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Deception, exploited workers, and cash handouts: How Worldcoin recruited its first half a million test users

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Deception, exploited workers, and cash handouts: How Worldcoin recruited its first half a million test users


In the end, it was something that Blania said, in passing, during our interview in early March that helped us finally begin to understand Worldcoin. 

“We will let privacy experts take our systems apart, over and over, before we actually deploy them on a large scale,” he said, responding to a question about the privacy-related backlash last fall. 

Blania had just shared how his company had onboarded 450,000 individuals to Worldcoin—meaning that its orbs had scanned 450,000 sets of eyes, faces, and bodies, stored all that data to train its neural network. The company recognized this data collection as problematic and aimed to stop doing it. Yet it did not provide these early users the same privacy protections. We were perplexed by this seeming contradiction: were we the ones lacking in vision and ability to see the bigger picture? After all, compared with the company’s stated goal of signing up one billion users, perhaps 450,000 is small.

But each one of those 450,000 is a person, with his or her own hopes, lives, and rights that have nothing to do with the ambitions of a Silicon Valley startup. 

Speaking to Blania clarified something we had struggled to make sense of: how a company could speak so passionately about its privacy-protecting protocols while clearly violating the privacy of so many. Our interview helped us see that, for Worldcoin, these legions of test users were not, for the most part, its intended end users. Rather, their eyes, bodies, and very patterns of life were simply grist for Worldcoin’s neural networks. The lower-level orb operators, meanwhile, were paid pennies to feed the algorithm, often grappling privately with their own moral qualms. The massive effort to teach Worldcoin’s AI to recognize who or what was human was, ironically, dehumanizing to those involved. 

When we put seven pages of reporting findings and questions to Worldcoin, the company’s response was that nearly everything negative that we uncovered were simply “isolated incident[s]” that ultimately wouldn’t matter anyway, because the next (public) iteration would be better. We believe that rights to privacy and anonymity are fundamental, which is why, within the next few weeks, everyone signing up for Worldcoin will be able to do so without sharing any of their biometric data with us,” the company wrote. That nearly half a million people had already been subject to their testing seemed of little import.

Rather, what really matters are the results: that Worldcoin will have an attractive user number to bolster its sales pitch as Web3’s preferred identity solution. And whenever the real, monetizable products—whether it’s the orbs, the Web3 passport, the currency itself, or all of the above—launch for its intended users, everything will be ready, with no messy signs of the labor or the human body parts behind it.

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The Download: metaverse fashion, and looser covid rules in China

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The Download: metaverse fashion, and looser covid rules in China


Fashion creator Jenni Svoboda is designing a beanie with a melted cupcake top, sprinkles, and doughnuts for ears. But this outlandish accessory isn’t destined for the physical world—Svoboda is designing for the metaverse. She’s working in a burgeoning, if bizarre, new niche: fashion stylists who create or curate outfits for people in virtual spaces.

Metaverse stylists are increasingly sought-after as frequent users seek help dressing their avatars—often in experimental, wildly creative looks that defy personal expectations, societal standards, and sometimes even physics. 

Stylists like Svoboda are among those shaping the metaverse fashion industry, which is already generating hundreds of millions of dollars. But while, to the casual observer, it can seem outlandish and even obscene to spend so much money on virtual clothes, there are deeper, more personal, reasons why people are hiring professionals to curate their virtual outfits. Read the full story.

—Tanya Basu

Making sense of the changes to China’s zero-covid policy

On December 1, 2019, the first known covid-19 patient started showing symptoms in Wuhan. Three years later, China is the last country in the world holding on to strict pandemic control restrictions. However, after days of intense protests that shocked the world, it looks as if things could finally change.

Beijing has just announced wide-ranging relaxations of its zero covid policy, including allowing people to quarantine at home instead of in special facilities for the first time.

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Uber’s facial recognition is locking Indian drivers out of their accounts 

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Uber checks that a driver’s face matches what the company has on file through a program called “Real-Time ID Check.” It was rolled out in the US in 2016, in India in 2017, and then in other markets. “This prevents fraud and protects drivers’ accounts from being compromised. It also protects riders by building another layer of accountability into the app to ensure the right person is behind the wheel,” Joe Sullivan, Uber’s chief security officer, said in a statement in 2017.

But the company’s driver verification procedures are far from seamless. Adnan Taqi, an Uber driver in Mumbai, ran into trouble with it when the app prompted him to take a selfie around dusk. He was locked out for 48 hours, a big dent in his work schedule—he says he drives 18 hours straight, sometimes as much as 24 hours, to be able to make a living. Days later, he took a selfie that locked him out of his account again, this time for a whole week. That time, Taqi suspects, it came down to hair: “I hadn’t shaved for a few days and my hair had also grown out a bit,” he says. 

More than a dozen drivers interviewed for this story detailed instances of having to find better lighting to avoid being locked out of their Uber accounts. “Whenever Uber asks for a selfie in the evenings or at night, I’ve had to pull over and go under a streetlight to click a clear picture—otherwise there are chances of getting rejected,” said Santosh Kumar, an Uber driver from Hyderabad. 

Others have struggled with scratches on their cameras and low-budget smartphones. The problem isn’t unique to Uber. Drivers with Ola, which is backed by SoftBank, face similar issues. 

Some of these struggles can be explained by natural limitations in face recognition technology. The software starts by converting your face into a set of points, explains Jernej Kavka, an independent technology consultant with access to Microsoft’s Face API, which is what Uber uses to power Real-Time ID Check. 

Adnan Taqi holds up his phone in the driver’s seat of his car. Variations in lighting and facial hair have likely caused him to lose access to the app.

SELVAPRAKASH LAKSHMANAN

“With excessive facial hair, the points change and it may not recognize where the chin is,” Kavka says. The same thing happens when there is low lighting or the phone’s camera doesn’t have a good contrast. “This makes it difficult for the computer to detect edges,” he explains.

But the software may be especially brittle in India. In December 2021, tech policy researchers Smriti Parsheera (a fellow with the CyberBRICS project) and Gaurav Jain (an economist with the International Finance Corporation) posted a preprint paper that audited four commercial facial processing tools—Amazon’s Rekognition, Microsoft Azure’s Face, Face++, and FaceX—for their performance on Indian faces. When the software was applied to a database of 32,184 election candidates, Microsoft’s Face failed to even detect the presence of a face in more than 1,000 images, throwing an error rate of more than 3%—the worst among the four. 

It could be that the Uber app is failing drivers because its software was not trained on a diverse range of Indian faces, Parsheera says. But she says there may be other issues at play as well. “There could be a number of other contributing factors like lighting, angle, effects of aging, etc.,” she explained in writing. “But the lack of transparency surrounding the use of such systems makes it hard to provide a more concrete explanation.” 

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The Download: Uber’s flawed facial recognition, and police drones

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The Download: Uber’s flawed facial recognition, and police drones


One evening in February last year, a 23-year-old Uber driver named Niradi Srikanth was getting ready to start another shift, ferrying passengers around the south Indian city of Hyderabad. He pointed the phone at his face to take a selfie to verify his identity. The process usually worked seamlessly. But this time he was unable to log in.

Srikanth suspected it was because he had recently shaved his head. After further attempts to log in were rejected, Uber informed him that his account had been blocked. He is not alone. In a survey conducted by MIT Technology Review of 150 Uber drivers in the country, almost half had been either temporarily or permanently locked out of their accounts because of problems with their selfie.

Hundreds of thousands of India’s gig economy workers are at the mercy of facial recognition technology, with few legal, policy or regulatory protections. For workers like Srikanth, getting blocked from or kicked off a platform can have devastating consequences. Read the full story.

—Varsha Bansal

I met a police drone in VR—and hated it

Police departments across the world are embracing drones, deploying them for everything from surveillance and intelligence gathering to even chasing criminals. Yet none of them seem to be trying to find out how encounters with drones leave people feeling—or whether the technology will help or hinder policing work.

A team from University College London and the London School of Economics is filling in the gaps, studying how people react when meeting police drones in virtual reality, and whether they come away feeling more or less trusting of the police. 

MIT Technology Review’s Melissa Heikkilä came away from her encounter with a VR police drone feeling unnerved. If others feel the same way, the big question is whether these drones are effective tools for policing in the first place. Read the full story.

Melissa’s story is from The Algorithm, her weekly newsletter covering AI and its effects on society. Sign up to receive it in your inbox every Monday.

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