#algorithmic feeds

Remember: enshittification isn't the result of worse people running tech companies today than in the years when tech services were good and useful. Rather, enshittification is rooted in the collapse of constraints that used to prevent those same people from making their services worse in service to increasing their profit margins:

https://pluralistic.net/2024/03/26/glitchbread/#electronic-shelf-tags

These companies always had the capacity to siphon value away from business customers (like publishers) and end-users (like searchers). That comes with the territory: digital businesses can alter their "business logic" from instant to instant, and for each user, allowing them to change payouts, prices and ranking. I call this "twiddling": turning the knobs on the system's back-end to make sure the house always wins:

https://pluralistic.net/2023/02/19/twiddler/

What changed wasn't the character of the leaders of these businesses, nor their capacity to cheat us. What changed was the consequences for cheating. When the tech companies merged to monopoly, they ceased to fear losing your business to a competitor.

Google's 90% search market share was attained by bribing everyone who operates a service or platform where you might encounter a search box to connect that box to Google. Spending tens of billions of dollars every year to make sure no one ever encounters a non-Google search is a cheaper way to retain your business than making sure Google is the very best search engine:

https://pluralistic.net/2024/02/21/im-feeling-unlucky/#not-up-to-the-task

Competition was once a threat to Google; for years, its mantra was "competition is a click away." Today, competition is all but nonexistent.

Then the surveillance business consolidated into a small number of firms. Two companies dominate the commercial surveillance industry: Google and Meta, and they collude to rig the market:

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

That consolidation inevitably leads to regulatory capture: shorn of competitive pressure, the companies that dominate the sector can converge on a single message to policymakers and use their monopoly profits to turn that message into policy:

https://pluralistic.net/2022/06/05/regulatory-capture/

This is why Google doesn't have to worry about privacy laws. They've successfully prevented the passage of a US federal consumer privacy law. The last time the US passed a federal consumer privacy law was in 1988. It's a law that bans video store clerks from telling the newspapers which VHS cassettes you rented:

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

In Europe, Google's vast profits lets it fly an Irish flag of convenience, thus taking advantage of Ireland's tolerance for tax evasion and violations of European privacy law:

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

Google doesn't fear competition, it doesn't fear regulation, and it also doesn't fear rival technologies. Google and its fellow Big Tech cartel members have expanded IP law to allow it to prevent third parties from reverse-engineer, hacking, or scraping its services. Google doesn't have to worry about ad-blocking, tracker blocking, or scrapers that filter out Google's lucrative, low-quality results:

https://locusmag.com/2020/09/cory-doctorow-ip/

Google doesn't fear competition, it doesn't fear regulation, it doesn't fear rival technology and it doesn't fear its workers. Google's workforce once enjoyed enormous sway over the company's direction, thanks to their scarcity and market power. But Google has outgrown its dependence on its workers, and lays them off in vast numbers, even as it increases its profits and pisses away tens of billions on stock buybacks:

https://pluralistic.net/2023/11/25/moral-injury/#enshittification

Google is fearless. It doesn't fear losing your business, or being punished by regulators, or being mired in guerrilla warfare with rival engineers. It certainly doesn't fear its workers.

Making search worse is good for Google. Reducing search quality increases the number of queries, and thus ads, that each user must make to find their answers:

https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan

If Google can make things worse for searchers without losing their business, it can make more money for itself. Without the discipline of markets, regulators, tech or workers, it has no impediment to transferring value from searchers and publishers to itself.

Which brings me back to AI search. When Google substitutes its own summaries for links to pages, it creates innumerable opportunities to charge publishers for preferential placement in those summaries.

This is true of any algorithmic feed: while such feeds are important – even vital – for making sense of huge amounts of information, they can also be used to play a high-speed shell-game that makes suckers out of the rest of us:

https://pluralistic.net/2024/05/11/for-you/#the-algorithm-tm

When you trust someone to summarize the truth for you, you become terribly vulnerable to their self-serving lies. In an ideal world, these intermediaries would be "fiduciaries," with a solemn (and legally binding) duty to put your interests ahead of their own:

https://pluralistic.net/2024/05/07/treacherous-computing/#rewilding-the-internet

But Google is clear that its first duty is to its shareholders: not to publishers, not to searchers, not to "partners" or employees.

AI search makes cheating so easy, and Google cheats so much. Indeed, the defects in AI give Google a readymade excuse for any apparent self-dealing: "we didn't tell you a lie because someone paid us to (for example, to recommend a product, or a hotel room, or a political point of view). Sure, they did pay us, but that was just an AI 'hallucination.'"

The existence of well-known AI hallucinations creates a zone of plausible deniability for even more enshittification of Google search. As Madeleine Clare Elish writes, AI serves as a "moral crumple zone":

https://estsjournal.org/index.php/ests/article/view/260

That's why, even if you're willing to believe that Google could make a great AI-based search, we can nevertheless be certain that they won't.

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/2024/05/15/they-trust-me-dumb-fucks/#ai-search

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

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djhughman https://commons.wikimedia.org/wiki/File:Modular_synthesizer_-_%22Control_Voltage%22_electronic_music_shop_in_Portland_OR_-_School_Photos_PCC_%282015-05-23_12.43.01_by_djhughman%29.jpg

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:

https://pluralistic.net/HowToDestroySurveillanceCapitalism

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:

https://pluralistic.net/2023/01/21/potemkin-ai/#hey-guys

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:

https://apnews.com/article/uber-lyft-new-york-city-wage-theft-9ae3f629cf32d3f2fb6c39b8ffcc6cc6

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:

https://pluralistic.net/2023/04/12/algorithmic-wage-discrimination/#fishers-of-men

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:

https://pluralistic.net/2023/07/24/rent-to-pwn/#kitt-is-a-demon

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:

https://pluralistic.net/2023/09/28/cloudalists/#cloud-capital

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:

https://www.ucl.ac.uk/bartlett/public-purpose/publications/2023/nov/algorithmic-attention-rents-theory-digital-platform-market-power

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:

https://pluralistic.net/2022/11/28/enshittification/#relentless-payola

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:

https://pluralistic.net/2023/05/19/fake-it-till-you-make-it/#millennial-lifestyle-subsidy

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:

https://pluralistic.net/2023/04/25/greedflation/#commissar-bezos

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:

https://www.bloomberg.com/news/articles/2023-11-02/amazon-boosted-junk-ads-hid-messages-with-signal-ftc-says

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:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3346776

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:

https://gizmodo.com/ftc-alleges-amazon-used-price-gouging-algorithm-1850986303

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":

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4331080

As I wrote in my enshittification essay:

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:

https://boingboing.net/2006/08/27/rigged-carny-game.html

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:

https://www.forbes.com/sites/emilybaker-white/2023/01/20/tiktoks-secret-heating-button-can-make-anyone-go-viral/

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:

https://www.eff.org/deeplinks/2023/04/platforms-decay-lets-put-users-first

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:

https://pluralistic.net/2023/01/10/the-courage-to-govern/#whos-in-charge

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:

https://www.thesling.org/in-public-discourse-and-congress-revolvers-defend-amazons-monopoly/

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:

https://pluralistic.net/2023/11/03/subprime-attention-rent-crisis/#euthanize-rentiers

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

The original E2E marked the turning point from telco-based systems where power was gathered at the center, controlled by carriers, to the packet-switched internet, where power moved to the edges. Under the old model, only the network operator could add new features. If you wanted to create, say, Caller ID, you needed to convince the phone company to update its switches to support a new signaling system (and you probably had to rent a Caller ID box from the carrier, too).

But packet-switching made it possible for new services to be created by people at the edges of the network. Once your device was connected to the internet, it could exchange data with any other device on the internet. If someone set up a voice-calling system and you connected to it, they could add Caller ID to it without asking Ma Bell for permission.

End to end was the core ethic of this system: the idea that the telcos that sat beneath these systems should get out of the way of their users, serving only to deliver data from willing senders to willing receivers as quickly, efficiently and reliably as possible.

E2E was a powerful idea, one that truly treated the telcos as utilities — the plumbing that sat beneath the services, obliged to serve its subscribers by doing their bidding to the extent they could. If you chose to use a internet calling service instead of making phone calls, the carrier’s job was to shuttle those packets around, not to slow them down or block them to funnel you into its rival service.

There’s a powerful logic to this: no one rents a phone line because they want to make sure that the carrier’s shareholders are getting the highest possible return on their investment. The reason we buy network connections is to get to the services we value.

We have no duty to arrange our affairs to the benefit of a carrier’s shareholders. If those shareholders are so emotionally fragile that they can’t bear the thought of network users making their own choices on which services to use, they should get into a different line of work.

E2E wasn’t a law, it was a principle. Principles are useful! They can be embedded in laws (for example, the laws that establish most network providers as common carriers often include an E2E rule), but just as importantly, they can give us a vocabulary for critiquing or designing services: “Ugh, I won’t use that service, it’s not end to end,” or “How can we make this work in an end to end way?”

Principles can be integrated into professional codes of ethics, or procurement rules for public bodies (“Our university only buys end to end services”). Tech groups and publications can use principles to rank competing technologies (“Which network providers are end to end?”).

Network Neutrality is a way of operationalizing E2E: the idea of Net Neutrality is that carriers should be obliged to treat all traffic the same. If you request Youtube packets from Comcast, Comcast should deliver those packets as quickly and reliably as it can, even though its parent company, Universal, owns several competing services.

Net Neutrality can be treated as a principle (“This ISP sucks — it violates Net Neutrality”) or as a regulation (“The FCC is fining your ISP because it violated Net Neutrality”). As a regulation, Net Neutrality has a problem: it’s hard to administer, because it’s very difficult to detect Net Neutrality violations. The internet is a “best effort” network, with no service guarantees, so when your Youtube connection starts to jitter, it’s hard to prove that this is because Comcast is screwing with it, as opposed to regular network congestion.

Which brings me to my E2E proposal: end to end for services. Contemporary services have no E2E. If you search for a product on Amazon, Amazon often won’t show you that product until you’ve looked at five screens’ worth of other products that have paid Amazon to interrupt your search:

https://pluralistic.net/2022/11/28/enshittification/#relentless-payola

If you hoist an email out of Gmail’s spam folder and add the sender to your address book, Gmail will still send that message to spam, or even block its server. It’s incredible that we had a Congressional debate about whether Gmail should mark politicians unsolicited fundraising emails as spam but not whether emails from your reps that you asked to receive should be delivered:

https://doctorow.medium.com/dead-letters-73924aa19f9d

Platform creators are workers whose boss is an algorithm that docks every paycheck to punish them for breaking rules they aren’t allowed to know about, because if the boss told you the rules, you’d learn how to violate them without him being able to punish you for it. Again, it’s wild that we’re arguing about “shadowbanning” (a service choosing not to send your work to people who never asked to see it), while ignoring the fact that platforms won’t deliver your posts to people who explicitly subscribed to your feed:

https://pluralistic.net/2023/01/21/potemkin-ai/#hey-guys

Alexander Graham Bell’s first telephone operators were young boys who entertained themselves by deliberately misconnecting calls, putting you in contact with people you never asked to talk to and refusing to connect you with the people you were trying to converse with.

As @brucesterling​ wrote in The Hacker Crackdown:

The boys were openly rude to customers. They talked back to subscribers, saucing off, uttering facetious remarks, and generally giving lip. The rascals took Saint Patrick’s Day off without permission. And worst of all they played clever tricks with the switchboard plugs: disconnecting calls, crossing lines so that customers found themselves talking to strangers, and so forth.

https://www.mit.edu/hacker/hacker.html

Bell fired those kids. Even the original telecoms monopolist understood that the point of a telephone network was to connect willing speakers with willing listeners.

Today’s tech barons are much more interested in charging other people to interrupt your consensual communications with nonconsensual and often irrelevant nonsense and ads. This is part of the enshittification cycle: first, the platforms lock you in by giving you a good deal, including feeds that contain the things you ask to see and search boxes that return the thing you’re looking for.

Then, platforms take away your surplus and give it to business customers. They spy on you and use the data to help target you on behalf of advertisers, whom they charge low rates for ads that are reliably delivered. They insert performers’ and media companies’ posts into your feed, generating traffic funnels that result in clicks to off-platform sites. They offer low fees and even subsidies to platform sellers and creators who produce DRM media, like ebooks and audiobooks.

Users get locked into the platform — by the collective action problem of convincing their friends to leave, by the collapse of local retail that can’t match the investor-funded subsidies of would-be monopolists, by DRM that they are legally prohibited from removing, causing them to lose their investment if they quit the service.

Business customers also get locked to the platform: platform sellers have to sell where the buyers are; publishers and creators have to provide media where the audiences are; advertisers have to run ads on the services they’ve optimized for.

Once everyone is locked in, the platform can fully enshittify, harvesting surpluses from users and business customers for themselves. Platforms can hike fees, charge media companies and creators to reach their own subscribers, block posts with links off-site, insert ads into media (like Audible is doing with paid audiobooks!), and so on.

This is the cycle that E2E seeks to interrupt. E2E for services would dictate that platforms should connect willing speakers and willing listeners. The best match for your search should be at the top of the results — even if someone is willing to pay more to put a worse match there. Emails should be delivered to people you’ve told your provider you want to correspond with — not sent to a spam folder or blocked.

As with the original E2E, there’s lots of ways we can use this principle. It can simply be a term for criticizing platforms (“You aren’t sending my posts to the people who follow me — that’s a violation of the end to end principle!”). It can be a law (“It is a deceptive and unfair practice for ecommerce companies to deliberately return search results that are not the best match they can locate for the users’ query”). It can be a punishment (“The FTC settled with Google today and ordered the company to implement a Gmail feature that permits users to identify senders whose messages will never be blocked or sent to spam”).

Lots of people are pissed off about Big Tech and many have proposed that we could make it better by treating platforms as “utilities.” But I don’t want President DeSantis to run my email provider, or to decide what’s too “woke” for me to see (or post) on social media.

An E2E rule, on the other hand, creates a role for government that doesn’t determine who gets to speak or what they get to say — rather, it ensures that when people speak and to others who want to hear them, the message gets through.

Unlike Net Neutrality, E2E is easy to administer. If I claim that your emails are being sent to spam after I marked you as a sender I want to hear from, we don’t have to do a forensic investigation into Google’s mail servers to determine if I’m right. You just send me an email we observe where it lands.

Likewise for search: if I search Amazon for a specific product or model number, it’s easy to tell whether that product is at the top of the search results or not.

Same goes for delivery to subscribers: if we suspect that Twitter is shadowbanning posters — say, for including their Mastodon addresses in their bios, or linking to posts on Mastodon — we just send some test messages and see whether they are delivered.

Beyond administratability, E2E has another advantage: cheap compliance. Lots of the rules we’ve created or proposed for service providers are incredibly complex and expensive to comply with. Take rules about “lawful but awful” content, which require platforms to somehow determine whether a message constitutes harassment and block it if it does.

These rules require an army of expensive human moderators or a vast, expensive machine learning system, or both — so they guarantee that Big Tech will rule the internet forever, because no one else can afford to launch a new service with better community norms and better practices.

By contrast, E2E is cheap to comply with. Trusted-sender lists for email providers, search engines that put best results first, and content delivery algorithms that show you the things you asked to see in the order that they were posted are all solved problems:

https://www.theatlantic.com/ideas/archive/2023/03/social-media-algorithms-twitter-meta-rss-reader/673282

This isn’t to say that platforms wouldn’t be allowed to offer algorithmic feeds and results. Think of how Tumblr does it: you can choose between a feed called “Following” (posts from people you follow) or “For You” (posts that Tumblr thinks you’ll enjoy). Forcing platforms to clearly label their recommendations and give you the choice of controlling your own feed is a powerful check against enshittification.

If you know when you’re in charge and when the platform is driving things, and if you can toggle away from platform-determined feeds to ones that you design, the platform has to be better than you at choosing what you see, or you won’t choose its recommendations.

Platform owners have hijacked the idea that “freedom of speech isn’t freedom of reach” to justify the now-ubiquitous practice of overriding users’ decisions about what they want to see:

https://pluralistic.net/2022/12/10/e2e/#the-censors-pen

The Old Internet had lots to going for it. It wasn’t perfect, though. While it was easy to find the things you knew you liked, it could be hard to find things you didn’t know you liked. Recommendations, whether they come from an algorithm or a human editor, are a source of endless delights. But when a we find something we like through one of those recommendations, we need to know that we can find more from that source if we choose to.

Sometimes it’s nice to scroll an algorithmic feed and get a string of surprises. But we are forced to use those feeds, they will inevitably enshittify, to our detriment, and to the detriment of the people who make the things that please us.

As ever, the important thing about a technology isn’t what it does, it’s who it does it for and who it does it to. When we control our feeds, we can choose to let a recommender system do the driving. If we’re locked into a recommendation system, it drives us.

Today (Mar 7), I’m doing a remote talk for TU Wien.

On Mar 9, you can catch me in person in Austin at the UT School of Design and Creative Technologies, and remotely at U Manitoba’s Ethics of Emerging Tech Lecture.

On Mar 10, Rebecca Giblin and I kick off the SXSW reading series.

Image: Felix Andrews (modified) https://commons.wikimedia.org/wiki/File:Elephant_side-view_Kruger.jpg

CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0/deed.en