Yet, while the speed and intention of this response to protect workers in the absence of an effective national-level US response was admirable, these Chinese companies are also tied up in forms of egregious human rights abuses.
Dahua is one of the major providers of “smart camp” systems that Vera Zhou experienced in Xinjiang (the company says its facilities are supported by technologies such as “computer vision systems, big data analytics and cloud computing”). In October 2019, both Dahua and Megvii were among eight Chinese technology firms placed on a list that blocks US citizens from selling goods and services to them (the list, which is intended to prevent US firms from supplying non-US firms deemed a threat to national interests, prevents Amazon from selling to Dahua, but not buying from them). BGI’s subsidiaries in Xinjiang were placed on the US no-trade list in July 2020.
Amazon’s purchase of Dahua heat-mapping cameras recalls an older moment in the spread of global capitalism that was captured by historian Jason Moore’s memorable turn of phrase: “Behind Manchester stands Mississippi.”
What did Moore mean by this? In his rereading of Friedrich Engels’s analysis of the textile industry that made Manchester, England, so profitable, he saw that many aspects of the British Industrial Revolution would not have been possible without the cheap cotton produced by slave labor in the United States. In a similar way, the ability of Seattle, Kansas City, and Seoul to respond as rapidly as they did to the pandemic relies in part on the way systems of oppression in Northwest China have opened up a space to train biometric surveillance algorithms.
The protections of workers during the pandemic depends on forgetting about college students like Vera Zhou. It means ignoring the dehumanization of thousands upon thousands of detainees and unfree workers.
At the same time, Seattle also stands before Xinjiang.
Amazon has its own role in involuntary surveillance that disproportionately harms ethno-racial minorities given its partnership with US Immigration and Customs Enforcement to target undocumented immigrants and its active lobbying efforts in support of weak biometric surveillance regulation. More directly, Microsoft Research Asia, the so-called “cradle of Chinese AI,” has played an instrumental role in the growth and development of both Dahua and Megvii.
Chinese state funding, global terrorism discourse, and US industry training are three of the primary reasons why a fleet of Chinese companies now leads the world in face and voice recognition. This process was accelerated by a war on terror that centered on placing Uyghurs, Kazakhs, and Hui within a complex digital and material enclosure, but it now extends throughout the Chinese technology industry, where data-intensive infrastructure systems produce flexible digital enclosures throughout the nation, though not at the same scale as in Xinjiang.
China’s vast and rapid response to the pandemic has further accelerated this process by rapidly implementing these systems and making clear that they work. Because they extend state power in such sweeping and intimate ways, they can effectively alter human behavior.
Alternative approaches
The Chinese approach to the pandemic is not the only way to stop it, however. Democratic states like New Zealand and Canada, which have provided testing, masks, and economic assistance to those forced to stay home, have also been effective. These nations make clear that involuntary surveillance is not the only way to protect the well-being of the majority, even at the level of the nation.
In fact, numerous studies have shown that surveillance systems support systemic racism and dehumanization by making targeted populations detainable. The past and current US administrations’ use of the Entity List to halt sales to companies like Dahua and Megvii, while important, is also producing a double standard, punishing Chinese firms for automating racialization while funding American companies to do similar things.
Increasing numbers of US-based companies are attempting to develop their own algorithms to detect racial phenotypes, though through a consumerist approach that is premised on consent. By making automated racialization a form of convenience in marketing things like lipstick, companies like Revlon are hardening the technical scripts that are available to individuals.
As a result, in many ways race continues to be an unthought part of how people interact with the world. Police in the United States and in China think about automated assessment technologies as tools they have to detect potential criminals or terrorists. The algorithms make it appear normal that Black men or Uyghurs are disproportionately detected by these systems. They stop the police, and those they protect, from recognizing that surveillance is always about controlling and disciplining people who do not fit into the vision of those in power. The world, not China alone, has a problem with surveillance.
To counteract the increasing banality, the everydayness, of automated racialization, the harms of biometric surveillance around the world must first be made apparent. The lives of the detainable must be made visible at the edge of power over life. Then the role of world-class engineers, investors, and public relations firms in the unthinking of human experience, in designing for human reeducation, must be made clear. The webs of interconnection—the way Xinjiang stands behind and before Seattle— must be made thinkable.
—This story is an edited excerpt from In The Camps: China’s High-Tech Penal Colony, by Darren Byler (Columbia Global Reports, 2021.) Darren Byler is an assistant professor of international studies at Simon Fraser University, focused on the technology and politics of urban life in China.
Quantum computing holds and processes information in a way that exploits the unique properties of fundamental particles: electrons, atoms, and small molecules can exist in multiple energy states at once, a phenomenon known as superposition, and the states of particles can become linked, or entangled, with one another. This means that information can be encoded and manipulated in novel ways, opening the door to a swath of classically impossible computing tasks.
As yet, quantum computers have not achieved anything useful that standard supercomputers cannot do. That is largely because they haven’t had enough qubits and because the systems are easily disrupted by tiny perturbations in their environment that physicists call noise.
Researchers have been exploring ways to make do with noisy systems, but many expect that quantum systems will have to scale up significantly to be truly useful, so that they can devote a large fraction of their qubits to correcting the errors induced by noise.
IBM is not the first to aim big. Google has said it is targeting a million qubits by the end of the decade, though error correction means only 10,000 will be available for computations. Maryland-based IonQ is aiming to have 1,024 “logical qubits,” each of which will be formed from an error-correcting circuit of 13 physical qubits, performing computations by 2028. Palo Alto–based PsiQuantum, like Google, is also aiming to build a million-qubit quantum computer, but it has not revealed its time scale or its error-correction requirements.
Because of those requirements, citing the number of physical qubits is something of a red herring—the particulars of how they are built, which affect factors such as their resilience to noise and their ease of operation, are crucially important. The companies involved usually offer additional measures of performance, such as “quantum volume” and the number of “algorithmic qubits.” In the next decade advances in error correction, qubit performance, and software-led error “mitigation,” as well as the major distinctions between different types of qubits, will make this race especially tricky to follow.
Refining the hardware
IBM’s qubits are currently made from rings of superconducting metal, which follow the same rules as atoms when operated at millikelvin temperatures, just a tiny fraction of a degree above absolute zero. In theory, these qubits can be operated in a large ensemble. But according to IBM’s own road map, quantum computers of the sort it’s building can only scale up to 5,000 qubits with current technology. Most experts say that’s not big enough to yield much in the way of useful computation. To create powerful quantum computers, engineers will have to go bigger. And that will require new technology.
Burkhart’s device was implanted in his brain around nine years ago, a few years after he was left unable to move his limbs following a diving accident. He volunteered to trial the device, which enabled him to move his hand and fingers. But it had to be removed seven and a half years later.
His particular implant was a small set of 100 electrodes, carefully inserted into a part of the brain that helps control movement. It worked by recording brain activity and sending these recordings to a computer, where they were processed using an algorithm. This was connected to a sleeve of electrodes worn on the arm. The idea was to translate thoughts of movement into electrical signals that would trigger movement.
Burkhart was the first to receive the implant, in 2014; he was 24 years old. Once he had recovered from the surgery, he began a training program to learn how to use it. Three times a week for around a year and a half, he visited a lab where the implant could be connected to a computer via a cable leading out of his head.
“It worked really well,” says Burkhart. “We started off just being able to open and close my hand, but after some time we were able to do individual finger movements.” He was eventually able to combine movements and control his grip strength. He was even able to play Guitar Hero.
“There was a lot that I was able to do, which was exciting,” he says. “But it was also still limited.” Not only was he only able to use the device in the lab, but he could only perform lab-based tasks. “Any of the activities we would do would be simplified,” he says.
For example, he could pour a bottle out, but it was only a bottle of beads, because the researchers didn’t want liquids around the electrical equipment. “It was kind of a bummer it wasn’t changing everything in my life, because I had seen how beneficial it could be,” he says.
At any rate, the device worked so well that the team extended the trial. Burkhart was initially meant to have the implant in place for 12 to 18 months, he says. “But everything was really successful … so we were able to continue on for quite a while after that.” The trial was extended on an annual basis, and Burkhart continued to visit the lab twice a week.
Leggett told researchers that she “became one” with her device. It helped her to control the unpredictable, violent seizures she routinely experienced, and allowed her to take charge of her own life. So she was devastated when, two years later, she was told she had to remove the implant because the company that made it had gone bust.
The removal of this implant, and others like it, might represent a breach of human rights, ethicists say in a paper published earlier this month. And the issue will only become more pressing as the brain implant market grows in the coming years and more people receive devices like Leggett’s. Read the full story.
—Jessica Hamzelou
You can read more about what happens to patients when their life-changing brain implants are removed against their wishes in the latest issue of The Checkup, Jessica’s weekly newsletter giving you the inside track on all things biotech. Sign up to receive it in your inbox every Thursday.
If you’d like to read more about brain implants, why not check out:
+ Brain waves can tell us how much pain someone is in. The research could open doors for personalized brain therapies to target and treat the worst kinds of chronic pain. Read the full story.
+ An ALS patient set a record for communicating via a brain implant. Brain interfaces could let paralyzed people speak at almost normal speeds. Read the full story.
+ Here’s how personalized brain stimulation could treat depression. Implants that track and optimize our brain activity are on the way. Read the full story.
