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The covid tech that is intimately tied to China’s surveillance state

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The covid tech that is intimately tied to China’s surveillance state


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.

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The hunter-gatherer groups at the heart of a microbiome gold rush

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The hunter-gatherer groups at the heart of a microbiome gold rush


The first step to finding out is to catalogue what microbes we might have lost. To get as close to ancient microbiomes as possible, microbiologists have begun studying multiple Indigenous groups. Two have received the most attention: the Yanomami of the Amazon rainforest and the Hadza, in northern Tanzania. 

Researchers have made some startling discoveries already. A study by Sonnenburg and his colleagues, published in July, found that the gut microbiomes of the Hadza appear to include bugs that aren’t seen elsewhere—around 20% of the microbe genomes identified had not been recorded in a global catalogue of over 200,000 such genomes. The researchers found 8.4 million protein families in the guts of the 167 Hadza people they studied. Over half of them had not previously been identified in the human gut.

Plenty of other studies published in the last decade or so have helped build a picture of how the diets and lifestyles of hunter-gatherer societies influence the microbiome, and scientists have speculated on what this means for those living in more industrialized societies. But these revelations have come at a price.

A changing way of life

The Hadza people hunt wild animals and forage for fruit and honey. “We still live the ancient way of life, with arrows and old knives,” says Mangola, who works with the Olanakwe Community Fund to support education and economic projects for the Hadza. Hunters seek out food in the bush, which might include baboons, vervet monkeys, guinea fowl, kudu, porcupines, or dik-dik. Gatherers collect fruits, vegetables, and honey.

Mangola, who has met with multiple scientists over the years and participated in many research projects, has witnessed firsthand the impact of such research on his community. Much of it has been positive. But not all researchers act thoughtfully and ethically, he says, and some have exploited or harmed the community.

One enduring problem, says Mangola, is that scientists have tended to come and study the Hadza without properly explaining their research or their results. They arrive from Europe or the US, accompanied by guides, and collect feces, blood, hair, and other biological samples. Often, the people giving up these samples don’t know what they will be used for, says Mangola. Scientists get their results and publish them without returning to share them. “You tell the world [what you’ve discovered]—why can’t you come back to Tanzania to tell the Hadza?” asks Mangola. “It would bring meaning and excitement to the community,” he says.

Some scientists have talked about the Hadza as if they were living fossils, says Alyssa Crittenden, a nutritional anthropologist and biologist at the University of Nevada in Las Vegas, who has been studying and working with the Hadza for the last two decades.

The Hadza have been described as being “locked in time,” she adds, but characterizations like that don’t reflect reality. She has made many trips to Tanzania and seen for herself how life has changed. Tourists flock to the region. Roads have been built. Charities have helped the Hadza secure land rights. Mangola went abroad for his education: he has a law degree and a master’s from the Indigenous Peoples Law and Policy program at the University of Arizona.

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan


Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisis—casualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimer’s.

Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who don’t live in the polluted, processed environment that most of the rest of us share. They’ve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost. 

But there is a major catch: we don’t know whether those in hunter-gatherer societies really do have “healthier” microbiomes—and if they do, whether the benefits could be shared with others. At the same time, members of the communities being studied are concerned about the risk of what’s called biopiracy—taking natural resources from poorer countries for the benefit of wealthier ones. Read the full story.

—Jessica Hamzelou

Eric Schmidt has a 6-point plan for fighting election misinformation

—by Eric Schmidt, formerly the CEO of Google, and current cofounder of philanthropic initiative Schmidt Futures

The coming year will be one of seismic political shifts. Over 4 billion people will head to the polls in countries including the United States, Taiwan, India, and Indonesia, making 2024 the biggest election year in history.

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Navigating a shifting customer-engagement landscape with generative AI

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Navigating a shifting customer-engagement landscape with generative AI


A strategic imperative

Generative AI’s ability to harness customer data in a highly sophisticated manner means enterprises are accelerating plans to invest in and leverage the technology’s capabilities. In a study titled “The Future of Enterprise Data & AI,” Corinium Intelligence and WNS Triange surveyed 100 global C-suite leaders and decision-makers specializing in AI, analytics, and data. Seventy-six percent of the respondents said that their organizations are already using or planning to use generative AI.

According to McKinsey, while generative AI will affect most business functions, “four of them will likely account for 75% of the total annual value it can deliver.” Among these are marketing and sales and customer operations. Yet, despite the technology’s benefits, many leaders are unsure about the right approach to take and mindful of the risks associated with large investments.

Mapping out a generative AI pathway

One of the first challenges organizations need to overcome is senior leadership alignment. “You need the necessary strategy; you need the ability to have the necessary buy-in of people,” says Ayer. “You need to make sure that you’ve got the right use case and business case for each one of them.” In other words, a clearly defined roadmap and precise business objectives are as crucial as understanding whether a process is amenable to the use of generative AI.

The implementation of a generative AI strategy can take time. According to Ayer, business leaders should maintain a realistic perspective on the duration required for formulating a strategy, conduct necessary training across various teams and functions, and identify the areas of value addition. And for any generative AI deployment to work seamlessly, the right data ecosystems must be in place.

Ayer cites WNS Triange’s collaboration with an insurer to create a claims process by leveraging generative AI. Thanks to the new technology, the insurer can immediately assess the severity of a vehicle’s damage from an accident and make a claims recommendation based on the unstructured data provided by the client. “Because this can be immediately assessed by a surveyor and they can reach a recommendation quickly, this instantly improves the insurer’s ability to satisfy their policyholders and reduce the claims processing time,” Ayer explains.

All that, however, would not be possible without data on past claims history, repair costs, transaction data, and other necessary data sets to extract clear value from generative AI analysis. “Be very clear about data sufficiency. Don’t jump into a program where eventually you realize you don’t have the necessary data,” Ayer says.

The benefits of third-party experience

Enterprises are increasingly aware that they must embrace generative AI, but knowing where to begin is another thing. “You start off wanting to make sure you don’t repeat mistakes other people have made,” says Ayer. An external provider can help organizations avoid those mistakes and leverage best practices and frameworks for testing and defining explainability and benchmarks for return on investment (ROI).

Using pre-built solutions by external partners can expedite time to market and increase a generative AI program’s value. These solutions can harness pre-built industry-specific generative AI platforms to accelerate deployment. “Generative AI programs can be extremely complicated,” Ayer points out. “There are a lot of infrastructure requirements, touch points with customers, and internal regulations. Organizations will also have to consider using pre-built solutions to accelerate speed to value. Third-party service providers bring the expertise of having an integrated approach to all these elements.”

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