Google is (still) losing the spam wars to zombie news-brands
I'm touring my new, nationally bestselling novel The Bezzle! Catch me TONIGHT (May 3) in CALGARY, then TOMORROW (May 4) in VANCOUVER, then onto Tartu, Estonia, and beyond!
Even Google admits – grudgingly – that it is losing the spam wars. The explosive proliferation of botshit has supercharged the sleazy "search engine optimization" business, such that results to common queries are 50% Google ads to spam sites, and 50% links to spam sites that tricked Google into a high rank (without paying for an ad):
It's nice that Google has finally stopped gaslighting the rest of us with claims that its search was still the same bedrock utility that so many of us relied upon as a key piece of internet infrastructure. This not only feels wildly wrong, it is empirically, provably false:
Not only that, but we know why Google search sucks. Memos released as part of the DOJ's antitrust case against Google reveal that the company deliberately chose to worsen search quality to increase the number of queries you'd have to make (and the number of ads you'd have to see) to find a decent result:
Google's antitrust case turns on the idea that the company bought its way to dominance, spending the some of the billions it extracted from advertisers and publishers to buy the default position on every platform, so that no one ever tried another search engine, which meant that no one would invest in another search engine, either.
Google's tacit defense is that its monopoly billions only incidentally fund these kind of anticompetitive deals. Mostly, Google says, it uses its billions to build the greatest search engine, ad platform, mobile OS, etc that the public could dream of. Only a company as big as Google (says Google) can afford to fund the R&D and security to keep its platform useful for the rest of us.
That's the "monopolistic bargain" – let the monopolist become a dictator, and they will be a benevolent dictator. Shriven of "wasteful competition," the monopolist can split their profits with the public by funding public goods and the public interest.
Google has clearly reneged on that bargain. A company experiencing the dramatic security failures and declining quality should be pouring everything it has to righting the ship. Instead, Google repeatedly blew tens of billions of dollars on stock buybacks while doing mass layoffs:
(Google's antitrust trial was shrouded in secrecy, thanks to the judge's deference to the company's insistence on confidentiality. The case is moving along though, and warrants your continued attention:)
Back in February, Housefresh – a rigorous review site for home air purifiers – published a viral, damning account of how Google had allowed itself to be overrun by spammers who purport to provide reviews of air purifiers, but who do little to no testing and often employ AI chatbots to write automated garbage:
https://housefresh.com/david-vs-digital-goliaths/
In the months since, Housefresh's Gisele Navarro has continued to fight for the survival of her high-quality air purifier review site, and has received many tips from insiders at the spam-farms and Google, all of which she recounts in a followup essay:
One of the worst offenders in spam wars is Dotdash Meredith, a content-farm that "publishes" multiple websites that recycle parts of each others' content in order to climb to the top search slots for lucrative product review spots, which can be monetized via affiliate links.
A Dotdash Meredith insider told Navarro that the company uses a tactic called "keyword swarming" to push high-quality independent sites off the top of Google and replace them with its own garbage reviews. When Dotdash Meredith finds an independent site that occupies the top results for a lucrative Google result, they "swarm a smaller site’s foothold on one or two articles by essentially publishing 10 articles [on the topic] and beefing up [Dotdash Meredith sites’] authority."
Dotdash Meredith has keyword swarmed a large number of topics. from air purifiers to slow cookers to posture correctors for back-pain:
The company isn't shy about this. Its own shareholder communications boast about it. What's more, it has competition.
Take Forbes, an actual news-site, which has a whole shadow-empire of web-pages reviewing products for puppies, dogs, kittens and cats, all of which link to high affiliate-fee-generating pet insurance products. These reviews are not good, but they are treasured by Google's algorithm, which views them as a part of Forbes's legitimate news-publishing operation and lets them draft on Forbes's authority.
This side-hustle for Forbes comes at a cost for the rest of us, though. The reviewers who actually put in the hard work to figure out which pet products are worth your money (and which ones are bad, defective or dangerous) are crowded off the front page of Google and eventually disappear, leaving behind nothing but semi-automated SEO garbage from Forbes:
There's a name for this: "site reputation abuse." That's when a site perverts its current – or past – practice of publishing high-quality materials to trick Google into giving the site a high ranking. Think of how Deadspin's private equity grifter owners turned it into a site full of casino affiliate spam:
The same thing happened to the venerable Money magazine:
https://moneygroup.pr/
Money is one of the many sites whose air purifier reviews Google gives preference to, despite the fact that they do no testing. According to Google, Money is also a reliable source of information on reprogramming your garage-door opener, buying a paint-sprayer, etc:
https://money.com/best-paint-sprayer/
All of this is made ten million times worse by AI, which can spray out superficially plausible botshit in superhuman quantities, letting spammers produce thousands of variations on their shitty reviews, flooding the zone with bullshit in classic Steve Bannon style:
As Gizmodo, Sports Illustrated and USA Today have learned the hard way, AI can't write factual news pieces. But it can pump out bullshit written for the express purpose of drafting on the good work human journalists have done and tricking Google – the search engine 90% of us rely on – into upranking bullshit at the expense of high-quality information.
A variety of AI service bureaux have popped up to provide AI botshit as a service to news brands. While Navarro doesn't say so, I'm willing to bet that for news bosses, outsourcing your botshit scams to a third party is considered an excellent way of avoiding your journalists' wrath. The biggest botshit-as-a-service company is ASR Group (which also uses the alias Advon Commerce).
Advon claims that its botshit is, in fact, written by humans. But Advon's employees' Linkedin profiles tell a different story, boasting of their mastery of AI tools in the industrial-scale production of botshit:
Now, none of this is particularly sophisticated. It doesn't take much discernment to spot when a site is engaged in "site reputation abuse." Presumably, the 12,000 googlers the company fired last year could have been employed to check the top review keyword results manually every couple of days and permaban any site caught cheating this way.
Instead, Google is has announced a change in policy: starting May 5, the company will downrank any site caught engaged in site reputation abuse. However, the company takes a very narrow view of site reputation abuse, limiting punishments to sites that employ third parties to generate or uprank their botshit. Companies that produce their botshit in-house are seemingly not covered by this policy.
As Navarro writes, some sites – like Forbes – have prepared for May 5 by blocking their botshit sections from Google's crawler. This can't be their permanent strategy, though – either they'll have to kill the section or bring it in-house to comply with Google's rules. Bringing things in house isn't that hard: US News and World Report is advertising for an SEO editor who will publish 70-80 posts per month, doubtless each one a masterpiece of high-quality, carefully researched material of great value to Google's users:
As Navarro points out, Google is palpably reluctant to target the largest, best-funded spammers. Its March 2024 update kicked many garbage AI sites out of the index – but only small bottom-feeders, not large, once-respected publications that have been colonized by private equity spam-farmers.
All of this comes at a price, and it's only incidentally paid by legitimate sites like Housefresh. The real price is borne by all of us, who are funneled by the 90%-market-share search engine into "review" sites that push low quality, high-price products. Housefresh's top budget air purifier costs $79. That's hundreds of dollars cheaper than the "budget" pick at other sites, who largely perform no original research.
Google search has a problem. AI botshit is dominating Google's search results, and it's not just in product reviews. Searches for infrastructure code samples are dominated by botshit code generated by Pulumi AI, whose chatbot hallucinates nonexistence AWS features:
This is hugely consequential: when these "hallucinations" slip through into production code, they create huge vulnerabilities for widespread malicious exploitation:
We've put all our eggs in Google's basket, and Google's dropped the basket – but it doesn't matter because they can spend $20b/year bribing Apple to make sure no one ever tries a rival search engine on Ios or Safari:
Google's response – laying off core developers, outsourcing to low-waged territories with weak labor protections and spending billions on stock buybacks – presents a picture of a company that is too big to care:
Google promised us a quid-pro-quo: let them be the single, authoritative portal ("organize the world’s information and make it universally accessible and useful"), and they will earn that spot by being the best search there is:
But – like the spammers at the top of its search result pages – Google didn't earn its spot at the center of our digital lives.
It cheated.
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:
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im not gonna go through whether or not its moral or mature or healthy to want attention for what you create, especially if youre sharing to hundreds or thousands of followers. i dont care if its moral or healthy to want attention.
what upsets me is the concept of FOLLOWERS now, not just that it replaced "friends" but also? it just does not mean what it used to mean? it used to be that you'd follow someone... to SEE THEIR POSTS. regardless of your relationship to that person, that was what the follow feature Did. it would Show You That Account's Posts in the main feed
and now thanks to The Algorithms— which are so anthropomorphized they might as well be folk tales at this point— it just... doesn't do that! it doesnt fucking do that!!!! WHY does the feature still exist! WHY can you have an audience of hundreds or THOUSANDS of people following you who check their phones daily if not HOURLY, following you TO SEE YOUR POSTS.... and they DON'T SEE YOUR POSTS?????? WHY CAN I NOT SEE POSTS FROM WHO IM FOLLOWING WHY IS MY FEED 90% NOT POSTS FROM PEOPLE I FOLLOW!!!! WHy DID THEY DO THIS TO EVERYTHING. AM I INSANE HELLO!! CAN ANYONE HEAR ME
Next TUESDAY (May 14), I'm on a livecast about AI AND ENSHITTIFICATION with TIM O'REILLY; on WEDNESDAY (May 15), I'm in NORTH HOLLYWOOD with HARRY SHEARER for a screening of STEPHANIE KELTON'S FINDING THE MONEY; FRIDAY (May 17), I'm at the INTERNET ARCHIVE in SAN FRANCISCO to keynote the 10th anniversary of the AUTHORS ALLIANCE.
Like Oscar Wilde, "I can resist anything except temptation," and my slow and halting journey to adulthood is really just me grappling with this fact, getting temptation out of my way before I can yield to it.
Behavioral economists have a name for the steps we take to guard against temptation: a "Ulysses pact." That's when you take some possibility off the table during a moment of strength in recognition of some coming moment of weakness:
Famously, Ulysses did this before he sailed into the Sea of Sirens. Rather than stopping his ears with wax to prevent his hearing the sirens' song, which would lure him to his drowning, Ulysses has his sailors tie him to the mast, leaving his ears unplugged. Ulysses became the first person to hear the sirens' song and live to tell the tale.
Ulysses was strong enough to know that he would someday be weak. He expressed his strength by guarding against his weakness. Our modern lives are filled with less epic versions of the Ulysses pact: the day you go on a diet, it's a good idea to throw away all your Oreos. That way, when your blood sugar sings its siren song at 2AM, it will be drowned out by the rest of your body's unwillingness to get dressed, find your keys and drive half an hour to the all-night grocery store.
Note that this Ulysses pact isn't perfect. You might drive to the grocery store. It's rare that a Ulysses pact is unbreakable – we bind ourselves to the mast, but we don't chain ourselves to it and slap on a pair of handcuffs for good measure.
People who run institutions can – and should – create Ulysses pacts, too. A company that holds the kind of sensitive data that might be subjected to "sneak-and-peek" warrants by cops or spies can set up a "warrant canary":
https://en.wikipedia.org/wiki/Warrant_canary
This isn't perfect. A company that stops publishing regular transparency reports might have been compromised by the NSA, but it's also possible that they've had a change in management and the new boss just doesn't give a shit about his users' privacy:
Likewise, a company making software it wants users to trust can release that code under an irrevocable free/open software license, thus guaranteeing that each release under that license will be free and open forever. This is good, but not perfect: the new boss can take that free/open code down a proprietary fork and try to orphan the free version:
https://news.ycombinator.com/item?id=39772562
A company can structure itself as a public benefit corporation and make a binding promise to elevate its stakeholders' interests over its shareholders' – but the CEO can still take a secret $100m bribe from cryptocurrency creeps and try to lure those stakeholders into a shitcoin Ponzi scheme:
A key resource can be entrusted to a nonprofit with a board of directors who are charged with stewarding it for the benefit of a broad community, but when a private equity fund dangles billions before that board, they can talk themselves into a belief that selling out is the right thing to do:
Ulysses pacts aren't perfect, but they are very important. At the very least, creating a Ulysses pact starts with acknowledging that you are fallible. That you can be tempted, and rationalize your way into taking bad action, even when you know better. Becoming an adult is a process of learning that your strength comes from seeing your weaknesses and protecting yourself and the people who trust you from them.
Which brings me to enshittification. Enshittification is the process by which platforms betray their users and their customers by siphoning value away from each until the platform is a pile of shit:
https://en.wikipedia.org/wiki/Enshittification
Enshittification is a spectrum that can be applied to many companies' decay, but in its purest form, enshittification requires:
a) A platform: a two-sided market with business customers and end users who can be played off against each other;
b) A digital back-end: a market that can be easily, rapidly and undetectably manipulated by its owners, who can alter search-rankings, prices and costs on a per-user, per-query basis; and
c) A lack of constraint: the platform's owners must not fear a consequence for this cheating, be it from competitors, regulators, workforce resignations or rival technologists who use mods, alternative clients, blockers or other "adversarial interoperability" tools to disenshittify your product and sever your relationship with your users.
he founders of tech platforms don't generally set out to enshittify them. Rather, they are constantly seeking some equilibrium between delivering value to their shareholders and turning value over to end users, business customers, and their own workers. Founders are consummate rationalizers; like parenting, founding a company requires continuous, low-grade self-deception about the amount of work involved and the chances of success. A founder, confronted with the likelihood of failure, is absolutely capable of talking themselves into believing that nearly any compromise is superior to shuttering the business: "I'm one of the good guys, so the most important thing is for me to live to fight another day. Thus I can do any number of immoral things to my users, business customers or workers, because I can make it up to them when we survive this crisis. It's for their own good, even if they don't know it. Indeed, I'm doubly moral here, because I'm volunteering to look like the bad guy, just so I can save this business, which will make the world over for the better":
(En)shit(tification) flows downhill, so tech workers grapple with their own version of this dilemma. Faced with constant pressure to increase the value flowing from their division to the company, they have to balance different, conflicting tactics, like "increasing the number of users or business customers, possibly by shifting value from the company to these stakeholders in the hopes of making it up in volume"; or "locking in my existing stakeholders and squeezing them harder, safe in the knowledge that they can't easily leave the service provided the abuse is subtle enough." The bigger a company gets, the harder it is for it to grow, so the biggest companies realize their gains by locking in and squeezing their users, not by improving their service::
That's where "twiddling" comes in. Digital platforms are extremely flexible, which comes with the territory: computers are the most flexible tools we have. This means that companies can automate high-speed, deceptive changes to the "business logic" of their platforms – what end users pay, how much of that goes to business customers, and how offers are presented to both:
https://pluralistic.net/2023/02/19/twiddler/
This kind of fraud isn't particularly sophisticated, but it doesn't have to be – it just has to be fast. In any shell-game, the quickness of the hand deceives the eye:
Under normal circumstances, this twiddling would be constrained by counterforces in society. Changing the business rules like this is fraud, so you'd hope that a regulator would step in and extinguish the conduct, fining the company that engaged in it so hard that they saw a net loss from the conduct. But when a sector gets very concentrated, its mega-firms capture their regulators, becoming "too big to jail":
Thus the tendency among the giant tech companies to practice the one lesson of the Darth Vader MBA: dismissing your stakeholders' outrage by saying, "I am altering the deal. Pray I don't alter it any further":
Where regulators fail, technology can step in. The flexibility of digital platforms cuts both ways: when the company enshittifies its products, you can disenshittify it with your own countertwiddling: third-party ink-cartridges, alternative app stores and clients, scrapers, browser automation and other forms of high-tech guerrilla warfare:
But tech giants' regulatory capture have allowed them to expand "IP rights" to prevent this self-help. By carefully layering overlapping IP rights around their products, they can criminalize the technology that lets you wrestle back the value they've claimed for themselves, creating a new offense of "felony contempt of business model":
https://locusmag.com/2020/09/cory-doctorow-ip/
A world where users must defer to platforms' moment-to-moment decisions about how the service operates, without the protection of rival technology or regulatory oversight is a world where companies face a powerful temptation to enshittify.
That's why we've seen so much enshittification in platforms that algorithmically rank their feeds, from Google and Amazon search to Facebook and Twitter feeds. A search engine is always going to be making a judgment call about what the best result for your search should be. If a search engine is generally good at predicting which results will please you best, you'll return to it, automatically clicking the first result ("I'm feeling lucky").
This means that if a search engine slips in the odd paid result at the top of the results, they can exploit your trusting habits to shift value from you to their investors. The congifurability of a digital service means that they can sprinkle these frauds into their services on a random schedule, making them hard to detect and easy to dismiss as lapses. Gradually, this acquires its own momentum, and the platform becomes addicted to lowering its own quality to raise its profits, and you get modern Google, which cynically lowered search quality to increase search volume:
And you get Amazon, which makes $38 billion every year, accepting bribes to replace its best search results with paid results for products that cost more and are of lower quality:
Social media's enshittification followed a different path. In the beginning, social media presented a deterministic feed: after you told the platform who you wanted to follow, the platform simply gathered up the posts those users made and presented them to you, in reverse-chronological order.
This presented few opportunities for enshittification, but it wasn't perfect. For users who were well-established on a platform, a reverse-chrono feed was an ungovernable torrent, where high-frequency trivialities drowned out the important posts from people whose missives were buried ten screens down in the updates since your last login.
For new users who didn't yet follow many people, this presented the opposite problem: an empty feed, and the sense that you were all alone while everyone else was having a rollicking conversation down the hall, in a room you could never find.
The answer was the algorithmic feed: a feed of recommendations drawn from both the accounts you followed and strangers alike. Theoretically, this could solve both problems, by surfacing the most important materials from your friends while keeping you abreast of the most important and interesting activity beyond your filter bubble. For many of us, this promise was realized, and algorithmic feeds became a source of novelty and relevance.
But these feeds are a profoundly tempting enshittification target. The critique of these algorithms has largely focused on "addictiveness" and the idea that platforms would twiddle the knobs to increase the relevance of material in your feed to "hack your engagement":
Less noticed – and more important – was how platforms did the opposite: twiddling the knobs to remove things from your feed that you'd asked to see or that the algorithm predicted you'd enjoy, to make room for "boosted" content and advertisements:
Users were helpless before this kind of twiddling. On the one hand, they were locked into the platform – not because their dopamine had been hacked by evil tech-bro wizards – but because they loved the friends they had there more than they hated the way the service was run:
On the other hand, the platforms had such an iron grip on their technology, and had deployed IP so cleverly, that any countertwiddling technology was instantaneously incinerated by legal death-rays:
Newer social media platforms, notably Tiktok, dispensed entirely with deterministic feeds, defaulting every user into a feed that consisted entirely of algorithmic picks; the people you follow on these platforms are treated as mere suggestions by their algorithms. This is a perfect breeding-ground for enshittification: different parts of the business can twiddle the knobs to override the algorithm for their own parochial purposes, shifting the quality:shit ratio by unnoticeable increments, temporarily toggling the quality knob when your engagement drops off:
All social platforms want to be Tiktok: nominally, that's because Tiktok's algorithmic feed is so good at hooking new users and keeping established users hooked. But tech bosses also understand that a purely algorithmic feed is the kind of black box that can be plausibly and subtly enshittified without sparking user revolts:
Back in 2004, when Mark Zuckerberg was coming to grips with Facebook's success, he boasted to a friend that he was sitting on a trove of emails, pictures and Social Security numbers for his fellow Harvard students, offering this up for his friend's idle snooping. The friend, surprised, asked "What? How'd you manage that one?"
Infamously, Zuck replied, "People just submitted it. I don't know why. They 'trust me.' Dumb fucks."
This was a remarkable (and uncharacteristic) self-aware moment from the then-nineteen-year-old Zuck. Of course Zuck couldn't be trusted with that data. Whatever Jiminy Cricket voice told him to safeguard that trust was drowned out by his need to boast to pals, or participate in the creepy nonconsensual rating of the fuckability of their female classmates. Over and over again, Zuckerberg would promise to use his power wisely, then break that promise as soon as he could do so without consequence:
Zuckerberg is a cautionary tale. Aware from the earliest moments that he was amassing power that he couldn't be trusted with, he nevertheless operated with only the weakest of Ulysses pacts, like a nonbinding promise never to spy on his users:
But the platforms have learned the wrong lesson from Zuckerberg. Rather than treating Facebook's enshittification as a cautionary tale, they've turned it into a roadmap. The Darth Vader MBA rules high-tech boardrooms.
Algorithmic feeds and other forms of "paternalistic" content presentation are necessary and even desirable in an information-rich environment. In many instances, decisions about what you see must be largely controlled by a third party whom you trust. The audience in a comedy club doesn't get to insist on knowing the punchline before the joke is told, just as RPG players don't get to order the Dungeon Master to present their preferred challenges during a campaign.
But this power is balanced against the ease of the players replacing the Dungeon Master or the audience walking out on the comic. When you've got more than a hundred dollars sunk into a video game and an online-only friend-group you raid with, the games company can do a lot of enshittification without losing your business, and they know it:
A tech company that seeks your trust for an algorithmic feed needs Ulysses pacts, or it will inevitably yield to the temptation to enshittify. From strongest to weakest, these are:
Not showing you an algorithmic feed at all;
https://joinmastodon.org/
"Composable moderation" that lets multiple parties provide feeds:
Maturity lies in being strong enough to know your weaknesses. Never trust someone who tells you that they will never yield to temptation! Instead, seek out people – and service providers – with the maturity and honesty to know how tempting temptation is, and who act before temptation strikes to make it easier to resist.
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:
Tomorrow (Nov 4), I'm keynoting the Hackaday Supercon in Pasadena, CA.
The thing is, any feed or search result is "algorithmic." "Just show me the things posted by people I follow in reverse-chronological order" is an algorithm. "Just show me products that have this SKU" is an algorithm. "Alphabetical sort" is an algorithm. "Random sort" is an algorithm.
Any process that involves more information than you can take in at a glance or digest in a moment needs some kind of sense-making. It needs to be put in some kind of order. There's always gonna be an algorithm.
But that's not what we mean by "the algorithm" (TM). When we talk about "the algorithm," we mean a system for ordering information that uses complex criteria that are not precisely known to us, and than can't be easily divined through an examination of the ordering.
There's an idea that a "good" algorithm is one that does not seek to deceive or harm us. When you search for a specific part number, you want exact matches for that search at the top of the results. It's fine if those results include third-party parts that are compatible with the part you're searching for, so long as they're clearly labeled. There's room for argument about how to order those results – do highly rated third-party parts go above the OEM part? How should the algorithm trade off price and quality?
It's hard to come up with an objective standard to resolve these fine-grained differences, but search technologists have tried. Think of Google: they have a patent on "long clicks." A "long click" is when you search for something and then don't search for it again for quite some time, the implication being that you've found what you were looking for. Google Search ads operate a "pay per click" model, and there's an argument that this aligns Google's ad division's interests with search quality: if the ad division only gets paid when you click a link, they will militate for placing ads that users want to click on.
Platforms are inextricably bound up in this algorithmic information sorting business. Platforms have emerged as the endemic form of internet-based business, which is ironic, because a platform is just an intermediary – a company that connects different groups to each other. The internet's great promise was "disintermediation" – getting rid of intermediaries. We did that, and then we got a whole bunch of new intermediaries.
Usually, those groups can be sorted into two buckets: "business customers" (drivers, merchants, advertisers, publishers, creative workers, etc) and "end users" (riders, shoppers, consumers, audiences, etc). Platforms also sometimes connect end users to each other: think of dating sites, or interest-based forums on Reddit. Either way, a platform's job is to make these connections, and that means platforms are always in the algorithm business.
Whether that's matching a driver and a rider, or an advertiser and a consumer, or a reader and a mix of content from social feeds they're subscribed to and other sources of information on the service, the platform has to make a call as to what you're going to see or do.
These choices are enormously consequential. In the theory of Surveillance Capitalism, these choices take on an almost supernatural quality, where "Big Data" can be used to guess your response to all the different ways of pitching an idea or product to you, in order to select the optimal pitch that bypasses your critical faculties and actually controls your actions, robbing you of "the right to a future tense."
I don't think much of this hypothesis. Every claim to mind control – from Rasputin to MK Ultra to neurolinguistic programming to pick-up artists – has turned out to be bullshit. Besides, you don't need to believe in mind control to explain the ways that algorithms shape our beliefs and actions. When a single company dominates the information landscape – say, when Google controls 90% of your searches – then Google's sorting can deprive you of access to information without you knowing it.
If every "locksmith" listed on Google Maps is a fake referral business, you might conclude that there are no more reputable storefront locksmiths in existence. What's more, this belief is a form of self-fulfilling prophecy: if Google Maps never shows anyone a real locksmith, all the real locksmiths will eventually go bust.
If you never see a social media update from a news source you follow, you might forget that the source exists, or assume they've gone under. If you see a flood of viral videos of smash-and-grab shoplifter gangs and never see a news story about wage theft, you might assume that the former is common and the latter is rare (in reality, shoplifting hasn't risen appreciably, while wage-theft is off the charts).
In the theory of Surveillance Capitalism, the algorithm was invented to make advertisers richer, and then went on to pervert the news (by incentivizing "clickbait") and finally destroyed our politics when its persuasive powers were hijacked by Steve Bannon, Cambridge Analytica, and QAnon grifters to turn millions of vulnerable people into swivel-eyed loons, racists and conspiratorialists.
As I've written, I think this theory gives the ad-tech sector both too much and too little credit, and draws an artificial line between ad-tech and other platform businesses that obscures the connection between all forms of platform decay, from Uber to HBO to Google Search to Twitter to Apple and beyond:
As a counter to Surveillance Capitalism, I've proposed a theory of platform decay called enshittification, which identifies how the market power of monopoly platforms, combined with the flexibility of digital tools, combined with regulatory capture, allows platforms to abuse both business-customers and end-users, by depriving them of alternatives, then "twiddling" the knobs that determine the rules of the platform without fearing sanction under privacy, labor or consumer protection law, and finally, blocking digital self-help measures like ad-blockers, alternative clients, scrapers, reverse engineering, jailbreaking, and other tech guerrilla warfare tactics:
One important distinction between Surveillance Capitalism and enshittification is that enshittification posits that the platform is bad for everyone. Surveillance Capitalism starts from the assumption that surveillance advertising is devastatingly effective (which explains how your racist Facebook uncles got turned into Jan 6 QAnons), and concludes that advertisers must be well-served by the surveillance system.
But advertisers – and other business customers – are very poorly served by platforms. Procter and Gamble reduced its annual surveillance advertising budget from $100m//year to $0/year and saw a 0% reduction in sales. The supposed laser-focused targeting and superhuman message refinement just don't work very well – first, because the tech companies are run by bullshitters whose marketing copy is nonsense, and second because these companies are monopolies who can abuse their customers without losing money.
The point of enshittification is to lock end-users to the platform, then use those locked-in users as bait for business customers, who will also become locked to the platform. Once everyone is holding everyone else hostage, the platform uses the flexibility of digital services to play a variety of algorithmic games to shift value from everyone to the business's shareholders. This flexibility is supercharged by the failure of regulators to enforce privacy, labor and consumer protection standards against the companies, and by these companies' ability to insist that regulators punish end-users, competitors, tinkerers and other third parties to mod, reverse, hack or jailbreak their products and services to block their abuse.
Enshittification needs The Algorithm. When Uber wants to steal from its drivers, it can just do an old-fashioned wage theft, but eventually it will face the music for that kind of scam:
The best way to steal from drivers is with algorithmic wage discrimination. That's when Uber offers occassional, selective drivers higher rates than it gives to drivers who are fully locked to its platform and take every ride the app offers. The less selective a driver becomes, the lower the premium the app offers goes, but if a driver starts refusing rides, the wage offer climbs again. This isn't the mind-control of Surveillance Capitalism, it's just fraud, shaving fractional pennies off your paycheck in the hopes that you won't notice. The goal is to get drivers to abandon the other side-hustles that allow them to be so choosy about when they drive Uber, and then, once the driver is fully committed, to crank the wage-dial down to the lowest possible setting:
This is the same game that Facebook played with publishers on the way to its enshittification: when Facebook began aggressively courting publishers, any short snippet republished from the publisher's website to a Facebook feed was likely to be recommended to large numbers of readers. Facebook offered publishers a vast traffic funnel that drove millions of readers to their sites.
But as publishers became more dependent on that traffic, Facebook's algorithm started downranking short excerpts in favor of medium-length ones, building slowly to fulltext Facebook posts that were fully substitutive for the publisher's own web offerings. Like Uber's wage algorithm, Facebook's recommendation engine played its targets like fish on a line.
When publishers responded to declining reach for short excerpts by stepping back from Facebook, Facebook goosed the traffic for their existing posts, sending fresh floods of readers to the publisher's site. When the publisher returned to Facebook, the algorithm once again set to coaxing the publishers into posting ever-larger fractions of their work to Facebook, until, finally, the publisher was totally locked into Facebook. Facebook then started charging publishers for "boosting" – not just to be included in algorithmic recommendations, but to reach their own subscribers.
Enshittification is modern, high-tech enabled, monopolistic form of rent seeking. Rent-seeking is a subtle and important idea from economics, one that is increasingly relevant to our modern economy. For economists, a "rent" is income you get from owning a "factor of production" – something that someone else needs to make or do something.
Rents are not "profits." Profit is income you get from making or doing something. Rent is income you get from owning something needed to make a profit. People who earn their income from rents are called rentiers. If you make your income from profits, you're a "capitalist."
Capitalists and rentiers are in irreconcilable combat with each other. A capitalist wants access to their factors of production at the lowest possible price, whereas rentiers want those prices to be as high as possible. A phone manufacturer wants to be able to make phones as cheaply as possible, while a patent-troll wants to own a patent that the phone manufacturer needs to license in order to make phones. The manufacturer is a capitalism, the troll is a rentier.
The troll might even decide that the best strategy for maximizing their rents is to exclusively license their patents to a single manufacturer and try to eliminate all other phones from the market. This will allow the chosen manufacturer to charge more and also allow the troll to get higher rents. Every capitalist except the chosen manufacturer loses. So do people who want to buy phones. Eventually, even the chosen manufacturer will lose, because the rentier can demand an ever-greater share of their profits in rent.
Digital technology enables all kinds of rent extraction. The more digitized an industry is, the more rent-seeking it becomes. Think of cars, which harvest your data, block third-party repair and parts, and force you to buy everything from acceleration to seat-heaters as a monthly subscription:
The cloud is especially prone to rent-seeking, as Yanis Varoufakis writes in his new book, Technofeudalism, where he explains how "cloudalists" have found ways to lock all kinds of productive enterprise into using cloud-based resources from which ever-increasing rents can be extracted:
The endless malleability of digitization makes for endless variety in rent-seeking, and cataloging all the different forms of digital rent-extraction is a major project in this Age of Enshittification. "Algorithmic Attention Rents: A theory of digital platform market power," a new UCL Institute for Innovation and Public Purpose paper by Tim O'Reilly, Ilan Strauss and Mariana Mazzucato, pins down one of these forms:
The "attention rents" referenced in the paper's title are bait-and-switch scams in which a platform deliberately enshittifies its recommendations, search results or feeds to show you things that are not the thing you asked to see, expect to see, or want to see. They don't do this out of sadism! The point is to extract rent – from you (wasted time, suboptimal outcomes) and from business customers (extracting rents for "boosting," jumbling good results in among scammy or low-quality results).
The authors cite several examples of these attention rents. Much of the paper is given over to Amazon's so-called "advertising" product, a $31b/year program that charges sellers to have their products placed above the items that Amazon's own search engine predicts you will want to buy:
This is a form of gladiatorial combat that pits sellers against each other, forcing them to surrender an ever-larger share of their profits in rent to Amazon for pride of place. Amazon uses a variety of deceptive labels ("Highly Rated – Sponsored") to get you to click on these products, but most of all, they rely two factors. First, Amazon has a long history of surfacing good results in response to queries, which makes buying whatever's at the top of a list a good bet. Second, there's just so many possible results that it takes a lot of work to sift through the probably-adequate stuff at the top of the listings and get to the actually-good stuff down below.
Amazon spent decades subsidizing its sellers' goods – an illegal practice known as "predatory pricing" that enforcers have increasingly turned a blind eye to since the Reagan administration. This has left it with few competitors:
The lack of competing retail outlets lets Amazon impose other rent-seeking conditions on its sellers. For example, Amazon has a "most favored nation" requirement that forces companies that raise their prices on Amazon to raise their prices everywhere else, which makes everything you buy more expensive, whether that's a Walmart, Target, a mom-and-pop store, or direct from the manufacturer:
But everyone loses in this "two-sided market." Amazon used "junk ads" to juice its ad-revenue: these are ads that are objectively bad matches for your search, like showing you a Seattle Seahawks jersey in response to a search for LA Lakers merch:
The more of these junk ads Amazon showed, the more revenue it got from sellers – and the more the person selling a Lakers jersey had to pay to show up at the top of your search, and the more they had to charge you to cover those ad expenses, and the more they had to charge for it everywhere else, too.
The authors describe this process as a transformation between "attention rents" (misdirecting your attention) to "pecuniary rents" (making money). That's important: despite decades of rhetoric about the "attention economy," attention isn't money. As I wrote in my enshittification essay:
You can't use attention as a medium of exchange. You can't use it as a store of value. You can't use it as a unit of account. Attention is like cryptocurrency: a worthless token that is only valuable to the extent that you can trick or coerce someone into parting with "fiat" currency in exchange for it. You have to "monetize" it – that is, you have to exchange the fake money for real money.
The authors come up with some clever techniques for quantifying the ways that this scam harms users. For example, they count the number of places that an advertised product rises in search results, relative to where it would show up in an "organic" search. These quantifications are instructive, but they're also a kind of subtweet at the judiciary.
In 2018, SCOTUS's ruling in American Express v Ohio changed antitrust law for two-sided markets by insisting that so long as one side of a two-sided market was better off as the result of anticompetitive actions, there was no antitrust violation:
For platforms, that means that it's OK to screw over sellers, advertisers, performers and other business customers, so long as the end-users are better off: "Go ahead, cheat the Uber drivers, so long as you split the booty with Uber riders."
But in the absence of competition, regulation or self-help measures, platforms cheat everyone – that's the point of enshittification. The attention rents that Amazon's payola scheme extract from shoppers translate into higher prices, worse goods, and lower profits for platform sellers. In other words, Amazon's conduct is so sleazy that it even threads the infinitesimal needle that the Supremes created in American Express.
Here's another algorithmic pecuniary rent: Amazon figured out which of its major rivals used an automated price-matching algorithm, and then cataloged which products they had in common with those sellers. Then, under a program called Project Nessie, Amazon jacked up the prices of those products, knowing that as soon as they raised the prices on Amazon, the prices would go up everywhere else, so Amazon wouldn't lose customers to cheaper alternatives. That scam made Amazon at least a billion dollars:
This is a great example of how enshittification – rent-seeking on digital platforms – is different from analog rent-seeking. The speed and flexibility with which Amazon and its rivals altered their prices requires digitization. Digitization also let Amazon crank the price-gouging dial to zero whenever they worried that regulators were investigating the program.
So what do we do about it? After years of being made to look like fumblers and clowns by Big Tech, regulators and enforcers – and even lawmakers – have decided to get serious.
The neoliberal narrative of government helplessness and incompetence would have you believe that this will go nowhere. Governments aren't as powerful as giant corporations, and regulators aren't as smart as the supergeniuses of Big Tech. They don't stand a chance.
But that's a counsel of despair and a cheap trick. Weaker US governments have taken on stronger oligarchies and won – think of the defeat of JD Rockefeller and the breakup of Standard Oil in 1911. The people who pulled that off weren't wizards. They were just determined public servants, with political will behind them. There is a growing, forceful public will to end the rein of Big Tech, and there are some determined public servants surfing that will.
In this paper, the authors try to give those enforcers ammo to bring to court and to the public. For example, Amazon claims that its algorithm surfaces the products that make the public happy, without the need for competitive pressure to keep it sharp. But as the paper points out, the only successful new rival ecommerce platform – Tiktok – has found an audience for an entirely new category of goods: dupes, "lower-cost products that have the same or better features than higher cost branded products."
The authors also identify "dark patterns" that platforms use to trick users into consuming feeds that have a higher volume of things that the company profits from, and a lower volume of things that users want to see. For example, platforms routinely switch users from a "following" feed – consisting of things posted by people the user asked to hear from – with an algorithmic "For You" feed, filled with the things the company's shareholders wish the users had asked to see.
Calling this a "dark pattern" reveals just how hollow and self-aggrandizing that term is. "Dark pattern" usually means "fraud." If I ask to see posts from people I like, and you show me posts from people who'll pay you for my attention instead, that's not a sophisticated sleight of hand – it's just a scam. It's the social media equivalent of the eBay seller who sends you an iPhone box with a bunch of gravel inside it instead of an iPhone. Tech bros came up with "dark pattern" as a way of flattering themselves by draping themselves in the mantle of dopamine-hacking wizards, rather than unimaginative con-artists who use a computer to rip people off.
These For You algorithmic feeds aren't just a way to increase the load of sponsored posts in a feed – they're also part of the multi-sided ripoff of enshittified platforms. A For You feed allows platforms to trick publishers and performers into thinking that they are "good at the platform," which both convinces to optimize their production for that platform, and also turns them into Judas Goats who conspicuously brag about how great the platform is for people like them, which brings their peers in, too.
In Veena Dubal's essential paper on algorithmic wage discrimination, she describes how Uber drivers whom the algorithm has favored with (temporary) high per-ride rates brag on driver forums about their skill with the app, bringing in other drivers who blame their lower wages on their failure to "use the app right":
If you go down to the midway at your county fair, you'll spot some poor sucker walking around all day with a giant teddy bear that they won by throwing three balls in a peach basket.
The peach-basket is a rigged game. The carny can use a hidden switch to force the balls to bounce out of the basket. No one wins a giant teddy bear unless the carny wants them to win it. Why did the carny let the sucker win the giant teddy bear? So that he'd carry it around all day, convincing other suckers to put down five bucks for their chance to win one:
The carny allocated a giant teddy bear to that poor sucker the way that platforms allocate surpluses to key performers – as a convincer in a "Big Store" con, a way to rope in other suckers who'll make content for the platform, anchoring themselves and their audiences to it.
Platform can't run the giant teddy-bear con unless there's a For You feed. Some platforms – like Tiktok – tempt users into a For You feed by making it as useful as possible, then salting it with doses of enshittification:
Other platforms use the (ugh) "dark pattern" of simply flipping your preference from a "following" feed to a "For You" feed. Either way, the platform can't let anyone keep the giant teddy-bear. Once you've tempted, say, sports bros into piling into the platform with the promise of millions of free eyeballs, you need to withdraw the algorithm's favor for their content so you can give it to, say, astrologers. Of course, the more locked-in the users are, the more shit you can pile into that feed without worrying about them going elsewhere, and the more giant teddy-bears you can give away to more business users so you can lock them in and start extracting rent.
For regulators, the possibility of a "good" algorithmic feed presents a serious challenge: when a feed is bad, how can a regulator tell if its low quality is due to the platform's incompetence at blocking spammers or guessing what users want, or whether it's because the platform is extracting rents?
The paper includes a suite of recommendations, including one that I really liked:
Regulators, working with cooperative industry players, would define reportable metrics based on those that are actually used by the platforms themselves to manage search, social media, e-commerce, and other algorithmic relevancy and recommendation engines.
In other words: find out how the companies themselves measure their performance. Find out what KPIs executives have to hit in order to earn their annual bonuses and use those to figure out what the company's performance is – ad load, ratio of organic clicks to ad clicks, average click-through on the first organic result, etc.
They also recommend some hard rules, like reserving a portion of the top of the screen for "organic" search results, and requiring exact matches to show up as the top result.
I've proposed something similar, applicable across multiple kinds of digital businesses: an end-to-end principle for online services. The end-to-end principle is as old as the internet, and it decrees that the role of an intermediary should be to deliver data from willing senders to willing receivers as quickly and reliably as possible. When we apply this principle to your ISP, we call it Net Neutrality. For services, E2E would mean that if I subscribed to your feed, the service would have a duty to deliver it to me. If I hoisted your email out of my spam folder, none of your future emails should land there. If I search for your product and there's an exact match, that should be the top result:
One interesting wrinkle to framing platform degradation as a failure to connect willing senders and receivers is that it places a whole host of conduct within the regulatory remit of the FTC. Section 5 of the FTC Act contains a broad prohibition against "unfair and deceptive" practices:
That means that the FTC doesn't need any further authorization from Congress to enforce an end to end rule: they can simply propose and pass that rule, on the grounds that telling someone that you'll show them the feeds that they ask for and then not doing so is "unfair and deceptive."
Some of the other proposals in the paper also fit neatly into Section 5 powers, like a "sticky" feed preference. If I tell a service to show me a feed of the people I follow and they switch it to a For You feed, that's plainly unfair and deceptive.
All of this raises the question of what a post-Big-Tech feed would look like. In "How To Break Up Amazon" for The Sling, Peter Carstensen and Darren Bush sketch out some visions for this:
https://www.thesling.org/how-to-break-up-amazon/
They imagine a "condo" model for Amazon, where the sellers collectively own the Amazon storefront, a model similar to capacity rights on natural gas pipelines, or to patent pools. They see two different ways that search-result order could be determined in such a system:
"specific premium placement could go to those vendors that value the placement the most [with revenue] shared among the owners of the condo"
or
"leave it to owners themselves to create joint ventures to promote products"
Note that both of these proposals are compatible with an end-to-end rule and the other regulatory proposals in the paper. Indeed, all these policies are easier to enforce against weaker companies that can't afford to maintain the pretense that they are headquartered in some distant regulatory haven, or pay massive salaries to ex-regulators to work the refs on their behalf:
The re-emergence of intermediaries on the internet after its initial rush of disintermediation tells us something important about how we relate to one another. Some authors might be up for directly selling books to their audiences, and some drivers might be up for creating their own taxi service, and some merchants might want to run their own storefronts, but there's plenty of people with something they want to offer us who don't have the will or skill to do it all. Not everyone wants to be a sysadmin, a security auditor, a payment processor, a software engineer, a CFO, a tax-preparer and everything else that goes into running a business. Some people just want to sell you a book. Or find a date. Or teach an online class.
Intermediation isn't intrinsically wicked. Intermediaries fall into pits of enshitffication and other forms of rent-seeking when they aren't disciplined by competitors, by regulators, or by their own users' ability to block their bad conduct (with ad-blockers, say, or other self-help measures). We need intermediaries, and intermediaries don't have to turn into rent-seeking feudal warlords. That only happens if we let it happen.
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:
