If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2026/11/04/genius-scan-is-neither/#x-marked-the-spot

“AI is being shoved down our throats” can mean any of several things. It can mean that our bosses are demanding that we use AI in reckless or nonsensical ways on the job:

https://www.404media.co/manifestos-fear-and-loser-thinking-inside-protons-ai-reckoning/

It can mean that Elon Musk and the NASDAQ have colluded to force ordinary retirement savers to bail out his emirati and tech oligarch buddies:

https://www.nytimes.com/2026/06/05/technology/spacex-indexes-401k.html

These are arguably the most important ways in which AI is shoved down our throats, but the most visible form of conscription into the number-go-up AI project is happening at the user interface level. This UI fuckery predates AI. For more than a decade, tech companies and their executives have colluded to trick, coerce and force you into using new features that they wanted to sell to their investors as the future of their companies.

Remember Google Plus, the Facebook-killing social layer that was going to give Google access to a new, multi-trillion-dollar market? Bradley Horowitz, then a VP at Google, charged every product team with cramming G+ into their offerings, tying their bonuses to G+ usage (at companies like Google, your bonus can dwarf your base salary).

Now, googlers are bright and resourceful people, and if you tell them that they can double their earnings by getting users to click on Google Plus buttons, they’ll come up with all kinds of ways to get you to do this. Some of those gambits will be the kind of thing that Horowitz doubtless hoped for: innovative and creative ways to add value to Google’s core offerings with G+ features.

But when the stakes are that high, Goodhart’s Law inevitably comes into play: “When a measure becomes a target, it ceases to be a good measure”:

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

The easiest way to get a user to click on a G+ button is to replace whatever button that user hits most often with a G+ version. Rather than introducing users to Google Plus in a way that turns them into G+ fans, you just frustrate them by tricking them into clicking on a useless button.

From a product manager’s perspective, it’s worth making whatever changes as are needed to ensure that your salary is doubled because you hit your “key performance indicator” (KPI), even if it’s at the expense of your users’ loyalty to your product. Preserving user loyalty at the expense of half your wages is a bad trade.

When a machine learning system does this, we call it “reward hacking.” AI programmers create an “objective function” for their system, a single number that the system will try every tactic to increase; then, more often than not, the AI program finds perverse shortcuts to make the number go up whether or not it achieves the programmer’s goal:

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

For example, if you charge an AI with coming up with the shortest run through a video game, it might well discover a bug that makes it impervious to enemy attacks or just lets it teleport to the end of the game. To avoid these perverse outcomes, programmers have to add more and more specificity to their objective functions: “speed run the game without teleporting or discovering an immortality hack.”

Not for nothing, many science fiction writers (including me) have noted that tech bosses’ fear of their own AI systems is a kind of emotional spillover from their frustrations with the corporations they run, where underlings engage in the same kinds of reward hacking that we see from chatbots:

https://pluralistic.net/2025/04/14/timmy-share/#a-superior-moral-justification-for-selfishness

Despite the ease with which metrics can be gamed, tech bosses remained committed to the use of KPIs to shift the priorities of their organizations, and they use the same objective function refinement technique that programmers use for reward-hacking AIs in a bid to prevent cheating by employees who hit their KPIs any way they can.

This explains a lot about the experience of watching a video on your phone. Any time you tune into a show on a streaming platform, you are forced to handle your phone with the delicacy of a photonegative. If any part of your hand brushes any part of the screen, you will immediately be whisked away from the video you’re watching to an entirely different one:

https://pluralistic.net/2022/05/15/the-fatfinger-economy/

Worse, after your program has been replaced with this new one, there’s no obvious way to get back to the show you were just watching. This is very weird, considering that the “back button” has been a part of computer interfaces since 1981:

https://www.merriam-webster.com/dictionary/back%20button

The reason you don’t get a back button is reward hacking. Streaming video platforms are under enormous pressure to successfully recommend their back-catalog to their users, because the alternative (commissioning or purchasing a steady stream of popular new shows) is very expensive. Investors put a lot of stock in streaming services’ “successful recommendation” rate.

So streaming service bosses charge their product teams with making “successful recommendations.” The easiest way to “recommend a show” is to booby-trap the streaming service’s UI so that touching any part of the screen takes you to a video you never asked to see.

This is obvious reward hacking, so streaming bosses refined their objective function: they made their teams’ bonuses contingent on getting you to watch a new video for a minimum time-frame. This in turn triggered the next volley in the reward-hacking wars, in which product teams took away the back button. This gives users any number of greased slides that whisk them away to a new video. To get back to the old video, users are forced to climb a greased pole.

This is the fatfinger economy: created in the 2010s by teams at large tech companies with KPI-obsessed bosses; refined in the 2020s by teams at bottom-line obsessed streaming media companies; and now perfected by teams being charged with cramming AI into every corner of our lives:

https://pluralistic.net/2025/05/02/kpis-off/#principal-agentic-ai-problem

The fatfinger economy is an extraordinary beneficiary of the drive to add “telemetry” to all of our apps. Today, an app vendor can call up a dashboard and find out which buttons and fields and sliders see the most use, and they can use that ranked list to figure out which buttons to replace with AI-demon-summoning lookalikes that help product teams “prove” to their bosses that they’ve “successfully integrated AI” and lets their bosses prove to their investors that “users value AI features.”

I recently switched from Android to Graphene, a de-googled phone operating system. Graphene’s maintainers are blissfully free from the imperative to show that “users value AI features,” and that’s why I have never accidentally summoned up an undismissable AI by tapping a Graphene UI element.

It’s a different story when it comes to apps. Graphene has many different ways to install apps, including via Google Play (Google’s default Android store). That’s useful because it lets you install your old Android apps after switching to Graphene, but it does leave you exposed to the fatfinger economy.

Last week, I got a painful reminder of the progress of the fatfinger economy outside of Graphene’s utopian pocket-universe. I make extensive use of an app called “Genius Scanner,” which lets me scan receipts and email them to myself (I do this a lot because, as a freelancer, I have to track a lot of different expenses). I bought a lifetime subscription to Genius Scanner in 2023, after getting burned by Camscanner (my previous, now enshittified scanning app), and I’ve been perfectly happy with it…until now.

Genius Scanner is obviously under pressure to drive AI adoption. I can tell because they’ve taken away the most important UI element and swapped it for a worse-than-useless AI button.

Here’s how I use Genius Scanner: I press the “make new scan” button and line up the receipt on the screen. Then I press the “retitle” button, which brings up a field that is populated with the current date and time (16 characters in all). This text used to be selected so that hitting the little “x” next to it deleted it, making it easy to title a new scan. After that, I’d just email it to myself.

As of last week, though, there is no button that deletes the date and time so you can enter a useful title. That little “x” has been replaced with a button that brings up an ad for the company’s new AI tools, which cost $40/year. There’s no way to tell the system that you’re not interested in buying a new subscription for the tool that you’ve already bought a lifetime sub for, and there’s no way to get that little “x” back.

To be clear: that little “x” represents one quarter of my receipt scanning workflow. They have swapped it out for an ad for a new subscription AI feature, and gave me 16 new keypresses on the backspace button to replace that single tap on the “x.” I have seen that ad about 100 times at this point, because I keep tapping the spot where the “x” used to be.

I’m certain that the company knew that its paying customers relied on the “x” to accomplish a vital function in any scanning app (giving good, descriptive titles to scans). They need the AI number to go up, so they replaced the “x” with the AI ad, which will let them tell their investors that they’ve got “strong consumer interest in their AI features.”

Meanwhile, they already have my money, so there’s no way I can punish them for their decision to screw me over to juke a meaningless stat. It’s as neat (and depressing) an example of the principle that “even if you’re paying for the product, you’re still the product” that you could ask for.

It’s also a perfect little object-lesson in the ways that companies can report increasing AI interest and usage without generating any interest or usage. In the fatfinger economy, every metric is a target, and is thereby rendered meaningless.

#20yrsago Army Times: Rumsfeld must go! https://web.archive.org/web/20061107220242/http://www.truthout.org/docs_2006/110406Z.shtml

#20yrsago UK is a surveillance society http://news.bbc.co.uk/1/hi/uk/6108496.stm

#20yrsago Record companies sue soccer mom’s kids https://web.archive.org/web/20061104145550/https://www.washingtonpost.com/wp-dyn/content/article/2006/11/02/AR2006110200114.html

#15yrsago HOWTO make your own skateboard truck lazy-susan table https://www.instructables.com/Skateboard-Table/

#15yrsago Home Secretary to OccupyLondon: you’re scaring the tourists https://www.bbc.co.uk/news/uk-england-london-15588987

#15yrsago Judge whose daughter released video of him beating her suspended from bench during judicial investigation https://web.archive.org/web/20111105234141/http://hosted.ap.org/dynamic/stories/U/US_VIDEOTAPED_BEATING_TEXAS

#15yrsago Prof who keeps announcing links between the Internet, childhood dementia and autism should publish theories in a scientific journal https://www.badscience.net/2011/11/why-wont-professor-greenfield-publish-this-theory-in-a-scientific-journal/

#10yrsago Internet of Things botnet threatens to knock the entire country of Liberia offline https://doublepulsar.com/shadows-kill-mirai-ddos-botnet-testing-large-scale-attacks-sending-threatening-messages-about-6a61553d1c7#.zg4448j8w

#10yrsago Black Lives Matter declares its opposition to TPP https://www.nakedcapitalism.com/2016/11/gauis-publius-tpp-has-picked-up-a-powerful-enemy-black-lives-matter.html

#20yrsago EFF fights another DMCA abuser https://web.archive.org/web/20061104133502/https://www.eff.org/deeplinks/archives/004973.php

#15yrsago Staircase covered in a cascade of synthetic human hair https://web.archive.org/web/20111030014202/http://www.jessicawohl.com/hairy-stairs

#15yrsago Entertainment industry incredibly profitable, healthy: but demands special pirate-hunting laws anyway https://arstechnica.com/tech-policy/2011/11/piracy-problems-us-copyright-industries-show-terrific-health/

#15yrsago There is no copyright policy, only Internet policy; there is no Internet policy, only policy https://locusmag.com/feature/cory-doctorow-its-time-to-stop-talking-about-copyright/

#10yrsago Sole and Despotic Dominion: how a 20th century copyright law is abolishing property for humans (but not corporations) https://locusmag.com/feature/cory-doctorow-sole-and-despotic-dominion/

#10yrsago Police in Quebec are spying on journalists and Snowden calls that “a threat to democracy” https://web.archive.org/web/20161104150400/https://motherboard.vice.com/read/edward-snowden-quebec-police-journalists-spying-surveillance

#10yrsago Donald Trump weaponized fine-print to make it impossible to sue Wall Street for fraud https://www.ibtimes.com/political-capital/how-donald-trump-used-fine-print-make-it-harder-sue-wall-street-fraud-2440890

#10yrsago High Court tells UK government that Brexit requires a vote in Parliament https://www.bbc.co.uk/news/uk-politics-37857785

#10yrsago Artist celebrates Patriot Act’s anniversary by handing out “Official Air Travel Replacement Knives” to arriving SFO passengers https://hyperallergic.com/on-anniversary-of-the-patriot-act-artist-passes-out-pocket-knives-at-the-airport/

#10yrsago A journalist finally uncovers the root of Trump supporters’ anger https://www.theawl.com/2016/11/i-talked-to-some-trump-voters-too/#.z9k84oxsg

#10yrsago A fake HP printer that’s actual an office-camouflaged cellular eavesdropping device https://www.wired.com/2016/11/evil-office-printer-hijacks-cellphone-connection/

#10yrsago UK hospitals shut down by malware, advise patients to go somewhere else for the duration https://www.zdnet.com/article/computer-virus-attack-forces-hospitals-to-cancel-operations-shut-down-systems/

If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2026/11/03/nobody-is-home/#metabolizers

Long before the Turing Test, there was the touring Edison Test: from 1915 to 1925, the scoundrel Thomas Edison put on a traveling show for his phonograph machine, touring venues around the USA. Edison set live performers and an Edison phonograph playing behind closed curtains that would be periodically pulled aside to reveal that the music the audience had taken to be live performance was actually a record player:

https://www.tomedison.org/blog/edisons-tone-tests

Now, if you’ve ever heard an Edison phonograph, this might seem like yet another tale in which old-timey people are revealed to be credulous yokels. You would never mistake one of those scratchy, hissing recordings for a live performance:

https://www.youtube.com/watch?v=96gIIFmEjY4

And indeed you wouldn’t, but not because the phonograph predates the evolution of the human brain’s anti-credulity lobe. The reason old-timey people couldn’t tell the difference between a phonograph and a live performance was that before the phonograph, every live performance had a performer.

The two were inseparable, and so when you encountered the sound of a musical performance, your brain would insist that there must be a performer as well. This is a well-understood principle in swindles, magic tricks and literature. It’s the basis of Douglas Adams’ towel gambit:

For some reason, if a strag discovers that a hitchhiker has his towel with him, he will automatically assume that he is also in possession of a toothbrush, washcloth, soap, tin of biscuits, flask, compass, map, ball of string, gnat spray, wet-weather gear, space suit etc, etc. Furthermore, the strag will then happily lend the hitchhiker any of these or a dozen other items that the hitchhiker might accidentally have “lost.”

All persons heretofore encountered in possession of a towel had all that other stuff, so the mere presence of a towel evokes an overwhelming intuition that all that other stuff must be nearby.

Like every conjuring trick and every swindle, this cognitive illusion swiftly regresses to the mean. After a few exposures to phonographs, the manifest differences between live performance and recordings become impossible to miss, and you stop making that mistake.

If one thing always signifies the presence of another — if a towel always implies a backpack full of supplies or if a performance always implies a performer — there’s no reason for you to entrain the neurological patterns needed to detect the performance without the performer. This doesn’t mean that it’s hard to develop the capacity to make this distinction, just that the ability to detect a phenomenon always post-dates your encounter with that phenomenon.

You’ve no doubt guessed by now that this is an analogy about AI. The implication of this ability to learn to discern differences after you encounter them (but not before) implies that a chatbot might pass the Turing Test at its introduction, but then come to fail the test after we’ve all had the experience with it that lets us tune our perceptions to spot the differences, which then become as unmissable as the needle hiss on a phonographic reproduction of a concert pianist.

This is an experience many of us have already had. Prior to chatbot-generated prose, we’d never had experience with writing that didn’t have a writer. Prior to image-gen output, we’d never had experience with paintings that didn’t have painters. At first, the output from these models was remarkable, and often indistinguishable from human-generated words and images. Even knowing that these works were extruded by an algorithm, it was hard to shake the conviction that they were the product of human creativity. These works were “eerie,” in the sense that Mark Fisher uses, “the seeming of intent without an intender”:

https://pluralistic.net/2024/05/13/spooky-action-at-a-close-up/#invisible-hand

Just like the strag inferring the existence of “toothbrush, washcloth, soap, tin of biscuits, flask, compass, map, ball of string, gnat spray, wet-weather gear, space suit etc, etc,” we automatically imputed to these works both a creator and a creative impulse. We supposed that their words and brushstrokes represented aesthetic and technical choices emanating from human creators who meant something by them (or at least were so satisfied by the accident of their appearance on the page that they left them stand). These creators were figments of our imagination. No one is home inside the AI. The intentionality we imputed to these works was the actual “AI hallucination”:

https://pluralistic.net/2026/09/21/sunsetting/#oh-mr-sun-sun-mr-golden-sun-please-shine-down-on-me

Just as important as the emergence of these hallucinations is their disappearance. For many of us, chatbots that used to pass the Turing Test now flunk it. The chatbots haven’t gotten worse at impersonating humans, we’ve just gotten better at spotting the difference between a human and a bot, just as we got better at hearing the difference between a phonograph and a pianist.

Writing without a writer and paintings without a painter are new phenomena, and learning to separate the formerly inseparable is the first step in our societal metabolization of these novelties. Recordings of musical performance have a place in our world, and so do performers.

This separation process is currently underway in many disciplines, thanks to the extraordinary capital available to AI companies. These companies are incinerating that capital in a series of extremely flash demos that are intended to ensure that the supply of bales of $100 bills that they feed to their money furnaces (“data centers”) never stops.

Lately, AI companies have made headlines with a series of mathematical accomplishments that left mathematicians in an uproar and non-mathematicians in a muddle. Obviously, while mathematicians are qualified to assess these accomplishments, the rest of us are not. Beyond simple arithmetic, most of us don’t do a lot of math on a regular basis, and even those of us who have to deploy a little geometry or stats typically don’t engage with math at a theoretical level.

To make things worse, math — like physics — is a crank-magnet. These highly abstract, closed systems rely on introspection to advance the field, and some of those advances have been contributed by untrained laity, so it can be hard to know if your amazing idea about physics or mathematics represents an outsider’s breakthrough or an amateurish cul-de-sac.

Every mathematician and physicist I know receives a steady stream of breathless, over-the-transom “proofs” that solve some long-standing problem in the field, and none of these experts in my orbit has ever found a breakthrough in this material. It’s a rare expert who will even respond to these unsolicited manuscripts. That’s not their job. As Teresa Nielsen Hayden says, “You are not responsible for the things you do in other people’s dreams.”

Unfortunately, this is a situation that is perfectly suited to AI. If you’ve introspected your way into a mathematical “breakthrough” that no mathematician will discuss with you, you can avail yourself of any number of chatbots who will assure you that you’ve broken exciting new theoretical ground, and these chatbots will even act as “research collaborators,” contributing more slop-physics or slop-math to your conclusions.

Again, as far as I know, no one has actually made a breakthrough this way, and the major impact on the field from giving chatbots to excitable outsiders has been to make the unsolicited manuscripts much longer, with the veneer of professionalism that means an expert might have to give them a second or even third glance to realize that they’re nonsense.

But some working mathematicians have found chatbots to be extremely useful “collaborators.” The most prominent of these is Terrence Tao, a Macarthur-winning mathematician who has excited many mathematicians and lay-people alike by publishing his chat-logs and the resulting mathematical work:

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

One way to understand Tao is as a “centaur,” the automation theory term for a worker who is assisted by a machine. For all that Tao describes Chatgpt as his collaborator, it’s clear from reading the chat-logs that it’s Tao who drives the research agenda. He sets the questions and the direction of the answers. Chatgpt doesn’t give him orders — it’s the other way around.

But for every problem Tao and Chatgpt solve together there are several mathematical problems that are being solved by chatbots without that kind of human collaboration. In particular, Openai has released a tsunami of “solutions” to longstanding mathematical problems, including some that carry large cash bounties and others that were posed by legends of the field, like Erdos.

This is mathematics without a mathematician, and — as with all the other separations cleft by the AI companies — it’s proving difficult to metabolize. Back in September, Fenner Stanley Tanswell published an opinion piece for the Mathematical Intelligencer entitled “The Enshittification of Mathematics” that tried to do just that:

https://rdcu.be/5uYGc2uo454a

Tanswell distinguishes between mathematics as a discipline practiced by mathematicians and the proofs and theorems that those mathematicians produce. He makes the point that when a mathematician finds the answer to some longstanding mathematical puzzle, they do so by creating “scaffolding” that bridges the new insight with the existing commons of mathematical understanding. The thing that makes a “solution” so exciting isn’t that a problem has been solved — it’s that the method for solving that problem prompts a cascading reconsideration of many other areas of mathematics, prompting shifts to large areas of the discipline.

This point is made even more forcefully by Giordano Scarciotti, a complex systems researcher at Imperial College London and science communicator who vlogs under the Youtube handle “Prof Gio.” Scarciotti’s most successful video to date is “You Truly Don’t Understand What Just Happened to Mathematics,” published last month:

https://www.youtube.com/watch?v=KqiDqJMxg6o

“You Truly Don’t Understand…” makes a similar point to Tanswell’s, using a thought experiment in which we wake up one day and discover an American flag on the surface of Mars. Without knowing how that flag got to Mars, the mere fact of its existence doesn’t help us get any closer to an actual Mars mission.

The output of mathematical models is a series of faits accomplis, often accomplished through brute-force, or sometimes through opaque methods that lack the “scaffolding” that bridges these outcomes into the broader field of mathematics. Scarciotti cites Euler’s work on the longstanding “Seven Bridges of Königsberg” problem, which asked whether it was possible to go on a walking tour of Königsberg such that you crossed each of the city’s seven bridges only once:

https://en.wikipedia.org/wiki/Seven_Bridges_of_K%C3%B6nigsberg

The point of that problem (and Euler’s solution to it) wasn’t to produce a set of Mapquest directions for a walking tour of Königsberg. In solving the Seven Bridges problem, Euler invented graph theory, an important area of mathematics that is routinely used today for many important applications, including computer networking. You can thank graph theory for helping to route the packets that brought these very words to you.

So far, we’ve figured out how to get a model to either rule out the possibility of taking that each-bridge-only-once walk or to give us the route map. What this computer-generated “mathematics” is not doing is advancing the field.

Tanswell points out that a world in which chatbots “solve” these problems is one where the role of mathematicians is reduced to being reverse centaurs, assistants to the machine whose job is to clean up after the chatbot’s research agenda. But there’s nothing about knowing that there’s no route map for a seven-bridge walking tour that makes it easier to invent graph theory, and a mathematician might spend years working on the computer’s “answer” to that problem only to conclude that the computer’s solution didn’t add any theoretical insight to the field.

In other words, in a world where mathematicians and mathematics are inseparable, every solution to a longstanding problem heralds an accompanying theoretical insight. Once we separate mathematics from mathematicians, we start to get solutions without insights. These are a lot less interesting than the kinds of solutions that mathematicians come up with.

This is a distinction the AI companies really don’t want us to dwell on. We’re meant to marvel at these very expensively derived solutions and conclude that the AI companies can be forgiven for spending $1T this year, even if they only grossed $50B in return.

But (as Scarciotti notes), there are real-world consequences in our failure to grasp this distinction: if we convince early-career mathematicians and promising mathematics students that the world no longer needs mathematicians because “the AI can do their jobs,” then we will choke off the supply of future mathematicians who we’ll either need to work in a Terrence Tao-like, centaurish relationship with chatbots (good), or even to serve as reverse centaurs, marking the chatbots’ homework to see if there are any theoretical insights to be found in it (bad).

This is one of the underappreciated consequences of AI mania. AI bosses are particularly interested in convincing us that AI can do the job of skilled professionals in fields where there is a chronic undersupply of experts, like radiology. A chatbot that helps a (centaur) radiologist by suggesting that they double-check some of their results might indeed save lives. But a chatbot that produces thousands of radiology reports for a single (reverse centaur) radiologist to approve at a velocity that precludes careful scrutiny is going to kill people.

Centaur radiology requires more radiologists, not fewer. A centaur radiologist processes fewer X-rays (because sometimes the chatbot tells them to double-check a diagnosis) than an unassisted radiologist. LLM-assisted radiology improves quality, not quantity.

That’s not what AI companies are selling. An AI company can’t turn a profit by raising the cost of radiology (even if that improves the quality of radiological analyses). So the firehouse of announcements from AI companies are always about putting radiologists out on the breadline — not about needing more radiologists, who will get a new radiology tool that helps them work better, if a little more slowly.

The pronouncements of AI companies aren’t just marketing hype, they’re attempts at self-fulfilling prophecy. If you convince all the would-be radiologists that the profession is about to be vaporized by chatbots, those people will not study radiology, and then we will need to retask the dwindling supply of human radiologists to marking the chatbots’ homework and hoping that they don’t kill too many people by missing the chatbots’ mistakes.

That’s the catastrophic outcome that both Scarciotti and Tanswell warn us of: if we convince people that we’re heading into a world of mathematics without mathematicians, that’s exactly what we’ll get, because no one will try to become a mathematician. But because mathematics without mathematicians is a set of guide maps for crossing Königsberg’s bridges (but not graph theory), then mathematics without mathematicians is also mathematics without mathematics.

#20yrsago Microsoft threatens China pull-out over jailed bloggers http://news.bbc.co.uk/1/hi/technology/6102180.stm

#15yrsago Righthaven copyright troll’s victims send in US marshals to seize its assets https://arstechnica.com/tech-policy/2011/11/us-marshals-turned-loose-to-collect-6372080-from-righthaven/

#15yrsago Supercuts: rapid-cut videos that collect repetition https://web.archive.org/web/20111103190737/http://www.wired.com/epicenter/2011/11/supercut/

#10yrsago Nebraska’s billionaire governor couldn’t preserve the death penalty through the law, so now he’s buying a ballot initiative https://www.motherjones.com/politics/2016/11/ricketts-nebraska-death-penalty/

#10yrsago Anti-vaxx conspiracy leaders back Donald Trump, claim it’s mutual https://scienceblogs.com/insolence/2016/11/02/donald-trump-and-disgraced-antivaccine-scientist-andrew-wakefield-best-buds-forever

#10yrsago New, fast-spreading IoT botnet hybridizes two less-effective strains to achieve quick dominance https://arstechnica.com/information-technology/2016/11/new-iot-botnet-that-borrows-from-notorious-mirai-infects-3500-devices/

If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2026/11/02/agony-verification/#great-turnbulls-ghost

After 25 years of fighting for human rights amid the wreckage of bad tech policy, I’m here to tell you that the road to hell is paved with badly thought-through tech policy.

The most galling thing about this wreckage is that it was both foreseeable and foreseen. Back when Sun Microsystems CEO Scott McNealy was telling the world “Privacy is dead, get over it,” digital rights advocates were saying, “Not only are digital tools pretty dang good at helping you protect your privacy, but a society-wide abolition of privacy sets us up for infinite harms long into the future”:

https://pluralistic.net/2025/10/31/losing-the-crypto-wars/#surveillance-monopolism

It wasn’t just business leaders who hated privacy, it was also our political classes. Bill Clinton tried to put a backdoor into every microchip (no, really):

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

The NSA managed to enact a total prohibition on civilian access to working encryption, on the grounds that we’re all safer if our spooks can spy on “bad guys” even if that means that every creep, petty crook, corporate or state-sponsored spy, and mafia can spy on us:

https://pluralistic.net/2026/04/09/bernstein-2/#win-some-lose-some

Even after that ban was overturned, governments encouraged the private sector to spy on us without limit, precaution or permission. Those private-sector troves of intimate, compromising data about every person alive constitute a warrantless, off-the-books surveillance system that cops, spies and government agencies can tap at will:

https://pluralistic.net/2026/10/13/petards-r-us/#nobus

To protect these surveillance capabilities, private firms and governments colluded to pass “anticircumvention” laws that make it illegal to reverse engineer our devices and apps to add privacy blockers to them, with the effect that every device we own and every app we use spies on us constantly:

https://pluralistic.net/2024/03/12/market-failure/#car-wars

At the same time, states either failed to pass new privacy laws (as in the USA, where federal consumer privacy law was last updated in 1988), or passed privacy laws that went unenforced (as in the EU, where “pretending to be Irish” allows US tech giants to flout EU privacy law):

https://pluralistic.net/2023/05/15/finnegans-snooze/#dirty-old-town

Our surveillance free-for-all world is objectively very bad. Over and over, companies and agencies who have been permitted to nonconsensually harvest and retain our data demonstrate that they are not capable of keeping that data safe, and no matter how badly they fuck up, nothing changes. It’s been nearly a decade since Equifax doxed 148 million Americans and not only is the company still in business, they’ve been permitted to buy up and absorb more commercial surveillance firms.

US regulators let Equifax buy Teletrack in 2021. Canadian regulators let them buy the Food Industry Credit Bureau in 2023. The same year, Brazilian regulators let Equifax buy Boa Vista Serviços. This all despite the fact that Equifax blamed its breach on shitty security practices after a string of mergers that led to it haphazardly combining databases from newly acquired surveillance companies.

Data isn’t the new oil. Data is the new oily rag: profitable only if you can warehouse it in vast quantities under unsafe conditions and have society pick up the bill for every conflagration:

https://locusmag.com/feature/cory-doctorow-zucks-empire-of-oily-rags/

Equifax is a serial reoffender, but rather than getting the corporate death-penalty, they’ve been made to pay coins-down-the-back-of-the-sofa fines that amount to a fraction of a fraction of a fraction of the costs they imposed on society by amassing these vast, flaming storehouses of oily rags.

Why wouldn’t Equifax reoffend? Our policymakers keep demanding less privacy, not more, and their indifference to the consequences is (almost) comical.

Take Malcolm Turnbull, the former Australian Prime Minister who uttered what remains, without a doubt, the single stupidest thing anyone anywhere has ever said about tech policy. Like many of his peers before, during, and since his reign, Turnbull had been trying to outlaw working encryption, insisting that every device have a Bill Clinton-esque back-door for the purpose of spying on “bad guys.” When told that the laws of mathematics dictated that any measure that let Australia’s cops spy on “bad guys” would also let bad guys spy on Australians, Turnbull replied, “The laws of mathematics are very commendable, but the only law that applies in Australia is the law of Australia”:

https://www.newscientist.com/article/2140747-laws-of-mathematics-dont-apply-here-says-australian-pm/

We could laugh Turnbull off…if he was an outlier. But while Turnbull had the world’s stupidest rejoinder to the scientifically irrefutable fact that banning encryption will let bad guys hack everything, he was hardly alone in wanting to ban encryption. Banning encryption is current policy in Canada:

https://blog.mozilla.org/netpolicy/2026/10/08/canadas-bill-c-22-threatens-encryption-users-privacy-and-the-security-of-digital-economies/

It’s also current policy in the UK:

https://pluralistic.net/2023/03/05/theyre-still-trying-to-ban-cryptography/

And in the EU:

https://fightchatcontrol.eu/

The difference between Malcolm Turnbull and, say, Canadian PM Mark Carney is that Turnbull was stupid enough to try to defend his ban on encryption, while Carney simply shakes his head at his critics’ naivete and continues to press forward with his catastrophic proposal to welcome every cybercriminal in the world to hack every morsel of Canadian data.

When it comes to bad privacy policy, our political classes aren’t content to rest on their laurels: hardly a week goes by without news of a new way to encourage (or even require) the private sector to recklessly collect and retain our data, despite the dead certainty that this data will eventually end up breaching and getting plastered all over the internet.

Take “age verification” laws. There’s no such thing as “age verification” — there’s just spying on everyone, all the time, creating (even more) records of all of our internet activities:

https://pluralistic.net/2026/05/19/shes-dead-of-course/#consensus-hallucination

Every promise of “privacy preserving” age verification is bullshit:

https://pluralistic.net/2025/08/14/bellovin/#wont-someone-think-of-the-cryptographers

If you think kids are experiencing internet harms today, just wait until we expose them to the harms of having even more of their data harvested, stored, breached, and weaponized against them:

https://pluralistic.net/2026/06/23/destroy-the-village/#to-save-it

If you want to protect kids from algorithmic manipulation and targeting by bad actors, what about banning spying on kids so no one can target them?

https://made-not-found-by-danah-boyd.ghost.io/no-one-paid-me-to-disagree-with-jonathan-haidt-it-was-teenagers-who-taught-me-that-he-was-wrong/

Now, at this point, you might be thinking, “How can we know who the kids are so we know who not to spy on?” You can’t. In order to not spy on kids, you’d just have to not spy on anyone:

https://pluralistic.net/2023/04/09/how-to-make-a-child-safe-tiktok/

“Don’t spy on anyone” is the kind of thing that has a reasonable chance of enhancing online privacy. But in the time-honored tradition of “we’ve tried nothing and we’re all out of ideas,” governments keep finding ways to make digital privacy worse, for example, by procuring Flock cameras for every lamp-post:

https://www.eff.org/deeplinks/2026/09/high-crime-lmao-how-cops-are-treating-mass-surveillance-joke

And then there’s UK Labour: after the success of a pilot program for an incredibly effective and safe privacy-preserving way of analyzing the country’s health records for research processes, they commissioned the Goldacre Report to evaluate the possibility of making this permanent:

https://pluralistic.net/2024/03/08/the-fire-of-orodruin/#are-we-the-baddies

After that report was completed and had a chance to be metabolized by policymakers, Labour acted upon it…by throwing it out and handing all of the country’s health data to Palantir, a serial mishandler of data and violator of privacy:

https://www.theguardian.com/technology/2026/sep/30/legal-objections-palantir-nhs-platform-handling-data

Here’s the scariest thing about bad privacy policy: it has a long fuse. The harms of commercial and private-sector digital surveillance can occur years or even decades after the decision to permit it.

There’s a straight line from the post-9/11 decision to encourage public agencies to gather, merge and warehouse data on every person in America, and the ability of ICE ethnic cleansing squads to break down people’s doors and drag them off to concentration camps; just as there’s a straight line from the decision to do nothing about the breach of every Social Security Number and the later theft of all Social Security data by adolescent DOGE criminals:

https://www.pcmag.com/news/is-your-ssn-in-the-national-public-data-breach-heres-how-to-find-out

But despite how obvious these connections are, the fact that they’re separated by a lot of time and space provides our policymakers with cover for making terrible decisions with foreseeably terrible outcomes. As a society, we lack object permanence, the ability to connect acts in the past with present-day phenomena.

When the press reports on a “Black October” of catastrophic, AI-fueled data breaches and hack attacks, they don’t mention a generation of policymakers’ indifference and hostility to information security:

https://pluralistic.net/2026/09/12/god-in-the-box/#llms-are-fake

Policymakers benefit from politics’ eternal now, in which disasters simply befall us, without any history or precedent or cause. Remember the One Big Beautiful Bill? Its architects designed it to wreak its worst harms after the midterms, with Medicaid work rules and food aid restrictions starting in December, and cuts to affordable housing and rural hospitals phasing in through the year:

https://www.tumblr.com/mostlysignssomeportents/832146932089700352

Black October is going to give way to Black November, Black December, Black 2027, and the Black 2030s — a string of cybersecurity catastrophes that will befall us until policymakers decide that keeping us safe is more important than making it easy for them to attack their chosen “bad guys.”

Here’s a preview of Black November: there’s a new strain of the Volta infostealer malware that uses AI tools to dox you even as it hacks you:

https://www.wired.com/story/kernel-panic-volta-autodoxer-ai-infostealer-malware/

How that works: your computer gets hacked and your data gets stolen, then it gets merged with breach data from Ticketmaster, Disney, AT&T and other companies that have recklessly compiled vast troves of data on all of us, stored it insecurely, and leaked it onto the internet where it will live forever.

Volta’s makers prompt their LLM “to act like an intelligence analyst and produce structured citation-backed assessment of the victim.” This lets the criminals prioritize their victims based on the expected return from exploiting them. It augments this dossier by combing through your Gmail as well as your Doordash and Uber Eats profiles. This merged data makes it much easier for criminals to call you up or email you (or have a chatbot call you up or email you) and trick you into giving up even more data:

https://pluralistic.net/2024/02/05/cyber-dunning-kruger/#swiss-cheese-security

Volta seems especially interested in younger internet users, targeting “Discord, Telegram, Steam, and Roblox sessions.” Of course, once our “age verification” services breach vast, eternally persistent, detailed troves of data on young internet users, this kind of AI-supercharged malware will be able to target kids with much greater fidelity and efficacy.

AI capabilities have made infostealers much worse, but the reason for that new potency lies in how AI capabilities are supercharged by breach data that is the foreseeable and foreseen consequence of generations of hostility to privacy on the part of policymakers and corporations who responded to the incentives policymakers created.

We are living in the age of oily rags. For decades we fucked around with letting the private sector warehouse our data and weaken our security so that public sector agencies could plunder our data and our computers at will. Now, we keep finding out that everything is on fire.

It’s going to take a long time to fix this, but we can do it. We can build more secure systems. We can make it much more of a legal ball-ache for companies to gather our data in the first place, and we can legalize and promote the creation of privacy blockers for browsers, phones, computers, cars, thermostats and smart speakers. We can enact corporate death-penalties for breaches to reflect the true societal cost of warehousing our data. We can ban Flock cameras and tear down the post-9/11 “fusion centers” that neatly package up our data for use by DOGE fascists and ICE thugs. We can ban our spy agencies from hoarding defects in widely used software, and instead require them to divulge these bugs so vendors can fix them:

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

And before we do any of that, we can just stop making it worse by ending the campaigns to require companies to spy on us and deliberately introduce security defects into their products.

#25yrsago NY Post blames pagans from Indianapolis for spam malware https://web.archive.org/web/20011103073038/http://www.nypost.com/news/regionalnews/33077.htm

#25yrsago The Shakespeare Programming Language https://web.archive.org/web/20011207071324/http://shakespearelang.sourceforge.net/report/shakespeare/

#25yrsago Appeals court: DeCSS is “pure speech” https://web.archive.org/web/20011102003502/https://www.wired.com/news/business/0,1367,48075,00.html

#20yrsago Apple drops Trusted Computing https://web.archive.org/web/20070106150844/https://www.osxbook.com/book/bonus/chapter10/tpm/

#15yrsago Study: why parents help their underage kids pretend to be 13 in order to use Internet sites https://firstmonday.org/ojs/index.php/fm/article/view/3850/3075

#15yrsago Blue Coat “deep packet inspection” tools used by Syrian secret police and other repressive regimes https://www.eff.org/deeplinks/2011/10/blue-coat-acknowledges-syrian-government-use-its-products

#15yrsago Extraordinary Catalog of Peculiar Inventions: awesomely dangerous pranks from the age of fraternal lodges https://memex.craphound.com/2011/11/01/extraordinary-catalog-of-peculiar-inventions-awesomely-dangerous-pranks-from-the-age-of-fraternal-lodges/

#10yrsago Cable prices have risen at more than double the rate of inflation for 20 years https://cordcutting.com/news/cable-prices-have-risen-faster-than-inflation-for-each-of-the-past-20-years/

#10yrsago Typical English village mystified by its cult status among Chinese tourists https://www.bbc.com/news/uk-england-oxfordshire-37820663

#1yrago There’s one thing EVERY government can do to shrink Big Tech https://pluralistic.net/2025/11/01/redistribution-vs-predistribution/#elbows-up-eurostack

#25yrsago Image analogies https://mrl.cs.nyu.edu/projects/image-analogies/

#25yrsago Cleaning the Fucking Kitchen for Dummies https://web.archive.org/web/20011007082222/https://www.fridgemagnet.org.uk/kitchen.html

#20yrsago Last minute changes snuck into Aussie DMCA https://web.archive.org/web/20061104133320/https://www.eff.org/deeplinks/archives/004975.php

#20yrsago Creative Commons 3.0 license drafts published https://creativecommons.org/2006/10/30/version30revisedlicensedrafts/

#15yrsago Dean of St Paul’s resigns over plan to evict OccupyLondon https://www.theguardian.com/uk/2011/oct/31/dean-st-pauls-resigns-occupy

#15yrsago The future of the living room: Authorised Domain https://dn711102.ca.archive.org/0/items/Cory_Doctorow_Podcast_215/Cory_Doctorow_Podcast_215_Authorised_Domain.mp3

#15yrsago Sales tax is still regressive, gravity still sucks, and George Osborne is still a delusional ideologue https://www.bbc.com/news/business-15519727

#15yrsago Prince Charles exercises a secret veto over a wide swath of UK legislation https://www.theguardian.com/uk/2011/oct/30/prince-charles-offered-veto-legislation

#15yrsago London cops recording movements & association with mobile tracking device: “blanket & indiscriminate” https://www.theguardian.com/uk/2011/oct/30/metropolitan-police-mobile-phone-surveillance

#10yrsago The Shadow Brokers dump more intel from the NSA’s elite Equation Group https://medium.com/@shadowbrokerss/message-5-trick-or-treat-e43f946f93e6#.x2c36nsfq

#10yrsago Wells Fargo blackballed employees who refused to commit fraud, forcing them out of the industry forever https://www.npr.org/sections/money/2016/10/28/499805238/episode-732-bad-form-wells-fargo

#10yrsago Listen: free recordings of Edgar Allen Poe stories, read by Vincent Price and Basil Rathbone https://open.spotify.com/album/6xDmRcD6sgsGbDvBRpyH5H?play=true&utm_source=open.spotify.com&utm_medium=open

#5yrsago Now, Put It Back! https://pluralistic.net/2021/10/31/now-put-it-back/

#1yrago The internet was made for privacy https://pluralistic.net/2025/10/31/losing-the-crypto-wars/#surveillance-monopolism

If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2026/10/31/burn-berne/#unvictored

It’s not often that I find myself on the same side as the US Copyright Office. In fact, I think this is the first time in 25 years that I’ve found myself cheering on the office’s official actions as good for art and good for free expression, taking the side of creative workers over our bosses.

The source of our miraculous accord: the US Copyright Office’s position on AI. The CO has taken the (entirely correct) position that copyright law exists to incentivize human acts of creative expression, which means that only works of human authorship are eligible for copyright.

This isn’t a controversial position within legal circles. But for media executives, this is shocking; absurd, even. This gap between the industrial and the legal understanding of copyright comes from a fundamental difference over the evocatively named legal doctrine of “sweat of the brow.”

“Sweat of the brow” is fundamental to a correct legal understanding of copyright. Copyright rewards and protects creativity but it does not protect hard work. You can labor for ten years over a phone book listing the numbers of every person in a town and (as a collection of uncopyrightable facts) it will receive no protection at all. Zero. Zilch. Anyone can copy and sell that phone book:

https://en.wikipedia.org/wiki/Feist_Publications,_Inc._v._Rural_Telephone_Service_Co.

Copyright law doesn’t care if you slaved over that collection of facts, if you missed sleep and your kids’ little league games to realize your grand vision. Copyright law doesn’t care if you plowed every cent into it, remortgaging your home and cashing in your (already resentful) kids’ college funds.

But: if you dash off a haiku in ten seconds while sitting on the toilet, shove it into your pocket and forget about it, and then your (still resentful) kids discover that crumpled haiku after your (highly suspicious) death, your kids will be able to claim a full 70 years’ worth of copyright over that forgotten triviality (the term of copyright for works of human authorship is life plus 70 years).

This is the uncontroversial and universally accepted legal understanding of copyright: all the copyright in the world for creative acts, no copyright at all for mere acts of labor. The “sweat of the brow” has nothing to do with a work’s eligibility for copyright.

But no media boss believes this. For media bosses, copyright is a pseudo-property† right, designed and operated to protect their bottom line. The point of copyright isn’t to incentivize creativity, but rather investment.

† Or not-so-pseudo

There’s obviously a relationship between creative acts and acts of investment, but it’s possible to create without investment (see: your haiku) and it’s possible to invest without creativity (see: your phone book).

And once again, the creativity that copyright protects is human creativity. This is a lesson that David Slater learned the hard way. Slater is a professional wildlife photographer and amateur monkey-trainer who combined his interests by teaching Celebes crested macaque monkeys to take selfies. But when Slater published a monkey’s selfie others copied and distributed the image without his permission, on the (entirely legally correct) basis that monkeys are not humans, and that means that works created by monkeys don’t get a copyright. This was also the Copyright Office’s position, and the position of the Ninth Circuit Court of Appeals:

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

This is the basis for the US Copyright Office’s repeated decision to refuse to extend copyright to AI-generated works. An algorithm is even less human than a monkey, so if you can’t get copyright over a monkey selfie, you definitely can’t copyright your chatbot’s slop. The US Copyright Office has successfully defended this position in multiple courts, triumphing over plaintiffs who were so persistent that they even got the Supreme Court to weigh in on the issue (the Supremes decided the case didn’t warrant their attention):

https://pluralistic.net/2026/03/03/its-a-trap-2/#inheres-at-the-moment-of-fixation

AI slop isn’t copyrightable, but there can be copyrightable elements in an AI-generated image. The most obvious element is the prompt. So long as your prompt contains some quantum of creativity (e.g. “Make me a beautiful flower whose loveliness is reminiscent of a newborn baby”, but not “make me a beautiful flower”), that prompt is copyrightable. That means you can use copyright to challenge others’ rights to present the same prompt to a chatbot. But while the prompt can be copyrighted, the image it gives rise to isn’t. So you can spend a month iteratively refining your prompt, consuming all your town’s water along with 200,000 gallons of diesel and that prompt will be yours for your life plus 70 years, but the image it generates is in the public domain, and anyone can copy it, sell it or give it away.

There are other ways that copyright can find its way into AI-generated material. You can make creative edits to it: if you output a slop novel and rewrite various sentences (providing those rewrites involve some creativity and not just mechanical corrections or word substitutions), then the edited sentences become copyrighted works, even though all the rest of the text remains uncopyrightable.

You can also get a “thin” copyright through selection. If you get your chatbot to output many images based on your prompt and choose your favorite, your selection can confer a tiny bit of copyright over that creative act of selection, but it will be harder to defend than even the other (attenuated and highly specific) forms of copyright.

Now, perhaps you’ve spotted an administrative problem lurking in this turn of events. How can someone else know what part of a work is AI-generated (and thus in the public domain) and which parts are human-edited/contributed (and thus copyrighted)? Just as importantly, how can you prove which parts of your work are not AI-generated and thus eligible for copyright protection.

This gets especially gnarly when you’re dealing with complex media. In an animation, an AI might do the rigging and movement for a human-created sprite. The sprite is copyrightable, but its movements aren’t. That would mean that I could remap your sprite’s movements onto a different sprite without infringing your copyright. Or say the sprite and its movements are human created (and thus copyrighted), but the backgrounds are procedurally generated? I could take those backgrounds and put new animations overtop of them.

The simplest, most reliable way to ensure the works you invest in are fully and entirely eligible for copyright is to just use humans for the whole project. Declare a “no-AI policy,” and hire human artists to produce the works you hope to sell. Monitor their activity to ensure they’re not using AI. Keep good records.

Now, as much as I like the idea that we’ve arrived at a copyright law that insists that a company can only get exclusive rights to its products by paying human artists to make them from end-to-end, I don’t think that’s likely to be the way it shakes out, but that doesn’t mean that this is a wash for artists.

The reality is that copyright claims are always “fact-intensive inquiries” that are expensive to litigate and difficult to adjudicate. It’s completely normal for copyright lawsuits to turn on documentary evidence gleaned from fragmentary records. This is simply intrinsic to copyright, because copyright is a doctrine that requires judges to assess whether things are “creative” and “original” as though these were freestanding categories that everyone could agree upon.

Of course, the rules of copyright can make this harder or easier. One way in which the rules make deciding copyright cases much, much harder is copyright’s broad prohibition on “formalities” (“formalities” is how copyright wonks refer to “red tape” or “paperwork”). For nearly all of American history, copyright ran on a key formality: deposit, registration and notice.

To secure a copyright for a new work, an artist (or their employer) had to send a copy of that work to the Library of Congress (deposit), along with paperwork detailing the claim of authorship (who made this, what parts of it did they make) (registration) and they had to display a copyright notice that told you who held the copyright to every work that was registered (notice). Both the filing and the notice required careful attention and precision, and screwing either one up could result in your losing your copyright. It’s an open secret among copyright scholars that Walt Disney screwed this up with the first Mickey cartoons, meaning they’ve been in the public domain since their release:

https://web.archive.org/web/20080725055415/http:/homepages.law.asu.edu/~dkarjala/opposingcopyrightextension/publicdomain/HedenkampFreeMickeyMouseVaSp&E(2003).htm

This system of copyright formalities meant that you could always tell whether a work was copyrighted, you could always find out who claimed the copyright over it, and which parts of the work were claimed under copyright and under what basis. What’s more, formalities created the Library of Congress, since the LoC acted as America’s “copyright deposit” library, holding deposit copies of every work that had ever been issued a US copyright.

The US system of formalities was descended from the English system, in which the Stationers’ Guild used a copyright registry to establish who had the rights to which books. But there were competing copyright systems, notably the “continental” system that was codified through the Berne Convention, a copyright treaty drafted by Victor Hugo (yes, that Victor Hugo).

Among other things, the Berne Convention abolished formalities. Much of the world adopted Berne, but the US held out until 1976. With the 1976 Copyright Act, Congress brought the US into compliance with Berne, abolishing formalities in the USA. As a compromise, the 1976 Act requires US authors to register their copyrights in order to obtain “statutory damages” (up to $150,000 per work). That’s a pretty good incentive, but even with that incentive, the vast majority — far in excess of 99.999999999999999999999999999999999999999% — of all copyrighted works are not registered with the Copyright Office. They are born copyrighted from the moment they are “fixed in a tangible medium” until 70 years after their authors die. But without registration, you can’t know when that copyright clock started ticking because you have no way to verify who the author of the work is. This not only makes it incredibly difficult to establish the copyright status of nearly every copyrighted work, but it also means that in nearly every case, you can’t readily determine who you should approach if you want to pay them for a copyright license.

Abolishing formalities has created a universe of orphan works: everything from napkin doodles to kindergartners’ finger paintings to message board posts. Within that universe is a kind of gaseous cloud that, if condensed, would come out to an infinitesimal planetoid, representing the entirety of commercial works whose authors give a damn about their copyright status. It’s a bad, bad system.

This system doesn’t do away with the need to keep careful records: like I said, copyright disputes usually require the close examination of documentary evidence. What formality abolition accomplished was the destruction of the regular system of record-keeping: rather than having a standard, universally agreed-upon way to determine the status and resolve disputes about a copyrighted work, now we have the scattershot, incoherent system that makes copyright disputes far more likely (because no one knows who to approach for copyright licenses) and far more difficult to resolve (because there’s no registry of copyrighted works).

Which brings me back to the question of AI and copyright. If a firm uses some AI in its work, it’s going to need to document that very carefully. Firms that don’t keep very close track of the elements of their products that come from AI will have a far harder time defending their commercial interests.

Basically, we’re about to recreate formalities, but managed by the private sector. To the extent that companies use AI in their work, they are going to have to track every pixel and every word and every note that is output by an AI system, and which parts were added or edited by humans after creation.

That means that companies that want to protect their commercial interests aren’t just going to get more protection based on how much work they get humans to do; they’re also going to have to treat copyright’s government-enforceable monopoly over expressive speech with the gravitas it deserves: not something you get automatically, but something you have to do real administrative work for.

#15yrsago Fresh German police-malware uncovered; everything the police said in defense to date revealed as lies https://www.ccc.de/en/updates/2011/analysiert-aktueller-staatstrojaner

#15yrsago Russia dumps daylight savings https://www.bbc.com/news/world-europe-15512177

#15yrsago Class War funnies: 1935 Daily Worker comics https://philnel.com/2011/02/02/hoff_teeth/

#15yrsago Christian groups: we will bodily protect Occupy London from St Paul’s https://www.theguardian.com/uk/2011/oct/29/christians-defend-occupy-london-protest

#10yrsago How Minnesota’s governor performed an economic miracle by raising tax on the rich and increasing minimum wage https://www.huffpost.com/entry/mark-dayton-minnesota-economy_b_6737786

#10yrsago Icelandic women walk off the job 14% early to protest 14% pay-gap https://www.teenvogue.com/story/women-iceland-protest-gender-wage-gap