Your boss wants to use surveillance data to cut your wages
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:
What industry calls "personalized pricing" is really surveillance pricing: using digital tools' flexibility to change the price for each user, and using surveillance data to guess the worst price you'll accept:
At root, surveillance pricing allows companies to revalue both your savings and your labor. If you get charged $2 for something I only pay $1 for, the seller is essentially reaching into your bank account and revaluing the dollars in it at 50 cents apiece. If you get paid $1 for a job that I make $2 for, then the boss is valuing your labor at 50% of my labor:
Surveillance pricing is a key part of enshittification, relying on three of the key enshittificatory factors that have transformed this era into the enshittocene:
I. Monopoly: Surveillance pricing is undesirable to both workers and buyers, so in a competitive market, surveillance pricing would drive labor and consumption to non-surveilling rivals:
II. Regulatory capture: Surveillance pricing only exists because of weak regulation and weak enforcement of existing regulations. To engage in surveillance pricing, a company must first put you under surveillance, something that is only possible in the absence of effective privacy law.
In the USA, privacy law hasn't been updated since Congress passed a law in 1988 that banned video-store clerks from disclosing your VHS rentals:
In the EU, the strong privacy provisions in the GDPR have been neutralized by US tech giants who fly an Irish flag of convenience. Ireland attracts these companies by allowing them to evade their taxes, but it can only keep these companies by allowing them to break any law that gets in their way, because if Meta can pretend to be Irish this week, it could pretend to be Maltese (or Cypriot, Luxembourgeois, or Dutch) next week:
What's more, competition laws in the EU and the USA ban surveillance pricing, but a half-century of lax competition law enforcement has allowed companies to routinely engage in the "unfair and deceptive methods of competition" banned in both territories.
III. Twiddling: "Twiddling" is my word for the way that digitized businesses can use computers' flexibility to alter their prices, offers, and other fundamentals on a per-user, per-session basis. It's not enough to spy on users: to engage in surveillance pricing, you have to be able to mobilize that surveillance data from instant to instant, changing the prices for every user. This can only be done once a business has been digitized:
https://pluralistic.net/2023/02/19/twiddler/
Combine monopoly, weak privacy law, weak competition law, and digitization, and you don't just make surveillance pricing possible – at that point, it's practically inevitable. This is what it means to create an enshittogenic policy environment: by arranging policy so that the most awful schemes of the worst people are the most profitable, you guarantee that those people will end up organizing commercial and labor markets.
When surveillance pricing is applied to labor, we call it "algorithmic wage discrimination," a term coined by Veena Dubal based on her research with Uber drivers:
Uber uses historic data on drivers to make inferences about how economically precarious they are, and then extracts a "desperation premium" from their wages. Drivers who are pickier about which rides they accept ("pickers") are offered higher wages than drivers who take any ride ("ants"):
On the back-end, Uber is inferring that the reason an ant will accept a worse job is that they have fewer choices – they are more strapped for cash and/or have fewer options for earning a higher wage.
This is a straightforward form of algorithmic wage discrimination, using the blunt signal of how discriminating a driver is when signing onto a job to titer the subsequent wage offered to that driver. More sophisticated forms of algorithmic wage discrimination draw on external sources of data to set the price of your labor.
That's the situation for contract nurses, whose traditional brick-and-mortar staffing agencies have been replaced by nationwide apps that market themselves as "Uber for nursing." These apps use commercial surveillance data from the unregulated data-broker sector to check on how much credit card debt a nurse is carrying and whether that debt is delinquent to set a wage: the more debt you have and the more dire your indebtedness is, the lower the wage you are offered (and therefore the more debt you accumulate – lather, rinse, repeat):
Surveillance wages are now proliferating to other parts of the economy, as "consultancies" offer software to employers that let them set all parts of your compensation – base wage, annual raises, and bonuses – based on your perceived desperation, as derived from commercial surveillance data that has been collected about you:
Genna Contino's Marketwatch article on the phenomenon offers a concise definition of "surveillance wages":
a system in which wages are based not on an employee’s performance or seniority, but on formulas that use their personal data, often collected without employees’ knowledge.
This means that carrying a credit-card balance, taking out a payday loan, or even discussing your indebtedness on social media can all lead to lower wages in the future. Contino references a recent report released by Dubal and tech strategist Wilneida Negrón, surveying 500 large firms, which concluded that surveillance wages are now being offered in sectors as diverse as "healthcare, customer service, logistics and retail." Customers for surveillance wage tools include "Intuit, Salesforce, Colgate-Palmolive, Amwell and Healthcare Services Group":
After a brief crackdown under Biden, the Trump regime has been extraordinarily welcoming to surveillance pricing companies, dropping investigations and cases against firms that engaged in the practice. A few states are stepping in to fill the gap, with New York state passing a rule requiring disclosure of surveillance pricing – a modest step that was nevertheless fought tooth-and-nail by the state's businesses.
In Colorado, a new House bill called the "Prohibit Surveillance Data to Set Prices and Wages Act" would prohibit the use of personal information in wage-setting:
https://leg.colorado.gov/bills/hb25-1264
This bill hasn't passed yet, but it's already doing useful work. Companies universally deny using surveillance data to set wages, insisting that they merely pay for consulting services that give them advice on how they could do surveillance wages – but don't actually take that advice. However, these same companies – including Uber and Lyft – are ferociously lobbying against the bill, raising an obvious question, articulated by the bill's co-sponsor Rep Javier Mabrey (D-1): if these companies don't pay surveillance wages, then "what is the problem of codifying in law that you’re not allowed to?"
Surveillance wages are a rare profitable use-case for AI, in part because surveillance wages don't need to be "correct" in order to be effective. An employee who is offered a wage that's slightly higher than the lowest sum they'd accept still represents a savings to the company's wage-bill. As ever, AI is great for fully automating tasks if you don't care whether they're done well:
The fact that surveillance wages are calculated by external contractors enables employers to engage in otherwise illegal price-fixing. If all the garages in town set mechanics' wages using the same surveillance pricing tool, then a mechanic looking for a job will get the same lowball offer from all nearby employers. If those bosses were to gather around a table and fix the wage for any (or all) mechanics, that would be wildly illegal, but the fact that this is done via a software package lets the bosses claim they're not actually colluding.
This is a common practice in other forms of price-fixing. We see it in meat, potato products, and, of course, rental accommodations (hey there, Realpage!). It's a genuinely stupid ruse based on the absurd idea that "it's not a crime if we do it with an app":
Speaking of crimes that are implausibly deniable when undertaken with an app: surveillance wages also allow employers to offer lower wages to women and brown and Black people while maintaining the pretense that they're in compliance with laws banning gender and racial discrimination.
In the wider economy, women and racialized people are already offered lower wages and – thanks to the legacy of racial discrimination in employment and housing – are more likely to be indebted:
By tapping into data brokers' dossiers that reveal the economic precarity of jobseekers, surveillance pricing allows employers to systematically lower the wages of women and Black and brown people, who have the highest incidence of indebtedness, while still claiming to offer race- and gender-blind wages. This is a phenomenon that Patrick Ball calls "empiricism washing": first, move the illegal racist discrimination into an algorithm, then insist that "numbers can't be racist."
But this isn't just about lowering wages at the bottom of the employment market. In recent history, the employers most eager to illegally lower their workers' wages are tech bosses, who had to pay massive fines for illegally colluding on "no poach" agreements to suppress the earning power of high-paid computer programmers:
(This is why the tech industry is so horny for AI – tech bosses can't wait to fire a ton of programmers and use the resulting terror to force down the wages of the remaining tech workers:)
Which means that the very programmers who write and maintain the surveillance wage software used on the rest of us are especially likely to have the tools they created turned on them.
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“Flexible labor” is a euphemism for “derisking capital”
I'm on a tour with my new book, the international bestseller Enshittification: catch me next in Lisbon, Cardiff, London and Oxford! Full schedule here.
Corporations aren't people, but people and corporations do share some characteristics. Whether you're a human being or an immortal sinister colony organism that uses humans as gut flora (e.g. a corporation), most of us need to pay the rent and cover our other expenses.
"Earning a living" is a fact of life for humans and for corporations, and in both cases, the failure to do so can have dire consequences. For most humans, the path to earning a living is in selling your labor: that is, by finding a job, probably with a corporation. In taking that job, you assume some risk – for example, that your boss might be a jerk who makes your life a living hell, or that the company will go bust and leave you scrambling to make rent.
The corporation takes a risk, too: you might be an ineffectual or even counterproductive employee who fails to work its capital to produce a surplus from which a profit can be extracted. You might also fail to show up for work, or come in late, and lower the productivity of the firm (say, because another worker will have to cover for you and fall behind on their own work). You could even quit your job.
Both workers and corporations seek to "de-risk" their position. Workers can vote for politicians who will set minimum wages, punish unsafe working conditions and on-the-job harassment, and require health and disability insurance. They can also unionize and get some or all of these measures through collective bargaining (they might even get more protections, such as workplace tribunals to protect them from jobsite harassment). These are all examples of measures that shift risk from workers to capital. If a boss hires or promotes an abusive manager or cuts corners on shop-floor safety, the company – not the workers – will ultimately have to pay the price for its managers' poor judgment.
Bosses also strive to de-risk their position, by shifting the risk onto workers. For example, bosses love noncompete clauses in contracts, which let them harness the power of the government to punish their workers for changing jobs, and other bosses for hiring them. Given a tight noncompete, a boss can impose such high costs on workers who quit that they will elect to stay, even in the face of degraded working conditions, inadequate pay, and abusive management:
If you have $250,000 worth of student debt and your boss has coerced you into signing a contract with a noncompete, that means that quitting your job will see you excluded for three years (or longer) from the field you paid all that money to get a degree in, but you will still be expected to pay your loans over that period. Missing the loan payments means sky-high penalties, which is how you get situations where you borrow $79k, pay back $190k, and still owe $236k:
Bosses can also coerce workers into signing contracts with "training repayment agreement provisions" (TRAPs), which force workers to pay thousands of dollars for the privilege of quitting their job. Put this in stark economic terms: if your boss can fine you $5,000 for quitting your job, he can impose $4,999 worth of risk on you without risking your departure:
Bosses also enter into illegal, secret "no poach" agreements whereby they all agree not to hire one another's workers. One particularly pernicious version of this is the "bondage fee," where a staffing agency will demand that all its clients agree never to hire one of its contractors. In NYC, the majority of "doorman buildings" use a staffing agency called Planned Companies, a subsidiary of Toronto-based Firstservice, whose standard contract contains a bondage fee provision. The upshot is that pretty much every doorman building is legally on the hook for huge cash fines if they hire pretty much anyone who has worked as a doorman anywhere in the city:
Again, this is a form of de-risking for capital. By creating barriers to workers quitting their jobs, bosses can reduce the risk that their workers will quit, even if the pay and working conditions are inadequate.
One of the most profound, effective and pervasive sites of de-risking is the gig economy, in which workers are not guaranteed any wages. By paying workers on a piecework basis – where you are only paid if a customer appears and consumes some of your labor – bosses can shift the risks associated with bad marketing, bad planning, and bad pricing onto their workers.
Think of an Uber driver: when an Uber driver clocks into the app, they make the whole system more valuable. Each additional Uber driver on the road shortens the average wait time for a taxi. What's more, Uber's algorithmic wage discrimination allows the company to pay lower wages when there are more workers available:
Lots of companies have hit on the strategy of increasing staffing levels in order to increase customer satisfaction. If you're a hardcore frequent flier, your chosen airline will give you a special number you can call to speak to a human in a matter of seconds, without ever being shunted to a chatbot. This is a gigantic perk – especially if you're flying at a time when air traffic controllers are quitting in droves because they haven't been paid in a month, and thousands of flights are being canceled, leaving travelers scrambling to get rebooked:
The airline that creates the secret, heavily staffed call center for its biggest customers is making a bet that those customers will spend enough money with the airline to cover the wage of those call-center employees. If the company bets wrong, it pays the penalty, taking a net loss on the call center.
But what if the airline could switch to a "gig economy" call center like Arise, a pyramid scheme that ropes in primarily Black women who have to pay for the privilege of answering phones, and pay for the privilege of quitting, but who can be fired at any time?
Well, in that case the airline could tap an effectively limitless pool of call-center workers who could keep its best customers happy, but without taking the risk that the wages for those workers will exceed the new business brought in by those frequent fliers. Instead, that risk is borne by the workers, who have to pay for their own training, and whose pay can be doled out on a piecework basis, only paying them when someone calls in, but not paying them to simply be available in case someone calls in.
This isn't merely an employer de-risking its position: rather, the company is shifting its risk onto its workers. By deploying the legal fiction of worker misclassification in which an employee is classed as an "independent contractor," the boss can shift all the risk of misallocating labor onto workers.
In other words, risk-shifting isn't eliminating risk, it's just moving it around. Remember: both the corporation and the humans who work for it have to earn a living. They both need money for rent and other bills, and they both face dire consequences if they fail to pay those bills. When your boss misclassifies you as a contractor and only pays you when there's a customer demanding your labor, the boss is shifting the risk that they won't be able to pay the rent (because they hired too many workers or marketed their product badly) to you. If your boss screws up, they can still pay the rent – because you won't be able to pay yours.
That's what bosses mean by a "flexible workforce": a workforce that can coerced into assuming risk that properly belongs to its employers. After all, if you get into your car and clock onto the Uber app and fail to get a fare, whose fault is that? Uber bosses have all kinds of levers they can pull to increase ridership: they can reduce fares, they can advertise, they can even ping Uber riders directly through the app. What can an Uber driver do to increase the likelihood that they will get a fare? Absolutely, positively nothing. But who assumes the risk if a driver cruises the streets for hours, burning gas, not earning elsewhere, and not making a dime? The driver.
Uber alone determines the conditions for drivers, including how many drivers they will allow to be on the streets at the same time. Uber alone has the aggregated statistics with which to estimate likely ridership. Uber alone has the ability to entice more riders to hail cars. And yet it is Uber drivers who bear the responsibility if Uber fucks any of this up, and Uber does fuck this up, so badly that the true average driver wage (that is, the wage for hours in the car, not just when there's a passenger in there with you) is $2.50/hour:
This is what it means to shift risk. Uber doesn't have to be disciplined about its fares or its staffing levels or its marketing, because its workers can be made to pay the penalties for its mistakes. It's like this throughout the gig economy: the rise and rise of a massive "flexible workforce" is actually the rise and rise of a system in which labor assumes capital's risk.
Capital's story about a "flexible workforce" is that the risk is somehow magicked away when you can reclassify a worker as a contractor, but that's not true. A business that can only secure its sustained operations by shifting risk to its workers is a corporation that only exists because the workers who produce its profits assume the risks for its managers' blunders.
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:
Operating a business is risky: you can't ever be sure how many customers you'll have, or what they'll show up looking for. If you guess wrong, you'll either have too few workers to serve the crowd, or you'll pay workers to stand around and wait for customers. This is true even when your "business" is a "hospital."
Capitalists hate capitalism. Capitalism is defined by risk – like the risk of competitors poaching your customers and workers. Capitalists all secretly dream of a "command economy" in which other people have to arrange their affairs to suit the capitalists' preferences, taking the risk off their shoulders. Capitalists love anti-competitive exclusivity deals with suppliers, and they really love noncompete "agreements" that ban their workers from taking better jobs:
One of the sleaziest, most common ways for capitalists to shed risk is by shifting it onto their workers' shoulders, for example, by sending workers home on slow days and refusing to pay them for the rest of their shifts. This is easy for capitalists to do because workers have a collective action problem: for workers to force their bosses not to do this, they all have to agree to go on strike, and other workers have to honor their picket-lines. That's a lot of chivvying and bargaining and group-forming, and it's very hard. Meanwhile, the only person the boss needs to convince to screw you this way is themself.
Libertarians will insist that this is impossible, of course, because workers will just quit and go work for someone else when this happens, and so bosses will be disciplined by the competition to find workers willing to put up with their bullshit. Of course, these same libertarians will tell you that it should be legal for your boss to require you to sign a noncompete "agreement" so you can't quit and get a job elsewhere in your field. They'll also tell you that we don't need antitrust enforcement to prevent your boss from buying up all the businesses you might work for if you do manage to quit.
In practice, the only way workers have successfully resisted being burdened with their bosses' risks is by a) forming a union, and then b) using the union to lobby for strong labor laws. Labor laws aren't a substitute for a union, but they are an important backstop, and of course, if you're not unionized, labor law is all you've got.
Enter the tech-bro, app in hand. The tech-bro's most absurd (and successful) ruse is "it's not a crime, I did it with an app." As in "it's not money-laundering, I did it with an app." Or "it's not a privacy violation, I did it with an app." Or "it's not securities fraud, I did it with an app." Or "it's not price-gouging, I did it with an app," or, importantly, "it's not a labor-law violation, I did it with an app."
The point of the "gig economy" is to use the "did it with an app" trick to avoid labor laws, so that bosses can shift risks onto workers, because capitalists hate capitalism. These apps were first used to immiserate taxi-drivers, and this was so successful that it spawned a whole universe of "Uber for __________" apps that took away labor rights from other kinds of workers, from dog-groomers to carpenters.
One group of workers whose rights are being devoured by gig-work apps is nurses, which is bad news, because without nurses, I would be dead by now.
A new report from the Roosevelt Institute goes deep on the way that nurses' lives are being destroyed by gig work apps that let bosses in America's wildly dysfunctional for-profit health care industry shift risk from bosses to the hardest-working group of health care professionals:
The report's authors interviewed nurses who were employed through three apps: Shiftkey, Shiftmed and Carerev, and reveal a host of risk-shifting, worker-abusing practices that has nurses working for so little that they can't afford medical insurance themselves.
Take Shiftkey: nurses are required to log into Shiftkey and indicate which shifts they are available for, and if they are assigned any of those shifts later but can't take them, their app-based score declines and they risk not being offered shifts in the future. But Shiftkey doesn't guarantee that you'll get work on any of those shifts – in other words, nurses have to pledge not to take any work during the times when Shiftkey might need them, but they only get paid for those hours where Shiftkey calls them out. Nurses assume all the risk that there won't be enough demand for their services.
Each Shiftkey nurse is offered a different pay-scale for each shift. Apps use commercially available financial data – purchased on the cheap from the chaotic, unregulated data broker sector – to predict how desperate each nurse is. The less money you have in your bank accounts and the more you owe on your credit cards, the lower the wage the app will offer you. This is a classic example of what the legal scholar Veena Dubal calls "algorithmic wage discrimination" – a form of wage theft that's supposedly legal because it's done with an app:
Shiftkey workers also have to bid against one another for shifts, with the job going to the worker who accepts the lowest wage. Shiftkey pays nominal wages that sound reasonable – one nurse's topline rate is $23/hour. But by payday, Shiftkey has used junk fees to scrape that rate down to the bone. Workers have to pay a daily $3.67 "safety fee" to pay for background checks, drug screening, etc. Nevermind that these tasks are only performed once per nurse, not every day – and nevermind that this is another way to force workers to assume the boss's risks. Nurses also pay daily fees for accident insurance ($2.14) and malpractice insurance ($0.21) – more employer risk being shifted onto workers. Workers also pay $2 per shift if they want to get paid on the same day – a payday lending-style usury levied against workers whose wages are priced based on their desperation. Then there's a $6/shift fee nurses pay as a finders' fee to the app, a fee that's up to $7/shift next year. All told, that $23/hour rate cashes out to $13/hour.
On top of that, gig nurses have to pay for their own uniforms, licenses, equipment and equipment, including different colored scrubs and even shoes for each hospital. And because these nurses are "their own bosses" they have to deduct their own payroll taxes from that final figure. As "self-employed" workers, they aren't entitled to overtime or worker's comp, they get no retirement plan, health insurance, sick days or vacation.
The apps sell themselves to bosses as a way to get vetted, qualified nurses, but the entire vetting process is automated. Nurses upload a laundry list of documents related to their qualifications and undergo a background check, but are never interviewed by a human. They are assessed through automated means – for example, they have to run a location-tracking app en route to callouts and their reliability scores decline if they lose mobile data service while stuck in traffic.
Shiftmed docks nurses who cancel shifts after agreeing to take them, but bosses who cancel on nurses, even at the last minute, get away at most a small penalty (having to pay for the first two hours of a canceled shift), or, more often, nothing at all. For example, bosses who book nurses through the Carerev app can cancel without penalty on a mere two hours' notice. One nurse quoted in the study describes getting up at 5AM for a 7AM shift, only to discover that the shift was canceled while she slept, leaving her without any work or pay for the day, after having made arrangements for her kid to get childcare. The nurse assumes all the risk again: blocking out a day's work, paying for childcare, altering her sleep schedule. If she cancels on Carerev, her score goes down and she will get fewer shifts in the future. But if the boss cancels, he faces no consequences.
Carerev also lets bosses send nurses home early without paying them for the whole day – and they don't pay overtime if a nurse stays after her shift ends in order to ensure that their patients are cared for. The librarian scholar Fobazi Ettarh coined the term "vocational awe" to describe how workers in caring professions will endure abusive conditions and put in unpaid overtime because of their commitment to the patrons, patients, and pupils who depend on them:
Many of the nurses in the study report having shifts canceled on them as they pull into the hospital parking lot. Needless to say, when your shift is canceled just as it was supposed to start, it's unlikely you'll be able to book a shift at another facility.
The American healthcare industry is dominated by monopolies. First came the pharma monopolies, when pharma companies merged and merged and merged, allowing them to screw hospitals with sky-high prices. Then the hospitals gobbled each other up, merging until most regions were dominated by one or two hospital chains, who could use buyer power to get a better deal on pharma prices – but also use seller power to screw the insurers with outrageous prices for care. So the insurers merged, too, until they could fight hospital price-gouging.
Everywhere you turn in the healthcare industry, you find another monopolist: pharmacists and pharmacy benefit managers, group purchasing organizations, medical beds, saline and supplies. Monopoly begets monopoly.
(Unitedhealthcare is extraordinary in that its divisions are among the most powerful players in all of these sectors, making it a monopolist among monopolists – for example, UHC is the nation's largest employer of physicians:)
But there two key stakeholders in American health-care who can't monopolize: patients and health-care workers. We are the disorganized, loose, flapping ends at the beginning and end of the healthcare supply-chain. We are easy pickings for the monopolists in the middle, which is why patients pay more for worse care every year, and why healthcare workers get paid less for worse working conditions every year.
This is the one area where the Biden administration indisputably took action, bringing cases, making rules, and freaking out investment bankers and billionaires by repeatedly announcing that crimes were still crimes, even if you used an app to commit them.
The kind of treatment these apps mete out to nurses is illegal, app or no. In an important speech just last month, FTC commissioner Alvaro Bedoya explained how the FTC Act empowered the agency to shut down this kind of bossware because it is an "unfair and deceptive" form of competition:
This is the kind of thing the FTC could be doing. Will Trump's FTC actually do it? The Trump campaign called the FTC "politicized" – but Trump's pick for the next FTC chair has vowed to politicize it even more:
Like Biden's FTC, Trump's FTC will have a target-rich environment if it wants to bring enforcement actions on behalf of workers. But Biden's trustbusters chose their targets by giving priority to the crooked companies that were doing the most harm to Americans, while Trump's trustbusters are more likely to give priority to the crooked companies that Trump personally dislikes:
Picks and Shovels is a new, standalone technothriller starring Marty Hench, my two-fisted, hard-fighting, tech-scam-busting forensic accountant. You can pre-order it on my latest Kickstarter, which features a brilliant audiobook read by Wil Wheaton.
The social function of the economics profession is to explain, over and over again, that your boss is actually right and that you don't really want the things you want, and you're secretly happy to be abused by the system. If that wasn't true, why would your "choose" commercial surveillance, abusive workplaces and other depredations?
In other words, economics is the "look what you made me do" stick that capitalism uses to beat us with. We wouldn't spy on you, rip you off or steal your wages if you didn't choose to use the internet, shop with monopolists, or work for a shitty giant company. The technical name for this ideology is "public choice theory":
Of all the terrible things that economists say we all secretly love, one of the worst is "price discrimination." This is the idea that different customers get charged different amounts based on the merchant's estimation of their ability to pay. Economists insist that this is "efficient" and makes us all better off. After all, the marginal cost of filling the last empty seat on the plane is negligible, so why not sell that seat for peanuts to a flier who doesn't mind the uncertainty of knowing whether they'll get a seat at all? That way, the airline gets extra profits, and they split those profits with their customers by lowering prices for everyone. What's not to like?
Plenty, as it turns out. With only four giant airlines who've carved up the country so they rarely compete on most routes, why would an airline use their extra profits to lower prices, rather than, say, increasing their dividends and executive bonuses?
For decades, the airline industry was the standard-bearer for price discrimination. It was basically impossible to know how much a plane ticket would cost before booking it. But even so, airlines were stuck with comparatively crude heuristics to adjust their prices, like raising the price of a ticket that didn't include a Saturday stay, on the assumption that this was a business flyer whose employer was footing the bill:
With digitization and mass commercial surveillance, we've gone from pricing based on context (e.g. are you buying your ticket well in advance, or at the last minute?) to pricing based on spying. Digital back-ends allow vendors to ingest massive troves of commercial surveillance data from the unregulated data-broker industry to calculate how desperate you are, and how much money you have. Then, digital front-ends – like websites and apps – allow vendors to adjust prices in realtime based on that data, repricing goods for every buyer.
As digital front-ends move into the real world (say, with digital e-ink shelf-tags in grocery stores), vendors can use surveillance data to reprice goods for ever-larger groups of customers and types of merchandise. Grocers with e-ink shelf tags reprice their goods thousands of times, every day:
Here's where an economist will tell you that actually, your boss is right. Many groceries are perishable, after all, and e-ink shelf tags allow grocers to reprice their goods every minute or two, so yesterday's lettuce can be discounted every fifteen minutes through the day. Some customers will happily accept a lettuce that's a little gross and liztruss if it means a discount. Those customers get a discount, the lettuce isn't thrown out at the end of the day, and everyone wins, right?
Well, sure, if. If the grocer isn't part of a heavily consolidated industry where competition is a distant memory and where grocers routinely collude to fix prices. If the grocer doesn't have to worry about competitors, why would they use e-ink tags to lower prices, rather than to gouge on prices when demand surges, or based on time of day (e.g. making frozen pizzas 10% more expensive from 6-8PM)?
And unfortunately, groceries are one of the most consolidated sectors in the modern world. What's more, grocers keep getting busted for colluding to fix prices and rip off shoppers:
Surveillance pricing is especially pernicious when it comes to apps, which allow vendors to reprice goods based not just on commercially available data, but also on data collected by your pocket distraction rectangle, which you carry everywhere, do everything with, and make privy to all your secrets. Worse, since apps are a closed platform, app makers can invoke IP law to criminalize anyone who reverse-engineers them to figure out how they're ripping you off. Removing the encryption from an app is a potential felony punishable by a five-year prison sentence and a $500k fine (an app is just a web-page skinned in enough IP to make it a crime to install a privacy blocker on it):
Large vendors love to sell you shit via their apps. With an app, a merchant can undetectably change its prices every few seconds, based on its estimation of your desperation. Uber pioneered this when they tweaked the app to raise the price of a taxi journey for customers whose batteries were almost dead. Today, everyone's getting in on the act. McDonald's has invested in a company called Plexure that pitches merchants on the use case of raising the cost of your normal breakfast burrito by a dollar on the day you get paid:
Surveillance pricing isn't just a matter of ripping off customers, it's also a way to rip off workers. Gig work platforms use surveillance pricing to titrate their wage offers based on data they buy from data brokers and scoop up with their apps. Veena Dubal calls this "algorithmic wage discrimination":
Take nurses: increasingly, American hospitals are firing their waged nurses and replacing them with gig nurses who are booked in via an app. There's plenty of ways that these apps abuse nurses, but the most ghastly is in how they price nurses' wages. These apps buy nurses' financial data from data-brokers so they can offer lower wages to nurses with lots of credit card debt, on the grounds that crushing debt makes nurses desperate enough to accept a lower wage:
This week, the excellent Lately podcast has an episode on price discrimination, in which cohost Vass Bednar valiantly tries to give economists their due by presenting the strongest possible case for charging different prices to different customers:
Bednar really tries, but – as she later agrees – this just isn't a very good argument. In fact, the only way charging different prices to different customers – or offering different wages to different workers – makes sense is if you're living in a socialist utopia.
After all, a core tenet of Marxism is "from each according to his ability, to each according to his needs." In a just society, people who need more get more, and people who have less, pay less:
Price discrimination, then, is a Bizarro-world flavor of cod-Marxism. Rather than having a democratically accountable state that sets wages and prices based on need and ability, price discrimination gives this authority to large firms with pricing power, no regulatory constraints, and unlimited access to surveillance data. You couldn't ask for a neater example of the maxim that "What matters isn't what technology does. What matters is who it does it for; and who it does it to."
Neoclassical economists say that all of this can be taken care of by the self-correcting nature of markets. Just give consumers and workers "perfect information" about all the offers being made for their labor or their business, and things will sort themselves out. In the idealized models of perfectly spherical cows of uniform density moving about on a frictionless surface, this does work out very well:
But while large companies can buy the most intimate information imaginable about your life and finances, IP law lets them capture the state and use it to shut down any attempts you make to discover how they operate. When an app called Para offered Doordash workers the ability to preview the total wage offered for a job before they accepted it, Doordash threatened them with eye-watering legal penalties, then threw dozens of full-time engineers at them, changing the app several times per day to shut out Para:
And when an Austrian hacker called Mario Zechner built a tool to scrape online grocery store prices – discovering clear evidence of price-fixing conspiracies in the process – he was attacked by the grocery cartel for violating their "IP rights":
Conservatism consists of exactly one proposition, to wit: There must be in-groups whom the law protects but does not bind, alongside out-groups whom the law binds but does not protect.
Of course, there wouldn't be any surveillance pricing without surveillance. When it comes to consumer privacy, America is a no-man's land. The last time Congress passed a new consumer privacy law was in 1988, when they enacted the Video Privacy Protection Act, which bans video-store clerks from revealing which VHS cassettes you take home. Congress has not addressed a single consumer privacy threat since Die Hard was still playing in theaters.
Corporate bullies adore a regulatory vacuum. The sleazy data-broker industry that has festered and thrived in the absence of a modern federal consumer privacy law is absolutely shameless. For example, every time an app shows you an ad, your location is revealed to dozens of data-brokers who pretend to be bidding for the right to show you an ad. They store these location data-points and combine them with other data about you, which they sell to anyone with a credit card, including stalkers, corporate spies, foreign governments, and anyone hoping to reprice their offerings on the basis of your desperation:
Under Biden, the outgoing FTC did incredible work to fill this gap, using its authority under Section 5 of the Federal Trade Commission Act (which outlaws "unfair and deceptive" practices) to plug some of the worst gaps in consumer privacy law:
But now the burden of enforcing these rules falls to Trump's FTC, whose new chairman has vowed to end the former FTC's "war on business." What America desperately needs is a new privacy law, one that has a private right of action (so that individuals and activist groups can sue without waiting for a public enforcer to take up their causes) and no "pre-emption" (so that states can pass even stronger privacy laws):
How will we get that law? Through a coalition. After all, surveillance pricing is just one of the many horrors that Americans have to put up with thanks to America's privacy law gap. The "privacy first" theory goes like this: if you're worried about social media's impact on teens, or women, or old people, you should start by demanding a privacy law. If you're worried about deepfake porn, you should start by demanding a privacy law. If you're worried about algorithmic discrimination in hiring, lending, or housing, you should start by demanding a privacy law. If you're worried about surveillance pricing, you should start by demanding a privacy law. Privacy law won't entirely solve all these problems, but none of them would be nearly as bad if Congress would just get off its ass and catch up with the privacy threats of the 21st century. What's more, the coalition of everyone who's worried about all the harms that arise from commercial surveillance is so large and powerful that we can get Congress to act:
Economists, meanwhile, will line up to say that this is all unnecessary. After all, you "sold" your privacy when you clicked "I agree" or walked under a sign warning you that facial recognition was in use in this store. The market has figured out what you value privacy at, and it turns out, that value is nothing. Any kind of privacy law is just a paternalistic incursion on your "freedom to contract" and decide to sell your personal information. It is "market distorting."
In other words, your boss is right.
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I'm on tour with my new, nationally bestselling novel The Bezzle! Catch me TONIGHT in PHOENIX (Changing Hands, Feb 29) then Tucson (Mar 10-11), San Francisco (Mar 13), and more!
Uber lies about everything, especially money. Oh, and labour. Especially labour. And geometry. Especially geometry! But especially especially money. They constantly lie about money.
Uber are virtuosos of mendacity, but in Toronto, the company has attained a heretofore unseen hat-trick: they told a single lie that is dramatically, materially untruthful about money, labour and geometry! It's an achievement for the ages.
Here's how they did it.
For several decades, Toronto has been clobbered by the misrule of a series of far-right, clownish mayors. This was the result of former Ontario Premier Mike Harris's great gerrymander of 1998, when the city of Toronto was amalgamated with its car-dependent suburbs. This set the tone for the next quarter-century, as these outlying regions – utterly dependent on Toronto for core economic activity and massive subsidies to pay the unsustainable utility and infrastructure bills for sprawling neighborhoods of single-family homes – proceeded to gut the city they relied on.
These "conservative" mayors – the philanderer, the crackhead, the sexual predator – turned the city into a corporate playground, swapping public housing and rent controls for out-of-control real-estate speculation and trading out some of the world's best transit for total car-dependency. As part of that decay, the city rolled out the red carpet for Uber, allowing the company to put as many unlicensed taxis as they wanted on the city's streets.
Now, it's hard to overstate the dire traffic situation in Toronto. Years of neglect and underinvestment in both the roads and the transit system have left both in a state of near collapse and it's not uncommon for multiple, consecutive main arteries to shut down without notice for weeks, months, or, in a few cases, years. The proliferation of Ubers on the road – driven by desperate people trying to survive the city's cost-of-living catastrophe – has only exacerbated this problem.
Uber, of course, would dispute this. The company insists – despite all common sense and peer-reviewed research – that adding more cars to the streets alleviates traffic. This is easily disproved: there just isn't any way to swap buses, streetcars, and subways for cars. The road space needed for all those single-occupancy cars pushes everything further apart, which means we need more cars, which means more roads, which means more distance between things, and so on.
It is an undeniable fact that geometry hates cars. But geometry loathes Uber. Because Ubers have all the problems of single-occupancy vehicles, and then they have the separate problem that they just end up circling idly around the city's streets, waiting for a rider. The more Ubers there are on the road, the longer each car ends up waiting for a passenger:
Anything that can't go on forever eventually stops. After years of bumbling-to-sinister municipal rule, Toronto finally reclaimed its political power and voted in a new mayor, Olivia Chow, a progressive of long tenure and great standing (I used to ring doorbells for her when she was campaigning for her city council seat). Mayor Chow announced that she was going to reclaim the city's prerogative to limit the number of Ubers on the road, ending the period of Uber's "self-regulation."
Uber, naturally, lost its shit. The company claims to be more than a (geometrically impossible) provider of convenient transportation for Torontonians, but also a provider of good jobs for working people. And to prove it, the company has promised to pay its drivers "120% of minimum wage." As I write for Ricochet, that's a whopper, even by Uber's standards:
Here's the thing: Uber is only proposing to pay 120% of the minimum wage while drivers have a passenger in the vehicle. And with the number of vehicles Uber wants on the road, most drivers will be earning nothing most of the time. Factor in that unpaid time, as well as expenses for vehicles, and the average Toronto Uber driver stands to make $2.50 per hour (Canadian):
Now, Uber's told a lot of lies over the years. Right from the start, the company implicitly lied about what it cost to provide an Uber. For its first 12 years, Uber lost $0.41 on every dollar it brought in, lighting tens of billions in investment capital provided by the Saudi royals on fire in an effort to bankrupt rival transportation firms and disinvestment in municipal transit.
Uber then lied to retail investors about the business-case for buying its stock so that the House of Saud and other early investors could unload their stock. Uber claimed that they were on the verge of producing a self-driving car that would allow them to get rid of drivers, zero out their wage bill, and finally turn a profit. The company spent $2.5b on this, making it the most expensive Big Store in the history of cons:
After years, Uber produced a "self-driving car" that could travel one half of one American mile before experiencing a potentially lethal collision. Uber quietly paid another company $400m to take this disaster off its hands:
The self-driving car lie was tied up in another lie – that somehow, automation could triumph over geometry. Robocabs, we were told, would travel in formations so tight that they would finally end the Red Queen's Race of more cars – more roads – more distance – more cars. That lie wormed its way into the company's IPO prospectus, which promised retail investors that profitability lay in replacing every journey – by car, cab, bike, bus, tram or train – with an Uber ride:
https://www.reuters.com/article/idUSKCN1RN2SK/
The company has been bleeding out money ever since – though you wouldn't know it by looking at its investor disclosures. Every quarter, Uber trumpets that it has finally become profitable, and every quarter, Hubert Horan dissects its balance sheets to find the accounting trick the company thought of this time. There was one quarter where Uber declared profitability by marking up the value of stock it held in Uber-like companies in other countries.
How did it get this stock? Well, Uber tried to run a business in those countries and it was such a total disaster that they had to flee the country, selling their business to a failing domestic competitor in exchange for stock in its collapsing business. Naturally, there's no market for this stock, which, in Uber-land, means you can assign any value you want to it. So that one quarter, Uber just asserted that the stock had shot up in value and voila, profit!
But all of those lies are as nothing to the whopper that Uber is trying to sell to Torontonians by blanketing the city in ads: the lie that by paying drivers $2.50/hour to fill the streets with more single-occupancy cars, they will turn a profit, reduce the city's traffic, and provide good jobs. Uber says it can vanquish geometry, economics and working poverty with the awesome power of narrative.
In other words, it's taking Toronto for a bunch of suckers.
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"Negotiating the Algorithm" is an incredibly exciting, visionary report on the ways that organized labor can and should respond to "algorithmic management" – all the ways in which bosses have turned your mobile phone into your implacable line-manager:
Obviously the "gig economy" was ground zero for this bullshit, with delivery drivers/riders and rideshare leading the pack, followed by all the other jobs getting sucked into piecework: dog walking, nursing, house cleaning and more. But – as the report notes – 79% of EU companies are doing algorithmic management.
The report (written by freelance writer Ben Wray) is published a year after the EU's Platform Work Directive was passed, and a year before it will go into force in all 27 EU member states. It's doing several different jobs: capturing the extent and abuses of algorithmic management; describing how workers can fight back; connecting this to the new EU law, and making the case for unions to invest heavily in making use of the Platform Work Directive's provisions to transform the EU labor market and protect the vast majority of EU members (not just those in unions) from bossware in all its forms.
Algorithmic management poses serious challenges for trade unions. It gives bosses a massive information advantage over workers at the bargaining table, capturing fine-grained information about activity on the shop floor. It creates opportunities for bosses to violate collective bargains on a per-worker basis, changing the work conditions and pay for every worker and even for every job. It lets bosses spy on workers even when they're not on the clock, and offers many ways for bosses to retaliate against workers.
Workers trapped by algorithmic management are stripped of agency and problem-solving opportunities. They are put under relentless time-pressure and can be forced into dangerous situations (as when a gig delivery app insists that riders follow a prescribed route, even when accidents and other hazards are in the way).
"Cloudworkers" and other algorithmically managed workers are relentlessly surveilled. Platforms like Upwork can switch on workers' device cameras and photograph them while they work. Often, worker data is sold to data-brokers and other third parties. Biases in gig platforms' algorithms can victimize workers – Black workers, for example, are sometimes fired by apps after failing a facial recognition step (facial recognition works less reliably with darker skin-tones). The app accuses the worker of violating terms of service by sharing their accounts and kicks them off.
Of course, there's no appeal for this. Algorithmic management goes hand-in-hand with other high-handed measures, like replacing the HR department with a chatbot or a semi-attended info@ email address. You also can't reach the HR department when your pay packet is light, facilitating wage-theft. When payment systems fail, workers are sometimes left with the bill for their robo-boss's technological failures.
So it's quite important that unions figure out a strategy to address algorithmic management. That's where the Platform Work Directive comes in. The PWD has quite sweeping and bold provisions that can protect workers, but these new rules aren't self-enforcing. Many EU states' data commissioners are grossly underfunded and stretched thin. While the PWD grants workers many rights, they will need to demand those rights – on the job and in the courts.
The new Directive, in combination with the General Data Protection Regulation (the EU's existing privacy law), allows workers and their representatives to demand extensive data-sets from employers, documenting everything from the algorithmic decision-making that goes into firing workers from an app to the process of calculating their pay and beyond. But employers deliver this data in obfuscated, hard-to-parse formats. Wray advocates for unions to staff up their own data analysis groups that can assist in these requests and make sense of the results.
Wray also advocates for union technologists who can produce worker-side apps that monitor boss's apps – like the UberCheats app, which compared the mileage that Uber paid drivers for to their actual distances traveled. While it's important for workers to be able to access the information their bosses have amassed on their work and personal lives, it's just as important that workers not be limited to working with data that bosses are willing to hand over. Employers can't be trusted to mark their own homework.
By investing in technology, unions can close the information gap with employers, and even use data and apps to gain an advantage over bosses. Wray describes how gig workers created "counter apps" that documented wage-theft, enabled mass refusal of lowball offers, and helped workers win their rights in court.
This technological capacity can also help union organizers, providing a unified digital back-end for union drives in all kinds of shops.
Wray acknowledges that it might be hard for unions to do this kind of advanced technical work in-house from the jump, and he isn't averse to having some of this work contracted out to third parties. But he proposes that this kind of arrangement should be modeled on "Chinese industrial policy…which in the 1980s and 1990s was known for bringing in western technological expertise but ensuring that it was the Chinese state and Chinese companies that reaped the knowledge from external experts."
He also moots the possibility of several unions combining forces to create a joint workers' technology shop that develops and supports tools for all kinds of unions across Europe. This sounds like a very exciting idea indeed – and maybe the answer to the legion of programmers who've asked me repeatedly how they can use their technical skills for good.
And as mentioned, the GDPR offers broad powers for workers to push back against bossware abuses. It lets workers demand the ratings system used to assess their work and to demand corrections to their scores – and it bans "hidden internal evaluations" of workers. It also gives workers the right to demand human intervention in automated decision-making.
When workers are "de-activated" (kicked off the app), the GDPR lets workers file a "subject access request" that forces the company to divulge "all personal information relating to that decision" with workers having the right to demand corrections to "inaccurate or incomplete information."
Despite the breadth of these powers, they have rarely been used, largely thanks to some rather gaping loopholes in the GDPR – for example, bosses can use the excuse that divulging information would reveal their trade secrets and expose their IP. The GDPR limits how far these excuses can go, but bosses routinely ignore those limits. Same goes for the all-purpose excuse that the algorithmic management is delivered by a third party tool. This excuse is illegal under the GDPR, but bosses roll it out all the time (and get away with it).
The Platform Work Directive patches many of the defects in the GDPR. It bans processing "a worker’s personal data in relation to: their emotional or psychological state; private exchanges; when they are not using the app; on the exercising of fundamental rights including worker organising; things that are personal to the worker including sexual orientation and migration status; biometric data when used to establish that person’s identity."
It expands rights to examine the workings and findings of "automation decision-making systems" and to demand that those findings be exported to a form that can be sent to the worker, and bans transfers to third parties. Workers can demand their data in a form that can be used e.g. to get another job, and their bosses have to pay any expenses associated with this.
The Platform Work Directive requires strict human oversight of automated systems, especially for things like de-activations. The Directive requires EU member-states to hold hearings every two years on this process. Workers have the right to demand human review of any automated decision, and sets a deadline of two weeks for bosses to reply. If the platform has made a mistake, it has two weeks more to make it up to the worker, either by giving them their jobs back, or paying "adequate compensation" for damages.
The Directive bans platforms from arbitrarily changing how their back-ends work and requires bosses to notify workers and consult with them on "changes to automated monitoring or decision-making systems." It requires bosses to pay experts (chosen by workers) to assess these changes.
All these new rules are exciting, but they'll only come into force if someone fights when they're broken. That's where unions come in. If bosses are caught cheating, the Directive requires them to reimburse unions for any experts they hire to fight the scams.
Wray proposes a detailed series of recommendations to unions for things they should demand in their contracts to maximize their chances to capitalize on the opportunities afforded by the Platform Work Directive, such as establishing a "governance body" within the company "to govern data formation, storage, handling and security issues. This body should include shop stewards and all members of the body should receive data training."
He also sets out technological tactics that unions can fund and capitalize on to maximize their use of the directive, such as hacking apps to allow gig workers to increase their earnings. He writes warmly of "the sock-puppet method," where many test accounts are used to place and book work through platforms to monitor their pricing systems to detect collusion and price rigging. This has been successfully used in Spain to create the basis for an ongoing lawsuit over price collusion.
The new world of algorithmic management and the new Platform Work Directive offers many opportunities to organized labor. However, there is always the possibility that an employer will simply refuse to follow the law – as Uber has done, after it was found guilty of violating data disclosure work and was fined €6,000/day until it came into compliance. Uber's now paid €500,000 in fines and has not disclosed the datat that the law and the courts require of it.
With algorithmic management, bosses have figured out new ways to evade the law and steal from workers. The Platform Work Directive gives workers and unions a whole suite of new tools to force bosses to play fair. It's not going to be easy, but the technological capacity workers and unions develop here can be repurposed to wage all-out digital class warfare.
Going to Defcon this weekend? I'm giving a keynote, "An Audacious Plan to Halt the Internet's Enshittification and Throw it Into Reverse," on Saturday at 12:30pm, followed by a book signing at the No Starch Press booth at 2:30pm!
https://info.defcon.org/event/?id=50826
Bezzle (n):
1. "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" (JK Gabraith)
2. Uber.
Uber was, is, and always will be a bezzle. There are just intrinsic limitations to the profits available to operating a taxi fleet, even if you can misclassify your employees as contractors and steal their wages, even as you force them to bear the cost of buying and maintaining your taxis.
The magic of early Uber – when taxi rides were incredibly cheap, and there were always cars available, and drivers made generous livings behind the wheel – wasn't magic at all. It was just predatory pricing.
Uber lost $0.41 on every dollar they brought in, lighting $33b of its investors' cash on fire. Most of that money came from the Saudi royals, funneled through Softbank, who brought you such bezzles as WeWork – a boring real-estate company masquerading as a high-growth tech company, just as Uber was a boring taxi company masquerading as a tech company.
Predatory pricing used to be illegal, but Chicago School economists convinced judges to stop enforcing the law on the grounds that predatory pricing was impossible because no rational actor would choose to lose money. They (willfully) ignored the obvious possibility that a VC fund could invest in a money-losing business and use predatory pricing to convince retail investors that a pile of shit of sufficient size must have a pony under it somewhere.
This venture predation let investors – like Prince Bone Saw – cash out to suckers, leaving behind a money-losing business that had to invent ever-sweatier accounting tricks and implausible narratives to keep the suckers on the line while they blew town. A bezzle, in other words:
Uber is a true bezzle innovator, coming up with all kinds of fairy tales and sci-fi gimmicks to explain how they would convert their money-loser into a profitable business. They spent $2.5b on self-driving cars, producing a vehicle whose mean distance between fatal crashes was half a mile. Then they paid another company $400 million to take this self-licking ice-cream cone off their hands:
Amazingly, self-driving cars were among the more plausible of Uber's plans. They pissed away hundreds of millions on California's Proposition 22 to institutionalize worker misclassification, only to have the rule struck down because they couldn't be bothered to draft it properly. Then they did it again in Massachusetts:
Remember when Uber was going to plug the holes in its balance sheet with flying cars? Flying cars! Maybe they were just trying to soften us up for their IPO, where they advised investors that the only way they'd ever be profitable is if they could replace every train, bus and tram ride in the world:
Honestly, the only way that seems remotely plausible is when it's put next to flying cars for comparison. I guess we can be grateful that they never promised us jetpacks, or, you know, teleportation. Just imagine the market opportunity they could have ascribed to astral projection!
Narrative capitalism has its limits. Once Uber went public, it had to produce financial disclosures that showed the line going up, lest the bezzle come to an end. These balance-sheet tricks were as varied as they were transparent, but the financial press kept falling for them, serving as dutiful stenographers for a string of triumphant press-releases announcing Uber's long-delayed entry into the league of companies that don't lose more money every single day.
One person Uber has never fooled is Hubert Horan, a transportation analyst with decades of experience who's had Uber's number since the very start, and who has done yeoman service puncturing every one of these financial "disclosures," methodically sifting through the pile of shit to prove that there is no pony hiding in it.
In 2021, Horan showed how Uber had burned through nearly all of its cash reserves, signaling an end to its subsidy for drivers and rides, which would also inevitably end the bezzle:
In mid, 2022, Horan showed how the "profit" Uber trumpeted came from selling off failed companies it had acquired to other dying rideshare companies, which paid in their own grossly inflated stock:
At the end of 2022, Horan showed how Uber invented a made-up, nonstandard metric, called "EBITDA profitability," which allowed them to lose billions and still declare themselves to be profitable, a lie that would have been obvious if they'd reported their earnings using Generally Accepted Accounting Principles (GAAP):
Like clockwork, Uber has just announced – once again – that it is profitable, and once again, the press has credulously repeated the claim. So once again, Horan has published one of his magisterial debunkings on Naked Capitalism:
Uber's $394m gains this quarter come from paper gains to untradable shares in its loss-making rivals – Didi, Grab, Aurora – who swapped stock with Uber in exchange for Uber's own loss-making overseas divisions. Yes, it's that stupid: Uber holds shares in dying companies that no one wants to buy. It declared those shares to have gained value, and on that basis, reported a profit.
Truly, any big number multiplied by an imaginary number can be turned into an even bigger number.
Now, Uber also reported "margin improvements" – that is, it says that it loses less on every journey. But it didn't explain how it made those improvements. But we know how the company did it: they made rides more expensive and cut the pay to their drivers. A 2.9m ride in Manhattan is now $50 – if you get a bargain! The base price is more like $70:
The number of Uber drivers on the road has a direct relationship to the pay Uber offers those drivers. But that pay has been steeply declining, and with it, the availability of Ubers. A couple weeks ago, I found myself at the Burbank train station unable to get an Uber at all, with the app timing out repeatedly and announcing "no drivers available."
Normally, you can get a yellow taxi at the station, but years of Uber's predatory pricing has caused a drawdown of the local taxi-fleet, so there were no taxis available at the cab-rank or by dispatch. It took me an hour to get a cab home. Uber's bezzle destroyed local taxis and local transit – and replaced them with worse taxis that cost more.
Uber won't say why its margins are improving, but it can't be coming from scale. Before the pandemic, Uber had far more rides, and worse margins. Uber has diseconomies of scale: when you lose money on every ride, adding more rides increases your losses, not your profits.
Meanwhile, Lyft – Uber's also-ran competitor – saw its margins worsen over the same period. Lyft has always been worse at lying about it finances than Uber, but it is in essentially the exact same business (right down to the drivers and cars – many drivers have both apps on their phones). So Lyft's financials offer a good peek at Uber's true earnings picture.
Lyft is actually slightly better off than Uber overall. It spent less money on expensive props for its long con – flying cars, robotaxis, scooters, overseas clones – and abandoned them before Uber did. Lyft also fired 24% of its staff at the end of 2022, which should have improved its margins by cutting its costs.
Uber pays its drivers less. Like Lyft, Uber practices algorithmic wage discrimination, Veena Dubal's term describing the illegal practice of offering workers different payouts for the same work. Uber's algorithm seeks out "pickers" who are choosy about which rides they take, and converts them to "ants" (who take every ride offered) by paying them more for the same job, until they drop all their other gigs, whereupon the algorithm cuts their pay back to the rates paid to ants:
All told, wage theft and wage cuts by Uber transferred $1b/quarter from labor to Uber's shareholders. Historically, Uber linked fares to driver pay – think of surge pricing, where Uber charged riders more for peak times and passed some of that premium onto drivers. But now Uber trumpets a custom pricing algorithm that is the inverse of its driver payment system, calculating riders' willingness to pay and repricing every ride based on how desperate they think you are.
This pricing is a per se antitrust violation of Section 2 of the Sherman Act, America's original antitrust law. That's important because Sherman 2 is one of the few antitrust laws that we never stopped enforcing, unlike the laws banning predator pricing:
Uber claims an 11% margin improvement. 6-7% of that comes from algorithmic price discrimination and service cutbacks, letting it take 29% of every dollar the driver earns (up from 22%). Uber CEO Dara Khosrowshahi himself says that this is as high as the take can get – over 30%, and drivers will delete the app.
Uber's food delivery service – a baling wire-and-spit Frankenstein's monster of several food apps it bought and glued together – is a loser even by the standards of the sector, which is unprofitable as a whole and experiencing an unbroken slide of declining demand.
Put it all together and you get a picture of the kind of taxi company Uber really is: one that charges more than traditional cabs, pays drivers less, and has fewer cars on the road at times of peak demand, especially in the neighborhoods that traditional taxis had always underserved. In other words, Uber has broken every one of its promises.
We replaced the "evil taxi cartel" with an "evil taxi monopolist." And it's still losing money.
Even if Lyft goes under – as seems inevitable – Uber can't attain real profitability by scooping up its passengers and drivers. When you're losing money on every ride, you just can't make it up in volume.
Image: JERRYE AND ROY KLOTZ MD (modified) https://commons.wikimedia.org/wiki/File:LA_BREA_TAR_PITS,_LOS_ANGELES.jpg
CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0/deed.en
I’m kickstarting the audiobook for “The Internet Con: How To Seize the Means of Computation,” a Big Tech disassembly manual to disenshittify the web and bring back the old, good internet. It’s a DRM-free book, which means Audible won’t carry it, so this crowdfunder is essential. Back now to get the audio, Verso hardcover and ebook:
http://seizethemeansofcomputation.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:
