Big Tech joins the race to build the world’s heaviest airplane
I'm at the end of my tour for my new book, the international bestseller Enshittification. My last two stops are CCC in Hamburg, Dec 27-30 and the Tattered Cover in Denver (Jan 22). Hope to see you!
I have a weird fascination with early-stage Bill Gates, after his mother convinced a pal of hers – chairman of IBM's board of directors – to give her son the contract to provide the operating system for the new IBM PC. Gates and his pal Paul Allen tricked another programmer into selling them the rights to DOS, which they sold to IBM, setting Microsoft on the path to be one of the most profitable businesses in human history.
IBM could have made its own OS, of course. They were just afraid to, because they'd just narrowly squeaked out of a 12-year antitrust war with the Department of Justice (evocatively memorialized as "Antitrust's Vietnam"):
The US government traumatized IBM so badly that they turned over their crown jewels to these two prep-school kids, who scammed a pal out of his operating system for $50k and made billions from it. Despite owing his business to IBM (or perhaps because of this fact), Gates routinely mocked IBM as a lumbering dinosaur that was headed for history's scrapheap. He was particularly scornful of IBM's software development methodology, which, to be fair, was pretty terrible: IBM paid programmers by the line of code. Gates called this "the race to build the world's heaviest airplane."
After all, judging software by lines of code is a terrible idea. To the extent that "number of lines of code" has any correlation with software quality, reliability or performance, it has a negative correlation. While it's certainly possible to write software with too few lines of code (e.g. when instructions are stacked on a single line, obfuscating its functionality and making it hard to maintain), it's far more common for programmers to use too many steps to solve a problem. The ideal software is just right: verbose enough to be legible to future maintainers, streamlined enough to omit redundancies.
This is broadly true of many products, and not just airplanes. Office memos should be long enough to be clear, but no longer. Home insulation should be sufficient to maintain the internal temperature, but no more.
Ironically, enterprise tech companies' bread and butter is selling exactly this kind of qualitative measurements for bosses who want an easy, numeric way to decide which of their workers to fire, and leading the pack is Microsoft, whose flagship Office365 lets bosses assess their workers' performance on meaningless metrics like how many words they type, ranking each worker against other workers within the division, with rival divisions and within rival firms. Yes, Microsoft actually boasts to companies about the fact that if you use their products, they will gather sensitive data about how your workers perform individually and as a team, and share than information with your competitors!
But while tech companies employed programmers to develop this kind of bossware to be used on other companies' employees, they were loathe to apply them to their own workers. For one thing, it's just a very stupid way to manage a workforce, as Bill Gates himself would be the first to tell you (candidly, provided he wasn't trying to sell you an enterprise Office 365 license). For another, tech workers wouldn't stand for it. After all, these were the "princes of labor," each adding a million dollars or more to their boss's bottom line, and in such scarce supply that a coder could quit a job after the morning scrum and have a new one by the pre-dinner pickleball break:
Tech workers mistook the fear this dynamic instilled in their bosses for respect. They thought the reason their bosses gave them free massage therapists and kombucha on tap and a gourmet cafeteria was that their bosses liked them. After all, these bosses were all techies. A coder wasn't a worker, they were a temporarily embarrassed founder. That's why Zuck and Sergey tuned into those engineering town hall meetings and tolerated being pelted with impertinent questions about the company's technology and business strategy.
Actually, tech bosses didn't like tech workers. They didn't see them as peers. They saw them workers. Problem workers, at that. Problems to be solved.
And wouldn't you know it, supply caught up with demand and tech companies instituted a program of mass layoffs. When Google laid off 12,000 workers (just before a $80b stock buyback that would have paid their wages for 27 years), they calmed investors by claiming that they weren't doing this because business was bad – they were just correcting some pandemic-era overhiring. But Google didn't just fire junior programmers – they targeted some of their most senior (and thus mouthiest and highest-paid) techies for the chop.
Today, Sergey and Zuck no longer attend engineering meetings ("Not a good use of my time" -M. Zuckerberg). Tech workers are getting laid off at the rate of naughts. And none of these bastards can shut up about how many programmers they plan on replacing with AI:
And wouldn't you know it, the shitty monitoring and ranking technology that programmers made to be used on other workers is finally being used on them:
Naturally, the excuse is monitoring AI usage. Microsoft – along with all the other AI-peddling tech companies – keep claiming that their workers adore using AI to write software, but somehow, also have to monitor workers so they can figure out which ones to fire because they're not using AI enough:
This is the "shitty technology adoption curve" in action. When you have a terrible, destructive technology, you can't just deploy it on privileged people who get taken seriously in policy circles. You start with people at the bottom of the privilege gradient: prisoners, mental patients, asylum-seekers. Then, you work your way up the curve – kids, gig workers, blue collar workers, pink collar workers. Eventually, it comes for all of us:
As Ed Zitron writes, tech hasn't had a big, successful product (on the scale of, say, the browser or the smartphone) in more than a decade. Tech companies have seemingly run out of new trillion-dollar industries to spawn. Tech bosses are pulling out all the stops to make their companies seem as dynamic and profitable as they were in tech's heyday.
Firing workers and blaming it on AI lets tech bosses transform a story that would freak out investors ("Our business is flagging and we had to fire a bunch of valuable techies") into one that will shake loose fresh billions in capital ("Our AI product is so powerful it let us fire a zillion workers!").
And for tech bosses, mass layoffs offer another, critical advantage: pauperizing those princes of labor, so that they can shed their company gyms and luxury commuter busses, cut wages and benefits, and generally reset the working expectations of the tech workers who sit behind a keyboard to match the expectations of tech workers who assemble iPhones, drive delivery vans, and pack boxes in warehouses.
For tech workers who currently don't have a pee bottle or a suicide net at their job-site, it's long past time to get over this founder-in-waiting bullshit and get organized. Recognize that you're a worker, and that workers' only real source of power isn't ephemeral scarcity, it's durable solidarity:
https://techworkerscoalition.org/
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:
Checking in on the state of Amazon’s chickenized reverse-centaurs
I'm on a tour with my new book, the international bestseller Enshittification: catch me next in Vancouver, Montreal, Ottawa! Full schedule here (New dates just added in San Diego and Denver!).
Amazon has invented a new kind of labor travesty: the chickenized reverse centaur. That's a worker who has to foot the bill to outfit a work environment where they nevertheless have no autonomy (chickenization) and whose body is conscripted to act as a peripheral for a digital system (reverse centaur):
"Chickenization" is a term out of labor economics, inspired by the brutal state of the poultry industry, where three giant processing companies have divided up the market so that every chicken farmer has just one place where they can sell their birds. To sell your birds to one of these plants, you have to give them total control over your operation. They sell you the baby chicks, they tell you what kind of coop to build and what lightbulbs to install and when they should be off or on. They tell you which vet to use and which medicines can be administered to your birds. They tell you what to feed your birds and when to feed them. They design your coop and tell you who is allowed to maintain it. The one thing they don't tell you is how much you'll be paid for your birds – that's something you only discover when it's time to sell them, and the sum you're offered is based on the packer's region-wide intelligence on how you and all your competitors are faring, and is calculated to be the smallest amount to allow you to roll over your loans and go into more debt to grow more birds for them.
At its root, "chickenization" is about de-risking, cloaked in the language of entrepreneurship. Chicken farmers assume all the risk for the poultry packers, but they're told that they're their own bosses. The only way in which a chicken farmer resembles an entrepreneur is that they have to bear all the risk of failure – without having any upside for success. Packers can (and do) secretly decide to experiment at farmers' expense, ordering some of their farmers to vary their feeding, light and veterinary routines to see if they can eke new efficiencies out of the process. If that works, the surplus is reaped by the packer. If that fails, the losses are borne by the farmer, who is never told that they were funding an experiment.
Amazon makes extensive use of chickenization in its many commercial arrangements, tightly defining the working conditions of many "self-employed" workers, like the clickwork "turkers" who power the Mechanical Turk service. But the most chickenized of all the people in Amazon's network of cutouts and arm's-length arrangements are the "entrepreneurs" who are lured into starting a "Delivery Service Platform" (DSP) business.
To start a DSP, you borrow lots of money to buy vans that you outfit to Amazon's exacting specifications, filling them with interior and exterior sensors and cameras, painting them with Amazon livery, and kitting them out with shelving and other infrastructure to Amazon's exacting specification. Then, you hire workers – giving Amazon a veto over who you hire – and you train them – using Amazon's training materials. You sign them up for Amazon's platforms, which monitor and rank those workers, and then you get paid either $0.10 per parcel, or maybe $0.50 per parcel, or sometimes $0.00 per parcel, all at Amazon's sole discretion.
That's a pretty chickenized arrangement. But what about reverse centaurs?
In automation theory, a "centaur" is someone who is assisted by some automation system (they are a fragile human head being assisted by a tireless machine). Therefore, a reverse centaur is a person who has been conscripted to serve as a peripheral for a machine, a human body surmounted and directed by a brute and uncaring head that not only uses them, but uses them up.
The drivers that DSPs hire are reverse centaurs. Using various forms of automation, Amazon drives these workers to work at a dangerous, humiliating and unsustainable pace, setting and enforcing not just quotas, but also scripting where drivers' eyes must be pointed, how they must accelerate and decelerate, what routes they take, and more. These edicts are enforced by the in-van and on-body automation systems that direct and discipline workers, tools that labor activists call "electronic whips":
The chickenized owners of DSPs must enforce the edicts Amazon brings down on their reverse centaur workers – Amazon can terminate any DSP, at any time, for any reason or no reason, stranding an "independent entrepreneur" with heavily mortgaged rolling stock that can only be used to deliver Amazon packages, long term leases on garages and parking lots, liability for driver accidents caused by automation systems that punish drivers for e.g. braking suddenly if someone steps into the road, and massive loans.
So when Amazon directs a DSP to fire or discipline a worker, that worker is in trouble. Amazon has hybridized chickenization and reverse centaurism, creating a chickenized reverse centaur, a new kind of labor travesty never seen before.
In "Driven Down," a new report from the DAIR Institute, authors Adrienne Williams, Alex Hanna and Sandra Barcenas draw on interviews with DSP drivers and Williams's own experience driving for Amazon to document the state of the Chickenized Reverse Centaur. It's not good:
"Driven Down" vividly describes – often in drivers' own words – how the life of a chickenized reverse centaur is one of wage theft, privacy invasions, humilation and on-the-job physical risks, for drivers and the communities they drive in.
DSP drivers interact with multiple automation systems – at least nine apps that monitor, score and discipline them. These apps are supposed to run on employer-supplied phones, but these phones are frequently broken, and drivers face severe punishment if these apps aren't all running during their shifts. As a result, drivers routinely install these apps on their own phones, and must give them broad, far-reaching permissions, such that drivers' own phones are surveilling them for Amazon 24/7, whether or not they're on the clock. It's not just DSP owners who are chickenized – it's also drivers, footing the bill for their own electronic whips.
First and foremost, these apps tell the drivers where to go and how to get there. Drivers are dispatched to hundreds of stops per day, on a computer-generated route that is not vetted or sanity-checked by a human before it is non-negotiably handed to a driver. Famously, plotting an efficient route among many points is one of the most insoluble computing problems, the so-called "traveling salesman" problem:
But it turns out that there is an optimal solution to the traveling salesman problem: get a computer to make a bizarre and dangerous approximation of the optimal route, and then blame and fine workers when it doesn't work. This doesn't optimize the route, but it does shift all the costs of a suboptimal route to workers.
Crucially, Amazon trusts its computer-generated routes, based on map data, over the word of drivers. For example, drivers are often directed to make "group stops" – where the driver parks the van and then delivers to multiple addresses at once (for example, at an apartment complex or office block). Amazon's mapping service assumes that addresses that are in the same complex or development are close together, even when they are very distant. If a driver dares to move and re-park their van to deliver parcels to distant addresses, the app punishes them for making an unauthorized positional adjustment. If a driver attempts to deliver all the parcels without moving the van, they are penalized for taking too long. Even if drivers report the mapping error, it persists, resulting in strings of infractions, day after day.
When drivers fail to make quota, the DSP's per-parcel payout is reduced. DSPs whose drivers perfectly obey the (irrational, impossible) orders of Amazon's apps get $0.50 per parcel delivered. If drivers fall short of the apps' expectations, the per parcel-rate can fall to $0.10, or, in some cases, zero.
This provides a powerful incentive to DSPs to pressure drivers to engage in unsafe practices if the alternative would displease the app. Drivers are penalized for sudden braking and swerving, for example, but are also penalized for missing quota, which puts drivers in the impossible position of having to drive as quickly as possible but also not to swerve or brake if a sudden traffic hazard pops up. In one absurd tale, a driver describes how they were shifted to an electric van that did regenerative braking when they released the accelerator. The app expected drivers to slow down by releasing the accelerator, not by touching the brakes, but this meant that the van's brake lights never switched on. When a driver slowed at a yellow light, they were badly rear-ended by a following UPS truck, whose driver had assumed the Amazon DSP driver was going to rush the light (because the van's brake lights didn't light up).
Meeting quota means that drivers are also not able to stop for bathroom breaks or to take car of other personal hygiene matters. This is bad enough when it means peeing in a bottle, but it's even worse when the only way to take care of period-related matters is to go into the back of the van – where cameras record everything you do – and manage things there.
Drivers are told many inconsistent things about those cameras. Some drivers have been told that the footage is only reviewed after an accident or complaint, but when drivers do get into accidents or have complaints lodged against them, they are often fired or disciplined without anyone reviewing the footage. Meanwhile, drivers are sometimes punished for things the cameras have recorded even when there was no complaint or accident.
The existence of all that empirical evidence of things happening in and outside an Amazon DSP van makes little to no difference to drivers' employment fairness. When a malfunctioning seatbelt sensor insists that a driver has removed their seatbelt while driving, 80+ times in a single shift, the driver struggled to get their docked wages or lost jobs back. When a driver swerved to avoid an oncoming big rig whose driver had fallen asleep and drifted across the media, the driver was penalized – the driver this happened to had his score in "Mentor" (one of the many apps) docked from 850 to 650. Amazon won't tell drivers what their Mentor scores mean, but many drivers – and DSP owners – believe than anything less than a perfect score will result in punishment or termination.
Attaining and maintaining a perfect score is an impossible task, because Amazon will not disclose what drivers are expected to do – it will only penalize them when they fail to do it. Take the photos that Amazon drivers are expected to snap of parcels after they are delivered. The criteria for these photos is incredibly strict – and also not disclosed. Drivers are penalized for having their hands or shoes or reflections in the image, for capturing customers or their pets, for capturing the house-number. They aren't allowed to photograph shoes that are left on the doormat. Drivers share tips with one another about how to take a picture without losing points, but it's a moving target.
Among drivers, there's a (likely correct) belief that Amazon will not tell them how the apps are generating their scores out of fear that if drivers knew the scoring rubric, they'd start to game it. This is a widespread practice within the world of content moderation and spamfighting, where security practitioners who would normally reject the idea of "security through obscurity" out of hand suddenly embrace secrecy-dependent security measures:
All this isn't just dangerous and dehumanizing, it's also impoverishing. Drivers who get downranked by these imperious and unaccountable and unexplained algorithms have their hours cut or get fired altogether. The apps set a quota that can't possibly be reached if drivers take their mandated (and unpaid) 30 minute lunch and two 15-minute breaks (drivers who miss quota twice are automatically terminated). This time is given over to unpaid labor. As the report explains:
Drivers are not paid for their 30 minute lunch. A full-time employee working an 8 to 10 hour shift would be working either 4 or 5 days out of each week. At $20 an hour, that is two hours a week for four-day employees, resulting in $40 of unpaid labor a week, $160 a month, almost $2,000 a year.
Drivers are also assigned "homework" – videos they are required watch and simulator exercises they are required to complete as remediation for their real or imagined infractions. This, too, is unpaid, mandatory work. Drivers are required to attend "stand up" meetings at the start of their shifts, and this is also often unpaid work.
Amazon makes a big show of "listening to drivers," but they're never heard. A driver who reported being held at gunpoint by literal Nazis who objected to having their parcels delivered by a Jew had his complaints ignored, and those violent, armed Nazi customers continued to get their parcels delivered.
Even modest requests go unanswered. Drivers for one DSP begged for porta-toilets in the parking lot, rather than having to waste time (and miss quota) legging it to a distant bathroom. They were ignored, and all 50 drivers continue to share a single toilet.
But – thanks to chickenization – none of this is Amazon's problem. It's all the problem of a chickenized DSP "entrepreneur" who serves as a useful accountability sink for Amazon and who can be bankrupted at a moment's notice should they fail to do Amazon's precise bidding.
There's one bright spot here, though: the National Labor Relations Board has brought a case in California seeking to have Amazon held to be a "joint employer" of those reverse centaurs behind the wheels of those vans:
This is the very last residue of the NLRB's authority, the rest having been drained away by Trump as part of Project 2025. If they prevail, it will open the door to drivers suing Amazon for unfair labor practices under both federal and state law – and in California and New York, that labor law just got a lot tougher for Amazon:
The chickenized reverse centaur is a new circle of labor hell, a genuinely innovative way of making workers' lives worse in order to extract more billions for one of the most profitable companies in history.
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:
You can get into a lot of trouble by assuming that rich people know what they're doing. For example, might assume that ad-tech works – bypassing peoples' critical faculties, reaching inside their minds and brainwashing them with Big Data insights, because if that's not what's happening, then why would rich people pour billions into those ads?
You might assume that private equity looters make their investors rich, because otherwise, why would rich people hand over trillions for them to play with?
The truth is, rich people are suckers like the rest of us. If anything, succeeding once or twice makes you an even bigger mark, with a sense of your own infallibility that inflates to fill the bubble your yes-men seal you inside of.
Rich people fall for scams just like you and me. Anyone can be a mark. I was:
But though rich people can fall for scams the same way you and I do, the way those scams play out is very different when the marks are wealthy. As Keynes had it, "The market can remain irrational longer than you can remain solvent." When the marks are rich (or worse, super-rich), they can be played for much longer before they go bust, creating the appearance of solidity.
Noted Keynesian John Kenneth Galbraith had his own thoughts on this. Galbraith coined the term "bezzle" to describe "the magic interval when a confidence trickster knows he has the money he has appropriated but the victim does not yet understand that he has lost it." In that magic interval, everyone feels better off: the mark thinks he's up, and the con artist knows he's up.
Rich marks have looong bezzles. Empirically incorrect ideas grounded in the most outrageous superstition and junk science can take over whole sections of your life, simply because a rich person – or rich people – are convinced that they're good for you.
Take "scientific management." In the early 20th century, the con artist Frederick Taylor convinced rich industrialists that he could increase their workers' productivity through a kind of caliper-and-stopwatch driven choreographry:
Taylor and his army of labcoated sadists perched at the elbows of factory workers (whom Taylor referred to as "stupid," "mentally sluggish," and as "an ox") and scripted their motions to a fare-the-well, transforming their work into a kind of kabuki of obedience. They weren't more efficient, but they looked smart, like obedient robots, and this made their bosses happy. The bosses shelled out fortunes for Taylor's services, even though the workers who followed his prescriptions were less efficient and generated fewer profits. Bosses were so dazzled by the spectacle of a factory floor of crisply moving people interfacing with crisply working machines that they failed to understand that they were losing money on the whole business.
To the extent they noticed that their revenues were declining after implementing Taylorism, they assumed that this was because they needed more scientific management. Taylor had a sweet con: the worse his advice performed, the more reasons their were to pay him for more advice.
Taylorism is a perfect con to run on the wealthy and powerful. It feeds into their prejudice and mistrust of their workers, and into their misplaced confidence in their own ability to understand their workers' jobs better than their workers do. There's always a long dollar to be made playing the "scientific management" con.
Today, there's an app for that. "Bossware" is a class of technology that monitors and disciplines workers, and it was supercharged by the pandemic and the rise of work-from-home. Combine bossware with work-from-home and your boss gets to control your life even when in your own place – "work from home" becomes "live at work":
Gig workers are at the white-hot center of bossware. Gig work promises "be your own boss," but bossware puts a Taylorist caliper wielder into your phone, monitoring and disciplining you as you drive your wn car around delivering parcels or picking up passengers.
In automation terms, a worker hitched to an app this way is a "reverse centaur." Automation theorists call a human augmented by a machine a "centaur" – a human head supported by a machine's tireless and strong body. A "reverse centaur" is a machine augmented by a human – like the Amazon delivery driver whose app goads them to make inhuman delivery quotas while punishing them for looking in the "wrong" direction or even singing along with the radio:
Bossware pre-dates the current AI bubble, but AI mania has supercharged it. AI pumpers insist that AI can do things it positively cannot do – rolling out an "autonomous robot" that turns out to be a guy in a robot suit, say – and rich people are groomed to buy the services of "AI-powered" bossware:
For an AI scammer like Elon Musk or Sam Altman, the fact that an AI can't do your job is irrelevant. From a business perspective, the only thing that matters is whether a salesperson can convince your boss that an AI can do your job – whether or not that's true:
The fact that AI can't do your job, but that your boss can be convinced to fire you and replace you with the AI that can't do your job, is the central fact of the 21st century labor market. AI has created a world of "algorithmic management" where humans are demoted to reverse centaurs, monitored and bossed about by an app.
The techbro's overwhelming conceit is that nothing is a crime, so long as you do it with an app. Just as fintech is designed to be a bank that's exempt from banking regulations, the gig economy is meant to be a workplace that's exempt from labor law. But this wheeze is transparent, and easily pierced by enforcers, so long as those enforcers want to do their jobs. One such enforcer is Alvaro Bedoya, an FTC commissioner with a keen interest in antitrust's relationship to labor protection.
Bedoya understands that antitrust has a checkered history when it comes to labor. As he's written, the history of antitrust is a series of incidents in which Congress revised the law to make it clear that forming a union was not the same thing as forming a cartel, only to be ignored by boss-friendly judges:
Bedoya is no mere historian. He's an FTC Commissioner, one of the most powerful regulators in the world, and he's profoundly interested in using that power to help workers, especially gig workers, whose misery starts with systemic, wide-scale misclassification as contractors:
In a new speech to NYU's Wagner School of Public Service, Bedoya argues that the FTC's existing authority allows it to crack down on algorithmic management – that is, algorithmic management is illegal, even if you break the law with an app:
Bedoya starts with a delightful analogy to The Hawtch-Hawtch, a mythical town from a Dr Seuss poem. The Hawtch-Hawtch economy is based on beekeeping, and the Hawtchers develop an overwhelming obsession with their bee's laziness, and determine to wring more work (and more honey) out of him. So they appoint a "bee-watcher." But the bee doesn't produce any more honey, which leads the Hawtchers to suspect their bee-watcher might be sleeping on the job, so they hire a bee-watcher-watcher. When that doesn't work, they hire a bee-watcher-watcher-watcher, and so on and on.
For gig workers, it's bee-watchers all the way down. Call center workers are subjected to "AI" video monitoring, and "AI" voice monitoring that purports to measure their empathy. Another AI times their calls. Two more AIs analyze the "sentiment" of the calls and the success of workers in meeting arbitrary metrics. On average, a call-center worker is subjected to five forms of bossware, which stand at their shoulders, marking them down and brooking no debate.
For example, when an experienced call center operator fielded a call from a customer with a flooded house who wanted to know why no one from her boss's repair plan system had come out to address the flooding, the operator was punished by the AI for failing to try to sell the customer a repair plan. There was no way for the operator to protest that the customer had a repair plan already, and had called to complain about it.
Workers report being sickened by this kind of surveillance, literally – stressed to the point of nausea and insomnia. Ironically, one of the most pervasive sources of automation-driven sickness are the "AI wellness" apps that bosses are sold by AI hucksters:
The FTC has broad authority to block "unfair trade practices," and Bedoya builds the case that this is an unfair trade practice. Proving an unfair trade practice is a three-part test: a practice is unfair if it causes "substantial injury," can't be "reasonably avoided," and isn't outweighed by a "countervailing benefit." In his speech, Bedoya makes the case that algorithmic management satisfies all three steps and is thus illegal.
On the question of "substantial injury," Bedoya describes the workday of warehouse workers working for ecommerce sites. He describes one worker who is monitored by an AI that requires him to pick and drop an object off a moving belt every 10 seconds, for ten hours per day. The worker's performance is tracked by a leaderboard, and supervisors punish and scold workers who don't make quota, and the algorithm auto-fires if you fail to meet it.
Under those conditions, it was only a matter of time until the worker experienced injuries to two of his discs and was permanently disabled, with the company being found 100% responsible for this injury. OSHA found a "direct connection" between the algorithm and the injury. No wonder warehouses sport vending machines that sell painkillers rather than sodas. It's clear that algorithmic management leads to "substantial injury."
What about "reasonably avoidable?" Can workers avoid the harms of algorithmic management? Bedoya describes the experience of NYC rideshare drivers who attended a round-table with him. The drivers describe logging tens of thousands of successful rides for the apps they work for, on promise of "being their own boss." But then the apps start randomly suspending them, telling them they aren't eligible to book a ride for hours at a time, sending them across town to serve an underserved area and still suspending them. Drivers who stop for coffee or a pee are locked out of the apps for hours as punishment, and so drive 12-hour shifts without a single break, in hopes of pleasing the inscrutable, high-handed app.
All this, as drivers' pay is falling and their credit card debts are mounting. No one will explain to drivers how their pay is determined, though the legal scholar Veena Dubal's work on "algorithmic wage discrimination" reveals that rideshare apps temporarily increase the pay of drivers who refuse rides, only to lower it again once they're back behind the wheel:
This is like the pit boss who gives a losing gambler some freebies to lure them back to the table, over and over, until they're broke. No wonder they call this a "casino mechanic." There's only two major rideshare apps, and they both use the same high-handed tactics. For Bedoya, this satisfies the second test for an "unfair practice" – it can't be reasonably avoided. If you drive rideshare, you're trapped by the harmful conduct.
The final prong of the "unfair practice" test is whether the conduct has "countervailing value" that makes up for this harm.
To address this, Bedoya goes back to the call center, where operators' performance is assessed by "Speech Emotion Recognition" algorithms, a psuedoscientific hoax that purports to be able to determine your emotions from your voice. These SERs don't work – for example, they might interpret a customer's laughter as anger. But they fail differently for different kinds of workers: workers with accents – from the American south, or the Philippines – attract more disapprobation from the AI. Half of all call center workers are monitored by SERs, and a quarter of workers have SERs scoring them "constantly."
Bossware AIs also produce transcripts of these workers' calls, but workers with accents find them "riddled with errors." These are consequential errors, since their bosses assess their performance based on the transcripts, and yet another AI produces automated work scores based on them.
In other words, algorithmic management is a procession of bee-watchers, bee-watcher-watchers, and bee-watcher-watcher-watchers, stretching to infinity. It's junk science. It's not producing better call center workers. It's producing arbitrary punishments, often against the best workers in the call center.
There is no "countervailing benefit" to offset the unavoidable substantial injury of life under algorithmic management. In other words, algorithmic management fails all three prongs of the "unfair practice" test, and it's illegal.
What should we do about it? Bedoya builds the case for the FTC acting on workers' behalf under its "unfair practice" authority, but he also points out that the lack of worker privacy is at the root of this hellscape of algorithmic management.
He's right. The last major update Congress made to US privacy law was in 1988, when they banned video-store clerks from telling the newspapers which VHS cassettes you rented. The US is long overdue for a new privacy regime, and workers under algorithmic management are part of a broad coalition that's closer than ever to making that happen:
Workers should have the right to know which of their data is being collected, who it's being shared by, and how it's being used. We all should have that right. That's what the actors' strike was partly motivated by: actors who were being ordered to wear mocap suits to produce data that could be used to produce a digital double of them, "training their replacement," but the replacement was a deepfake.
With a Trump administration on the horizon, the future of the FTC is in doubt. But the coalition for a new privacy law includes many of Trumpland's most powerful blocs – like Jan 6 rioters whose location was swept up by Google and handed over to the FBI. A strong privacy law would protect their Fourth Amendment rights – but also the rights of BLM protesters who experienced this far more often, and with far worse consequences, than the insurrectionists.
The "we do it with an app, so it's not illegal" ruse is wearing thinner by the day. When you have a boss for an app, your real boss gets an accountability sink, a convenient scapegoat that can be blamed for your misery.
The fact that this makes you worse at your job, that it loses your boss money, is no guarantee that you will be spared. Rich people make great marks, and they can remain irrational longer than you can remain solvent. Markets won't solve this one – but worker power can.
Denise Prudhomme's bosses at Wells Fargo insisted that the in-person camaraderie of their offices warranted a mandatory return-to-office policy, but when she died at her desk in her Tempe, AZ office, no one noticed for four days.
That was in August. Now, Wells Fargo United has published a statement on her death, one that vibrates with anger at the callously selective surveillance that Wells Fargo inflicts on its workforce:
The union points out that Wells Fargo workers are subjected to continuous, fine-grained on-the-job surveillance from a variety of bossware tools that count their keystrokes and create tables of the distancess their mice cross each day:
Wells Fargo's message to its workforce is, "You can't be trusted," a policy that Wells Fargo doubled down on with its Return to Office mandate. Return to Office is often pitched as a chance to improve teamwork, communication, and human connection with your co-workers, and there's no arguing with the idea that spending some time in person with people can help improve working relationships (I attended a week-long, all-hands, staff retreat for EFF earlier this month and it was fantastic, primarily due to its in-person nature).
But our bosses don't want us back in the office because they enjoy our company, nor because they're so excited about having hired such a swell bunch of folks and can't wait to see how we all get along together. As John Quiggin writes, the biggest reason to force us back to the office is to get a bunch of us to quit:
As one of Musk's toadies put it in a private message before the Twitter takeover, "Sharpen your blades boys. 2 day a week Office requirement = 20% voluntary departures":
The other reason to spy on us is because they don't trust us. Remember all the panic about "quiet quitting" and "no one wants to work"? Bosses' hypothesis was that eking out a bare minimum living on from a couple of small-dollar covid stimulus checks was preferable to working for them for a full paycheck.
Every accusation is a a confession. When your boss tells you that he thinks that you can't be trusted to do a good job without total, constant surveillance, he's really saying, "I only bother to do my CEO job when I'm afraid of getting fired':
As Wells Fargo United notes, Wells Fargo employees like Denise Prudhomme are spied on from the moment they set foot in the building until the moment they clock out (and sometimes the spying continues when you're off the clock):
Wells Fargo monitors our every move and keystroke using remote, electronic technologies—purportedly to evaluate our productivity—and will fire us if we are caught not making enough keystrokes on our computers.
The Arizona Republic coverage notes further that Prudhomme had to log her comings and goings from the Wells Fargo offices with a badge, so Wells Fargo could see that Prudhomme had entered the premises four days before, but hadn't left:
Wells Fargo has mandated in-person working, even when that means crossing a state line to be closer to the office. They've created "hub cities" where workers are supposed to turn up. This may sound convivial, but Prudhomme was the only member of her team working out of the Tempe hub, so she was being asked to leave her home, travel long distances, and spend her days in a distant corner of the building where no one ventured for periods of (at least) four days at a time.
Bosses are so convinced that they themselves would goof off if they could that they fixate on forcing employees to spend their days in the office, no matter what the cost. Back in March 2020, Charter CEO Tom Rutledge – then the highest-paid CEO in America – instituted a policy that every back office staffer had to work in person at his call centers. This was the most deadly phase of the pandemic, there was no PPE to speak of, we didn't understand transmission very well, and vaccines didn't exist yet. Charter is a telecommunications company and it was booming as workers across America upgraded their broadband so they could work from home, and the CEO's response was to ban remote work. His customer service centers were superspreading charnel houses:
That Wells Fargo would leave a dead employee at her desk for four days is par for the course for the third-largest commercial bank in America. This is Wells Fargo, remember, the company that forced its low-level bank staff to open two million fake accounts in order to steal from their customers and defraud their shareholders, then fired and blackballed staff who complained:
It's not like Wells Fargo treats its workers badly but does well by everyone else. Remember, those fake accounts existed as part of a fraud on the company's investors. The company went on to steal $76m from its customers on currency conversions. They also foreclosed on customers who were up to date on their mortgages, seizing and selling off all their possessions. They argued that when bosses pressured tellers into forging customers on fraudulent account-opening paperwork, that those customers had lost their right to sue, since the fraudulent paperwork had a binding arbitration clause. When they finally agreed to pay restitution to their victims, they made the payments opt-in, ensuring that most of the millions of people they stole from would never get their money back.
They stole millions with fraudulent "home warranties." They stole millions from small businesses with fake credit-card fees. They defrauded 800,000 customers through an insurance scam, and stole 25,000 customers' cars with illegal repos. They led the pre-2008 pack on mis-selling deceptive mortgages that blew up and triggered the foreclosure epidemic. They loaned vast sums to Trump, who slashed their taxes, and then they fired 26.000 workers and did a $40.6B stock buyback. They stole 525 homes from mortgage borrowers and blamed it on a "computer glitch":
Given all this, two things are obvious: first, if anyone is going to be monitored for crimes, fraud and scams, it should be Wells Fargo, not its workers. Second, Wells Fargo's surveillance system exists solely to terrorize workers, not to help them. As Wells Fargo United writes:
We demand improved safety precautions that are not punitive or cause further stress for employees. The solution is not more monitoring, but ensuring that we are all connected to a supportive work environment instead of warehoused away in a back office.
Tor Books as just published two new, free LITTLE BROTHER stories: VIGILANT, about creepy surveillance in distance education; and SPILL, about oil pipelines and indigenous landback.
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:
The future of Amazon coders is the present of Amazon warehouse workers
I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me in BURBANK with WIL WHEATON TONIGHT (Mar 13), and in SAN DIEGO at MYSTERIOUS GALAXY on Mar 24. More tour dates here.
My theory of the "shitty technology adoption curve" holds that you can predict the future impact of abusive technologies on you by observing the way these are deployed against people who have less social power than you:
When you have a new, abusive technology, you can't just aim it at rich, powerful people, because when they complain, they get results. To successfully deploy that abusive tech, you need to work your way up the privilege gradient, starting with people with no power, like prisoners, refugees, and mental patients. This starts the process of normalization, even as it sands down some of the technology's rough edges against their tender bodies. Once that's done, you can move on to people with more social power – immigrants, blue collar workers, school children. Step by step, you normalize and smooth out the abusive tech, until you can apply it to everyone – even rich and powerful people. Think of the deployment of CCTV, facial recognition, location tracking, and web surveillance.
All this means that blue collar workers are the pioneering early adopters of the bossware that will shortly be tormenting their white-collar colleagues elsewhere in the business. It's as William Gibson prophesied: "The future is here, it's just not evenly distributed" (it's pooled up thick and noxious around the ankles of blue-collar workers, refugees, mental patients, etc).
Nowhere is this rule more salient than in Big Tech firms. Tech companies have thoroughly segregated workforces. Delivery drivers, customer service reps, data-labelers, warehouse workers and other "green badge," low-status workers are the testing ground for their employer's own disciplinary technology, which monitors them down to the keystroke, the eye-movement, and the pee break. Meanwhile, the "blue badge" white-collar coders get stock options, gourmet cafeterias, free massages, day care and complimentary egg-freezing so they can delay fertility. Companies like Google not only use separate entrance for their different classes of workers – they stagger their shifts so that the elite workers don't even see their lower-status counterparts.
Importantly, almost none of these workers – whether low-status or high – are unionized. Tech union density is so thin, it's almost nonexistent. It's easy to see why elite tech workers wouldn't bother with unionizing: with such fantastic wages and so many perks, why endure the tedium of meetings and memos? But then there's the rest of the workers, who are subjected to endless "electronic whipping" by bossware and who take home wages that look like pocket change when compared to the tech division's compensation. These workers have every reason to unionize, living as they do in the dystopian future of labor.
At Amazon warehouses, workers are injured at three times the rate of warehouse workers at competing firms. They are penalized for "time off task" (like taking a piss break). They are made to stand in long, humiliating body-search lines when they go on- and off-shift, hours every week, without compensation. Variations on this theme play out in other blue-collar sectors of the Amazon empire, like Amazon delivery drivers and Whole Food shelf-stockers.
Those workers have every reason to unionize, and they have done their damndest, but Amazon has defeated worker union drives, again and again. How does Amazon win these battles? Simple: they cheat. They illegally fire union organizers:
They spend millions on anti-union tech, spying on workers and creating "heatmaps" that let them direct their anti-union efforts to specific stores and facilities:
That's just the tip of the iceberg. A new investigation by Northwestern University's Teke Wiggin draws on worker interviews and FOIA requests to the NLRB to assemble a first-of-its-kind catalog of Amazon's labor-disciplining, union-busting tactics:
Disciplining labor and busting unions go hand in hand. It's a simple equation: the harder it is for your workers to form a union, the worse you can treat them without facing labor reprisals, because individual workers' options are limited to a) quitting or b) sucking it up, while unionized workers can grieve, sue, and strike.
At the core of Amazon's labor discipline technology is "algorithmic management," which is exactly what it sounds like: replacing middle managers with software that counts your keystrokes, watches your eyeballs, or applies a virtual caliper to some other metric to decide whether you're a good worker or a rotten apple:
Automation theory describes two poles of workplace automation: centaurs (in which workers are assisted by technology) and "reverse-centaurs" (in which workers provide assistance to technology):
Amazon is a reverse-centaurism pioneer. Take the delivery drivers whose every maneuver, eyeball movement, and turn signal is analyzed and inevitably, found wanting, as workers seek to satisfy impossible quotas that can't even be met if you pee in a bottle instead of taking toilet breaks:
Then there's the warehouse workers who are also tormented with impossible, pisscall-annihilating quotas. Some of these workers are fitted with haptic wristbands that buzz to tell them they're being too slow at picking up an item and dropping it into a box, pushing them to faster, joint-destroying paces that account for Amazon's enduring position as the most worker-maiming warehouse employer in the nation:
In his paper, Wiggin does important work connecting these "electronic whips" to Amazon's arsenal of traditional union-busting weapons, like "captive audience" meetings where workers are forced to sit through hours of anti-union indoctrination. For Wiggin, bossware tools aren't just a stick to beat workers with – they're also a carrot that can be used to diffuse a worker's outrage ahead of a key union vote.
Algorithmic management isn't just software that wrings more work out of workers – it's software that replaces managers. By surveilling workers – both on the job and in social media spaces (like subreddits) where workers gather to talk, Amazon can tune the "electronic whip," reducing quotas and easing the pace of work so that workers view their jobs more favorably and are more receptive to anti-union propaganda.
This is "twiddling" – exploiting the digital flexibility of a system to "twiddle the knobs" governing its business logic, changing everything from prices to wages, search rankings to recommendations, in realtime, for every customer and worker:
https://pluralistic.net/2023/02/19/twiddler/
Twiddling combines surveillance data with flexible business logic to create an unbeatable house advantage. If you're an Amazon shopper, you get twiddled all the time, as Amazon replaces the best matches for your searches with paid results. If you buy that first product result, you'll pay an average of 29% more than the best match for your search:
Worker-side twiddling is even more dystopian. When a nurse is assigned a shift by an "Uber for nurses" app, the app checks whether the worker has overdue credit card bills, which trigger lower wages (on the theory that an indebted worker is a desperate worker):
When it comes to union-busting, Amazon's found a new use for twiddling: lessening the pace of work, which Wiggin calls "algorithmic slack-cutting." The important thing about algorithmic slack-cutting is that it's only temporary. The algorithm that reduces your work-load in the runup to a union vote can then dial the pace of work up afterward, by small, random increments that are below the threshold at which they register on the human sensory apparatus. They're not so much boiling the frog as poaching it.
Meanwhile, Amazon gets to flood the zone with anti-union messages, including mandatory messages on the app that assigns your shifts – a captive audience meeting in every pocket.
Between social media surveillance and on-the-job surveillance, Amazon has built a powerful training set for algorithms designed to crush workplace democracy. That's how things go for Amazon's warehouse workers and delivery drivers, and the shelf-stockers at Whole Foods.
But of course, the picture is very different for Amazon's techies, who enjoy the industry standard of high wages and lavish perks.
For now.
The tech industry is in the midst of three years' worth of mass layoffs: 260K in 2023, 150k in 2024, tens of thousands this year. None of this is due to a shortfall in profits, mind: Google laid off 12,000 workers just weeks after staging a stock buyback that would have funded their salaries for 27 years. Meta just announced a 5% across-the-board headcount cut and that it was doubling its executive bonuses.
In other words, tech is firing workers not because it must, but because it can. When workers depend on scarcity – instead of unions – as a source of power, they dig their own graves. For well-paid, scarcity-based coders, every new computer science graduate is the enemy, eroding the scarcity that your wages depend on.
Amazon coders get to come to work with pink mohawks, facial piercings, and black t-shirts that say things their bosses don't understand. They get to pee whenever they want to. That's not because Jeff Bezos is sentimentally attached to techies and bears personal animus toward warehouse workers. Jeff Bezos wants to pay his workforce as little as he can. He treats his tech workers with respect because he's afraid of them, because if they quit, he can't replace them, and without their work, he can't make money.
Once there's an army of unemployed coders who'll take your job, Jeff Bezos doesn't have to fear you anymore. He can fire you and replace you the next day.
Bezos is obviously incredibly horny for this. Like most tech bosses, he dreams of a world in which entitled hackers can't call their bosses dumbshits and decline to frog when they shout "jump!" That's why Amazon PR puts so much energy into trumpeting the business's use of AI to replace coders:
It's not just that they're excited about firing coders and saving money – they're even more excited about transforming the job of "Amazon coder," from someone who solves complex technical problems to someone who performs tedious code review on automatically generated code barfed up by a chatbot:
"Code reviewer" is a much less fulfilling job than "programmer." Code reviewers are also easier to replace than programmers. A code reviewer is a reverse-centaur, a servant to the machine. Every time you hear "AI-assisted programmer," you should substitute "programmer-assisted AI."
Programming is even more bossware-ready than working in a warehouse. The machines coders use are much easier to fit with surveillance technology that monitors their performance – and spies on their communications, looking for dissenting chatter – than a warehouse floor. The only thing that stopped Jeff Bezos from treating his programmers like his warehouse workers is their scarcity. That scarcity is now going away.
That's bad news for Amazon customers, too. Tech workers often feel a sense of duty to their users, a "vocational awe" that drives them to put in long hours to make things their users will enjoy. The labor power of tech workers has long served as a check on the impulse to enshittify those products:
As tech workers' power wanes, they don't just lose the ability to protect themselves from their bosses' greediest, most sadistic urges – they also lose the power to defend all of us. Smart tech workers know this. That's why Amazon tech workers walked out in support of Amazon warehouse workers:
Wiggin's report isn't just a snapshot of Amazon warehouse workers' dystopian present – it's a promise of Amazon tech workers' future. The future is here, in Amazon warehouses, and every day, it's getting closer to Amazon's technical offices.
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:
Business school professors trained an AI to judge workers’ personalities based on their faces
I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me TODAY (Feb 17) for an event at KEPLER'S in MENLO PARK with CHARLIE JANE ANDERS and TOMORROW (Feb 18) for an event with WIL WHEATON in LA. More tour dates here.
Theory-free inference is a hell of a drug. For years, Big Data advocates – the larval form of today's AI weirdos – have insisted that if you have enough data, you can infer causal relationships between complex phenomena without ever having to understand how x causes y, and thus, we can slay the dread "correlation is not causation" beast.
This is cousin to Milton Friedman's famous economic catechism:
Truly important and significant hypotheses will be found to have "assumptions" that are wildly inaccurate descriptive representations of reality, and, in general, the more significant the theory, the more unrealistic the assumptions (in this sense)
AI turns out to be a great tool for creating plausible statistical correlates of imaginary phenomena. Remember the guy who claimed to have invented Machine Learning Gaydar by analyzing the faces of gay people and comparing them to straight people? Same dude later claimed to have invented an AI that could guess, from your face, whether you were a Republican or a Democrat:
This is just AI Phrenology, a continuation of the "scientific racism" movement that was invented to provide a justification for colonialism, slavery, genocide and eugenics. It imagines that there are invisible genetic traits that determine things like your ability to be a good boss, or whether you will cheat on your partner, or whether you are destined to be rich. It's a kind of cod-scientific astrology, where you get to declare yourself to have been born with "good blood" that destined you to rule over others.
Amazingly, this "scientific" philosophy has somehow managed to thrive after the rise of computational genomics, the science that analyzes population-scale genetic surveys to identify whether there is any genetic basis for the idea of "races" (and other cherished distinctions of the "human diversity" movement) have been shown to have no discernible basis in, you know, genetics.
As Adam Rutherford – a superb science communication and accomplished computational genomist – writes in his 2020 book How To Argue With a Racist, nearly everyone on Earth is descended from the same tiny group of survivors of a couple of severe genetic bottlenecks, the exception being Africa, where there is far more genetic diversity than in the rest of the world:
A Swede and an Australian Aboriginal person are more closely related than two members of the different groups of San people. If genes were the dispositive factors in human personality and accomplishment, we'd expect to see far more variance in the outcomes of African people than we do between, say, Inuit people and Italians. And yet, somehow people who all live in the same society, facing the same structural challenges of post-colonialism, international looting, and a global IP regime that denies them the ability to manufacture their own medicines and fix their own equipment produces people with remarkably similar outcomes. Meanwhile, it's surprisingly easy to predict the life outcomes of people from very different societies, based on those societies' position in the global hierarchy.
Sure, genetics play a role in shaping our outcomes. We are built out of the interactions between our genome and the physical and social world around us. But all evidence points to the social and physical factors grossly outweighing the genes. Back to astrology: distant celestial objects inarguably interact with us at our births and through our lives. Some infinitesimal tidal stress is exerted upon the Earth by other planets; photons streaming from faraway, long-dead stars shower down upon us. But the gravity exerted by, say, Saturn, on your body as you pass through the birth canal is less than the force exerted by the paper covers the midwife wears over her shoes in the birthing room. Sure, those disposable covers are a lot less massy than Saturn – but they're far closer, which matters when you're talking about forces that attenuate at the square of distance.
Genes play an important role in the development of your brain and the systems that regulate it, like hormones and nerve signals. But that role is clearly swamped by the role that the physical and social environment play as you grow up. You don't have "good blood" or "bad blood."
But people who believe in – and benefit from – social hierarchy have always yearned for a freestanding, objective basis for the fact that they have more and everyone else has less. That's the origin of "efficient markets hypothesis" (I'm rich because the market thinks I'm a good "capital allocater"), of "meritocracy" (if I'm rich, I must have merit), and "evolutionary psychology" ("Honey, it's not my fault I fucked my grad students – blame the bonobos!"):
Which brings me to this week's caliper-wielding AI: the "Photo Big 5" AI that can look at your face and predict whether you're going to be good at having an MBA:
This is the creation of four academics at elite institutions – however, their discipline isn't genetics. They're business school professors. They got a bunch of MBAs' self-assessed results on surveys of "Big 5 personality types" – itself a kind of astrological exercise with barely more rigor than, say, Meyers-Briggs – and then fed these results, along with the subjects' Linkedin profile photos and self-reported salaries and titles to an ML and produced – voila! – a machine that tells you whether you'll be a good manager based on your face!
This is an objectively very funny exercise, like AI Gaydar for middle-managers. They resort to some hilarious obfuscation:
Photo Big 5 exhibits only modest correlations with cognitive measures like GPA and standardized test scores, yet offers comparable incremental predictive power for labor outcomes.
In other words, we created a new random-number generator that is as bad at predicting your life-chances as the SATs or your GPA, two extremely bad ways of predicting your life chances – except to the extent that both numbers can be inflated if you start with a bunch of money and hire elite test-prep consultants. Good thing personal appearance has no correlates with wealth and there's no way to spend money to look more like a member of the elite? Naw, it must be the genetics underpinning the relationships between your "craniofacial features and behavior."
It's easy to see why AI is so tempting to people who want to incinerate any qualitative factors in a complex societal problem, transforming them into dubious quantitative residue that an algorithm can do math on:
It's junk science at scale, with a business model. The purpose of this automated eugenics is the same as every "rational" account of hierarchy in human history: to retroactively justify winners, and to condemn losers before the game even starts.
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:
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:
The Biden administration disappointed, frustrated and enraged in so many ways, including abetting a genocide – but one consistent bright spot over the past four years was the unseen-for-generations frontal assault on corporate power and corporate corruption.
The three words that define this battle above all others are "unfair and deceptive" – words that appear in Section 5 of the Federal Trade Commission Act and other legislation modeled on it, like USC40 Section 41712(a), which gives the Department of Transportation the power to ban "unfair and deceptive" practices as well:
When Congress created an agency to punish "unfair and deceptive" conduct, they were saying to the American people, "You have a right not to be cheated." While this may sound obvious, it's hardly how the world works.
To get a sense of how many ripoffs are part of our daily lives, let's take a little tour of the ways that the FTC and other agencies have used the "unfair and deceptive" standard to defend you over the past four years. Take Amazon Prime: Amazon executives emailed one another, openly admitting that in their user tests, the public was consistently fooled by Amazon's "get free shipping with Prime" dialog boxes, thinking they were signing up for free shipping and not understanding that they were actually signing up to send the company $140/year. They had tested other versions of the signup workflow that users were able to correctly interpret, but they decided to go with the confusing version because it made them more money:
Getting you signed up for Prime isn't just a matter of taking $140 out of your pocket once – because while Amazon has produced a greased slide that whisks you into a recurring Prime subscription, the process for canceling that recurring payment is more like a greased pole you must climb to escape the Prime pit. This is typical of many services, where signing up happens in a couple clicks, but canceling is a Kafkaesque nightmare. The FTC decided that this was an "unfair and deceptive" business practice and used its authority to create a "Click to Cancel" rule that says businesses have to make it as easy to cancel a recurring payment as it was to sign up for it:
Once businesses have you locked in, they also spy on you, ingesting masses of commercial surveillance data that you "consented" to by buying a car, or clicking to a website, or installing an app, or just physically existing in space. They use this to implement "surveillance pricing," raising prices based on their estimation of your desperation. Uber got caught doing this a decade ago, raising the price of taxi rides for users whose batteries were about to die, but these days, everyone's in on the game. For example, McDonald's has invested in a company that spies on your finances to determine when your payday is, and then raises the price of your usual breakfast sandwich by a dollar the day you get paid:
Everything about this is "unfair and deceptive" – from switching prices the second you click into the store to the sham of consent that consists of, say, picking up your tickets to a show and being ordered to download an app that comes with 20,000 words of terms and conditions that allows the company that sends you a QR code to spy on you for the rest of your life in any way they can and sell the data to anyone who'll buy it.
As bad as it is to be trapped in an abusive relationship as a shopper, it's a million times worse to be trapped as a worker. One in 18 American workers is under a noncompete "agreement" that makes it illegal for you to change jobs and work for someone else in the same industry. The vast majority of these workers are in low-waged food-service jobs. The primary use of the American noncompete is to stop the cashier at Wendy's from getting an extra $0.25/hour by taking a job at McDonald's.
Noncompetes are shrouded in a fog of easily dispelled bossly bullshit: claims that noncompetes raise wages (empirically, this is untrue), or that they enable "IP"-intensive industries to grow by protecting their trade secrets. This claim is such bullshit: you can tell by the fact that noncompetes are banned under California's state constitution and yet the most IP-intensive industries have attracted hundreds of billions – if not trillions – in investment capital even though none of their workforce can be bound under a noncompete. The FTC's order banning noncompetes for every worker in America simply brings the labor regime that created Silicon Valley and Hollywood to the rest of the country:
Noncompetes aren't the only "unfair and deceptive" practice used against American workers. The past decade has seen the rise of private equity consolidation in several low-waged industries, like pet grooming. The new owners of every pet grooming salon within 20 miles of your house haven't just slashed workers' wages, they've also cooked up a scheme that lets them charge workers thousands of dollars if they quit these shitty jobs. This scheme is called a "training repayment agreement provision" (TRAP!): workers who are TRAPped at Petsmart are made to work doing menial jobs like sweeping up the floor for three to four weeks. Petsmart calls this "training," and values it at $5,500. If you quit your pet grooming job in the next two years, you legally owe PetSmart $5,500 to "repay" them for the training:
Workers are also subjected to "unfair and deceptive" bossware: "AI" tools sold to bosses that claim they can sort good workers from bad, but actually serve as random-number generators that penalize workers in arbitrary, life-destroying ways:
Some of the most "unfair and deceptive" conduct we endure happens in shadowy corners of industry, where obscure middlemen help consolidated industries raise prices and pick your pocket. All the meat you buy in the grocery store comes from a cartel of processing and packing companies that all subscribe to the same "price consulting" services that tells them how to coordinate across-the-board price rises (tell me again how greedflation isn't a thing?):
It's not just food, it's all of Maslow's Hierarchy of Needs. Take shelter: the highly consolidated landlord industry uses apps like Realpage to coordinate rental price hikes, turning the housing crisis into a housing emergency:
And of course, health is the most "unfair and deceptive" industry of all. Useless middlemen like "Pharmacy Benefit Managers" ("a spreadsheet with political power" -Matt Stoller) coordinate massive price-hikes in the drugs you need to stay alive, which is why Americans pay substantially more for medicine than anyone else in the world, even as the US government spends more than any other to fund pharma research, using public money:
It's not just drugs: every piece of equipment – think hospital beds and nuclear medicine machines – as well as all the consumables – from bandages to saline – at your local hospital runs through a cartel of "Group Purchasing Organizations" that do for hospital equipment what PBMs do for medicine:
For the past four years, we've lived in an America where a substantial portion of the administrative state went to war every day to stamp out unfair and deceptive practices. It's still happening: yesterday, the CFPB (which Musk has vowed to shut down) proposed a new rule that would ban the entire data brokerage industry, who nonconsensually harvest information about every American, and package it up into categories like "teenagers from red states seeking abortions" and "military service personnel with gambling habits" and "seniors with dementia" and sell this to marketers, stalkers, foreign governments and anyone else with a credit-card:
And on the same day, the FTC banned the location brokers who spy on your every movement and sell your past and present location, again, to marketers, stalkers, foreign governments and anyone with a credit card:
These are tantalizing previews of a better life for every American, one in which the rule is, "play fair." That's not the world that Trump and his allies want to build. Their motto isn't "cheaters never prosper" – it's "caveat emptor," let the buyer beware.
Remember the 2016 debate where Clinton accused Trump of cheating on his taxes and he admitted to it, saying "That makes me smart?" Trumpism is the movement of "that makes me smart" life, where if you get scammed, that's your own damned fault. Sorry, loser, you lost.
Nowhere do you see this more than in cryptocurrencyland, so it's not a coincidence that tens – perhaps hundreds – in dark crypto money was flushed into the election, first to overpower Democratic primaries and kick out Dem legislators who'd used their power to fight the "unfair and deceptive" crowd:
And then to fight Dems across the board (even the Dems whose primary victories were funded by dark crypto money) and elect the GOP as the party of "caveat emptor"/"that makes me smart":
Crypto epitomizes the caveat emptor economy. By design, fraudulent crypto transactions can't be reversed. If you get suckered, that's canonically a you problem. And boy oh boy, do crypto users get suckered (including and especially those who buy Trump's shitcoins):
https://www.web3isgoinggreat.com/
And for crypto users who get ripped off because they've parked their "money" in an online wallet, there's no sympathy, just "not your keys, not your coins":
A cornerstone of the "unfair and deceptive" world is that only suckers – that is, outsiders, marks and little people – have to endure consequences when they get rooked. When insiders get ripped off, all principle is jettisoned. So it's not surprising that when crypto insiders got taken for millions the first time they created a DAO, they tore up all the rules of the crypto world and gave themselves the mulligan that none of the rest of us are entitled to in cryptoland:
Where you find crypto, you find Elon Musk, the guy who epitomizes caveat emptor thinking. This is a guy who has lied to drivers to get them to buy Teslas by promising "full self driving in one year," every year, since 2015:
Musk told investors that he had a "prototype" autonomous robot that could replace their workers, then demoed a guy in a robot suit, pretending to be a robot:
This is entirely typical of the AI sector, in which "AIs" are revealed, over and over, to be low-waged workers pretending to be robots, so much so that Indian tech industry insiders joke that "AI" stands for "Absent Indians":
Musk's view is that he's not a liar, merely a teller of premature truths. Autonomous cars and robots are just around the corner (just like the chatbots that can do your job, and not merely convince your boss to fire you while failing to do your job). He's not tricking you, he's just faking it until he makes it. It's not a scam, it's inspirational. Of course, if he's wrong and you are scammed, well, that's a you problem. Caveat emptor. That makes him smart.
Musk does this all the time. Take the Twitter blue tick, originally conceived of as a way to keep Twitter users from being scammed ("unfair and deceptive") by con artists pretending to be famous people. Musk's inaugural act at Twitter was to take away blue ticks from verified users and sell them to anyone who'd pay $8/month. Almost no one coughed up for this – the main exception being scammers, who used their purchased, unverified blue ticks to steal from Twitter users ("that makes me smart").
As Twitter hemorrhaged advertising revenue and Musk became increasingly desperate to materialize an army of $8/month paid subscribers, he pulled another scam: he nonconsensually applied blue ticks to prominent accounts, in a bid to trick normies into thinking that widely read people valued blue ticks so much they were paying for them out of their own pockets:
https://www.bbc.com/news/technology-65365366
If you were tricked into buying a blue tick on this pretense, well, caveat emptor. Besides, it's not a lie, it's a premature truth. Someday all those widely read users with nonconsensual blue ticks will surely value them so highly that they do start to pay for them. And if they don't? Well, Musk got your $8: "that makes me smart."
Scammers will always tell you that they're not lying to you, merely telling premature truths. Sam Bankman-Fried's defenders will tell you that he didn't actually steal all those billions. He gambled them on a bet that (sorta-kinda) paid off. Eventually, he was able to make all his victims (sorta-kinda) whole, so it's not even a theft:
Likewise, Tether, a "stablecoin" that was unable to pass an audit for many years as it issued unbacked, unregulated securities while lying and saying that for every dollar they minted, they had a dollar in reserves. Tether now (maybe) has reserves to equal its outstanding coins, so obviously all those years where they made false claims, they weren't lying, merely telling a premature truth:
If Tether had failed a margin call during those years and you'd lost everything, well, caveat emptor. The Tether insiders were always insulated from that risk, and that's all that matters: "that makes me smart."
When I think about the next four years, this is how I frame it: the victory of "that makes me smart" over "fairness and truth."
For years, progressives have pointed out the right's hypocrisy, despite that fact that Americans have been conditioned to be so cynical that even the rankest hypocrisy doesn't register. But "caveat emptor?" That isn't just someone else's bad belief or low ethics: it's the way that your life is materially, significantly worsened. The Biden administration – divided between corporate Dems and the Warren/Sanders wing that went to war on "unfair and deceptive" – was ashamed and nearly silent on its groundbreaking work fighting for fairness and honesty. That was a titanic mistake.
Americans may not care about hypocrisy, but they really care about being stolen from. No one wants to be a sucker.
