#Enshittification is the process by which digital platforms devour themselves: first they dangle goodies in front of end users. Once users are locked in, the goodies are taken away and dangled before business customers who supply goods to the users. Once those business customers are stuck on the platform, the goodies are clawed away and showered on the platform's shareholders:
https://pluralistic.net/2023/01/21/potemkin-ai/#hey-guys
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If you'd like an essay-formatted version of this thread to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
https://pluralistic.net/2023/04/12/algorithmic-wage-discrimination/#fishers-of-men
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Enshittification isn't synonomous with "fraud," "price gouging" or "wage theft." Enshittification is intrinsically digital, because moving all those goodies around requires the flexibility that comes with a *digital* businesses. #JeffBezos, grocer, can't rapidly change the price of eggs at #WholeFoods without an army of kids with pricing guns on roller-skates. Jeff Bezos, grocer, can change the price of eggs on #AmazonFresh just by #twiddling a knob on the service's back-end.
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Twiddling is the key to enshittification: rapidly adjusting prices, conditions and offers. As with any shell game, the quickness of the hand deceives the eye. Tech monopolists aren't smarter than the Gilded Age sociopaths who monopolized rail or coal - they use the same tricks as those monsters of history, but they do them faster and with computers:
https://doctorow.medium.com/twiddler-1b5c9690cce6
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If Rockefeller wanted to crush a freight company, he couldn't just click a mouse and lay down a pipeline that ran on the same route, and then click another mouse to make it go away when he was done. When Bezos wants to bankrupt Diapers.com - a company that refused to sell itself to #Amazon - he just moved a slider so that diapers on Amazon were being sold below cost.
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Amazon lost $100m over three months, diapers.com went bankrupt, and every investor learned that competing with Amazon was a losing bet:
That's the power of twiddling - but twiddling cuts both ways. The same flexibility that digital businesses enjoy is hypothetically available to *workers* and *users*.
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The airlines pioneered twiddling ticket prices, and that naturally gave rise to #countertwiddling, in the form of comparison shopping sites that scraped the airlines' sites to predict when tickets would be cheapest:
https://pluralistic.net/2023/02/27/knob-jockeys/#bros-be-twiddlin
The airlines - like all abusive businesses - refused to tolerate this. *They* were allowed to touch their knobs as much as they wanted - indeed, they couldn't *stop* touching those knobs.
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But when *we* tried to twiddle back, that was "#FelonyContemptOfBusinessModel," and the airlines sued:
https://www.cnbc.com/2014/12/30/airline-sues-man-for-founding-a-cheap-flights-website.html
And sued:
https://www.nytimes.com/2018/01/06/business/southwest-airlines-lawsuit-prices.html
Platforms don't just hate it when end-users twiddle back - if anything they are even more aggressive when their business-users dare to twiddle.
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Take Para, an app that #Doordash drivers used to get a peek at the wages offered for jobs before they accepted them - something that Doordash hid from its workers. Doordash ruthlessly attacked Para, saying that by letting drivers know how much they'd earn before they did the work, Para was violating the law:
https://www.eff.org/deeplinks/2021/08/tech-rights-are-workers-rights-doordash-edition
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DoorDash workers are embroiled in a bitter labor dispute with the company: at issue, the tips that “Dashers” depend on to make the difference between a living wage and the poorhouse. DoorDash has a long history of abusing its workers’ tips; including a particularly ugly case brought by the...
Which law? Well, take your pick. The modern meaning of "#IP" is "any law that lets me use the law to control my competitors, competition or customers." Platforms use a mix of #anticircumvention law, #patent, #copyright, #contract, #cybersecurity and other legal systems to weave together a thicket of rules that allow them to shut down rivals for their Felony Contempt of Business Model:
https://locusmag.com/2020/09/cory-doctorow-ip/
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Enshittification relies on *unlimited* twiddling (by platforms), and a general *prohibition* on countertwiddling (by platform users). Enshittification is a form of fishing, in which bait is dangled before different groups of users and then nimbly withdrawn when they lunge for it. Twiddling puts the suppleness into the enshittifier's fishing-rod, and a ban on countertwiddling weighs down platform users so they're always a bit too slow to catch the bait.
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Nowhere do we see twiddling's impact more than the "#GigEconomy," where workers are misclassified as contractors and put to work for an app that scripts their every move to the finest degree. When an app is your boss, you work for an employer who docks your pay for violating rules that you aren't allowed to know - and where your attempts to learn those rules are constantly frustrated by the endless back-end twiddling that changes the rules faster than you can learn them.
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As with every question of technology, the issue isn't twiddling *per se* - it's who does the twiddling and who gets twiddled. A worker armed with digital tools can play gig work employers off each other and force them to bid up the price of their labor; they can form co-ops with other workers that auto-refuse jobs that don't pay enough, and use digital tools to organize to shift power from bosses to workers:
https://pluralistic.net/2022/12/02/not-what-it-does/#who-it-does-it-to
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Take #ReverseCentaurs. In AI research, a #centaur is a human assisted by a machine that does more than either could do on their own. For example, a chess master and a chess program can play a better game together than either could play separately. A *reverse* centaur is a *machine assisted by a human*, where the machine is in charge and the human is a meat-puppet.
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Think of Amazon warehouse workers wearing haptic wristbands that buzz at them continuously dictating where their hands must be; or Amazon drivers whose eye-movements are continuously tracked in order to penalize drivers who look in the "wrong" direction:
https://pluralistic.net/2021/02/17/reverse-centaur/#reverse-centaur
The difference between a centaur and a reverse centaur is the difference between a machine that makes your life better and a machine that makes your life worse so that your boss gets richer.
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Reverse centaurism is the 21st Century's answer to #Taylorism, the pseudoscience that saw white-coated "experts" subject workers to humiliating choreography down to the smallest movement of your fingertip:
https://pluralistic.net/2022/08/21/great-taylors-ghost/#solidarity-or-bust
While reverse centaurism was born in warehouses and other company-owned facilities, gig work let it make the leap into workers' homes and cars.
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The 21st century has seen a return to the #CottageIndustry - a form of production that once saw workers labor far from their bosses and thus beyond their control - but shriven of the autonomy and dignity that working from home once afforded:
https://doctorow.medium.com/gig-work-is-the-opposite-of-steampunk-463e2730ef0d
The rise and rise of #bossware - which allows for remote surveillance of workers in their homes and cars - has turned "#WorkFromHome" into "#LiveAtWork."
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Reverse centaurs can now be #chickenized - a term from labor economics that describes how poultry farmers, who sell their birds to one of three vast poultry processors who have divided up the country like the Pope dividing up the "New World," are uniquely exploited:
https://onezero.medium.com/revenge-of-the-chickenized-reverse-centaurs-b2e8d5cda826
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A #ChickenizedReverseCentaur has it rough: they must pay for the machines they use to make money for their bosses, they must obey the orders of the app that controls their work, and they are denied any of the protections that a traditional worker might enjoy, even as they are prohibited from deploying digital self-help measures that let them twiddle back to bargain for a better wage.
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All of this sets the stage for a phenomenon called #AlgorithmicWageDiscrimination, in which two workers doing the same job under the same conditions will see radically different payouts for that work. These payouts are continuously tweaked in the background by an algorithm that tries to predict the minimum sum a worker will accept to remain available *without* payment, to ensure sufficient workers to pick up jobs as they arise.
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This phenomenon - and proposed policy and labor solutions to it - is expertly analyzed in "On Algorithmic Wage Discrimination," a superb paper by UC Law San Franciscos #VeenaDubal:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4331080
Dubal uses empirical data and enthnographic accounts from Uber drivers and other gig workers to explain how endless, self-directed twiddling allows gig companies pay workers less and pay themselves more.
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As @brianmerchant explains in his #LATimes article on Dubal's research, the goal of the payment algorithm is to guess how often a given driver needs to receive fair compensation in order to keep them driving when the payments are *unfair*:
https://www.latimes.com/business/technology/story/2023-04-11/algorithmic-wage-discrimination
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The algorithm combines nonconsensual dossiers compiled on individual drivers with population-scale data to seek an equilibrium between keeping drivers waiting, unpaid, for a job; and how much a driver needs to be paid for an individual job, in order to keep that driver from clocking out and doing something else.
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Here's how that works. Sergio Avedian, a writer for #TheRideshareGuy, ran an experiment with two brothers who both drove for Uber; one drove a Tesla and drove intermittently, the other brother rented a hybrid sedan and drove frequently. Sitting side-by-side with the brothers, Avedian showed how the brother with the Tesla was offered more for every trip:
https://www.youtube.com/watch?v=UADTiL3S67I
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Uber wants to lure intermittent drivers into becoming frequent drivers. Uber doesn't pay for an oversupply of drivers, because it only pays drivers when they have a passenger in the car. Having drivers on call - but idle - is a way for Uber to shift the cost of maintaining a capacity cushion to its workers.
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What's more, what Uber charges *customers* is not based on how much it pays its workers. As Uber's head of product explained: Uber uses "machine-learning techniques to estimate how much groups of customers are willing to shell out for a ride. Uber calculates riders’ propensity for paying a higher price for a particular route at a certain time of day.
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"For instance, someone traveling from a wealthy neighborhood to another tony spot might be asked to pay more than another person heading to a poorer part of town, even if demand, traffic and distance are the same."
Uber has historically described its business a pure supply-and-demand matching system, where a rush of demand for rides triggers #SurgePricing, which lures out drivers, which takes care of the demand.
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This sounds like the operational conditioning system of "Pigeons with Intermittent Rewards" but for exploitive jobs
https://medium.com/invisible-illness/what-pigeons-can-teach-you-about-expectations-6ea4816655a4
Two experiments were conducted demonstrating that under certain conditions pigeons may peck at a higher rate on a key that produces intermittent reinforcement following a delay than on one that always produces reinforcement following the same delay duration. ...
Cory Doctorow
Nicole Parsons
pete_hardie