathmatch https://web.archive.org/web/20110817205045/http://notch.tumblr.com/post/9038258448/hey-bethesda-lets-settle-this

#15yrsago Muphry’s Law: the inevitability of typos in discussions of typos https://web.archive.org/web/20101227141449/https://www.editorscanberra.org/muphrys-law/

#15yrsago Copyright complaint as phishing email https://memex.craphound.com/2011/08/18/copyright-complaint-as-phishing-email/

#15yrsago Rep Allen West pens “dumbest thing ever written on congressional stationery” https://web.archive.org/web/20110914030034/https://thinkprogress.org/security/2011/08/17/297619/allen-west-nuts/

#10yrsago The NSA’s program of tech sabotage created the Shadow Brokers https://web.archive.org/web/20160818132904/https://www.wired.com/2016/08/shadow-brokers-mess-happens-nsa-hoards-zero-days/

#10yrsago Walmarts are high-crime zones thanks to staff cuts, but America gets the bill https://web.archive.org/web/20160818000539/https://www.bloomberg.com/features/2016-walmart-crime/

#10yrsago DoJ says it will end private federal prisons https://www.motherjones.com/politics/2016/08/department-justice-plans-end-private-prison/

#10yrsago Fiction: Sgt. Augmento, Bruce Sterling’s robots-take-our-jobs story https://web.archive.org/web/20160818161624/https://motherboard.vice.com/read/sgt-augmento

#10yrsago Las Vegas: high unionization rates mean smaller wage-gaps for women, especially older women https://www.nytimes.com/2016/08/17/opinion/how-unions-help-cocktail-servers.html

#10yrsago The incredible true story of the Epcot Horizons superfans who ruled the ride https://web.archive.org/web/20160822031741/https://dangerousminds.net/comments/the_true_story_of_the_unauthorized_daredevil_documentation_of_the_horizons_/

#10yrsago Predictive policing predicts police harassment, not crime https://web.archive.org/web/20160821093834/https://link.springer.com/article/10.1007/s11292-016-9272-0

#10yrsago UC Davis Chancellor spent $400K+ to scrub her online reputation after pepper-spray incident https://www.sacbee.com/news/local/article94733812.html

#10yrsago Reputation systems work because people are mostly good https://timharford.com/2016/08/the-meaning-of-trust-in-the-age-of-airbnb/

#10yrsago The guy who started Serbia’s ethnic cleansing led a pro-Trump rally in Belgrade https://web.archive.org/web/20160817022133/https://theintercept.com/2016/08/16/serb-inspired-ethnic-cleansing-bosnia-leads-vote-trump-rally-belgrade/

#10yrsago Europe’s banks want to store billions in cash to fight back against negative interest https://web.archive.org/web/20160817152157/https://www.cnbc.com/2016/08/16/banks-look-for-cheap-way-to-store-cash-piles-as-rates-go-negative.html

#10yrsago Kill Rock Stars president explains why the radio plays the same songs over and over https://www.youtube.com/watch?v=ThrXkYwTBP8

#10yrsago Snowden explains the Shadow Brokers/Equation Group/NSA hack https://www.techdirt.com/2016/08/16/ed-snowden-explains-why-hackers-published-nsas-hacking-tools/

#10yrsago Hackers claim to have stolen NSA cyberweapons, auctioning them to highest bidder https://web.archive.org/web/20160816035711/https://motherboard.vice.com/read/hackers-hack-nsa-linked-equation-group

#10yrsago What life is like when you really understand advanced mathematics https://www.quora.com/What-is-it-like-to-understand-advanced-mathematics-Does-it-feel-analogous-to-having-mastery-of-another-language-like-in-programming-or-linguistics

#10yrsago Parents who can’t pay the bill for kids’ incarceration can still go bankrupt, a US court rules https://archive.thinkprogress.org/everything-wrong-with-how-our-justice-system-treats-poor-people-in-one-awful-case-bfd91a6fa114/

#10yrsago UK Intellectual Property Office grants trademark on “should’ve” https://www.bbc.co.uk/news/business-37092366

#10yrsago The Greatest of Marlys! is the Lynda Barry book we’ve been waiting for https://memex.craphound.com/2016/08/16/the-greatest-of-marlys-is-the-lynda-barry-book-weve-been-waiting-for/

#5yrsago Housing, money laundry, speculation and precarity https://pluralistic.net/2021/08/16/die-miete-ist-zu-hoch/#assets-v-human-rights

#5yrsago Big Oil caught lying about methane https://pluralistic.net/2021/08/17/king-bullet/#methanescan

#5yrsago Sandman Slim's final adventure https://pluralistic.net/2021/08/17/king-bullet/#sticking-the-dismount

#5yrsago The Sacklers threaten us all with a good time https://pluralistic.net/2021/08/18/lets-make-a-deal/#art-of-the-deal

#1yrago Zuckermuskian solipsism https://pluralistic.net/2025/08/18/seeing-like-a-billionaire/#npcs

#1yrago LLMs are slot-machines https://pluralistic.net/2025/08/16/jackpot/#salience-bias

Upcoming appearances (permalink)

A photo of me onstage, giving a speech, pounding the podium.


A screenshot of me at my desk, doing a livecast.

Recent appearances (permalink)


A grid of my books with Will Stahle covers..

Latest books (permalink)


A cardboard book box with the Macmillan logo.

Upcoming books (permalink)

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

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

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

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


Colophon (permalink)

Today's top sources:

Currently writing:

  • “Once Is Enemy Action,” a science fiction novel about the origins of modern technofascism. Friday's words: 564 (6039 total).

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

  • A Little Brother short story about DIY insulin PLANNING

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

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

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

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

ISSN: 3066-764X

Received — 12 August 2026 ⏭ Activism

Pluralistic: Model collapse (12 Aug 2026)

✇Pluralistic: Daily links from Cory Doctorow
By: Cory Doctorow
12 August 2026 at 10:55


Today's links


A collage made of architectural features from 'Variae Architecturae Formae' (1636), a collection of engravings. The architectural arches, buildings, fountains, etc, are layered atop each other and placed around each other to create an infinite, recombinant built environment.

Model collapse (permalink)

One of my favorite rhetorical and analytical moves is joining things together (showing that two different, seemingly unrelated ideas are aspects of the same phenomenon) and taking them apart (resolving a paradox by demonstrating that what appears to be one, contradictory thing is actually two different things that have been lumped together).

"Taking things apart" is a very useful framework for understanding AI. How do we resolve the (seeming) paradox that some skilled workers report wonderful results from their work with AI, while others are full of dire warnings about the lurking defects in their AI-assisted outputs? Simple: the first group are "centaurs" (humans who are assisted by machines) and the second are "reverse centaurs" (humans who have been pressed into service as peripherals for machines):

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

What are we to make of the people who've been fired by bosses who replaced them with AI, in light of the fact that AI is demonstrably not able to do their (former) jobs? Again, it's simple if you separate out two distinct phenomena: "AI can do your job" is the first. The second is: "Your boss is a credulous dolt who is infinitely horny for replacing lippy workers with pliable machines, which made him an easy mark for an AI salesman who convinced him to fire you and replace you with an AI that can't do your job":

https://pluralistic.net/2025/03/18/asbestos-in-the-walls/#government-by-spicy-autocomplete

This is also a useful move for understanding the AI investment bubble. It's not just billionaires who don't think other people are as real as they are and consequently their jobs can be done by chatbots. It's also billionaires who believe that bosses can be sold AI and don't care if the AI is defective, because that's your boss's problem after he buys the AI and fires you. They don't have to believe in AI in order to think it's a good investment: like an investor betting that Joe Rogan can sell millions of dollars' worth of peptides to desperate young men, they are assessing the sales potential, not the merits of the thing for sale:

https://pluralistic.net/2026/08/03/andor/#either

As useful as "taking things apart" is, "putting things together" is also a very important technique for assessing, critiquing and improving AI. In a stellar essay entitled "Temperature Zero for Culture: Why Everything Is Starting to Look the Same" by the data scientist Lauren Leek, we get a top-notch example of "putting things together":

https://laurenleek.substack.com/p/temperature-zero-for-culture-why

Leek's essay is one of those fabulous, wide-ranging, cross-disciplinary pieces, touching on urban design, music trends, synthetic LLM crowds, Netflix recommendation algorithms, and several other subjects, all seeking to resolve a(nother) (seeming) paradox: how is it that we have so much potential variety, but everything is so manifestly the same?

The answer is complicated and nuanced, but Leek's foundational point is that in a data-driven society, "predictions" are self-fulfilling prophecies. As Leek puts it: "Once prediction shapes the choices in front of us, we lose the ability to tell the difference between what people wanted and what the system made easy to want."

This is a pervasive issue across many domains. Leek says that economists call it "performativity," while machine learning researchers call it "model collapse" and urbanists call it "placelessness."

"Performativity" describes how, once a market has been modeled by economists, that model becomes the foundation for economic policy, which pushes the market to conform to the model:

https://press.princeton.edu/books/paperback/9780691138497/do-economists-make-markets

"Model collapse" describes how machine learning models that are trained on their own predictions become incredibly bland, with all variety disappearing from the system's predictions:

https://pluralistic.net/2024/03/14/inhuman-centipede/#enshittibottification

This is hugely consequential: it's why bias proliferates through predictive policing algorithms: train a model with data from racist stop-and-frisks and it will predict that all the weapons and drugs in a city are to be found in Black and brown peoples' pockets. Turn those predictions into recommendations telling cops where to go look for weapons and drugs and they will double down on racist stops, producing even more biased training data, which turns into still more bias in the predictions:

https://hrdag.org/2016/10/10/predictive-policing-reinforces-police-bias/

"Placelessness" is the urbanist's name for "when everywhere optimises toward the same template." I think of it as Flinstones Syndrome, where the same background is looped behind Fred and Barney as they drive through Bedrock. In New York City, it's Citibank-bodega-Chipotle-Walgreens; in the Chicago suburbs, it's the strip malls with a Chili's, a gas station, and a big box store.

Leek proposes that these are all expressions of the same underlying phenomenon, a failure mode of data science that takes a world of "granular personal data" and arrives at a world where "personalisation produc[es] more sameness."

To these excellent examples, I'd add another one, from the world of monetary policy: Goodhart's Law, which holds that "When a measure becomes a target, it ceases to be a good measure":

https://en.wikipedia.org/wiki/Goodhart%27s_law

Goodhart's Law captures a wide variety of phenomena. When Google first deployed Pagerank, they showed that by counting the inbound links to all the pages on the web, you could extract a signal about which pages were most important (because there was no reason to link to a page unless you found it noteworthy).

But once Pagerank became the dominant means by which web users found pages, counting links stopped being useful: first, because people used Pagerank to find the best pages and link to them, making it impossible for new pages to get the inbound links needed to supersede incumbent pages; and second, because it's easy for fraudsters to create inbound links for low-quality pages in bulk, once there's a reason to do so.

Counting inbound links was a world-beating retrospective way of predicting which page would best match a searcher's query, but once it shaped the world it sought to analyze, it ceased to be a good prospective way to predict which page would best match your queries.

Leek is a brilliant data scientist and an even better science communicator, with a knack for crisp, readily understood explanations. How can a world of granular, highly varied data turn into a world of homogeneous choices? Simple: start with a set of items ("cuisines, genres, shop types") and a standard algorithm for sorting them. Let users choose from those recommendations. The mode (average) of those choices "gets shown more, so it gets picked more, so the model grows more confident the mode is what people want, and the tails starve." Run this for a few rounds and the evenly distributed catalog of choices "collapses onto one dominant option."

This is intrinsic in the choices we make in designing recommendation algorithms, tilting them towards the likelihood of a successful recommendation. A recommender that wants to succeed every time will make the safest possible recommendations, "so an algorithm that is uncertain about you, and it is always at least a little uncertain, hedges toward the average."

Then she busts out a beautiful, perfect little statistics aphorism: "Personalisation under a standard loss function is regression to the collective mean with extra steps." That is to say, "regression to the mean" (the tendency of varied things to become more standardized) cannot be avoided with the standard personalization algorithm. That algorithm is going to play it safe, showing you things that are broadly palatable, and because your choices are constrained to the average, you will choose average things.

This is how recommendation systems – and other analytical tools that produce predictions that are then turned into action – force so many diverse phenomena (streets, markets, media recommendations) into sameness. The fact that these recommenders are self-fulfilling prophecies means that "they don't have to be right," only "listened to."

This explains the sameness of so many of London's high streets. Leek examines 640 shopping streets, characterizing 18,000 food places spread out across them, flagging all the chain restaurants. Her analysis shows that any two London streets will, on average, share about half of their "food profile."

Obviously, this is most pronounced on streets with chain outlets, and it doesn't take that many chain outlets before a street's sameness shoots up: "A relatively small number of repeated names is enough to make otherwise different streets resemble one another more." So why do streets with chains resemble one another so much? Because the chains use an algorithm (weighting footfall, proximity to train stations, demographics, and competitors) to decide where to put their restaurants. If a street with a Gail's Bakery on it feels like every other street with a Gail's Bakery, that's because Gail's only puts its restaurants in places that have highly similar characteristics, measured to a high degree of accuracy and controlled by a narrow set of tolerances.

In other words, every street that feels like it should have a Gail's will eventually get a Gail's, whereupon that street will feel even more like all the other streets that have a Gail's, because it will share one more common factor with those other streets (a Gail's).

Leek points here to her earlier work on pub closures in the UK. The UK has experienced an epidemic of pub closures, with thousands of pubs disappearing since 2016:

https://laurenleek.substack.com/p/britain-lost-14000-third-places-they

Her research found that the biggest predictor of a pub surviving was its similarity to the median pub; which is to say that the more distinctive a pub was, the more "character" it had, the more likely it was to close. Pubs that are different from the average pub are harder to categorize, which means they're harder for a bank manager to assess for creditworthiness or for a landlord to justify extending a long-term lease to. The algorithms used to allocate capital and real estate are also recommenders, and they also drive variety out of the system.

This same phenomenon acts on culture. In an age of music recommendation algorithms, hit songs are changing; today's songs use a smaller vocabulary of unique words and repeat those words more often:

Vocabulary richness, distinct words relative to length, has fallen by more than a quarter since the early 1960s, while the share of repeated lines has climbed by nearly a third. The modern hit says less and says it more often, because the hook that works gets repeated.

But that's not the whole story! While each song resembles itself more ("saying less more often"), within that constraint, there's far more variety today than before: a given song's (constrained) vocabulary has grown more distinct when compared to all the other songs' vocabularies. Songs repeat the words they use, but the words repeated in songs are getting more different.

For Leek, this is the key to understanding the whole phenomenon and (more importantly) doing something about it. Music recommendation systems optimized for a singable hook, but did not optimize on any of the other variables in songs, so those dimensions acquired a broader range, even as the optmized variable got flatter and narrower.

This means that the tendency of recommenders to "flatten the world" isn't a single blunt outcome: it depends on which dimension we choose to flatten through recommendation, and who chooses to flatten that dimension.

A media recommender optimizes for consumption, showing you a tractable set of things it believes you'll watch, read or listen to. When you choose from among this limited set, the recommender takes note of that fact and shows you more of the same, pushing everything to a greige median. All the movies, books and songs you might have liked that were omitted from that initial set are excluded from being recommended in the future. The features of that media that you might have appreciated "decay out of consideration." They are never tested for desirability. The model collapses.

How badly does it collapse? Leek cites Movietweetings' data on which movies people watch: out of a million public movie ratings, half relate to the top 2% of movies in the set. There's 38,000 films in the set, but just 380 titles account for 40% of the ratings. Leek argues (persuasively) that this isn't because recommenders are good at "knowing your taste" – rather, they are good at "narrowing the menu."

Leek relates this to her work on creating LLM "personas" – synthetic populations meant to mimic the tastes and proclivities of real groups of people, that you can interrogate "before you spend money asking actual humans." While this would be useful for many applications, "it fails in exactly the way this whole essay is about."

Leek went to enormous lengths to reproduce the traits that make people interesting to study in aggregate, painstakingly replicating the ways that social connections, psychological outlook and demographic factors predict people's beliefs. The result was a set of LLM personas with "elaborate stories" about how they differed from one another, but whose survey responses about planned actions were homogeneous in a way that real populations are not.

This, Leek writes, is the same force that homogenizes other data-driven predictors. Because she'd ordered her LLM to reproduce the statistically validated relationships between different factors that predict a person's beliefs, each synthetic persona was a homogenized average. It's like the paradox of "The Average Man," where military uniforms sized to the average of all service personnel fit no one, because no one is average:

https://archive.org/details/DTIC_AD0010203

The thing is (as Leek points out) the idea that synthetic personas are a good way to understand the preferences of a real population is not a harmless delusion: it's a product that's being actively sold to governments, campaigning politicians and marketers. It's a self-fulfilling prophecy that drives governance, political campaigns and product design to the same homogeneous median that is making every shopping street in London feel the same.

This matters. As Leek writes, ecologists have long understood the importance of variety for systemic resilience: they call it "the insurance value of biodiversity." A diverse system has reservoirs of species and variation that may not be optimized for how things stand now, but that can move into niches created when things change in ways that lay waste to the previously dominant organisms. As anyone whose favorite banana went extinct can tell you, homogeneity works well, but diversity fails well:

https://en.wikipedia.org/wiki/Gros_Michel

The brittleness of algorithm-induced homogeneity is compounded by the fact that recommenders obscure the true preferences of people. If you watch two Scandinavian crime dramas after Netflix recommends them to you, it will keep showing you more Scandy crime for the next decade – even if there's another kind of programming that you'd vastly prefer (if only you knew about it). This means that decision-makers who choose which shows will get made in the future will keep on funding their safe Danish detectives, to the exclusion of whatever might emerge from the same weird attractor that produced the K-Pop Demon Hunter fortune.

Transpose this failure mode onto states, bank managers and landlords, and we see whole ranges of policies, businesses and activities that never come into existence, despite the popularity, prosperity and joy they might bring us.

But Leek doesn't end with this worrisome note. Instead, she identifies this whole thing – model collapse, placelessness, performativity, even Goodhart's Law – as an expression of one of the best-understood tradeoffs in computer science: "exploration vs exploitation":

Any system learning from feedback has to divide its effort between exploiting what already scores well and exploring options it hasn’t tried, in case they’re better.

Computer scientists have long understood that focusing on exploitation to the exclusion of exploration is a trap that locks you into "the first decent option" so you can never discover the best one.

Which means that this algorithmic homogeneity has a well-understood corrective: "forcing exploration back in." The problem is that markets hate this kind of exploration. A company that lives and dies by how many clicks it gets is never going to sacrifice 20% of its traffic by showing its users weird, untested options that score worse than the median because these weird things have never had a chance to prove that they are desirable.

This is a classic market failure, and, as Leek points out, there are regulatory responses in the UK (the Digital Markets, Competition and Consumers Act) and the EU (the Digital Services Act), both of which require the largest platforms to open up their recommendation systems, but so far, regulators have focused on "online harms" rather than variety (though the DSA does require platforms to offer algorithmic recommendations that are not based on your personal traits).

Leek identifies this willingness of states to set conditions for algorithm design as a means by which "exploration" can be forced back into the system. She's also bullish on interoperability, so that users can leave platforms with bad recommenders, without losing access to their media or social circles. As she writes, "the deepest discipline on a feed that has trapped you is the credible ability to leave it and take your data with you." I couldn't agree more:

https://pluralistic.net/2023/01/08/watch-the-surpluses/

She's less hopeful about individual responses. Demanding that you be an "adventurous consumer" is a way of letting systems off the hook. When every street has the same restaurants and every bookshop has the same books and the people in your life are all locked into one of two social media platforms, "choosing wisely" only gets you so far. Shopping isn't politics!

https://pluralistic.net/2026/05/21/purity-culture/#stop-fucking-that-chicken

Leek is a superb writer. After reading this piece yesterday, I sent it to half a dozen people and then read everything else in Leek's newsletter archives. Not only is it all brilliant, but I also realized that she'd written one of the most memorable articles about cities and platforms I've read in the last year, "How Google Maps quietly allocates survival across London’s restaurants – and how I built a dashboard to see through it":

https://laurenleek.substack.com/p/how-google-maps-quietly-allocates

I should have added Leek's newsletter to my RSS reader when I read that last December. I've rectified that oversight! What a fantastic thinker, scientist and communicator! If she isn't being relentlessly pestered by editors and literary agents offering her a book deal, then it really does prove that the recommender systems are elevating the bland median over the thoroughly, delightfully spiky outliers.

Hey look at this (permalink)


A shelf of leatherbound history books with a gilt-stamped series title, 'The World's Famous Events.'

Object permanence (permalink)

#25yrsago Awful, stupid Wired report on Dutch hacker camp https://web.archive.org/web/20011007084604/https://www.wired.com/news/culture/0,1284,46033,00.html

#25yrsaog Excellent NYT story about the internal contradictions of the DMCA https://memex.craphound.com/2001/08/13/excellent-nyt-story-about-the/

#20yrsago Our faulty intuition about open systems https://www.ft.com/content/64167124-263d-11db-afa1-0000779e2340

#20yrsago Defending against the last plot won’t save us from the next one https://www.schneier.com/blog/archives/2006/08/terrorism_secur.html

#20yrsago NBC: Hair-gel terrorists posed no risk last week https://web.archive.org/web/20060813194630/http://www.msnbc.msn.com/id/14320452/

#15yrsago AT&T merger leak: it’s all about raising prices and reducing competition https://web.archive.org/web/20110920222524/http://www.broadbandreports.com/shownews/Leaked-ATT-Letter-Demolishes-Case-For-TMobile-Merger-115652

#10yrsago What’s inside a Tiki Bird? https://miehana.blogspot.com/2016/08/fancy-feathers-restoring-tiki-room-birds.html

#5yrsago End of the line for Reaganomics https://pluralistic.net/2021/08/13/post-bork-era/#manne-down

#5yrsago Smart cities are neither, 2021 edition https://pluralistic.net/2021/08/13/post-bork-era/#our-streets

#1yrago Maga's boss class think they are immune to American carnage https://pluralistic.net/2025/08/13/then-they-came-for-me/#boss-politics

Upcoming appearances (permalink)

A photo of me onstage, giving a speech, pounding the podium.


A screenshot of me at my desk, doing a livecast.

Recent appearances (permalink)


A grid of my books with Will Stahle covers..

Latest books (permalink)


A cardboard book box with the Macmillan logo.

Upcoming books (permalink)

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

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

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

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


Colophon (permalink)

Today's top sources:

Currently writing:

  • “Once Is Enemy Action,” a science fiction novel about the origins of modern technofascism. Today's words: 546 (4161 total).

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

  • A Little Brother short story about DIY insulin PLANNING

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