Imagine that you are ordering food on a delivery app. You open the app, select a meal, and someone—let’s call him Joe—accepts to collect and deliver it. This transaction involves a third party, the restaurant, but neither you nor Joe know that your dinner also depends on another person—perhaps her name is Jenny.
Miles and miles away, maybe in another country or even continent, Jenny is blinking at her computer screen, comparing Joe’s photo ID on the app’s database to a selfie he has just taken for the app. Joe, who normally has a full beard, decided to shave that morning. In one picture he is beardless, but in the other he isn’t—will Jenny recognise him?
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Loosely known as “crowd work” or “micro-tasking,” this type of work encompasses a wide range of tasks that machines can’t complete efficiently on their own. Through dedicated platforms, businesses like delivery apps and other data-hungry organisations tap into a dispersed and atomised pool of workers.
Most workers are not employees, but independent contractors paid by piece-rate. Jenny earns £0.04 for every picture she identifies. Later, as she logs onto the platform that lists these jobs, and signs onto more tasks like tagging images or completing short surveys, she might get an extra three pounds. For a few pennies, she could label content, help algorithms know what a “happy” song sounds like or whether a nipple is male or female, and thus subject to censorship on social media.
Every day we search the internet, use app services, consume tweets and other information. We often assume these platforms work by the magic of technology alone. “It’s seen as automated because that’s how it’s sold!” a crowd worker told me. “Look here at this fancy app that AUTOMATICALLY does whatever stuff a potential customer might want AUTOMATED.”
But behind it all are people, hiding in plain sight.
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Crowd work arguably began around 2005, when Amazon set up Mechanical Turk, the world’s first micro-work marketplace that connects workers with “requesters” in need of human intelligence. The company’s name is no coincidence. The Mechanical Turk was an 18th-century chess-playing robot that turned out to be powered by a series of small-statured chess masters hidden inside the machine. Likewise, the modern-day Mechanical Turk—or mTurk, for short—is designed to propel tech wizardry by keeping human labour out of sight: Jeff Bezos called it “artificial artificial intelligence.”
“We’ve never quite had industries so completely sell contract labour as automation,” anthropologist Mary L. Gray said in an interview with Technology Review. Alongside computer scientist Siddharth Suri, she coined the term “ghost work” to describe an economy in which workers’ contributions are completely erased from what the consumer sees in the end product.
Researchers have been trying to determine the size of this workforce for years. The Online Labour Index, set up in 2016, is the first economic indicator to track jobs posted to online gig economy platforms, but its creator, economist Otto Kässi, believes this method only reveals the tip of the iceberg. “Crowd work platforms are super opaque about the workforce behind them,” he told me.
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In 2016, Amazon banned data scientist Panos Ipeirotis from Mechanical Turk after his Mechanical Turk Tracker, an application that collected the number of available tasks on the platform every six minutes, revealed a dramatic drop in the number of active requesters. “Perhaps because they believed that I was coming up with incorrect conclusions,” he wrote to me in an email.
The opacity also makes it hard to know more about the workers. Kassi says there are two conflicting views: it is estimated that half the “Turkers,” as they are called, are in the United States; at the same time, labour in south-east Asia, a traditional outsourcing destination, is rapidly growing, potentially pushing wages down.
Despite a relatively small sample, the most commonly cited study about earnings on Amazon’s mTurk found that the median hourly wage of a worker is $2 (£1.40), with about 4 per cent of Turkers earning more than $7.25 (£5.12) an hour. Later research found that workers in the US make an average of $3.01 (£2.12) per hour while those in India earn $1.41 (£1).
“Certainly identifying a dog on a picture can't be worth more than a couple of pennies or cents,” said Fabian Stephany, an economist at Oxford’s Internet Institute. But he warns against generalising, as there are tasks where people can leverage their skills to a very profitable margin. Jack*, who started working on Mechanical Turk in 2012, eventually became a “Master Worker,” an elite status granted by Amazon to the best performing Turkers. He now specialises in helping computers process and understand human languages.
Kelsey Tucker, who lives in Colorado in the US, only began crowd work after losing her job last year. “You have to really dedicate yourself and learn how to use the platform best for you,” she said. “I’m still a newbie but the longer I go I find tips and tricks to get surveys that pay higher and interest me.”
Competition and the technicality of the work are some of the challenges. But other factors can contribute to low pay. The anonymity of workers—on mTurk, they are identified by a string of random numbers and letters—increases the possibility of abuse. Some don’t see anonymised workers as real people, says Jack, recalling a Michigan State University academic who offered tasks paying exactly… £0.
Depending on who you are speaking to, crowd work is either heralded as the pinnacle of opportunity and freedom, or a system of global exploitation. Leila Janah, the entrepreneur widely credited for introducing the term “micro-work” over a decade ago, believed that it could bring jobs to the developing world, lift people out of poverty and help them build skills. At the same time, crowd work platforms are designed so that employers have the power—they can price a job to find someone who will do it for the lowest pay, encouraging workers to undercut each other on wage in a race to the bottom. To get the highest paying jobs, many workers use scripts, extensions and software that enhance their productivity. This, in addition to the lack of a shared geographical workspace and not knowing your colleagues, makes it harder to collectively organise and bargain.
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Many crowd workers I reached out to were unwilling to speak. One Turker I spoke to said, “most Turkers are not interested in giving away their time”; another compared the competitive environment of crowd work to a “fight club.” But some workers have been collaborating. Turkopticon, an advocacy project and browser extension, helps Turkers share information with each other about employers. Online forums like Turk Crowd or Reddit’s r/mTurk convey an image of a community—albeit one that is closed to the public.
As a form of remote work, crowdsourced work has gained popularity during the pandemic. Research has linked rising local unemployment levels to the growth of crowd work. On YouTube, videos explaining how to make easy money on these platforms have cropped up since lockdown. Ghost work is likely to have attracted newly unemployed people who were stuck at home over the past year, but whether they’ll last is hard to tell—high worker turnover is common.
Kelsey Tucker, who makes at most 60 dollars a day, hopes that this new work will be better than her previous office job. The majority of her tasks so far involve checking tax rates on receipts, but what she enjoys the most is working with lawyers on the platform. “Law firms will basically look for mock jurors to present their case to and get a feel for the potential verdict,” she explains. For at least an hour, she reads or listens to the arguments, testimonies and evidence of both sides, and once both parties have presented, she has to say if she would convict, dismiss, or award money if it’s a settlement issue. “My favourite one involved a medical malpractice suit,” she said: it “might actually nudge me towards a career.”
*Names have been changed
