Slowly and without fanfare, around the end of the aughts, social media took its place. The change was almost invisible, but it had enormous consequences. Instead of facilitating the modest use of existing connections—largely for offline life (to organize a birthday party, say)—social software turned those connections into a latent broadcast channel. All at once, billions of people saw themselves as celebrities, pundits, and tastemakers.
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The Age of Social Media Is Ending - The Atlantic - 0 views
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A global broadcast network where anyone can say anything to anyone else as often as possible, and where such people have come to think they deserve such a capacity, or even that withholding it amounts to censorship or suppression—that’s just a terrible idea from the outset. And it’s a terrible idea that is entirely and completely bound up with the concept of social media itself: systems erected and used exclusively to deliver an endless stream of content.
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“social media,” a name so familiar that it has ceased to bear meaning. But two decades ago, that term didn’t exist
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a “web 2.0” revolution in “user-generated content,” offering easy-to-use, easily adopted tools on websites and then mobile apps. They were built for creating and sharing “content,”
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As the original name suggested, social networking involved connecting, not publishing. By connecting your personal network of trusted contacts (or “strong ties,” as sociologists call them) to others’ such networks (via “weak ties”), you could surface a larger network of trusted contacts
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The whole idea of social networks was networking: building or deepening relationships, mostly with people you knew. How and why that deepening happened was largely left to the users to decide.
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That changed when social networking became social media around 2009, between the introduction of the smartphone and the launch of Instagram. Instead of connection—forging latent ties to people and organizations we would mostly ignore—social media offered platforms through which people could publish content as widely as possible, well beyond their networks of immediate contacts.
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Social media turned you, me, and everyone into broadcasters (if aspirational ones). The results have been disastrous but also highly pleasurable, not to mention massively profitable—a catastrophic combination.
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A social network is an idle, inactive system—a Rolodex of contacts, a notebook of sales targets, a yearbook of possible soul mates. But social media is active—hyperactive, really—spewing material across those networks instead of leaving them alone until needed.
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The authors propose social media as a system in which users participate in “information exchange.” The network, which had previously been used to establish and maintain relationships, becomes reinterpreted as a channel through which to broadcast.
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The toxicity of social media makes it easy to forget how truly magical this innovation felt when it was new. From 2004 to 2009, you could join Facebook and everyone you’d ever known—including people you’d definitely lost track of—was right there, ready to connect or reconnect. The posts and photos I saw characterized my friends’ changing lives, not the conspiracy theories that their unhinged friends had shared with them
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Twitter, which launched in 2006, was probably the first true social-media site, even if nobody called it that at the time. Instead of focusing on connecting people, the site amounted to a giant, asynchronous chat room for the world. Twitter was for talking to everyone—which is perhaps one of the reasons journalists have flocked to it
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on Twitter, anything anybody posted could be seen instantly by anyone else. And furthermore, unlike posts on blogs or images on Flickr or videos on YouTube, tweets were short and low-effort, making it easy to post many of them a week or even a day.
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When we look back at this moment, social media had already arrived in spirit if not by name. RSS readers offered a feed of blog posts to catch up on, complete with unread counts. MySpace fused music and chatter; YouTube did it with video (“Broadcast Yourself”)
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soon enough, all social networks became social media first and foremost. When groups, pages, and the News Feed launched, Facebook began encouraging users to share content published by others in order to increase engagement on the service, rather than to provide updates to friends. LinkedIn launched a program to publish content across the platform, too. Twitter, already principally a publishing platform, added a dedicated “retweet” feature, making it far easier to spread content virally across user networks.
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From being asked to review every product you buy to believing that every tweet or Instagram image warrants likes or comments or follows, social media produced a positively unhinged, sociopathic rendition of human sociality.
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Other services arrived or evolved in this vein, among them Reddit, Snapchat, and WhatsApp, all far more popular than Twitter. Social networks, once latent routes for possible contact, became superhighways of constant content
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Although you can connect the app to your contacts and follow specific users, on TikTok, you are more likely to simply plug into a continuous flow of video content that has oozed to the surface via algorithm.
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In the social-networking era, the connections were essential, driving both content creation and consumption. But the social-media era seeks the thinnest, most soluble connections possible, just enough to allow the content to flow.
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Facebook and all the rest enjoyed a massive rise in engagement and the associated data-driven advertising profits that the attention-driven content economy created. The same phenomenon also created the influencer economy, in which individual social-media users became valuable as channels for distributing marketing messages or product sponsorships by means of their posts’ real or imagined reach
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“influencer” became an aspirational role, especially for young people for whom Instagram fame seemed more achievable than traditional celebrity—or perhaps employment of any kind.
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social-media operators discovered that the more emotionally charged the content, the better it spread across its users’ networks. Polarizing, offensive, or just plain fraudulent information was optimized for distribution. By the time the platforms realized and the public revolted, it was too late to turn off these feedback loops.
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Rounding up friends or business contacts into a pen in your online profile for possible future use was never a healthy way to understand social relationships.
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when social networking evolved into social media, user expectations escalated. Driven by venture capitalists’ expectations and then Wall Street’s demands, the tech companies—Google and Facebook and all the rest—became addicted to massive scale
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Social media showed that everyone has the potential to reach a massive audience at low cost and high gain—and that potential gave many people the impression that they deserve such an audience.
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On social media, everyone believes that anyone to whom they have access owes them an audience: a writer who posted a take, a celebrity who announced a project, a pretty girl just trying to live her life, that anon who said something afflictive
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When network connections become activated for any reason or no reason, then every connection seems worthy of traversing.
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people just aren’t meant to talk to one another this much. They shouldn’t have that much to say, they shouldn’t expect to receive such a large audience for that expression, and they shouldn’t suppose a right to comment or rejoinder for every thought or notion either.
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This is also why journalists became so dependent on Twitter: It’s a constant stream of sources, events, and reactions—a reporting automat, not to mention an outbound vector for media tastemakers to make tastes.
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That’s no surprise, I guess, given that the model was forged in the fires of Big Tech companies such as Facebook, where sociopathy is a design philosophy.
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If change is possible, carrying it out will be difficult, because we have adapted our lives to conform to social media’s pleasures and torments. It’s seemingly as hard to give up on social media as it was to give up smoking en masse
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Quitting that habit took decades of regulatory intervention, public-relations campaigning, social shaming, and aesthetic shifts. At a cultural level, we didn’t stop smoking just because the habit was unpleasant or uncool or even because it might kill us. We did so slowly and over time, by forcing social life to suffocate the practice. That process must now begin in earnest for social media.
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Something may yet survive the fire that would burn it down: social networks, the services’ overlooked, molten core. It was never a terrible idea, at least, to use computers to connect to one another on occasion, for justified reasons, and in moderation
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The problem came from doing so all the time, as a lifestyle, an aspiration, an obsession. The offer was always too good to be true, but it’s taken us two decades to realize the Faustian nature of the bargain.
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when I first wrote about downscale, the ambition seemed necessary but impossible. It still feels unlikely—but perhaps newly plausible.
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To win the soul of social life, we must learn to muzzle it again, across the globe, among billions of people. To speak less, to fewer people and less often–and for them to do the same to you, and everyone else as well
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We cannot make social media good, because it is fundamentally bad, deep in its very structure. All we can do is hope that it withers away, and play our small part in helping abandon it.
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The Theory That Explains the Structure of the Internet - The Atlantic - 1 views
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A paper posted online last month has reignited a debate about one of the oldest, most startling claims in the modern era of network science: the proposition that most complex networks in the real world—from the World Wide Web to interacting proteins in a cell—are “scale-free.” Roughly speaking, that means that a few of their nodes should have many more connections than others, following a mathematical formula called a power law, so that there’s no one scale that characterizes the network.
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Purely random networks do not obey power laws, so when the early proponents of the scale-free paradigm started seeing power laws in real-world networks in the late 1990s, they viewed them as evidence of a universal organizing principle underlying the formation of these diverse networks. The architecture of scale-freeness, researchers argued, could provide insight into fundamental questions such as how likely a virus is to cause an epidemic, or how easily hackers can disable a network.
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Amazingly simple and far-reaching natural laws govern the structure and evolution of all the complex networks that surround us,” wrote Barabási (who is now at Northeastern University in Boston) in Linked. He later added: “Uncovering and explaining these laws has been a fascinating roller-coaster ride during which we have learned more about our complex, interconnected world than was known in the last hundred years.”
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“These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain,” wrote the study’s authors, Anna Broido and Aaron Clauset of the University of Colorado at Boulder.
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Network scientists agree, by and large, that the paper’s analysis is statistically sound. But when it comes to interpreting its findings, the paper seems to be functioning like a Rorschach test, in which both proponents and critics of the scale-free paradigm see what they already believed to be true. Much of the discussion has played out in vigorous Twitter debates.
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The scale-free paradigm in networks emerged at a historical moment when power laws had taken on an outsize role in statistical physics. In the 1960s and 1970s, they had played a key part in universal laws that underlie phase transitions in a wide range of physical systems, a finding that earned Kenneth Wilson the 1982 Nobel Prize in physics. Soon after, power laws formed the core of two other paradigms that swept across the statistical-physics world: fractals, and a theory about organization in nature called self-organized criticality.
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From the beginning, though, the scale-free paradigm also attracted pushback. Critics pointed out that preferential attachment is far from the only mechanism that can give rise to power laws, and that networks with the same power law can have very different topologies. Some network scientists and domain experts cast doubt on the scale-freeness of specific networks such as power grids, metabolic networks, and the physical internet.
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If you were to observe 1,000 falling objects instead of just a rock and a feather, Clauset says, a clear picture would emerge of how both gravity and air resistance work. But his and Broido’s analysis of nearly 1,000 networks has yielded no similar clarity. “It is reasonable to believe a fundamental phenomenon would require less customized detective work” than Barabási is calling for, Clauset wrote on Twitter.
Tackling the Challenges of Network Administration: A Comprehensive Guide - 7 views
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shared by Javier E on 12 Aug 14
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How a Simple Spambot Became the Second Most Powerful Member of an Italian Social Networ... - 0 views
www.technologyreview.com/...r-of-an-italian-social-network
social network influence popular automated robot
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Luca Maria Aiello and a few pals from the University of Turin in Italy began studying a social network called aNobii.com in which people exchange information and opinions about the books they love. Each person has a site that anybody can visit. Users can then choose to set up social links with others
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To map out the structure of the network, Aiello and co-created an automated crawler that starts by visiting one person’s profile on the network and then all of the people that connect to this node in turn. It then visits each of the people that link to these nodes and so on. In this way, the bot builds up a map of the network
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people began to respond to the crawler’s visits. That gave the team an idea. “The unexpected reactions the bot caused by its visits motivated us to set up a social experiment in two parts to answer the question: can an individual with no trust gain popularity and influence?”
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Aiello and co were careful to ensure that the crawler did not engage with anybody on the network in any way other than to visit his or her node. Their idea was to isolate a single, minimal social activity and test how effective it was in gaining popularity.
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They began to record the reactions to lajello’s visits including the number of messages it received, their content, the links it received and how they varied over time and so on.
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By December 2011, lajello’s profile had become one of the most popular on the entire social network. It had received more than 66,000 visits as well as 2435 messages from more than 1200 different people. In terms of the number of different message received, a well-known writer was the most popular on this network but lajello was second.
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“Our experiment gives strong support to the thesis that popularity can be gained just with continuous “social probing”,” conclude Aiello and co. “We have shown that a very simple spambot can attract great interest even without emulating any aspects of typical human behavior.”
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Having created all this popularity, Aiello and co wanted to find out how influential the spam bot could be. So they started using the bot to send recommendations to users on who else to connect to.The spam bot could either make a recommendation chosen at random or one that was carefully selected by a recommendation engine. It then made its recommendations to users that had already linked to lajello and to other users chosen at random.
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“Among the 361 users who created at least one social connection in the 36 hours after the recommendation, 52 per cent followed suggestion given by the bot,” they say.
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shows just how easy it is for an automated bot to play a significant role in a social network. Popularity appears easy to buy using nothing more than page visits, at least in this experiment. What is more, this popularity can be easily translated into influence
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It is not hard to see the significance of this work. Social bots are a fact of life on almost every social network and many have become so sophisticated they are hard to distinguish from humans. If the simplest of bots created by Aiello and co can have this kind of impact, it is anybody’s guess how more advanced bots could influence everything from movie reviews and Wikipedia entries to stock prices and presidential elections.
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ThinkUp Helps the Social Network User See the Online Self - NYTimes.com - 1 views
www.nytimes.com/...-user-see-the-online-self.html
social network reflection psychology social media self-knowledge self-control
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In addition to a list of people’s most-used words and other straightforward stats like follower counts, ThinkUp shows subscribers more unusual information such as how often they thank and congratulate people, how frequently they swear, whose voices they tend to amplify and which posts get the biggest reaction and from whom.
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after using ThinkUp for about six months, I’ve found it to be an indispensable guide to how I navigate social networks.
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Every morning the service delivers an email packed with information, and in its weighty thoroughness, it reminds you that what you do on Twitter and Facebook can change your life, and other people’s lives, in important, sometimes unforeseen ways.
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ThinkUp is something like Elf on the Shelf for digitally addled adults — a constant reminder that someone is watching you, and that you’re being judged.
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“The goal is to make you act like less of a jerk online,” Ms. Trapani said. “The big goal is to create mindfulness and awareness, and also behavioral change.”
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One of the biggest dangers is saying something off the cuff that might make sense in a particular context, but that sounds completely off the rails to the wider public. The problem, in other words, is acting without thinking — being caught up in the moment, without pausing to reflect on the long-term consequences. You’re never more than a few taps away from an embarrassment that might ruin your career, or at least your reputation, for years to come.
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Because social networks often suggest a false sense of intimacy, they tend to lower people’s self-control.
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Like a drug or perhaps a parasite, they worm into your devices, your daily habits and your every free moment, and they change how you think.Continue reading the main story Continue reading the main story
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people often tweet and update without any perspective about themselves. That’s because Facebook and Twitter, as others have observed, have a way of infecting our brains.
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For those of us most deeply afflicted, myself included, every mundane observation becomes grist for a 140-character quip, and every interaction a potential springboard into an all-consuming, emotionally wrenching flame battle.
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getting a daily reminder from ThinkUp that there are good ways and bad ways to behave online — has a tendency to focus the mind.
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More basically, though, it’s helped me pull back from social networks. Each week, ThinkUp tells me how often I’ve tweeted. Sometimes that number is terribly high — a few weeks ago it was more than 800 times — and I realize I’m probably overtaxing my followers
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ThinkUp charges $5 a month for each social network you connect to it. Is it worth it? After all, there’s a better, more surefire way of avoiding any such long-term catastrophe caused by social media: Just stop using social networks.
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even though “never tweet” became a popular, ironic thing to tweet this year, actually never tweeting, and never being on Facebook, is becoming nearly impossible for many people.
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your online profile plays an important role in how you’re perceived by potential employers. In a recent survey commissioned by the job-hunting site CareerBuilder, almost half of companies said they perused job-seekers’ social networking profiles to look for red flags and to see what sort of image prospective employees portrayed online.
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The main issue constraining growth, the founders say, is that it has been difficult to explain to people why they might need ThinkUp.
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That may change as more people falter on social networks, either by posting unthinking comments that end up damaging their careers, or simply by annoying people to the point that their online presence becomes a hindrance to their real-life prospects.
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The Fall of Facebook - The Atlantic - 0 views
www.theatlantic.com/...2
gatekeeper information facebook social network messaging smartphone technology social media
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Alexis C. Madrigal Nov 17 2014, 7:59 PM ET Social networking is not, it turns out, winner take all. In the past, one might have imagined that switching between Facebook and “some other network” would be difficult, but the smartphone interface makes it easy to be on a dozen networks. All messages come to the same place—the phone’s notifications screen—so what matters is what your friends are doing, not which apps they’re using.
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if I were to put money on an area in which Facebook might be unable to dominate in the future, it would be apps that take advantage of physical proximity. Something radically new could arise on that front, whether it’s an evolution of Yik Yak
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The Social Machine, predicts that text will be a less and less important part of our asynchronous communications mix. Instead, she foresees a “very fluid interface” that would mix text with voice, video, sensor outputs (location, say, or vital signs), and who knows what else
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the forthcoming Apple Watch seems like a step toward the future Donath envisions. Users will be able to send animated smiley faces, drawings, voice snippets, and even their live heartbeats, which will be tapped out on the receiver’s wrist.
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A simple but rich messaging platform—perhaps with specialized hardware—could replace the omnibus social network for most purposes. “I think we’re shifting in a weird way to one-on-one conversations on social networks and in messaging apps,” says Shani Hilton, the executive editor for news at BuzzFeed, the viral-media site. “People don’t want to perform their lives publicly in the same way that they wanted to five years ago.”
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Facebook is built around a trade-off that it has asked users to make: Give us all your personal information, post all your pictures, tag all your friends, and so on, forever. In return, we’ll optimize your social life. But this output is only as good as the input. And it turns out that, when scaled up, creating this input—making yourself legible enough to the Facebook machine that your posts are deemed “relevant” and worthy of being displayed to your mom and your friends—is exhausting labor.
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These new apps, then, are arguments that we can still have an Internet that is weird, and private. That we can still have social networks without the social network. And that we can still have friends on the Internet without “friending” them.
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A Brief History of Information Gatekeepers 1871: Western Union controls 90 percent of U.S. telegraph traffic. 1947: 97 percent of the country’s radio stations are affiliated with one of four national networks. 1969: Viewership for the three nightly network newscasts hits an all-time high, with 50 percent of all American homes tuning in. 1997: About half of all American homes with Internet access get it through America Online. 2002: Microsoft Internet Explorer captures 97 percent of the worldwide browser market. 2014: Amazon sells 63 percent of all books bought online—and 40 percent of books overall.
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Understanding the Social Networks | Talking Points Memo - 0 views
talkingpointsmemo.com/...erstanding-the-social-networks
social network extremism addiction algorithm engagement advertising psychology social media
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Even when people understand in some sense – and often even in detail – how the algorithms work they still tend to see these platforms as modern, digital versions of the town square. There have always been people saying nonsensical things, lying, unknowingly peddling inaccurate information. And our whole civic order is based on a deep skepticism about any authority’s ability to determine what’s true or accurate and what’s not. So really there’s nothing new under the sun, many people say.
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But all of these points become moot when the networks – the virtual pubic square – are actually run by a series of computer programs designed to maximize ‘engagement’ and strong emotion for the purposes of selling advertising.
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But really all these networks are running experiments that put us collectively into the role of Pavlov’s dogs.
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The algorithms are showing you things to see what you react to and showing you more of the things that prompt an emotional response, that make it harder to leave Facebook or Instagram or any of the other social networks.
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really if your goal is to maximize engagement that is of course what you’d do since anger is a far more compelling and powerful emotion than appreciation.
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Facebook didn’t do that. That’s coded into our neurology. Facebook really is an extremism generating machine. It’s really an inevitable part of the core engine.
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it’s not just Facebook. Or perhaps you could say it’s not even Facebook at all. It’s the mix of machine learning and the business models of all the social networks
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They have real upsides. They connect us with people. Show us fun videos. But they are also inherently destructive. And somehow we have to take cognizance of that – and not just as a matter of the business decisions of one company.
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the social networks – meaning the mix of machine learning and advertising/engagement based business models – are really something new under the sun. They’re addiction and extremism generating systems. It’s what they’re designed to do.
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Opinion | How to Be More Resilient - The New York Times - 1 views
www.nytimes.com/...xiety-depression-research.html
resilient toughness happiness psychology brain science stress
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As a psychiatrist, I’ve long wondered why some people get ill in the face of stress and adversity — either mentally or physically — while others rarely succumb.
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not everyone gets PTSD after exposure to extreme trauma, while some people get disabling depression with minimal or no stress
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What makes people resilient, and is it something they are born with or can it be acquired later in life?
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New research suggests that one possible answer can be found in the brain’s so-called central executive network, which helps regulate emotions, thinking and behavior
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used M.R.I. to study the brains of a racially diverse group of 218 people, ages 12 to 14, living in violent neighborhoods in Chicago
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the youths who had higher levels of functional connectivity in the central executive network had better cardiac and metabolic health than their peers with lower levels of connectivity
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when neighborhood homicide rates went up, the young people’s cardiometabolic risk — as measured by obesity, blood-pressure and insulin levels, among other variables — also increased, but only in youths who showed lower activity in this brain network
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“Active resilience happens when people who are vulnerable find resources to cope with stress and bounce back, and do so in a way that leaves them stronger, ready to handle additional stress, in more adaptive ways.”
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the more medically hardy young people were no less anxious or depressed than their less fortunate peers, which suggests that while being more resilient makes you less vulnerable to adversity, it doesn’t guarantee happiness — or even an awareness of being resilient.
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there is good reason to believe the link may be causal because other studies have found that we can change the activity in the self-control network, and increase healthy behaviors, with simple behavioral interventions
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One plausible explanation is that greater activity in this network increases self-control, which most likely reduces some unhealthy behaviors people often use to cope with stress, like eating junk food or smoking
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n one study, two weeks of mindfulness training produced a 60 percent reduction in smoking, compared with no reduction in a control group that focused on relaxation. An M.R.I. following mindfulness training showed increased activity in the anterior cingulate cortex and prefrontal cortex, key brain areas in the executive self-control network
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Clearly self-control is one critical component of resilience that can be easily fostered. But there are others.
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For example, mindfulness training, which involves attention control, emotion regulation and increased self-awareness, can increase connectivity within this network and help people to quit smoking.
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she and colleagues studied the brains of depressed patients who died. They found that the most disrupted genes were those for growth factors, proteins that act like a kind of brain fertilizer.
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“We came to realize that depressed people have lost their power to remodel their brains. And that is in fact devastating because brain remodeling is something we need to do all the time — we are constantly rewiring our brains based on past experience and the expectation of how we need to use them in the future,
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one growth factor that is depleted in depressed brains, called fibroblast growth factor 2, also plays a role in resilience. When they gave it to stressed animals, they bounced back faster and acted less depressed. And when they gave it just once after birth to animals that had been bred for high levels of anxiety and inhibition, they were hardier for the rest of their lives.
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The good news is that we have some control over our own brain BDNF levels: Getting more physical exercise and social support, for example, has been shown to increase BDNF.
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Perhaps someday we might be able to protect young people exposed to violence and adversity by supplementing them with neuroprotective growth factors. We know enough now to help them by fortifying their brains through exercise, mindfulness training and support systems
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Some people have won the genetic sweepstakes and are naturally tough. But there is plenty the rest of us can do to be more resilient and healthier.
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Why it's as hard to escape an echo chamber as it is to flee a cult | Aeon Essays - 0 views
aeon.co/...hamber-as-it-is-to-flee-a-cult
echo-chamber epistemic bubble trust goodwill Descartes network information truth rationality cult filter reliability corroborated bias psychology
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there are two very different phenomena at play here, each of which subvert the flow of information in very distinct ways. Let’s call them echo chambers and epistemic bubbles. Both are social structures that systematically exclude sources of information. Both exaggerate their members’ confidence in their beliefs.
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An epistemic bubble is when you don’t hear people from the other side. An echo chamber is what happens when you don’t trust people from the other side.
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But that omission can also be entirely inadvertent. Even if we’re not actively trying to avoid disagreement, our Facebook friends tend to share our views and interests
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An ‘echo chamber’ is a social structure from which other relevant voices have been actively discredited. Where an epistemic bubble merely omits contrary views, an echo chamber brings its members to actively distrust outsiders.
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an echo chamber is something like a cult. A cult isolates its members by actively alienating them from any outside sources. Those outside are actively labelled as malignant and untrustworthy.
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In epistemic bubbles, other voices are not heard; in echo chambers, other voices are actively undermined.
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The way to break an echo chamber is not to wave “the facts” in the faces of its members. It is to attack the echo chamber at its root and repair that broken trust.
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Looking to others for corroboration is a basic method for checking whether one has reasoned well or badly
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They have been in the limelight lately, most famously in Eli Pariser’s The Filter Bubble (2011) and Cass Sunstein’s #Republic: Divided Democracy in the Age of Social Media (2017).
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The general gist: we get much of our news from Facebook feeds and similar sorts of social media. Our Facebook feed consists mostly of our friends and colleagues, the majority of whom share our own political and cultural views
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various algorithms behind the scenes, such as those inside Google search, invisibly personalise our searches, making it more likely that we’ll see only what we want to see. These processes all impose filters on information.
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Such filters aren’t necessarily bad. The world is overstuffed with information, and one can’t sort through it all by oneself: filters need to be outsourced.
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Each individual person in my network might be superbly reliable about her particular informational patch but, as an aggregate structure, my network lacks what Sanford Goldberg in his book Relying on Others (2010) calls ‘coverage-reliability’. It doesn’t deliver to me a sufficiently broad and representative coverage of all the relevant information.
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An ‘epistemic bubble’ is an informational network from which relevant voices have been excluded by omission
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Suppose that I believe that the Paleo diet is the greatest diet of all time. I assemble a Facebook group called ‘Great Health Facts!’ and fill it only with people who already believe that Paleo is the best diet. The fact that everybody in that group agrees with me about Paleo shouldn’t increase my confidence level one bit. They’re not mere copies – they actually might have reached their conclusions independently – but their agreement can be entirely explained by my method of selection.
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Luckily, though, epistemic bubbles are easily shattered. We can pop an epistemic bubble simply by exposing its members to the information and arguments that they’ve missed.
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Their research centres on Rush Limbaugh, a wildly successful conservative firebrand in the United States, along with Fox News and related media
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His constant attacks on the ‘mainstream media’ are attempts to discredit all other sources of knowledge. He systematically undermines the integrity of anybody who expresses any kind of contrary view.
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outsiders are not simply mistaken – they are malicious, manipulative and actively working to destroy Limbaugh and his followers. The resulting worldview is one of deeply opposed force, an all-or-nothing war between good and evil
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The result is a rather striking parallel to the techniques of emotional isolation typically practised in cult indoctrination
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cult indoctrination involves new cult members being brought to distrust all non-cult members. This provides a social buffer against any attempts to extract the indoctrinated person from the cult.
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The echo chamber doesn’t need any bad connectivity to function. Limbaugh’s followers have full access to outside sources of information
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As Elijah Millgram argues in The Great Endarkenment (2015), modern knowledge depends on trusting long chains of experts. And no single person is in the position to check up on the reliability of every member of that chain
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Their worldview can survive exposure to those outside voices because their belief system has prepared them for such intellectual onslaught.
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exposure to contrary views could actually reinforce their views. Limbaugh might offer his followers a conspiracy theory: anybody who criticises him is doing it at the behest of a secret cabal of evil elites, which has already seized control of the mainstream media.
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Perversely, exposure to outsiders with contrary views can thus increase echo-chamber members’ confidence in their insider sources, and hence their attachment to their worldview.
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‘evidential pre-emption’. What’s happening is a kind of intellectual judo, in which the power and enthusiasm of contrary voices are turned against those contrary voices through a carefully rigged internal structure of belief.
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One might be tempted to think that the solution is just more intellectual autonomy. Echo chambers arise because we trust others too much, so the solution is to start thinking for ourselves.
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that kind of radical intellectual autonomy is a pipe dream. If the philosophical study of knowledge has taught us anything in the past half-century, it is that we are irredeemably dependent on each other in almost every domain of knowledge
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Limbaugh’s followers regularly read – but do not accept – mainstream and liberal news sources. They are isolated, not by selective exposure, but by changes in who they accept as authorities, experts and trusted sources.
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we depend on a vastly complicated social structure of trust. We must trust each other, but, as the philosopher Annette Baier says, that trust makes us vulnerable. Echo chambers operate as a kind of social parasite on that vulnerability, taking advantage of our epistemic condition and social dependency.
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I am quite confident that there are plenty of echo chambers on the political Left. More importantly, nothing about echo chambers restricts them to the arena of politics
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The world of anti-vaccination is clearly an echo chamber, and it is one that crosses political lines. I’ve also encountered echo chambers on topics as broad as diet (Paleo!), exercise technique (CrossFit!), breastfeeding, some academic intellectual traditions, and many, many more
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Here’s a basic check: does a community’s belief system actively undermine the trustworthiness of any outsiders who don’t subscribe to its central dogmas? Then it’s probably an echo chamber.
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much of the recent analysis has lumped epistemic bubbles together with echo chambers into a single, unified phenomenon. But it is absolutely crucial to distinguish between the two.
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Echo chambers are far more pernicious and far more robust. They can start to seem almost like living things. Their belief systems provide structural integrity, resilience and active responses to outside attacks
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the two phenomena can also exist independently. And of the events we’re most worried about, it’s the echo-chamber effects that are really causing most of the trouble.
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new data does, in fact, seem to show that people on Facebook actually do see posts from the other side, or that people often visit websites with opposite political affiliation.
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their basis for evaluation – their background beliefs about whom to trust – are radically different. They are not irrational, but systematically misinformed about where to place their trust.
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Not only do some political figures seem to speak with a blatant disregard for the facts, but their supporters seem utterly unswayed by evidence. It seems, to some, that truth no longer matters.
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This is an explanation in terms of total irrationality. To accept it, you must believe that a great number of people have lost all interest in evidence or investigation, and have fallen away from the ways of reason.
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echo chambers offers a less damning and far more modest explanation. The apparent ‘post-truth’ attitude can be explained as the result of the manipulations of trust wrought by echo chambers.
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We don’t have to attribute a complete disinterest in facts, evidence or reason to explain the post-truth attitude. We simply have to attribute to certain communities a vastly divergent set of trusted authorities.
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An echo chamber doesn’t destroy their members’ interest in the truth; it merely manipulates whom they trust and changes whom they accept as trustworthy sources and institutions.
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in many ways, echo-chamber members are following reasonable and rational procedures of enquiry. They’re engaging in critical reasoning. They’re questioning, they’re evaluating sources for themselves, they’re assessing different pathways to information. They are critically examining those who claim expertise and trustworthiness, using what they already know about the world
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none of this weighs against the existence of echo chambers. We should not dismiss the threat of echo chambers based only on evidence about connectivity and exposure.
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Notice how different what’s going on here is from, say, Orwellian doublespeak, a deliberately ambiguous, euphemism-filled language designed to hide the intent of the speaker.
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echo chambers don’t trade in vague, ambiguous pseudo-speech. We should expect that echo chambers would deliver crisp, clear, unambiguous claims about who is trustworthy and who is not
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clearly articulated conspiracy theories, and crisply worded accusations of an outside world rife with untrustworthiness and corruption.
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In an epistemically healthy life, the variety of our informational sources will put an upper limit to how much we’re willing to trust any single person. Everybody’s fallible; a healthy informational network tends to discover people’s mistakes and point them out. This puts an upper ceiling on how much you can trust even your most beloved leader
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Being caught in an echo chamber is not always the result of laziness or bad faith. Imagine, for instance, that somebody has been raised and educated entirely inside an echo chamber
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when the child finally comes into contact with the larger world – say, as a teenager – the echo chamber’s worldview is firmly in place. That teenager will distrust all sources outside her echo chamber, and she will have gotten there by following normal procedures for trust and learning.
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It certainly seems like our teenager is behaving reasonably. She could be going about her intellectual life in perfectly good faith. She might be intellectually voracious, seeking out new sources, investigating them, and evaluating them using what she already knows.
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The worry is that she’s intellectually trapped. Her earnest attempts at intellectual investigation are led astray by her upbringing and the social structure in which she is embedded.
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Echo chambers might function like addiction, under certain accounts. It might be irrational to become addicted, but all it takes is a momentary lapse – once you’re addicted, your internal landscape is sufficiently rearranged such that it’s rational to continue with your addiction
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Similarly, all it takes to enter an echo chamber is a momentary lapse of intellectual vigilance. Once you’re in, the echo chamber’s belief systems function as a trap, making future acts of intellectual vigilance only reinforce the echo chamber’s worldview.
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There is at least one possible escape route, however. Notice that the logic of the echo chamber depends on the order in which we encounter the evidence. An echo chamber can bring our teenager to discredit outside beliefs precisely because she encountered the echo chamber’s claims first. Imagine a counterpart to our teenager who was raised outside of the echo chamber and exposed to a wide range of beliefs. Our free-range counterpart would, when she encounters that same echo chamber, likely see its many flaws
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Those caught in an echo chamber are giving far too much weight to the evidence they encounter first, just because it’s first. Rationally, they should reconsider their beliefs without that arbitrary preference. But how does one enforce such informational a-historicity?
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Meditations on First Philosophy (1641). He had come to realise that many of the beliefs he had acquired in his early life were false. But early beliefs lead to all sorts of other beliefs, and any early falsehoods he’d accepted had surely infected the rest of his belief system.
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The only solution, thought Descartes, was to throw all his beliefs away and start over again from scratch.
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He could start over, trusting nothing and no one except those things that he could be entirely certain of, and stamping out those sneaky falsehoods once and for all. Let’s call this the Cartesian epistemic reboot.
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Notice how close Descartes’s problem is to our hapless teenager’s, and how useful the solution might be. Our teenager, like Descartes, has problematic beliefs acquired in early childhood. These beliefs have infected outwards, infesting that teenager’s whole belief system. Our teenager, too, needs to throw everything away, and start over again.
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when she starts from scratch, we won’t demand that she trust only what she’s absolutely certain of, nor will we demand that she go it alone
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For the social reboot, she can proceed, after throwing everything away, in an utterly mundane way – trusting her senses, trusting others. But she must begin afresh socially – she must reconsider all possible sources of information with a presumptively equanimous eye. She must take the posture of a cognitive newborn, open and equally trusting to all outside sources
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we’re not asking people to change their basic methods for learning about the world. They are permitted to trust, and trust freely. But after the social reboot, that trust will not be narrowly confined and deeply conditioned by the particular people they happened to be raised by.
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Such a profound deep-cleanse of one’s whole belief system seems to be what’s actually required to escape. Look at the many stories of people leaving cults and echo chambers
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Take, for example, the story of Derek Black in Florida – raised by a neo-Nazi father, and groomed from childhood to be a neo-Nazi leader. Black left the movement by, basically, performing a social reboot. He completely abandoned everything he’d believed in, and spent years building a new belief system from scratch. He immersed himself broadly and open-mindedly in everything he’d missed – pop culture, Arabic literature, the mainstream media, rap – all with an overall attitude of generosity and trust.
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It was the project of years and a major act of self-reconstruction, but those extraordinary lengths might just be what’s actually required to undo the effects of an echo-chambered upbringing.
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we need to attack the root, the systems of discredit themselves, and restore trust in some outside voices.
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Stories of actual escapes from echo chambers often turn on particular encounters – moments when the echo-chambered individual starts to trust somebody on the outside.
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Black’s is case in point. By high school, he was already something of a star on neo-Nazi media, with his own radio talk-show. He went on to college, openly neo-Nazi, and was shunned by almost every other student in his community college. But then Matthew Stevenson, a Jewish fellow undergraduate, started inviting Black to Stevenson’s Shabbat dinners. In Black’s telling, Stevenson was unfailingly kind, open and generous, and slowly earned Black’s trust. This was the seed, says Black, that led to a massive intellectual upheaval – a slow-dawning realisation of the depths to which he had been misled
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Similarly, accounts of people leaving echo-chambered homophobia rarely involve them encountering some institutionally reported fact. Rather, they tend to revolve around personal encounters – a child, a family member, a close friend coming out.
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We don’t simply trust people as educated experts in a field – we rely on their goodwill. And this is why trust, rather than mere reliability, is the key concept
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goodwill is a general feature of a person’s character. If I demonstrate goodwill in action, then you have some reason to think that I also have goodwill in matters of thought and knowledge.
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f one can demonstrate goodwill to an echo-chambered member – as Stevenson did with Black – then perhaps one can start to pierce that echo chamber.
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the path I’m describing is a winding, narrow and fragile one. There is no guarantee that such trust can be established, and no clear path to its being established systematically.
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what we’ve found here isn’t an escape route at all. It depends on the intervention of another. This path is not even one an echo-chamber member can trigger on her own; it is only a whisper-thin hope for rescue from the outside.
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shared by Javier E on 02 Nov 14
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This is what your brain looks like on magic mushrooms (Wired UK) - 0 views
www.wired.co.uk/...c-mushrooms-does-to-your-brain
brain science research neural nets consciousness drugs
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In recent years, a focus on brain structures and regions has given way to an emphasis on neurological networks: how cells and regions interact, with consciousness shaped not by any given set of brain regions, but by their interplay.
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In mathematical terms, said Petri, normal brains have a well-ordered correlation state. There's not much cross-linking between networks. That changes after the psilocybin dose. Suddenly the networks are cross-linking like crazy, but not in random ways. New types of order emerge.
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Perhaps some aspects of consciousness arise from these meta-networks -- and to investigate the proposition, the researchers analysed fMRI scans of 15 people after being injected with psilocybin, the active ingredient in magic mushrooms, and compared them to scans of their brain activity after receiving a placebo.
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"One possible by-product of this greater communication across the whole brain is the phenomenon of synaesthesia" -- the experience, common during psychedelic experiences, of sensory mix-up: tasting colours, feeling sounds, seeing smells, and so on.
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A truer way of visualising it, he said, would be in three dimensions, with connections between networks forming a sponge-like topography.
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"The big question in neuroscience is where consciousness comes from," Petri said. For now, he said, "We don't know."
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The Economics of Bitcoin - Econlib - 0 views
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Bitcoin is an ingenious peer-to-peer “virtual” or “digital currency” that challenges the way economists have traditionally thought about money.
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My conclusion is that, in principle, nothing stands in the way of the whole world embracing Bitcoin or some other digital currency. Yet I predict that, even with the alternative of Bitcoin, people would resort to gold if only governments got out of the way.
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According to its official website: “Bitcoin uses peer-to-peer technology to operate with no central authority; managing transactions and the issuing of bitcoins is carried out collectively by the network.”
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To fully understand how Bitcoin operates, one would need to learn the subtleties of public-key cryptography.
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In the real world, when people want to buy something using Bitcoin, they transfer their ownership of a certain number of bitcoins to other people, in exchange for goods and services.
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This transfer is effected by the network of computers performing computations and thereby changing the “public key” to which the “sold” bitcoins are assigned.
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The encryption involved in Bitcoin concerns the identification of the legitimate owner of a particular bitcoin.
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Without delving into the mathematics, suffice it to say: There is a way that the legitimate owner of a bitcoin can publicly demonstrate to the computers in the network that he or she really is the owner of that bitcoin.
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Only someone with the possession of the “private key” will be able to produce a valid “signature” that convinces the computers in the network to update the public ledger to reflect the transfer of the bitcoin to another party.
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When Bitcoin was first implemented in early 2009, computers in the network—dubbed “miners”—received 50 new bitcoins when performing the computations necessary to add a “block” of transactions to the public ledger.
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In principle, the developers of Bitcoin could have released all 21 million units of the currency immediately with the software.
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With the current arrangement—where the “mining” operations needed to keep the system running simultaneously yield new bitcoins to the machines performing the calculations—there is an incentive for owners to devote their machines’ processing power to the network.
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Here, the danger is that the issuing institution—once it had gotten the world to accept its notes or electronic deposits as money—would face an irresistible temptation to issue massive quantities.6
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Bitcoin has no such vulnerability. No external technological or physical event could cause Bitcoin inflation, and since no one is in charge of Bitcoin, there is no one tempted to inflate “from within.”
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Some critics argue that Bitcoin’s fixed quantity would imply constant price deflation. Although this is true, everyone will have seen this coming with more than a century’s notice, and so long-term contracts would have been designed accordingly.
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Whether to call Bitcoin a “fiat” currency depends on the definition. If “fiat” means a currency that is not legally redeemable in some other commodity, then yes, Bitcoin is a fiat currency. But if “fiat” means a currency relying on government fiat to define what will count as legal money, then Bitcoin is not.
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Bitcoin is an ingenious concept that challenges the way economists have traditionally thought about money. Its inbuilt scarcity provides an assurance of purchasing power arguably safer than any other system yet conceived.
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Opinion | Trump May Start a Social Network. Here's My Advice. - The New York Times - 0 views
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Recast your past failures as successes, engage in meaningless optics, and other tips from the Silicon Valley playbook.
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Tech is hard stuff, and new ventures should be attempted with extreme care, especially by those whose history of entrepreneurship is littered with the carcasses of, say, Trump Steaks.
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Or Trump Water. Or Trump University. Or Trump magazine. Or Trump Casinos. Or Trump Mortgages. Or Trump Airlines. Or Trump Vodka. Or the Trump pandemic response. Or, of course, the 2020 Trump presidential campaign.
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Even if “fail” and “don’t work” are the same thing, in tech these are seen as a badge of honor rather than as a sign that you are terrible at executing a business plan and engage in only meaningless optics.
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uckily, this fits right in your wheelhouse — a talent that you have displayed in spades since the beginnings of your career.
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“genius is 1 percent inspiration and 99 percent perspiration.” I might rephrase that for your entry into tech by saying, genius is 1 percent instigation and 99 percent perfidy.
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Instigation and perfidy, in fact, make the perfect formula for a modern-day social network, so you are already well on your way, given your skill set.
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Self-aggrandizing though badly spelled streams that actually reveal a profound lack of self-esteem? Check.
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Inciting violence over election fraud with both explicit and cryptic messages to your base, in order to get them to think they should attack the Capitol, like, for real? Checkmate
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A social network requires a lot of it, including servers, apps and content moderation tools. You’ll need a whole army of geeks whom you’ll have to pay real money.
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As for your future competitors … Twitter has seen its shares rise sharply since it tossed you off for life.
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You still might get a reprieve over at Facebook, where an oversight board is contemplating your fate. We’ll see what the chief executive, Mark Zuckerberg, decides after the board makes a ruling.
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Keep in mind, Mr. Zuckerberg really is the most powerful man in the world; that was even the case when you were in the Oval Office.
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Avoid MeinSpace and InstaGraft, for obvious reasons. The narcissist in you might go for The_Donald, which you might now be able to use, since Reddit banned the 800,000-member forum with that name for violating its rules against harassment, hate speech, content manipulation and more.
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shared by johnsonel7 on 20 Oct 19
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Computers Are Learning to Read-But They're Still Not So Smart | WIRED - 0 views
www.wired.com/...-but-theyre-still-not-so-smart
research artificial intelligence pattern recognition
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computers still weren’t very good at understanding the written word. Sure, they had become decent at simulating that understanding in certain narrow domains, like automatic translation or sentiment analysis (for example, determining if a sentence sounds “mean or nice,” he said). But Bowman wanted measurable evidence of the genuine article: bona fide, human-style reading comprehension in English. So he came up with a test
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The machines bombed. Even state-of-the-art neural networks scored no higher than 69 out of 100 across all nine tasks: a D-plus, in letter grade terms. Bowman and his coauthors weren’t surprised. Neural networks — layers of computational connections built in a crude approximation of how neurons communicate within mammalian brains
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It produced a GLUE score of 80.5. On this brand-new benchmark designed to measure machines’ real understanding of natural language — or to expose their lack thereof — the machines had jumped from a D-plus to a B-minus in just six months.
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The only problem is that perfect rulebooks don’t exist, because natural language is far too complex and haphazard to be reduced to a rigid set of specifications.
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Researchers simply fed their neural networks massive amounts of written text copied from freely available sources like Wikipedia — billions of words, preformatted into grammatically correct sentences — and let the networks derive next-word predictions on their own. In essence, it was like asking the person inside a Chinese room to write all his own rules, using only the incoming Chinese messages for reference.“The great thing about this approach is it turns out that the model learns a ton of stuff about syntax,”
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The nonsequential nature of the transformer represented sentences in a more expressive form, which Uszkoreit calls treelike. Each layer of the neural network makes multiple, parallel connections between certain words while ignoring others — akin to a student diagramming a sentence in elementary school. These connections are often drawn between words that may not actually sit next to each other in the sentence. “Those structures effectively look like a number of trees that are overlaid,” Uszkoreit explained.
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But instead of concluding that BERT could apparently imbue neural networks with near-Aristotelian reasoning skills, they suspected a simpler explanation: that BERT was picking up on superficial patterns in the way the warrants were phrased.