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.
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 reason for their newfound popularity is obvious: the rise and rise of algorithmic management tools, in which your boss is an app. That IBM slide is right: turning an app into your boss allows your actual boss to create an "accountability sink" in which there is no obvious way to blame a human or even a company for your maltreatment:
App-based management-by-bossware treats the bug identified by the unknown author of that IBM slide into a feature. When an app is your boss, it can force you to scab:
But tech giveth and tech taketh away. Digital technology is infinitely flexible: the program that spies on you can be defeated by another program that defeats spying. Every time your algorithmic boss hacks you, you can hack your boss back:
Technologists and labor organizers need one another. Even the most precarious and abused workers can team up with hackers to disenshittify their robo-bosses:
One tech-savvy group on the cutting edge of dismantling the Torment Nexus is Algorithms Exposed, a tiny, scrappy group of EU hacker/academics who recruit volunteers to reverse engineer and modify the algorithms that rule our lives as workers and as customers:
Algorithms Exposed have an admirable supply of seemingly boundless energy. Every time I check in with them, I learn that they've spun out yet another special-purpose subgroup. Today, I learned about Reversing Works, a hacking team that reverse engineers gig work apps, revealing corporate wrongdoing that leads to multimillion euro fines for especially sleazy companies.
One such company is Foodinho, an Italian subsidiary of the Spanish food delivery company Glovo. Foodinho/Glovo has been in the crosshairs of Italian labor enforcers since before the pandemic, racking up millions in fines – first for failing to file the proper privacy paperwork disclosing the nature of the data processing in the app that Foodinho riders use to book jobs. Then, after the Italian data commission investigated Foodinho, the company attracted new, much larger fines for its out-of-control surveillance conduct.
As all of this was underway, Reversing Works was conducting its own research into Glovo/Foodinho's app, running it on a simulated Android handset inside a PC so they could peer into app's data collection and processing. They discovered a nightmarish world of pervasive, illegal worker surveillance, and published their findings a year ago in November, 2023:
That report reveals all kinds of extremely illegal behavior. Glovo/Foodinho makes its riders' data accessible across national borders, so Glovo managers outside of Italy can access fine-grained surveillance information and sensitive personal information – a major data protection no-no.
Worse, Glovo's app embeds trackers from a huge number of other tech platforms (for chat, analytics, and more), making it impossible for the company to account for all the ways that its riders' data is collected – again, a requirement under Italian and EU data protection law.
All this data collection continues even when riders have clocked out for the day – its as though your boss followed you home after quitting time and spied on you.
The research also revealed evidence of a secretive worker scoring system that ranked workers based on undisclosed criteria and reserved the best jobs for workers with high scores. This kind of thing is pervasive in algorithmic management, from gig work to Youtube and Tiktok, where performers' videos are routinely suppressed because they crossed some undisclosed line. When an app is your boss, your every paycheck is docked because you violated a policy you're not allowed to know about, because if you knew why your boss was giving you shitty jobs, or refusing to show the video you spent thousands of dollars making to the subscribers who asked to see it, then maybe you could figure out how to keep your boss from detecting your rulebreaking next time.
All this data-collection and processing is bad enough, but what makes it all a thousand times worse is Glovo's data retention policy – they're storing this data on their workers for four years after the worker leaves their employ. That means that mountains of sensitive, potentially ruinous data on gig workers is just lying around, waiting to be stolen by the next hacker that breaks into the company's servers.
Reversing Works's report made quite a splash. A year after its publication, the Italian data protection agency fined Glovo another 5 million euros and ordered them to cut this shit out:
As the report points out, Italy is extremely well set up to defend workers' rights from this kind of bossware abuse. Not only do Italian enforcers have all the privacy tools created by the GDPR, the EU's flagship privacy regulation – they also have the benefit of Italy's 1970 Workers' Statute. The Workers Statute is a visionary piece of legislation that protects workers from automated management practices. Combined with later privacy regulation, it gave Italy's data regulators sweeping powers to defend Italian workers, like Glovo's riders.
Italy is also a leader in recognizing gig workers as de facto employees, despite the tissue-thin pretense that adding an app to your employment means that you aren't entitled to any labor protections. In the case of Glovo, the fine-grained surveillance and reputation scoring were deemed proof that Glovo was employer to its riders.
Reversing Works' report is a fascinating read, especially the sections detailing how the researchers recruited a Glovo rider who allowed them to log in to Glovo's platform on their account.
As Reversing Works points out, this bottom-up approach – where apps are subjected to technical analysis – has real potential for labor organizations seeking to protect workers. Their report established multiple grounds on which a union could seek to hold an abusive employer to account.
But this bottom-up approach also holds out the potential for developing direct-action tools that let workers flex their power, by modifying apps, or coordinating their actions to wring concessions out of their bosses.
After all, the whole reason for the gig economy is to slash wage-bills, by transforming workers into contractors, and by eliminating managers in favor of algorithms. This leaves companies extremely vulnerable, because when workers come together to exercise power, their employer can't rely on middle managers to pressure workers, deal with irate customers, or step in to fill the gap themselves:
Only by seizing the means of computation, workers and organized labor can turn the tables on bossware – both by directly altering the conditions of their employment, and by producing the evidence and tools that regulators can use to force employers to make those alterations permanent.
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:
"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.
CAUGHT IN THE CRUNCH: The Surveillance State Comes to Your Local Supermarket
How four decades of union destruction paved the way for algorithmic exploitation and corporate price-gouging
Walk into any Coles outlet today and you’re not just buying milk. You’re feeding a surveillance machine processing 10 billion rows of data through Peter Thiel’s Palantir Technologies, a versatile crew that also helps ICE hunt undocumented immigrants, works with the IDF and tracks targets…
