https://www.theatlantic.com

  • Forum ouvert par le Network for Computational Modeling in Social and Ecological Sciences (#CoMSES) pour que la communauté ABM puisse échanger sur le sujet :

    https://forum.comses.net/c/covid-19/24

    –-> Vous pourrez notamment y trouver une revue/veille des démarches de modélisation de l’épidémie.

    #modélisation #covid-19 #coronavirus #épidémie

    –—

    PS. Je mets ci-dessous dans ce fil de discussion des liens vers des sites qui proposent des modélisations que je reçois notamment via la mailing-list geotamtam... mais... je n’y connais rien... donc aucune idée de ce que partage (ceci dit, ça vient d’un réseau de chercheurs...), je me dis que ça peut peut-être servir à quelques seenthisien·nes...

  • Coronavirus and the Blindness of Authoritarianism - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/02/coronavirus-and-blindness-authoritarianism/606922

    par Zeynep Tufekci

    Authoritarian blindness is a perennial problem, especially in large countries like China with centralized, top-down administration. Indeed, Xi would not even be the first Chinese ruler to fall victim to the totality of his own power. On August 4, 1958, buoyed by reports pouring in from around the country of record grain, rice, and peanut production, an exuberant Chairman Mao Zedong wondered how to get rid of the excess, and advised people to eat “five meals a day.” Many did, gorging themselves in the new regime canteens and even dumping massive amounts of “leftovers” down gutters and toilets. Export agreements were made to send tons of food abroad in return for machinery or currency. Just months later, perhaps the greatest famine in recorded history began, in which tens of millions would die because, in fact, there was no such surplus. Quite the opposite: The misguided agricultural policies of the Great Leap Forward had caused a collapse in food production. Yet instead of reporting the massive failures, the apparatchiks in various provinces had engaged in competitive exaggeration, reporting ever-increasing surpluses both because they were afraid of reporting bad news and because they wanted to please their superiors.

    Mao didn’t know famine was at hand, because he had set up a system that ensured he would hear lies.

    Smart rulers have tried to create workarounds to avoid this authoritarian dilemma. Dynastic China, for example, had institutionalized mechanisms to petition the emperor: a right that was theoretically granted to everyone, including the lowest farmers and the poorest city dwellers. This system was intended to check corruption in provinces and uncover problems, but in practice, it was limited in many ways, filtered through courtiers to a single emperor, who could listen to only so many in a day. Many rulers also cultivated their own independent sources of information in far-flung provinces.

    Thanks to technology, there is a much more robust option for authoritarians in the 21st century: big-data analytics in a digital public sphere. For a few years, it appeared that China had found a way to be responsive to its citizens without giving them political power. Researchers have shown, for example, that posts on Weibo (China’s Twitter) complaining about problems in governance or corruption weren’t all censored. Many were allowed to stay up, allowing crucial information to trickle up to authorities. For example, viral posts about forced demolitions (a common occurrence in China) or medical mistreatment led to authorities sacking the officials involved, or to victim compensation that would otherwise not have occurred. A corrupt official was even removed from office after outraged netizens on social media pointed out the expensive watches he wore, which were impossible to buy on his government salary.

    The public sphere in China during those years wasn’t a free-for-all, to be sure. One couldn’t call for collective action or for deposing the central government. But social media gave citizens a voice and a way to make an impact, and it served as an early-warning system for party leaders. (The only other topic that seemed to be off-limits was the censors themselves—researchers found that they eagerly zapped complaints directed at them.)

    Unlike books, though, apps can spy on people.

    One hundred million or so people in China have been, ahem, persuaded to download a party-propaganda app named “Study Xi, Strong Nation,” which makes users watch inculcation videos and take quizzes in a gamified, points-based system. It also allegedly gives the government access to the complete contents of users’ phones. It almost doesn’t matter whether the app contains such backdoor access or not: Reasonable people will act as if it does and be wary in all of their communications. Xi has also expanded China’s system of cameras linked to facial-recognition databases, which may someday be able to identify people everywhere they go. Again, the actual workings of the system are secondary to their chilling effects: For ordinary people, the safe assumption is that if they are in the wrong place at the wrong time, the authorities will know.

    An earlier hint that Xi’s China was falling into authoritarian blindness came during the ongoing Hong Kong protests. The demonstrations had started over a minor demand—the withdrawal of an extradition bill of little strategic importance to Beijing. Protest is the traditional way that Hong Kongers, who do not have full voting rights, express discontent. But this time the Beijing insiders miscalculated. They genuinely believed that the real cause for the Hong Kong unrest was the high rents on the densely populated island, and also thought that the people did not support the protesters. Authoritarian blindness had turned an easily solvable problem into a bigger, durable crisis that exacted a much heavier political toll, a pattern that would repeat itself after a mysterious strain of pneumonia emerged in a Wuhan seafood market.

    In early December, a strange cluster of patients from a local seafood market, which also sold wildlife for consumption, started showing up in Wuhan hospitals. These initial patients developed a fever and pneumonia that did not seem to be caused by any known viruses. Given the SARS experience of 2003, local doctors were quickly alarmed. With any such novel virus, medical providers are keen to know how it spreads: If the virus is unable to spread from human to human, it’s a tragedy, but a local one, and for only a few people. If it can sustainably spread from human to human, as was the case with SARS, it could turn into a global pandemic, with potentially massive numbers of victims.

    Given exponential growth dynamics of infectious diseases, containing an epidemic is straightforward early on, but nearly impossible once a disease spreads among a population. So it’s maximally important to identify and quarantine candidate cases as early as possible, and that means leadership must have access to accurate information.

    Before the month of December was out, the hospitals in Wuhan knew that the coronavirus was spreading among humans. Medical workers who had treated the sick but never visited the seafood market were falling ill. On December 30, a group of doctors attempted to alert the public, saying that seven patients were in isolation due to a SARS-like disease. On the same day, an official document admitting both a link to the seafood market and a new disease was leaked online. On December 31, facing swirling rumors, the Wuhan government made its first official announcement, confirming 27 cases but, crucially, denying human-to-human transmission. Teams in hazmat suits were finally sent to close down the seafood market, though without explaining much to the befuddled, scared vendors. On January 1, police said they had punished eight medical workers for “rumors,” including a doctor named Li Wenliang, who was among the initial group of whistleblowers.

    While the unsuspecting population of Wuhan, a city of 11 million, went about its business, the local government did not update the number of infected people from January 5 to January 10. But the signs of sustained human-to-human transmission grew. Emergency wards were filling up, not just with people who had been to the seafood market, but with their family members as well. On January 6, Li noticed an infection in the scan of a fellow doctor, but officials at the hospital “ordered him not to disclose any information to the public or the media.” On January 7, another infected person was operated on, spreading the disease to 14 more medical workers.

    It’s not clear why Xi let things spin so far out of control. It might be that he brushed aside concerns from his aides until it was too late, but a stronger possibility is that he did not know the crucial details. Hubei authorities may have lied, not just to the public but also upward—to the central government. Just as Mao didn’t know about the massive crop failures, Xi may not have known that a novel coronavirus with sustained human-to-human transmission was brewing into a global pandemic until too late.

    It’s nearly impossible to gather direct evidence from such a secretive state, but consider the strong, divergent actions before and after January 20—within one day, Hubei officials went from almost complete cover-up and business as usual to shutting down a whole city.

    #Zeynep_Tufekci #Coronavirus #Xi_Jinping #Autoritarisme #Information #Alerte

  • Coronavirus Outbreak : What Happens to the Gig Economy ? - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/02/coronavirus-gig-economy/607204

    The shadow of the new coronavirus finally reached American shores this week, as markets jittered downward and new cases crept up. The scope of any outbreak here is not clear, but experts suspect that the virus will become widespread. While the disease, known as COVID-19, is a global phenomenon, the response to it is necessarily local, and divvied up among more than 2,600 local health departments in the U.S. Municipal governments have prepared plans and local officials are on high alert, (...)

    #Amazon #Lyft #Uber #discrimination #conducteur·trice·s #santé #travail #GigEconomy

    ##santé

  • The Software to Write Every Possible Melody - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/02/whats-the-point-of-writing-every-possible-melody/607120

    Do-do-do-do-do-do-do-do-do-do-do-re, do-do-do-do-do-do-do-do-do-do-do-mi … you get the picture. In an era when millions of songwriters upload music to the internet—and just about any song can be plucked from obscurity by TikTok teens—it seems inevitable that the same melodies end up in different songs. There have been a number of high-profile music copyright-infringement cases, including a multimillion-dollar decision against Katy Perry for her song “Dark Horse.” A jury found that she’d (...)

    #algorithme #son #copyright #art

  • How Dating Became a ’Market’ - The Atlantic
    https://www.theatlantic.com/family/archive/2020/02/modern-dating-odds-economy-apps-tinder-math/606982

    February 25, 2020 by Ashley Fetters and Kaitlyn Tiffany - The ‘Dating Market’ Is Getting Worse

    The old but newly popular notion that one’s love life can be analyzed like an economy is flawed—and it’s ruining romance.

    Ever since her last relationship ended this past August, Liz has been consciously trying not to treatThe ‘Dating Market’ Is Getting Worse

    The old but newly popular notion that one’s love life can be analyzed like an economy is flawed—and it’s ruining romance.
    Ashley FettersKaitlyn Tiffany
    February 25, 2020 dating as a “numbers game.” By the 30-year-old Alaskan’s own admission, however, it hasn’t been going great.

    Liz has been going on Tinder dates frequently, sometimes multiple times a week—one of her New Year’s resolutions was to go on every date she was invited on. But Liz, who asked to be identified only by her first name in order to avoid harassment, can’t escape a feeling of impersonal, businesslike detachment from the whole pursuit.

    “It’s like, ‘If this doesn’t go well, there are 20 other guys who look like you in my inbox.’ And I’m sure they feel the same way—that there are 20 other girls who are willing to hang out, or whatever,” she said. “People are seen as commodities, as opposed to individuals.”

    It’s understandable that someone like Liz might internalize the idea that dating is a game of probabilities or ratios, or a marketplace in which single people just have to keep shopping until they find “the one.” The idea that a dating pool can be analyzed as a marketplace or an economy is both recently popular and very old: For generations, people have been describing newly single people as “back on the market” and analyzing dating in terms of supply and demand. In 1960, the Motown act the Miracles recorded “Shop Around,” a jaunty ode to the idea of checking out and trying on a bunch of new partners before making a “deal.” The economist Gary Becker, who would later go on to win the Nobel Prize, began applying economic principles to marriage and divorce rates in the early 1970s. More recently, a plethora of market-minded dating books are coaching singles on how to seal a romantic deal, and dating apps, which have rapidly become the mode du jour for single people to meet each other, make sex and romance even more like shopping.

    The unfortunate coincidence is that the fine-tuned analysis of dating’s numbers game and the streamlining of its trial-and-error process of shopping around have taken place as dating’s definition has expanded from “the search for a suitable marriage partner” into something decidedly more ambiguous. Meanwhile, technologies have emerged that make the market more visible than ever to the average person, encouraging a ruthless mind-set of assigning “objective” values to potential partners and to ourselves—with little regard for the ways that framework might be weaponized. The idea that a population of single people can be analyzed like a market might be useful to some extent to sociologists or economists, but the widespread adoption of it by single people themselves can result in a warped outlook on love.

    Moira Weigel, the author of Labor of Love: The Invention of Dating, argues that dating as we know it—single people going out together to restaurants, bars, movies, and other commercial or semicommercial spaces—came about in the late 19th century. “Almost everywhere, for most of human history, courtship was supervised. And it was taking place in noncommercial spaces: in homes, at the synagogue,” she said in an interview. “Somewhere where other people were watching. What dating does is it takes that process out of the home, out of supervised and mostly noncommercial spaces, to movie theaters and dance halls.” Modern dating, she noted, has always situated the process of finding love within the realm of commerce—making it possible for economic concepts to seep in.

    The application of the supply-and-demand concept, Weigel said, may have come into the picture in the late 19th century, when American cities were exploding in population. “There were probably, like, five people your age in [your hometown],” she told me. “Then you move to the city because you need to make more money and help support your family, and you’d see hundreds of people every day.” When there are bigger numbers of potential partners in play, she said, it’s much more likely that people will begin to think about dating in terms of probabilities and odds.

    Eva Illouz, directrice d’etudes (director of studies) at the École des Hautes Études en Sciences Sociales in Paris, who has written about the the application of economic principles to romance, agrees that dating started to be understood as a marketplace as courtship rituals left private spheres, but she thinks the analogy fully crystallized when the sexual revolution of the mid-20th century helped dissolve many lingering traditions and taboos around who could or should date whom. People began assessing for themselves what the costs or benefits of certain partnerships might be—a decision that used to be a family’s rather than an individual’s. “What you have is people meeting each other directly, which is exactly the situation of a market,” she said. “Everybody’s looking at everybody, in a way.”

    In the modern era, it seems probable that the way people now shop online for goods—in virtual marketplaces, where they can easily filter out features they do and don’t want—has influenced the way people “shop” for partners, especially on dating apps, which often allow that same kind of filtering. The behavioral economics researcher and dating coach Logan Ury said in an interview that many single people she works with engage in what she calls “relationshopping.”

    Read: The rise of dating-app fatigue

    “People, especially as they get older, really know their preferences. So they think that they know what they want,” Ury said—and retroactively added quotation marks around the words “know what they want.” “Those are things like ‘I want a redhead who’s over 5’7”,’ or ‘I want a Jewish man who at least has a graduate degree.’” So they log in to a digital marketplace and start narrowing down their options. “They shop for a partner the way that they would shop for a camera or Bluetooth headphones,” she said.

    But, Ury went on, there’s a fatal flaw in this logic: No one knows what they want so much as they believe they know what they want. Actual romantic chemistry is volatile and hard to predict; it can crackle between two people with nothing in common and fail to materialize in what looks on paper like a perfect match. Ury often finds herself coaching her clients to broaden their searches and detach themselves from their meticulously crafted “checklists.”

    The fact that human-to-human matches are less predictable than consumer-to-good matches is just one problem with the market metaphor; another is that dating is not a one-time transaction. Let’s say you’re on the market for a vacuum cleaner—another endeavor in which you might invest considerable time learning about and weighing your options, in search of the best fit for your needs. You shop around a bit, then you choose one, buy it, and, unless it breaks, that’s your vacuum cleaner for the foreseeable future. You likely will not continue trying out new vacuums, or acquire a second and third as your “non-primary” vacuums. In dating, especially in recent years, the point isn’t always exclusivity, permanence, or even the sort of long-term relationship one might have with a vacuum. With the rise of “hookup culture” and the normalization of polyamory and open relationships, it’s perfectly common for people to seek partnerships that won’t necessarily preclude them from seeking other partnerships, later on or in addition. This makes supply and demand a bit harder to parse. Given that marriage is much more commonly understood to mean a relationship involving one-to-one exclusivity and permanence, the idea of a marketplace or economy maps much more cleanly onto matrimony than dating.

    The marketplace metaphor also fails to account for what many daters know intuitively: that being on the market for a long time—or being off the market, and then back on, and then off again—can change how a person interacts with the marketplace. Obviously, this wouldn’t affect a material good in the same way. Families repeatedly moving out of houses, for example, wouldn’t affect the houses’ feelings, but being dumped over and over by a series of girlfriends might change a person’s attitude toward finding a new partner. Basically, ideas about markets that are repurposed from the economy of material goods don’t work so well when applied to sentient beings who have emotions. Or, as Moira Weigel put it, “It’s almost like humans aren’t actually commodities.”

    When market logic is applied to the pursuit of a partner and fails, people can start to feel cheated. This can cause bitterness and disillusionment, or worse. “They have a phrase here where they say the odds are good but the goods are odd,” Liz said, because in Alaska on the whole there are already more men than women, and on the apps the disparity is even sharper. She estimates that she gets 10 times as many messages as the average man in her town. “It sort of skews the odds in my favor,” she said. “But, oh my gosh, I’ve also received a lot of abuse.”

    Recently, Liz matched with a man on Tinder who invited her over to his house at 11 p.m. When she declined, she said, he called her 83 times later that night, between 1 a.m. and 5 a.m. And when she finally answered and asked him to stop, he called her a “bitch” and said he was “teaching her a lesson.” It was scary, but Liz said she wasn’t shocked, as she has had plenty of interactions with men who have “bubbling, latent anger” about the way things are going for them on the dating market. Despite having received 83 phone calls in four hours, Liz was sympathetic toward the man. “At a certain point,” she said, “it becomes exhausting to cast your net over and over and receive so little.”

    Read: Tinder’s most notorious men

    This violent reaction to failure is also present in conversations about “sexual market value”—a term so popular on Reddit that it is sometimes abbreviated as “SMV”—which usually involve complaints that women are objectively overvaluing themselves in the marketplace and belittling the men they should be trying to date.

    The logic is upsetting but clear: The (shaky) foundational idea of capitalism is that the market is unfailingly impartial and correct, and that its mechanisms of supply and demand and value exchange guarantee that everything is fair. It’s a dangerous metaphor to apply to human relationships, because introducing the idea that dating should be “fair” subsequently introduces the idea that there is someone who is responsible when it is unfair. When the market’s logic breaks down, it must mean someone is overriding the laws. And in online spaces populated by heterosexual men, heterosexual women have been charged with the bulk of these crimes.

    “The typical clean-cut, well-spoken, hard-working, respectful, male” who makes six figures should be a “magnet for women,” someone asserted recently in a thread posted in the tech-centric forum Hacker News. But instead, the poster claimed, this hypothetical man is actually cursed because the Bay Area has one of the worst “male-female ratios among the single.” The responses are similarly disaffected and analytical, some arguing that the gender ratio doesn’t matter, because women only date tall men who are “high earners,” and they are “much more selective” than men. “This can be verified on practically any dating app with a few hours of data,” one commenter wrote.

    Economic metaphors provide the language for conversations on Reddit with titles like “thoughts on what could be done to regulate the dating market,” and for a subreddit named sarcastically “Where Are All The Good Men?” with the stated purpose of “exposing” all the women who have “unreasonable standards” and offer “little to no value themselves.” (On the really extremist end, some suggest that the government should assign girlfriends to any man who wants one.) Which is not at all to say that heterosexual men are the only ones thinking this way: In the 54,000-member subreddit r/FemaleDatingStrategy, the first “principle” listed in its official ideology is “be a high value woman.” The group’s handbook is thousands of words long, and also emphasizes that “as women, we have the responsibility to be ruthless in our evaluation of men.”

    The design and marketing of dating apps further encourage a cold, odds-based approach to love. While they have surely created, at this point, thousands if not millions of successful relationships, they have also aggravated, for some men, their feeling that they are unjustly invisible to women.

    Men outnumber women dramatically on dating apps; this is a fact. A 2016 literature review also found that men are more active users of these apps—both in the amount of time they spend on them and the number of interactions they attempt. Their experience of not getting as many matches or messages, the numbers say, is real.

    But data sets made available by the apps can themselves be wielded in unsettling ways by people who believe the numbers are working against them. A since-deleted 2017 blog post on the dating app Hinge’s official website explained an experiment conducted by a Hinge engineer, Aviv Goldgeier. Using the Gini coefficient, a common measure of income inequality within a country, and counting “likes” as income, Goldgeier determined that men had a much higher (that is, worse) Gini coefficient than women. With these results, Goldgeier compared the “female dating economy” to Western Europe and the “male dating economy” to South Africa. This is, obviously, an absurd thing to publish on a company blog, but not just because its analysis is so plainly accusatory and weakly reasoned. It’s also a bald-faced admission that the author—and possibly the company he speaks for—is thinking about people as sets of numbers.

    In a since-deleted 2009 official blog post, an OkCupid employee’s data analysis showed women rating men as “worse-looking than medium” 80 percent of the time, and concluded, “Females of OkCupid, we site founders say to you: ouch! Paradoxically, it seems it’s women, not men, who have unrealistic standards for the opposite sex.” This post, more than a decade later, is referenced in men’s-rights or men’s-interest subreddits as “infamous” and “we all know it.”

    Even without these creepy blog posts, dating apps can amplify a feeling of frustration with dating by making it seem as if it should be much easier. The Stanford economist Alvin Roth has argued that Tinder is, like the New York Stock Exchange, a “thick” market where lots of people are trying to complete transactions, and that the main problem with dating apps is simply congestion. To him, the idea of a dating market is not new at all. “Have you ever read any of the novels of Jane Austen?” he asked. “Pride and Prejudice is a very market-oriented novel. Balls were the internet of the day. You went and showed yourself off.”

    Read: The five years that changed dating

    Daters have—or appear to have—a lot more choices on a dating app in 2020 than they would have at a provincial dance party in rural England in the 1790s, which is good, until it’s bad. The human brain is not equipped to process and respond individually to thousands of profiles, but it takes only a few hours on a dating app to develop a mental heuristic for sorting people into broad categories. In this way, people can easily become seen as commodities—interchangeable products available for acquisition or trade. “What the internet apps do is that they enable you to see, for the first time ever in history, the market of possible partners,” Illouz, the Hebrew University sociology professor, said. Or, it makes a dater think they can see the market, when really all they can see is what an algorithm shows them.

    The idea of the dating market is appealing because a market is something a person can understand and try to manipulate. But fiddling with the inputs—by sending more messages, going on more dates, toggling and re-toggling search parameters, or even moving to a city with a better ratio—isn’t necessarily going to help anybody succeed on that market in a way that’s meaningful to them.

    Last year, researchers at Ohio State University examined the link between loneliness and compulsive use of dating apps—interviewing college students who spent above-average time swiping—and found a terrible feedback loop: The lonelier you are, the more doggedly you will seek out a partner, and the more negative outcomes you’re likely to be faced with, and the more alienated from other people you will feel. This happens to men and women in the same way.

    “We found no statistically significant differences for gender at all,” the lead author, Katy Coduto, said in an email. “Like, not even marginally significant.”

    There may always have been a dating market, but today people’s belief that they can see it and describe it and control their place in it is much stronger. And the way we speak becomes the way we think, as well as a glaze to disguise the way we feel. Someone who refers to looking for a partner as a numbers game will sound coolly aware and pragmatic, and guide themselves to a more odds-based approach to dating. But they may also suppress any honest expression of the unbearably human loneliness or desire that makes them keep doing the math.

    #startups #société #mariage #etremmeteurs

  • Bloomberg needs to take down Sanders — immediately (opinion) - CNN
    https://www.cnn.com/2020/02/22/opinions/bloomberg-needs-to-take-down-sanders-lockhart/index.html

    If Bloomberg wants to make it past the Democratic National Convention in July, his strategy needs to change —quickly. His first objective is to nab the nomination, and to do that, he needs to direct his resources to take down Sanders before he even has a chance at Trump.

    As it stands, Sanders has a chance to run the table as the rest of the field fights each other for the honor of coming in second. Sanders has emerged as the Democratic front-runner, and his support stands at 25% among Democrats and independents who lean Democratic, according to the most recent Quinnipiac poll.

    But that’s not enough to win the general election. I don’t believe the country is prepared to support a Democratic socialist, and I agree with the theory that Sanders would lose in a matchup against Trump. In a general election battle between two divisive figures who both preach the politics of grievance, I believe Trump will win the battle to the bottom and remain the last man standing.

    Given that the primary calendar dictates that 60% of delegates will be determined by St. Patrick’s Day, the primary race could be effectively over in less than a month. Of all the other Democratic candidates, Bloomberg may be the only one who can stop the Sanders freight train and still have a shot at winning the White House.

    But let’s not forget — Bloomberg is already skipping the first four voting states in favor of concentrating on Super Tuesday. With his disastrous performance in the Las Vegas debate, it appears he won’t be building any organic momentum in this race. He has to buy it.
    If Bloomberg has any chance of winning the nomination, he has to redirect his resources during the primary and run ads against Sanders — not Trump.

    Bloomberg needs to use the next $400 million in ad spending to attack Sanders on his potential weaknesses in a general election and highlight how far left his campaign is. Hitting him on his past record on guns is a must.

  • Coronavirus and the Blindness of Authoritarianism - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/02/coronavirus-and-blindness-authoritarianism/606922

    China’s use of surveillance and censorship makes it harder for Xi Jinping to know what’s going on in his own country. China is in the grip of a momentous crisis. The novel coronavirus that emerged late last year has already claimed three times more lives than the SARS outbreak in 2003, and it is still spreading. More than 50 million people (more than the combined metro populations of New York, Los Angeles, Chicago, and San Francisco) remain under historically unprecedented lockdown, unable to (...)

    #Weibo #algorithme #CCTV #smartphone #manipulation #technologisme #domination #vidéo-surveillance #santé #surveillance #bug (...)

    ##santé ##écoutes

  • The Future of Politics Is Bots Drowning Out Humans - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/01/future-politics-bots-drowning-out-humans/604489

    They’re mouthpieces for foreign actors, domestic political groups, even the candidates themselves. And soon you won’t be able to tell they’re bots. Presidential-campaign season is officially, officially, upon us now, which means it’s time to confront the weird and insidious ways in which technology is warping politics. One of the biggest threats on the horizon : Artificial personas are coming, and they’re poised to take over political debate. The risk arises from two separate threads coming (...)

    #algorithme #manipulation #élections #électeurs #haine #microtargeting #profiling #bot

  • The 2020 Election Will Be a War of Disinformation - The Atlantic
    https://www.theatlantic.com/magazine/archive/2020/03/the-2020-disinformation-war/605530

    How new technologies and techniques pioneered by dictators will shape the 2020 election One day last fall, I sat down to create a new Facebook account. I picked a forgettable name, snapped a profile pic with my face obscured, and clicked “Like” on the official pages of Donald Trump and his reelection campaign. Facebook’s algorithm prodded me to follow Ann Coulter, Fox Business, and a variety of fan pages with names like “In Trump We Trust.” I complied. I also gave my cellphone number to the (...)

    #manipulation #élections #électeurs #haine #microtargeting #profiling #BigData

  • ICE Contract With GitHub Sparks Developer Protests - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/01/ice-contract-github-sparks-developer-protests/604339

    Developers are protesting after revelations that the source-code repository GitHub contracted with ICE. But if you restrict access to open-source code, is it still open ? For the past two years, software engineers and systems administrators from San Jose to Seattle have engaged in the tech industry’s latest rite of passage : reading the news to discover that their employer contributed to something they find unethical. In 2018, Google workers learned of the company’s secret U.S. military (...)

    #Google #ICE #Microsoft #Facebook #GitHub #militaire #algorithme

  • The Iowa Caucus : More Than an App and Tech Problem - The Atlantic
    https://www.theatlantic.com/technology/archive/2020/02/iowa-caucus-app-tech/606094

    Its app didn’t solve much, but it did reveal a lot. It’s all fun and games until someone’s app messes up the Democratic Iowa caucus. Before yesterday’s debacle, “Shadow” was merely a playful name. A small team of political technologists had given it to their company when it launched early last year, largely as a reference to their primary product : Lightrail, which is supposed to make moving data among different campaign tools easier. Light and Shadow, get it ? That might have been clever in a (...)

    #élections #technologisme #data #bug

  • Why Do People Still Love Consumer Tech ? - The Atlantic
    https://www.theatlantic.com/health/archive/2020/01/why-do-people-still-love-consumer-tech/604909

    Everywhere I turned, there were signs that I didn’t totally understand. “Can textiles empower mothers to share their personal experience of pregnancy ?” one big, blue banner asked, fighting for attention among hundreds of others in a cavernous exhibition hall. “Shop with your DNA,” implored another. Just around the corner, in lofted lights, a company promised that its products are “where sleep tech meets holistic wellness.” Across the room, a plumbing-fixture company got right down to business (...)

    #domotique #technologisme #domination #InternetOfThings #marketing

  • The Online Hell of Amazon’s Mechanical Turk - The Atlantic
    https://www.theatlantic.com/business/archive/2018/01/amazon-mechanical-turk/551192

    Technology has helped rid the American economy of many of the routine, physical, low-paid jobs that characterized the workplace of the last century. Gone are the women who sewed garments for pennies, the men who dug canals by hand, the children who sorted through coal. Today, more and more jobs are done at a computer, designing new products or analyzing data or writing code. But technology is also enabling a new type of terrible work, in which Americans complete mind-numbing tasks for (...)

    #Amazon #Clickworker #CrowdFlower #AmazonMechanicalTurk #conditions #GigEconomy #travail #travailleurs (...)

    ##Toluna

  • Your Health Data Are a Gold Mine for Advertisers
    https://www.theatlantic.com/technology/archive/2019/03/flu-google-kinsa-sick-thermometer-smart/584077

    In the hospital and at home, illness data can be lucrative. Hospitals across the nation are piloting voice-enabled smart speakers in patients’ rooms, including Cedars-Sinai Medical Center in Los Angeles and Boston Children’s Hospital. These institutions are hoping that smart speakers will make patients more comfortable, help staff stay organized, and, in some cases, keep people out of hospitals and emergency rooms altogether. Early results are promising, but health-care providers are still (...)

    #Google #Amazon #domotique #Alexa #BigData #data #santé #enfants

    ##santé

  • Google’s Totally Creepy, Totally Legal Health-Data Harvesting
    https://www.theatlantic.com/technology/archive/2019/11/google-project-nightingale-all-your-health-data/601999

    Google is an emerging health-care juggernaut, and privacy laws weren’t written to keep up. The summer after college, I moved back home to take care of my widower grandfather. Part of my job was to manage his medications ; at 80, he was becoming a fall risk and often complained that his prescriptions made him light-headed. But getting someone on the phone was exhausting, and privacy law prevented pharmaceutical call-line employees from answering some of my questions about side effects. So (...)

    #Ascension #Google #Microsoft #Amazon #Facebook #algorithme #bracelet #Fitbit #HealthDataHub #prédiction #BigData #data #marketing #profiling #publicité (...)

    ##publicité ##santé

  • The Sneaky Genius of Facebook’s New Preventative Health Tool
    https://www.theatlantic.com/technology/archive/2020/01/facebook-launches-new-preventative-health-tool/604567

    The feature looks likely to fill gaps in care—and to further draw users into Facebook’s ecosystem. In April 2018, Facebook sent the Yale cardiologist and researcher Freddy Abnousi on a strictly confidential assignment to liaise with medical groups across the country on behalf of Building 8, Facebook’s experimental research team. Building 8—which had originally been led by Regina Dugan, the former director of the Defense Advanced Research Projects Agency—worked on long-term, moonshot projects, (...)

    #Facebook #data #profiling #santé

    ##santé

  • Australia is burning


    https://pretendingnottopanic.com/2020/01/03/australia-is-burning
    https://www.bbc.com/news/world-australia-50951043

    Australia rarely gets the attention most countries get, partly because the land is so remote. The wildfires there are so extreme that they can’t be ignored, and yet probably aren’t getting the attention they’d get if they happened on one of the larger continents. About 10,000,000 acres have burned. That’s 5 times the acreage burned in California a couple of years ago, when many media outlets concentrated on celebrities’ homes that were in danger. The cause of Australia’s fires are being debated. Regardless of the initial cause, the fires are causing fires, and the fires are causing weather changes that cause yet more fires. It is hard to ignore the impact of Australia’s record heat that has persisted. The record average maximum summer temperature was 107F. That means some areas were even hotter. Climate change is more than the air getting a bit hotter. Cascading effects and various feedback mechanisms are unexpected consequences that amplify the impact. If it can happen there, where else can it happen? What other consequences and mechanisms aren’t we aware of?

    #Australie

    • C’est le texte le plus dérangeant et puissant que j’aie lu de la semaine, notamment parce que ça nous dit où en est le capitalisme vis-à-vis de l’exploitation de la nature : c’est toujours open bar, la course à l’innovation technique mais en version pseudo-verte.

      Many people imagine the seabed to be a vast expanse of sand, but it’s a jagged and dynamic landscape with as much variation as any place onshore. Mountains surge from underwater plains, canyons slice miles deep, hot springs billow through fissures in rock, and streams of heavy brine ooze down hillsides, pooling into undersea lakes.

      At full capacity, these companies expect to dredge thousands of square miles a year. Their collection vehicles will creep across the bottom in systematic rows, scraping through the top five inches of the ocean floor. Ships above will draw thousands of pounds of sediment through a hose to the surface, remove the metallic objects, known as polymetallic nodules, and then flush the rest back into the water. Some of that slurry will contain toxins such as mercury and lead, which could poison the surrounding ocean for hundreds of miles. The rest will drift in the current until it settles in nearby ecosystems. An early study by the Royal Swedish Academy of Sciences predicted that each mining ship will release about 2 million cubic feet of discharge every day, enough to fill a freight train that is 16 miles long. The authors called this “a conservative estimate,” since other projections had been three times as high. By any measure, they concluded, “a very large area will be blanketed by sediment to such an extent that many animals will not be able to cope with the impact and whole communities will be severely affected by the loss of individuals and species.”

      Scientists divide the ocean into five layers of depth. Closest to the surface is the “sunlight zone,” where plants thrive; then comes the “twilight zone,” where darkness falls; next is the “midnight zone,” where some creatures generate their own light; and then there’s a frozen flatland known simply as “the abyss.” Oceanographers have visited these layers in submersible vehicles for half a century, but the final layer is difficult to reach. It is known as the “hadal zone,” in reference to Hades, the ancient Greek god of the underworld, and it includes any water that is at least 6,000 meters below the surface—or, in a more Vernian formulation, that is 20,000 feet under the sea. Because the hadal zone is so deep, it is usually associated with ocean trenches, but several deepwater plains have sections that cross into hadal depth.

      The ISA has issued more mining licenses for nodules than for any other seabed deposit. Most of these licenses authorize contractors to exploit a single deepwater plain. Known as the Clarion-Clipperton Zone, or CCZ, it extends across 1.7 million square miles between Hawaii and Mexico—wider than the continental United States. When the Mining Code is approved, more than a dozen companies will accelerate their explorations in the CCZ to industrial-scale extraction. Their ships and robots will use vacuum hoses to suck nodules and sediment from the seafloor, extracting the metal and dumping the rest into the water. How many ecosystems will be covered by that sediment is impossible to predict. Ocean currents fluctuate regularly in speed and direction, so identical plumes of slurry will travel different distances, in different directions, on different days. The impact of a sediment plume also depends on how it is released. Slurry that is dumped near the surface will drift farther than slurry pumped back to the bottom. The circulating draft of the Mining Code does not specify a depth of discharge. The ISA has adopted an estimate that sediment dumped near the surface will travel no more than 62 miles from the point of release, but many experts believe the slurry could travel farther. A recent survey of academic research compiled by Greenpeace concluded that mining waste “could travel hundreds or even thousands of kilometers.”

      https://storage.googleapis.com/planet4-international-stateless/2019/06/f223a588-in-deep-water-greenpeace-deep-sea-mining-2019.pdf

      Building a vehicle to function at 36,000 feet, under 2 million pounds of pressure per square foot, is a task of interstellar-type engineering. It’s a good deal more rigorous than, say, bolting together a rover to skitter across Mars. Picture the schematic of an iPhone case that can be smashed with a sledgehammer more or less constantly, from every angle at once, without a trace of damage, and you’re in the ballpark—or just consider the fact that more people have walked on the moon than have reached the bottom of the Mariana Trench, the deepest place on Earth.

      While scientists struggle to reach the deep ocean, human impact has already gotten there. Most of us are familiar with the menu of damages to coastal water: overfishing, oil spills, and pollution, to name a few. What can be lost in the discussion of these issues is how they reverberate far beneath.

      Maybe the greatest alarm in recent years has followed the discovery of plastic floating in the ocean. Scientists estimate that 17 billion pounds of polymer are flushed into the ocean each year, and substantially more of it collects on the bottom than on the surface. Just as a bottle that falls from a picnic table will roll downhill to a gulch, trash on the seafloor gradually makes its way toward deepwater plains and hadal trenches. After his expedition to the trenches, Victor Vescovo returned with the news that garbage had beaten him there. He found a plastic bag at the bottom of one trench, a beverage can in another, and when he reached the deepest point in the Mariana, he watched an object with a large S on the side float past his window. Trash of all sorts is collecting in the hadal—Spam tins, Budweiser cans, rubber gloves, even a mannequin head.

      Scientists are just beginning to understand the impact of trash on aquatic life.

      https://marinedebris.noaa.gov/info/patch.html

      Microbes that flourish on plastic have ballooned in number, replacing other species as their population explodes in a polymer ocean.

      If it seems trivial to worry about the population statistics of bacteria in the ocean, you may be interested to know that ocean microbes are essential to human and planetary health. About a third of the carbon dioxide generated on land is absorbed by underwater organisms, including one species that was just discovered in the CCZ in 2018. The researchers who found that bacterium have no idea how it removes carbon from the environment, but their findings show that it may account for up to 10 percent of the volume that is sequestered by oceans every year.

      “There are more than a million microbes per milliliter of seawater,” he said, “so the chance of finding new antibiotics in the marine environment is high.” McCarthy agreed. “The next great drug may be hidden somewhere deep in the water,” he said. “We need to get to the deep-sea organisms, because they’re making compounds that we’ve never seen before. We may find drugs that could be used to treat gout, or rheumatoid arthritis, or all kinds of other conditions.”

      Marine biologists have never conducted a comprehensive survey of microbes in the hadal trenches. The conventional tools of water sampling cannot function at extreme depth, and engineers are just beginning to develop tools that can. Microbial studies of the deepwater plains are slightly further along—and scientists have recently discovered that the CCZ is unusually flush with life.

      Venter has been accused of trying to privatize the human genome, and many of his critics believe his effort to create new organisms is akin to playing God. He clearly doesn’t have an aversion to profit-driven science, and he’s not afraid to mess with nature—yet when I asked him about the prospect of mining in deep water, he flared with alarm. “We should be very careful about mining in the ocean,” he said. “These companies should be doing rigorous microbial surveys before they do anything else. We only know a fraction of the microbes down there, and it’s a terrible idea to screw with them before we know what they are and what they do.”

      As a group, they have sought to position DeepGreen as a company whose primary interest in mining the ocean is saving the planet. They have produced a series of lavish brochures to explain the need for a new source of battery metals, and Gerard Barron, the CEO, speaks with animated fervor about the virtues of nodule extraction.

      His case for seabed mining is straightforward. Barron believes that the world will not survive if we continue burning fossil fuels, and the transition to other forms of power will require a massive increase in battery production. He points to electric cars: the batteries for a single vehicle require 187 pounds of copper, 123 pounds of nickel, and 15 pounds each of manganese and cobalt. On a planet with 1 billion cars, the conversion to electric vehicles would require several times more metal than all existing land-based supplies—and harvesting that metal from existing sources already takes a human toll.

      L’enfer sur Terre, que cette histoire de seabed mining puisse être considérée comme écolo, de même qu’un milliard de bagnoles « vertes » !

      Mining companies may promise to extract seabed metal with minimal damage to the surrounding environment, but to believe this requires faith. It collides with the force of human history, the law of unintended consequences, and the inevitability of mistakes. I wanted to understand from Michael Lodge how a UN agency had made the choice to accept that risk.

      “Why is it necessary to mine the ocean?” I asked him.

      He paused for a moment, furrowing his brow. “I don’t know why you use the word necessary,” he said. “Why is it ‘necessary’ to mine anywhere? You mine where you find metal.”

      #extractivisme #extractivisme_marin #mer #océan #eau #mine #capitalisme_vert #tourisme_de_l'extrême par nos amis les #milliardaires #biologie_de_synthèse aussi #microbes #antibiotiques et un gros #beurk

  • The Dark Side of the Chinese Dream - The Atlantic
    https://www.theatlantic.com/international/archive/2019/11/dark-side-chinese-dream/602113

    November 23, 2019 Story by Frank Langfitt - A Woman Missing in the Mountains

    A Chinese American woman searches for her missing sister in China, encountering the dark side of the country’s economic rise.

    A few years back, I created a free taxi service in Shanghai in the hope of meeting a variety of Chinese people to tell the story of the country’s rapid transformation through their eyes. I drove scores of passengers and stayed in touch with the most interesting ones, profiling them in radio stories for NPR, where I worked as the Shanghai correspondent.

    About a year after I started driving, I received a cryptic message from a Chinese American woman named Crystal, who had grown up outside the city of Harbin in northeastern China and now lived in central Michigan. Crystal said she was returning to China in the fall to continue a search for her little sister, Winnie, who’d vanished two years earlier near the country’s border with Laos. Winnie had married a farmer, who she said had beaten her. She had fled their home and then disappeared.

    “By reading and listening to your reports,” wrote Crystal, who had heard my free-taxi radio stories on NPR, “I know you can help me.”

    Two months later, I met Crystal in Jinghong, a city in Yunnan province, in southwest China. She was a slim 44-year-old who wore jeans, a blue polo shirt, and sneakers. We drove in my rented SUV to see an attorney for advice on the law surrounding missing persons. He explained that although the police were legally obligated to search for people who’d disappeared, they rarely made much effort. Too many people went missing in China, and the cops didn’t have the resources. Crystal, who’d been living in the United States for six years and had an especially favorable impression of American law enforcement, was appalled.

    “Don’t you understand?” the lawyer said, shaking his head and laughing. “This is China. We’re not in America.”

    This became one theme of our journey: how different the country of Crystal’s birth was from her adopted one.

    After lunch that day, we drove across the muddy Mekong river and soon came to a military checkpoint manned by armed soldiers in camouflage, helmets, and body armor. I wondered what they were looking for. Crystal guessed correctly: drugs. We were just north of the Golden Triangle, a hub for opium and human trafficking where the borders of Laos, Thailand, and Myanmar (also known as Burma) meet.

    As we drove on, climbing into the mountains, Crystal filled me in on her family’s history. She’d grown up in the 1970s and ’80s on a farm, and was eight years older than Winnie. The family lived in a one-bedroom mud-brick house with a dirt floor and a grass roof. They relied on government rations, which weren’t enough to feed them all. Crystal’s mother couldn’t produce milk for Winnie, who as an infant suffered from calcium deficiency, which Crystal thinks affected her little sister’s intelligence. “She was kind of slow,” Crystal recalled. “She studied so hard, but she never got good scores.”

    Had the sisters been born a decade or two earlier, they would have probably remained in the countryside and lived similar, circumscribed lives under Mao Zedong’s socialist system. But economic reforms by Mao’s successor, Deng Xiaoping, created something new: the opportunity to succeed and the chance to fail. Crystal moved to Harbin, the provincial capital, where she studied and became a nurse. Winnie left school at 16 and headed to Harbin as well, where she fell into the default profession for many uneducated migrant women—sex work.

    During the Communist era, Mao had all but eradicated prostitution, but after the economy began to open up, it returned with a vengeance. Tens of millions of men moved to coastal cities on their own to work, creating tremendous demand. Undereducated women left the farm as well, providing supply.

    Winnie would call Crystal when her older sister was in the U.S. and tell her of the dangers of her work, of the beatings she suffered. Crystal urged Winnie to quit the business. Instead, Winnie climbed the next rung of the career ladder and became the mistress of a businessman. Working as an ernai—or “second wife”—is widely seen as an occupation and includes a contract. These women can expect an apartment and a monthly allowance, depending on the size of the city where they live and their perceived market value. Having a mistress is common among well-to-do businessmen and government officials in China: In 2013, a Renmin University study found that nearly all corrupt officials had adulterous affairs, and that most of those kept a mistress.

    As the late 2000s arrived, Winnie turned 30. Her skin was not yet creased, but her youth was beginning to fade and she often looked tired. She took her savings and moved from northeast China to the other end of the country, where she could enjoy anonymity and her money would go further. She bought six small apartments in Jinghong and became a landlady. In the fall of 2013, Winnie stunned her family by announcing that she’d married a rubber farmer named Luo and moved into his tiny house in a remote village. In the beginning, she said her husband treated her like a queen, washing her feet and making her meals. But Winnie kept her secrets. She didn’t tell Luo about the apartments she owned, and when she traveled to the city to check on her real estate, he became suspicious.

    “He always said I went to Jinghong to look for other men,” Winnie told Crystal at the time over WeChat, China’s most popular messaging app. “A couple of days ago, he smashed my phone.”

    Luo had beaten her twice, Winnie said, and she had threatened that if he did so again, she would leave him or commit suicide. Crystal asked whether Luo was aware of Winnie’s past, arguing that he would likely never trust her. “You’d better find a good place and go into hiding to start a new life,” she told her younger sister.

    Winnie grew more distraught. She was now 34. Her dream of finding a lasting relationship and building a new, independent life was slipping away. “I myself feel empty, always feel empty,” Winnie told Crystal as she wept over WeChat. “I simply want to find a man who dearly loves me. Why is it so difficult?”

    Winnie took Crystal’s advice, eventually boarding a bus and riding 10 hours to a nearby city, where she checked into a hotel. “You take care and let’s stay in touch,” Crystal told her. “Okay,” Winnie messaged back.

    A few days later, Winnie checked out of the hotel and vanished.

    That was nearly two years ago, and in all the time Winnie had been missing, she’d never reached out to tell family members she was okay.

    There was one cause for hope: Police had received an alert that Winnie’s government-issued ID number had been used at a bank in northeastern China, where she’d lived before marrying Luo. A lawyer had told her that if she disappeared for two years, she could dissolve her marriage without having to face her husband, Winnie had told Crystal in their conversations. If that were the case, Crystal thought, perhaps she would emerge in a couple of months.

    After several hours on the road, Crystal and I arrived at the police station where officers had supposedly investigated Winnie’s disappearance. It quickly became clear police had all but ignored the case, not even checking Winnie’s social-media accounts. I pressed them for the village of Winnie’s husband, Luo. The officer cautioned us against approaching Luo, who’d recently been released from jail for stealing a motorbike; although they didn’t tell us at the time, police also believed that he dealt drugs.

    We ignored their advice, and pressed on to the village. I guided the SUV up a one-lane road past fishponds, farmers weighed down with wicker baskets, and men on motorbikes. We eventually met Luo walking along the road in a black T-shirt, shorts, and flip-flops. He invited us back to his home. He said during their brief courtship, Winnie had been very pleasant.

    “But after our marriage, she turned into a different person,” Luo said. “She was very irritable. One night I was out harvesting rubber. She went to a bank to wire money to someone. I asked her who she was sending the money to. She refused to say.”

    Luo said they argued and admitted that he had slapped her once but insisted he didn’t beat her in the way she had described to Crystal. Glowering, Crystal confronted him.

    “Do you know what happened exactly?” she asked angrily. “Where did she go? Or did you kill her?”

    “If I’d killed her, I wouldn’t still be here,” said Luo, taken aback by Crystal’s prosecutorial tone. He seemed to know little about his wife. She didn’t tell him where she lived in Jinghong and refused to let him see her ID card. The day they picked up their marriage license, Luo learned Winnie had divorced another man a month earlier.

    We said goodbye to Luo and made our way back out of the valley. “Do you think he killed your sister?” I asked Crystal.

    “Not really,” she said. “I was just trying to get a reaction out of him.”

    The more we learned, the more questions we had.

    “My God, little sister,” Crystal said. “What did you leave behind?”

    The next morning, we returned to Jinghong to meet Cao, a friend of Winnie’s. The first thing that struck me was just how different Cao was from Luo. Winnie’s husband was a poor country boy in his 20s, whereas Cao, a businessman who worked in biofuel, was in his mid-30s, tall, confident, and gregarious, with the chiseled features of a movie star. He said he met Winnie at an outdoor market one evening and they’d struck up a friendship. He said he knew nothing of her marriages, but sensed she was looking to settle down and start a family. Cao was friendly and charming, but provided very little information.

    Running out of leads, I drove Crystal to the airport, where she flew to the northeast in hopes of finding who had used her sister’s police ID number at the bank. That trip was a disaster. Bank officials told her that Winnie didn’t have an account after all. Because of a glitch, a computer had mistakenly spit out Winnie’s ID number, triggering a false alert to police.

    Crystal returned to Jinghong and went to the apartment where Winnie had stashed her belongings nearly two years earlier as she prepared to go on the run. The apartment was a time capsule of a life interrupted, crammed with artifacts from Winnie’s past. There was a pile of instructional DVDs on stripping and exotic dancing and a book filled with the personal confessions of prostitutes, including those who had tried to leave the life but failed.

    However, the contents of her home also suggested Winnie was trying to turn a corner and become an independent businesswoman. She’d obtained a flyer for a local bar for sale and had been chatting online with a supplier of beer-making equipment. Her library was a collection of Chinese-language self-help and educational books with titles such as The Must-Have Book for Cultivating Character, From Mediocrity to Excellence, and Lessons on Managing People.

    Reinvention is now as much a part of China’s mythology as America’s, and Winnie’s collection of books reminded me of Jay Gatsby and the American gospel of self-improvement. She was trying to change and pursue success as her big sister had, part of what Chinese President Xi Jinping has called the Chinese Dream. What set Winnie apart, though, was her earlier path. She had made her money beyond China’s gleaming skyscrapers, in the shadows amid the gritty reality of city life, and she hadn’t been entirely able to leave it behind. Among her belongings were several SIM cards and health-care records indicating that she had operated under an alias for years. One document showed that several months before her disappearance, she’d become pregnant. But there was something odd: A month after the pregnancy test, she went to the hospital under her alias and had her IUD removed, which suggested she couldn’t have been pregnant in the first place.

    There was more. Hidden amid Winnie’s clothing was a handwritten note. “Cao and Winnie must be together for their whole lives,” it read, with what appeared to be a signature from Cao. “If they don’t stay together, Cao’s family must break up and his family members must die.”

    The note implied that if Cao—who had insisted he had been nothing more than a friend—left Winnie, he would curse his own family and wish for their destruction. Stored on Winnie’s laptop were videos of Cao and her cuddling together and having sex, which Cao knew could serve as ammunition if Winnie ever chose to expose their relationship.

    I headed to the hospital that performed the pregnancy test and explained the situation to the doctors. “Please take a look; can you tell us if it is real or fake?” I asked, showing a cellphone photo of the document. The doctor was skeptical. “It’s not done by us,” she said dismissively. “Our department doesn’t have a doctor by this name or an ID number like this. This report is fake.” Another physician called up Winnie’s medical records and found an earlier, legitimate pregnancy test, which had been negative. He said Winnie appeared to have created the positive test using a Word document. “Some girls want to take some leave from their jobs,” the female doctor explained. “Others lie to a man, saying, ‘I’m pregnant,’ to get a sum of money.”

    I was feeling anxious about where our search was heading, so I called Cao and told him I’d seen the note threatening his family. Cao acknowledged the relationship and said in the months before Winnie disappeared, his wife came to Jinghong and discovered the affair. He had a tearful breakup with Winnie, but said they remained friends. He said his wife forgave him. Cao said he last saw Winnie not long before she vanished and thought she’d become a victim of the region’s drug trade or human trafficking.

    I had been working on this trip with the help of my Shanghai news assistant, Yang Zhuo. We were almost out of leads, but had several phone numbers from Winnie’s papers, including one she’d put on a flyer to rent out one of her Jinghong apartments. We didn’t want to spook anyone who might answer, so Yang dialed and I listened in.

    A man picked up. “Do you have any apartments to sell or rent?” Yang asked.

    “Who are you?” the man answered. Yang said he wanted to buy an apartment and had gotten his phone number from a realtor. The man was unconvinced, demanding to know where Yang was at that moment, how Yang had obtained the number and the name of the supposed realtor who had provided it. Yang tried to finesse the answers.

    “Okay,” the man said, “where are you right now?” Yang, sensing danger, declined to say. My heart began beating faster. These were not the questions of someone trying to hang up on a misdialed call or someone who might have been randomly reassigned Winnie’s phone number. This was the longest wrong-number conversation I’d ever heard. “Can we meet up?” the man pressed.

    “If you don’t have an apartment to sell,” Yang responded, “we can forget about it.” There was a long pause and then the man hung up.

    Yang and I looked at each other wide-eyed. The story of Winnie’s disappearance was growing more chilling with each new detail. I spoke with NPR security personnel, who advised that continuing to look for Winnie was unwise. Even Crystal agreed that it was no longer safe to keep digging.

    I never did find out what happened to Winnie. The facts, though, supported a general theory: She’d moved to Yunnan to turn her life around and fallen in love with a married man. She wanted what her big sister had—a stable life with a good income and a lifelong romantic partner. But to secure that, Winnie faked a pregnancy and threatened to expose their affair, a dangerous strategy, even more so on the edge of the Golden Triangle, where few would miss someone like her, another anonymous migrant. Instead of achieving her Chinese dream, Winnie had descended into a Chinese noir.

    I returned to Shanghai and visited Wei Wujun, a private detective I knew who’d made a career of investigating adultery. Wei saw his booming business as a measure of the problems beneath what some called the China miracle. Market economics had thrust the country forward at warp speed, providing previously unimaginable temptations. But the construction of a moral framework to help people grapple with such extraordinary change had lagged far behind. China’s radical transformation was more than most people could absorb or navigate.

    “China’s huge economic success has concealed people’s falling morals and spiritual degradation,” Wei told me. “Its exterior looks shiny and splendid and the entire world is watching, but actually its inside is rotten to the core.”

    I asked Wei what he thought had happened to Winnie. Throughout his years of tracking adultery cases, he said, he’d seen many people who took the sorts of risks Winnie did end up the same way.

    “She’s dead,” he said.

    Before Crystal returned home to the U.S., she made one last attempt to find her little sister. She rode a bus nine hours through the mountains to the hotel where Winnie had last been seen. She put up flyers in the city market and asked people if they’d seen anyone fitting her description. The journey was grueling. The bus passed through military checkpoints and careened along twisting roads with no guardrails. She couldn’t understand the other passengers, who spoke local dialects. As she prepared to fly back to Michigan, I asked Crystal what she had learned in her nearly three weeks in China.

    “I miss my life in America,” she said, laughing and sniffling at the same time. “I think I was spoiled by the civility of America.”

    She also couldn’t shake the sense that she’d failed her baby sister. Crystal had made it out and built a happy life overseas with an attorney husband and a house overlooking a lake, while Winnie spiraled downward thousands of miles away. Under Communism, most people’s lives in China had been pretty similar, but under capitalism, there were winners and losers. Some rode the economic wave and won, while others, like Winnie, lost and paid for it.

    This article is an adapted excerpt from Langfitt’s new book, The Shanghai Free Taxi: Journeys with the Hustlers and Rebels of the New China.

    #Chine #fémicide