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Javier E

The Coming Software Apocalypse - The Atlantic - 1 views

www.theatlantic.com/...540393

software programming failure design

shared by Javier E on 26 Sep 17 - No Cached
  • Our standard framework for thinking about engineering failures—reflected, for instance, in regulations for medical devices—was developed shortly after World War II, before the advent of software, for electromechanical systems. The idea was that you make something reliable by making its parts reliable (say, you build your engine to withstand 40,000 takeoff-and-landing cycles) and by planning for the breakdown of those parts (you have two engines). But software doesn’t break. Intrado’s faulty threshold is not like the faulty rivet that leads to the crash of an airliner. The software did exactly what it was told to do. In fact it did it perfectly. The reason it failed is that it was told to do the wrong thing.
  • Software failures are failures of understanding, and of imagination. Intrado actually had a backup router, which, had it been switched to automatically, would have restored 911 service almost immediately. But, as described in a report to the FCC, “the situation occurred at a point in the application logic that was not designed to perform any automated corrective actions.”
  • “The problem is that software engineers don’t understand the problem they’re trying to solve, and don’t care to,” says Leveson, the MIT software-safety expert. The reason is that they’re too wrapped up in getting their code to work.
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  • Code is too hard to think about. Before trying to understand the attempts themselves, then, it’s worth understanding why this might be: what it is about code that makes it so foreign to the mind, and so unlike anything that came before it.
  • Technological progress used to change the way the world looked—you could watch the roads getting paved; you could see the skylines rise. Today you can hardly tell when something is remade, because so often it is remade by code.
  • Software has enabled us to make the most intricate machines that have ever existed. And yet we have hardly noticed, because all of that complexity is packed into tiny silicon chips as millions and millions of lines of cod
  • The programmer, the renowned Dutch computer scientist Edsger Dijkstra wrote in 1988, “has to be able to think in terms of conceptual hierarchies that are much deeper than a single mind ever needed to face before.” Dijkstra meant this as a warning.
  • As programmers eagerly poured software into critical systems, they became, more and more, the linchpins of the built world—and Dijkstra thought they had perhaps overestimated themselves.
  • What made programming so difficult was that it required you to think like a computer.
  • The introduction of programming languages like Fortran and C, which resemble English, and tools, known as “integrated development environments,” or IDEs, that help correct simple mistakes (like Microsoft Word’s grammar checker but for code), obscured, though did little to actually change, this basic alienation—the fact that the programmer didn’t work on a problem directly, but rather spent their days writing out instructions for a machine.
  • Though he runs a lab that studies the future of computing, he seems less interested in technology per se than in the minds of the people who use it. Like any good toolmaker, he has a way of looking at the world that is equal parts technical and humane. He graduated top of his class at the California Institute of Technology for electrical engineering,
  • “The serious problems that have happened with software have to do with requirements, not coding errors.” When you’re writing code that controls a car’s throttle, for instance, what’s important is the rules about when and how and by how much to open it. But these systems have become so complicated that hardly anyone can keep them straight in their head. “There’s 100 million lines of code in cars now,” Leveson says. “You just cannot anticipate all these things.”
  • a nearly decade-long investigation into claims of so-called unintended acceleration in Toyota cars. Toyota blamed the incidents on poorly designed floor mats, “sticky” pedals, and driver error, but outsiders suspected that faulty software might be responsible
  • software experts spend 18 months with the Toyota code, picking up where NASA left off. Barr described what they found as “spaghetti code,” programmer lingo for software that has become a tangled mess. Code turns to spaghetti when it accretes over many years, with feature after feature piling on top of, and being woven around
  • Using the same model as the Camry involved in the accident, Barr’s team demonstrated that there were actually more than 10 million ways for the onboard computer to cause unintended acceleration. They showed that as little as a single bit flip—a one in the computer’s memory becoming a zero or vice versa—could make a car run out of control. The fail-safe code that Toyota had put in place wasn’t enough to stop it
  • . In all, Toyota recalled more than 9 million cars, and paid nearly $3 billion in settlements and fines related to unintended acceleration.
  • The problem is that programmers are having a hard time keeping up with their own creations. Since the 1980s, the way programmers work and the tools they use have changed remarkably little.
  • This is the trouble with making things out of code, as opposed to something physical. “The complexity,” as Leveson puts it, “is invisible to the eye.”
  • The fact that the two of them were thinking about the same problem in the same terms, at the same time, was not a coincidence. They had both just seen the same remarkable talk, given to a group of software-engineering students in a Montreal hotel by a computer researcher named Bret Victor. The talk, which went viral when it was posted online in February 2012, seemed to be making two bold claims. The first was that the way we make software is fundamentally broken. The second was that Victor knew how to fix it.
  • “Visual Studio is one of the single largest pieces of software in the world,” he said. “It’s over 55 million lines of code. And one of the things that I found out in this study is more than 98 percent of it is completely irrelevant. All this work had been put into this thing, but it missed the fundamental problems that people faced. And the biggest one that I took away from it was that basically people are playing computer inside their head.” Programmers were like chess players trying to play with a blindfold on—so much of their mental energy is spent just trying to picture where the pieces are that there’s hardly any left over to think about the game itself.
  • in early 2012, Victor had finally landed upon the principle that seemed to thread through all of his work. (He actually called the talk “Inventing on Principle.”) The principle was this: “Creators need an immediate connection to what they’re creating.” The problem with programming was that it violated the principle. That’s why software systems were so hard to think about, and so rife with bugs: The programmer, staring at a page of text, was abstracted from whatever it was they were actually making.
  • “Our current conception of what a computer program is,” he said, is “derived straight from Fortran and ALGOL in the late ’50s. Those languages were designed for punch cards.”
  • WYSIWYG (pronounced “wizzywig”) came along. It stood for “What You See Is What You Get.”
  • Victor’s point was that programming itself should be like that. For him, the idea that people were doing important work, like designing adaptive cruise-control systems or trying to understand cancer, by staring at a text editor, was appalling.
  • With the right interface, it was almost as if you weren’t working with code at all; you were manipulating the game’s behavior directly.
  • When the audience first saw this in action, they literally gasped. They knew they weren’t looking at a kid’s game, but rather the future of their industry. Most software involved behavior that unfolded, in complex ways, over time, and Victor had shown that if you were imaginative enough, you could develop ways to see that behavior and change it, as if playing with it in your hands. One programmer who saw the talk wrote later: “Suddenly all of my tools feel obsolete.”
  • hen John Resig saw the “Inventing on Principle” talk, he scrapped his plans for the Khan Academy programming curriculum. He wanted the site’s programming exercises to work just like Victor’s demos. On the left-hand side you’d have the code, and on the right, the running program: a picture or game or simulation. If you changed the code, it’d instantly change the picture. “In an environment that is truly responsive,” Resig wrote about the approach, “you can completely change the model of how a student learns ... [They] can now immediately see the result and intuit how underlying systems inherently work without ever following an explicit explanation.” Khan Academy has become perhaps the largest computer-programming class in the world, with a million students, on average, actively using the program each month.
  • “Everyone thought I was interested in programming environments,” he said. Really he was interested in how people see and understand systems—as he puts it, in the “visual representation of dynamic behavior.” Although code had increasingly become the tool of choice for creating dynamic behavior, it remained one of the worst tools for understanding it. The point of “Inventing on Principle” was to show that you could mitigate that problem by making the connection between a system’s behavior and its code immediate.
  • “Typically the main problem with software coding—and I’m a coder myself,” Bantegnie says, “is not the skills of the coders. The people know how to code. The problem is what to code. Because most of the requirements are kind of natural language, ambiguous, and a requirement is never extremely precise, it’s often understood differently by the guy who’s supposed to code.”
  • In a pair of later talks, “Stop Drawing Dead Fish” and “Drawing Dynamic Visualizations,” Victor went one further. He demoed two programs he’d built—the first for animators, the second for scientists trying to visualize their data—each of which took a process that used to involve writing lots of custom code and reduced it to playing around in a WYSIWYG interface.
  • Victor suggested that the same trick could be pulled for nearly every problem where code was being written today. “I’m not sure that programming has to exist at all,” he told me. “Or at least software developers.” In his mind, a software developer’s proper role was to create tools that removed the need for software developers. Only then would people with the most urgent computational problems be able to grasp those problems directly, without the intermediate muck of code.
  • Victor implored professional software developers to stop pouring their talent into tools for building apps like Snapchat and Uber. “The inconveniences of daily life are not the significant problems,” he wrote. Instead, they should focus on scientists and engineers—as he put it to me, “these people that are doing work that actually matters, and critically matters, and using really, really bad tools.”
  • Bantegnie’s company is one of the pioneers in the industrial use of model-based design, in which you no longer write code directly. Instead, you create a kind of flowchart that describes the rules your program should follow (the “model”), and the computer generates code for you based on those rules
  • In a model-based design tool, you’d represent this rule with a small diagram, as though drawing the logic out on a whiteboard, made of boxes that represent different states—like “door open,” “moving,” and “door closed”—and lines that define how you can get from one state to the other. The diagrams make the system’s rules obvious: Just by looking, you can see that the only way to get the elevator moving is to close the door, or that the only way to get the door open is to stop.
  • . In traditional programming, your task is to take complex rules and translate them into code; most of your energy is spent doing the translating, rather than thinking about the rules themselves. In the model-based approach, all you have is the rules. So that’s what you spend your time thinking about. It’s a way of focusing less on the machine and more on the problem you’re trying to get it to solve.
  • The ideas spread. The notion of liveness, of being able to see data flowing through your program instantly, made its way into flagship programming tools offered by Google and Apple. The default language for making new iPhone and Mac apps, called Swift, was developed by Apple from the ground up to support an environment, called Playgrounds, that was directly inspired by Light Table.
  • On this view, software becomes unruly because the media for describing what software should do—conversations, prose descriptions, drawings on a sheet of paper—are too different from the media describing what software does do, namely, code itself.
  • for this approach to succeed, much of the work has to be done well before the project even begins. Someone first has to build a tool for developing models that are natural for people—that feel just like the notes and drawings they’d make on their own—while still being unambiguous enough for a computer to understand. They have to make a program that turns these models into real code. And finally they have to prove that the generated code will always do what it’s supposed to.
  • tice brings order and accountability to large codebases. But, Shivappa says, “it’s a very labor-intensive process.” He estimates that before they used model-based design, on a two-year-long project only two to three months was spent writing code—the rest was spent working on the documentation.
  • uch of the benefit of the model-based approach comes from being able to add requirements on the fly while still ensuring that existing ones are met; with every change, the computer can verify that your program still works. You’re free to tweak your blueprint without fear of introducing new bugs. Your code is, in FAA parlance, “correct by construction.”
  • “people are not so easily transitioning to model-based software development: They perceive it as another opportunity to lose control, even more than they have already.”
  • The bias against model-based design, sometimes known as model-driven engineering, or MDE, is in fact so ingrained that according to a recent paper, “Some even argue that there is a stronger need to investigate people’s perception of MDE than to research new MDE technologies.”
  • “Human intuition is poor at estimating the true probability of supposedly ‘extremely rare’ combinations of events in systems operating at a scale of millions of requests per second,” he wrote in a paper. “That human fallibility means that some of the more subtle, dangerous bugs turn out to be errors in design; the code faithfully implements the intended design, but the design fails to correctly handle a particular ‘rare’ scenario.”
  • Newcombe was convinced that the algorithms behind truly critical systems—systems storing a significant portion of the web’s data, for instance—ought to be not just good, but perfect. A single subtle bug could be catastrophic. But he knew how hard bugs were to find, especially as an algorithm grew more complex. You could do all the testing you wanted and you’d never find them all.
  • An algorithm written in TLA+ could in principle be proven correct. In practice, it allowed you to create a realistic model of your problem and test it not just thoroughly, but exhaustively. This was exactly what he’d been looking for: a language for writing perfect algorithms.
  • TLA+, which stands for “Temporal Logic of Actions,” is similar in spirit to model-based design: It’s a language for writing down the requirements—TLA+ calls them “specifications”—of computer programs. These specifications can then be completely verified by a computer. That is, before you write any code, you write a concise outline of your program’s logic, along with the constraints you need it to satisfy
  • Programmers are drawn to the nitty-gritty of coding because code is what makes programs go; spending time on anything else can seem like a distraction. And there is a patient joy, a meditative kind of satisfaction, to be had from puzzling out the micro-mechanics of code. But code, Lamport argues, was never meant to be a medium for thought. “It really does constrain your ability to think when you’re thinking in terms of a programming language,”
  • Code makes you miss the forest for the trees: It draws your attention to the working of individual pieces, rather than to the bigger picture of how your program fits together, or what it’s supposed to do—and whether it actually does what you think. This is why Lamport created TLA+. As with model-based design, TLA+ draws your focus to the high-level structure of a system, its essential logic, rather than to the code that implements it.
  • But TLA+ occupies just a small, far corner of the mainstream, if it can be said to take up any space there at all. Even to a seasoned engineer like Newcombe, the language read at first as bizarre and esoteric—a zoo of symbols.
  • this is a failure of education. Though programming was born in mathematics, it has since largely been divorced from it. Most programmers aren’t very fluent in the kind of math—logic and set theory, mostly—that you need to work with TLA+. “Very few programmers—and including very few teachers of programming—understand the very basic concepts and how they’re applied in practice. And they seem to think that all they need is code,” Lamport says. “The idea that there’s some higher level than the code in which you need to be able to think precisely, and that mathematics actually allows you to think precisely about it, is just completely foreign. Because they never learned it.”
  • “In the 15th century,” he said, “people used to build cathedrals without knowing calculus, and nowadays I don’t think you’d allow anyone to build a cathedral without knowing calculus. And I would hope that after some suitably long period of time, people won’t be allowed to write programs if they don’t understand these simple things.”
  • Programmers, as a species, are relentlessly pragmatic. Tools like TLA+ reek of the ivory tower. When programmers encounter “formal methods” (so called because they involve mathematical, “formally” precise descriptions of programs), their deep-seated instinct is to recoil.
  • Formal methods had an image problem. And the way to fix it wasn’t to implore programmers to change—it was to change yourself. Newcombe realized that to bring tools like TLA+ to the programming mainstream, you had to start speaking their language.
  • he presented TLA+ as a new kind of “pseudocode,” a stepping-stone to real code that allowed you to exhaustively test your algorithms—and that got you thinking precisely early on in the design process. “Engineers think in terms of debugging rather than ‘verification,’” he wrote, so he titled his internal talk on the subject to fellow Amazon engineers “Debugging Designs.” Rather than bemoan the fact that programmers see the world in code, Newcombe embraced it. He knew he’d lose them otherwise. “I’ve had a bunch of people say, ‘Now I get it,’” Newcombe says.
  • In the world of the self-driving car, software can’t be an afterthought. It can’t be built like today’s airline-reservation systems or 911 systems or stock-trading systems. Code will be put in charge of hundreds of millions of lives on the road and it has to work. That is no small task.
Javier E

It's Time for a Real Code of Ethics in Teaching - Noah Berlatsky - The Atlantic - 3 views

www.theatlantic.com/...274722

ethics teaching cheating analysis education

shared by Javier E on 07 Apr 13 - No Cached
  • More 5inShare Email Print A defendant in the Atlanta Public Schools case turns herself in at the Fulton County Jail on April 2. (David Goldman/AP) Earlier this week at The Atlantic, Emily Richmond asked whether high-stakes testing caused the Atlanta schools cheating scandal. The answer, I would argue, is yes... just not in the way you might think. Tests don't cause unethical behavior. But they did cause the Atlanta cheating scandal, and they are doing damage to the teaching profession. The argument that tests do not cause unethical behavior is fairly straightforward, and has been articulated by a number of writers. Jonathan Chait quite correctly points out that unethical behavior occurs in virtually all professions -- and that it occurs particularly when there are clear incentives to succeed. Incentivizing any field increases the impetus to cheat. Suppose journalism worked the way teaching traditionally had. You get hired at a newspaper, and your advancement and pay are dictated almost entirely by your years on the job, with almost no chance of either becoming a star or of getting fired for incompetence. Then imagine journalists changed that and instituted the current system, where you can get really successful if your bosses like you or be fired if they don't. You could look around and see scandal after scandal -- phone hacking! Jayson Blair! NBC's exploding truck! Janet Cooke! Stephen Glass! -- that could plausibly be attributed to this frightening new world in which journalists had an incentive to cheat in order to get ahead. It holds true of any field. If Major League Baseball instituted tenure, and maybe used tee-ball rules where you can't keep score and everybody gets a chance to hit, it could stamp out steroid use. Students have been cheating on tests forever -- massive, systematic cheating, you could say. Why? Because they have an incentive to do well. Give teachers and administrators an incentive for their students to do well, and more of them will cheat. For Chait, then, teaching has just been made more like journalism or baseball; it has gone from an incentiveless occupation to one with incentives.
  • Chait refers to violations of journalistic ethics -- like the phone-hacking scandal -- and suggests they are analogous to Major-League steroid use, and that both are similar to teachers (or students) cheating on tests. But is phone hacking "cheating"
  • Phone hacking was, then, not an example of cheating. It was a violation of professional ethics. And those ethics are not arbitrarily imposed, but are intrinsic to the practice of journalism as a profession committed to public service and to truth.
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  • Using "cheating" as an ethical lens tends to both trivialize and infantilize teacher's work
  • Ethics for teachers is not, apparently, first and foremost about educating their students, or broadening their minds. Rather, ethics for teachers in our current system consists in following the rules. The implicit, linguistic signal being given is that teachers are not like journalists or doctors, committed to a profession and to the moral code needed to achieve their professional goals. Instead, they are like athletes playing games, or (as Chait says) like children taking tests.
  • Behaving ethically matters, but how it matters, and what it means, depends strongly on the context in which it occurs.
  • Professions with social respect and social capital, like doctors and lawyers, collaborate in the creation of their own standards. The assumption is that those standards are intrinsic to the profession's goals, and that, therefore, professionals themselves are best equipped to establish and monitor them. Teachers' standards, though, are imposed from outside -- as if teachers are children, or as if teaching is a game.
  • High-stakes testing, then, does leads to cheating. It does not create unethical behavior -- but it does create the particular unethical behavior of "cheating."
  • We have reached a point where we can only talk about the ethics of the profession in terms of cheating or not cheating, as if teachers' main ethical duty is to make sure that scantron bubbles get filled in correctly. Teachers, like journalists, should have a commitment to truth; like doctors, they have a duty of care. Translating those commitments and duties into a bureaucratized measure of cheating-or-not-cheating diminishes ethic
  • For teachers it is, literally, demoralizing. It severs the moral experience of teaching from the moral evaluation of teaching, which makes it almost impossible for good teachers (in all the senses of "good") to stay in the system.
  • We need better ethics for teachers -- ethics that treat them as adults and professionals, not like children playing games.
Javier E

They're Watching You at Work - Don Peck - The Atlantic - 2 views

www.theatlantic.com/...354681

data analytics work Big Data university potential aptitude

shared by Javier E on 16 Dec 13 - No Cached
  • Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.
  • By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007.
  • The application of predictive analytics to people’s careers—an emerging field sometimes called “people analytics”—is enormously challenging, not to mention ethically fraught
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  • By the end of World War II, however, American corporations were facing severe talent shortages. Their senior executives were growing old, and a dearth of hiring from the Depression through the war had resulted in a shortfall of able, well-trained managers. Finding people who had the potential to rise quickly through the ranks became an overriding preoccupation of American businesses. They began to devise a formal hiring-and-management system based in part on new studies of human behavior, and in part on military techniques developed during both world wars, when huge mobilization efforts and mass casualties created the need to get the right people into the right roles as efficiently as possible. By the 1950s, it was not unusual for companies to spend days with young applicants for professional jobs, conducting a battery of tests, all with an eye toward corner-office potential.
  • But companies abandoned their hard-edged practices for another important reason: many of their methods of evaluation turned out not to be very scientific.
  • this regime, so widespread in corporate America at mid-century, had almost disappeared by 1990. “I think an HR person from the late 1970s would be stunned to see how casually companies hire now,”
  • Many factors explain the change, he said, and then he ticked off a number of them: Increased job-switching has made it less important and less economical for companies to test so thoroughly. A heightened focus on short-term financial results has led to deep cuts in corporate functions that bear fruit only in the long term. The Civil Rights Act of 1964, which exposed companies to legal liability for discriminatory hiring practices, has made HR departments wary of any broadly applied and clearly scored test that might later be shown to be systematically biased.
  • about a quarter of the country’s corporations were using similar tests to evaluate managers and junior executives, usually to assess whether they were ready for bigger roles.
  • Aptitude, skills, personal history, psychological stability, discretion, loyalty—companies at the time felt they had a need (and the right) to look into them all. That ambit is expanding once again, and this is undeniably unsettling. Should the ideas of scientists be dismissed because of the way they play a game? Should job candidates be ranked by what their Web habits say about them? Should the “data signature” of natural leaders play a role in promotion? These are all live questions today, and they prompt heavy concerns: that we will cede one of the most subtle and human of skills, the evaluation of the gifts and promise of other people, to machines; that the models will get it wrong; that some people will never get a shot in the new workforce.
  • Knack makes app-based video games, among them Dungeon Scrawl, a quest game requiring the player to navigate a maze and solve puzzles, and Wasabi Waiter, which involves delivering the right sushi to the right customer at an increasingly crowded happy hour. These games aren’t just for play: they’ve been designed by a team of neuroscientists, psychologists, and data scientists to suss out human potential. Play one of them for just 20 minutes, says Guy Halfteck, Knack’s founder, and you’ll generate several megabytes of data, exponentially more than what’s collected by the SAT or a personality test. How long you hesitate before taking every action, the sequence of actions you take, how you solve problems—all of these factors and many more are logged as you play, and then are used to analyze your creativity, your persistence, your capacity to learn quickly from mistakes, your ability to prioritize, and even your social intelligence and personality. The end result, Halfteck says, is a high-resolution portrait of your psyche and intellect, and an assessment of your potential as a leader or an innovator.
  • When the results came back, Haringa recalled, his heart began to beat a little faster. Without ever seeing the ideas, without meeting or interviewing the people who’d proposed them, without knowing their title or background or academic pedigree, Knack’s algorithm had identified the people whose ideas had panned out. The top 10 percent of the idea generators as predicted by Knack were in fact those who’d gone furthest in the process.
  • What Knack is doing, Haringa told me, “is almost like a paradigm shift.” It offers a way for his GameChanger unit to avoid wasting time on the 80 people out of 100—nearly all of whom look smart, well-trained, and plausible on paper—whose ideas just aren’t likely to work out.
  • He has encouraged the company’s HR executives to think about applying the games to the recruitment and evaluation of all professional workers.
  • scoring distance from work could violate equal-employment-opportunity standards. Marital status? Motherhood? Church membership? “Stuff like that,” Meyerle said, “we just don’t touch”—at least not in the U.S., where the legal environment is strict. Meyerle told me that Evolv has looked into these sorts of factors in its work for clients abroad, and that some of them produce “startling results.”
  • consider the alternative. A mountain of scholarly literature has shown that the intuitive way we now judge professional potential is rife with snap judgments and hidden biases, rooted in our upbringing or in deep neurological connections that doubtless served us well on the savanna but would seem to have less bearing on the world of work.
  • We may like to think that society has become more enlightened since those days, and in many ways it has, but our biases are mostly unconscious, and they can run surprisingly deep. Consider race. For a 2004 study called “Are Emily and Greg More Employable Than Lakisha and Jamal?,” the economists Sendhil Mullainathan and Marianne Bertrand put white-sounding names (Emily Walsh, Greg Baker) or black-sounding names (Lakisha Washington, Jamal Jones) on similar fictitious résumés, which they then sent out to a variety of companies in Boston and Chicago. To get the same number of callbacks, they learned, they needed to either send out half again as many résumés with black names as those with white names, or add eight extra years of relevant work experience to the résumés with black names.
  • a sociologist at Northwestern, spent parts of the three years from 2006 to 2008 interviewing professionals from elite investment banks, consultancies, and law firms about how they recruited, interviewed, and evaluated candidates, and concluded that among the most important factors driving their hiring recommendations were—wait for it—shared leisure interests.
  • Lacking “reliable predictors of future performance,” Rivera writes, “assessors purposefully used their own experiences as models of merit.” Former college athletes “typically prized participation in varsity sports above all other types of involvement.” People who’d majored in engineering gave engineers a leg up, believing they were better prepared.
  • the prevailing system of hiring and management in this country involves a level of dysfunction that should be inconceivable in an economy as sophisticated as ours. Recent survey data collected by the Corporate Executive Board, for example, indicate that nearly a quarter of all new hires leave their company within a year of their start date, and that hiring managers wish they’d never extended an offer to one out of every five members on their team
  • In the late 1990s, as these assessments shifted from paper to digital formats and proliferated, data scientists started doing massive tests of what makes for a successful customer-support technician or salesperson. This has unquestionably improved the quality of the workers at many firms.
  • In 2010, however, Xerox switched to an online evaluation that incorporates personality testing, cognitive-skill assessment, and multiple-choice questions about how the applicant would handle specific scenarios that he or she might encounter on the job. An algorithm behind the evaluation analyzes the responses, along with factual information gleaned from the candidate’s application, and spits out a color-coded rating: red (poor candidate), yellow (middling), or green (hire away). Those candidates who score best, I learned, tend to exhibit a creative but not overly inquisitive personality, and participate in at least one but not more than four social networks, among many other factors. (Previous experience, one of the few criteria that Xerox had explicitly screened for in the past, turns out to have no bearing on either productivity or retention
  • the idea that hiring was a science fell out of favor. But now it’s coming back, thanks to new technologies and methods of analysis that are cheaper, faster, and much-wider-ranging than what we had before
  • Gone are the days, Ostberg told me, when, say, a small survey of college students would be used to predict the statistical validity of an evaluation tool. “We’ve got a data set of 347,000 actual employees who have gone through these different types of assessments or tools,” he told me, “and now we have performance-outcome data, and we can split those and slice and dice by industry and location.”
  • Evolv’s tests allow companies to capture data about everybody who applies for work, and everybody who gets hired—a complete data set from which sample bias, long a major vexation for industrial-organization psychologists, simply disappears. The sheer number of observations that this approach makes possible allows Evolv to say with precision which attributes matter more to the success of retail-sales workers (decisiveness, spatial orientation, persuasiveness) or customer-service personnel at call centers (rapport-building)
  • There are some data that Evolv simply won’t use, out of a concern that the information might lead to systematic bias against whole classes of people
  • When Xerox started using the score in its hiring decisions, the quality of its hires immediately improved. The rate of attrition fell by 20 percent in the initial pilot period, and over time, the number of promotions rose. Xerox still interviews all candidates in person before deciding to hire them, Morse told me, but, she added, “We’re getting to the point where some of our hiring managers don’t even want to interview anymore”
  • what most excites him are the possibilities that arise from monitoring the entire life cycle of a worker at any given company.
  • Mullainathan expressed amazement at how little most creative and professional workers (himself included) know about what makes them effective or ineffective in the office. Most of us can’t even say with any certainty how long we’ve spent gathering information for a given project, or our pattern of information-gathering, never mind know which parts of the pattern should be reinforced, and which jettisoned. As Mullainathan put it, we don’t know our own “production function.”
  • What begins with an online screening test for entry-level workers ends with the transformation of nearly every aspect of hiring, performance assessment, and management.
  • I turned to Sandy Pentland, the director of the Human Dynamics Laboratory at MIT. In recent years, Pentland has pioneered the use of specialized electronic “badges” that transmit data about employees’ interactions as they go about their days. The badges capture all sorts of information about formal and informal conversations: their length; the tone of voice and gestures of the people involved; how much those people talk, listen, and interrupt; the degree to which they demonstrate empathy and extroversion; and more. Each badge generates about 100 data points a minute.
  • he tried the badges out on about 2,500 people, in 21 different organizations, and learned a number of interesting lessons. About a third of team performance, he discovered, can usually be predicted merely by the number of face-to-face exchanges among team members. (Too many is as much of a problem as too few.) Using data gathered by the badges, he was able to predict which teams would win a business-plan contest, and which workers would (rightly) say they’d had a “productive” or “creative” day. Not only that, but he claimed that his researchers had discovered the “data signature” of natural leaders, whom he called “charismatic connectors” and all of whom, he reported, circulate actively, give their time democratically to others, engage in brief but energetic conversations, and listen at least as much as they talk.
  • His group is developing apps to allow team members to view their own metrics more or less in real time, so that they can see, relative to the benchmarks of highly successful employees, whether they’re getting out of their offices enough, or listening enough, or spending enough time with people outside their own team.
  • Torrents of data are routinely collected by American companies and now sit on corporate servers, or in the cloud, awaiting analysis. Bloomberg reportedly logs every keystroke of every employee, along with their comings and goings in the office. The Las Vegas casino Harrah’s tracks the smiles of the card dealers and waitstaff on the floor (its analytics team has quantified the impact of smiling on customer satisfaction). E‑mail, of course, presents an especially rich vein to be mined for insights about our productivity, our treatment of co-workers, our willingness to collaborate or lend a hand, our patterns of written language, and what those patterns reveal about our intelligence, social skills, and behavior.
  • people analytics will ultimately have a vastly larger impact on the economy than the algorithms that now trade on Wall Street or figure out which ads to show us. He reminded me that we’ve witnessed this kind of transformation before in the history of management science. Near the turn of the 20th century, both Frederick Taylor and Henry Ford famously paced the factory floor with stopwatches, to improve worker efficiency.
  • “The quantities of data that those earlier generations were working with,” he said, “were infinitesimal compared to what’s available now. There’s been a real sea change in the past five years, where the quantities have just grown so large—petabytes, exabytes, zetta—that you start to be able to do things you never could before.”
  • People analytics will unquestionably provide many workers with more options and more power. Gild, for example, helps companies find undervalued software programmers, working indirectly to raise those people’s pay. Other companies are doing similar work. One called Entelo, for instance, specializes in using algorithms to identify potentially unhappy programmers who might be receptive to a phone cal
  • He sees it not only as a boon to a business’s productivity and overall health but also as an important new tool that individual employees can use for self-improvement: a sort of radically expanded The 7 Habits of Highly Effective People, custom-written for each of us, or at least each type of job, in the workforce.
  • the most exotic development in people analytics today is the creation of algorithms to assess the potential of all workers, across all companies, all the time.
  • The way Gild arrives at these scores is not simple. The company’s algorithms begin by scouring the Web for any and all open-source code, and for the coders who wrote it. They evaluate the code for its simplicity, elegance, documentation, and several other factors, including the frequency with which it’s been adopted by other programmers. For code that was written for paid projects, they look at completion times and other measures of productivity. Then they look at questions and answers on social forums such as Stack Overflow, a popular destination for programmers seeking advice on challenging projects. They consider how popular a given coder’s advice is, and how widely that advice ranges.
  • The algorithms go further still. They assess the way coders use language on social networks from LinkedIn to Twitter; the company has determined that certain phrases and words used in association with one another can distinguish expert programmers from less skilled ones. Gild knows these phrases and words are associated with good coding because it can correlate them with its evaluation of open-source code, and with the language and online behavior of programmers in good positions at prestigious companies.
  • having made those correlations, Gild can then score programmers who haven’t written open-source code at all, by analyzing the host of clues embedded in their online histories. They’re not all obvious, or easy to explain. Vivienne Ming, Gild’s chief scientist, told me that one solid predictor of strong coding is an affinity for a particular Japanese manga site.
  • Gild’s CEO, Sheeroy Desai, told me he believes his company’s approach can be applied to any occupation characterized by large, active online communities, where people post and cite individual work, ask and answer professional questions, and get feedback on projects. Graphic design is one field that the company is now looking at, and many scientific, technical, and engineering roles might also fit the bill. Regardless of their occupation, most people leave “data exhaust” in their wake, a kind of digital aura that can reveal a lot about a potential hire.
  • professionally relevant personality traits can be judged effectively merely by scanning Facebook feeds and photos. LinkedIn, of course, captures an enormous amount of professional data and network information, across just about every profession. A controversial start-up called Klout has made its mission the measurement and public scoring of people’s online social influence.
  • Now the two companies are working together to marry pre-hire assessments to an increasing array of post-hire data: about not only performance and duration of service but also who trained the employees; who has managed them; whether they were promoted to a supervisory role, and how quickly; how they performed in that role; and why they eventually left.
  • Over time, better job-matching technologies are likely to begin serving people directly, helping them see more clearly which jobs might suit them and which companies could use their skills. In the future, Gild plans to let programmers see their own profiles and take skills challenges to try to improve their scores. It intends to show them its estimates of their market value, too, and to recommend coursework that might allow them to raise their scores even more. Not least, it plans to make accessible the scores of typical hires at specific companies, so that software engineers can better see the profile they’d need to land a particular job
  • Knack, for its part, is making some of its video games available to anyone with a smartphone, so people can get a better sense of their strengths, and of the fields in which their strengths would be most valued. (Palo Alto High School recently adopted the games to help students assess careers.) Ultimately, the company hopes to act as matchmaker between a large network of people who play its games (or have ever played its games) and a widening roster of corporate clients, each with its own specific profile for any given type of job.
  • When I began my reporting for this story, I was worried that people analytics, if it worked at all, would only widen the divergent arcs of our professional lives, further gilding the path of the meritocratic elite from cradle to grave, and shutting out some workers more definitively. But I now believe the opposite is likely to happen, and that we’re headed toward a labor market that’s fairer to people at every stage of their careers
  • For decades, as we’ve assessed people’s potential in the professional workforce, the most important piece of data—the one that launches careers or keeps them grounded—has been educational background: typically, whether and where people went to college, and how they did there. Over the past couple of generations, colleges and universities have become the gatekeepers to a prosperous life. A degree has become a signal of intelligence and conscientiousness, one that grows stronger the more selective the school and the higher a student’s GPA, that is easily understood by employers, and that, until the advent of people analytics, was probably unrivaled in its predictive powers.
  • the limitations of that signal—the way it degrades with age, its overall imprecision, its many inherent biases, its extraordinary cost—are obvious. “Academic environments are artificial environments,” Laszlo Bock, Google’s senior vice president of people operations, told The New York Times in June. “People who succeed there are sort of finely trained, they’re conditioned to succeed in that environment,” which is often quite different from the workplace.
  • because one’s college history is such a crucial signal in our labor market, perfectly able people who simply couldn’t sit still in a classroom at the age of 16, or who didn’t have their act together at 18, or who chose not to go to graduate school at 22, routinely get left behind for good. That such early factors so profoundly affect career arcs and hiring decisions made two or three decades later is, on its face, absurd.
  • I spoke with managers at a lot of companies who are using advanced analytics to reevaluate and reshape their hiring, and nearly all of them told me that their research is leading them toward pools of candidates who didn’t attend college—for tech jobs, for high-end sales positions, for some managerial roles. In some limited cases, this is because their analytics revealed no benefit whatsoever to hiring people with college degrees; in other cases, and more often, it’s because they revealed signals that function far better than college history,
  • Google, too, is hiring a growing number of nongraduates. Many of the people I talked with reported that when it comes to high-paying and fast-track jobs, they’re reducing their preference for Ivy Leaguers and graduates of other highly selective schools.
  • This process is just beginning. Online courses are proliferating, and so are online markets that involve crowd-sourcing. Both arenas offer new opportunities for workers to build skills and showcase competence. Neither produces the kind of instantly recognizable signals of potential that a degree from a selective college, or a first job at a prestigious firm, might. That’s a problem for traditional hiring managers, because sifting through lots of small signals is so difficult and time-consuming.
  • all of these new developments raise philosophical questions. As professional performance becomes easier to measure and see, will we become slaves to our own status and potential, ever-focused on the metrics that tell us how and whether we are measuring up? Will too much knowledge about our limitations hinder achievement and stifle our dreams? All I can offer in response to these questions, ironically, is my own gut sense, which leads me to feel cautiously optimistic.
  • Google’s understanding of the promise of analytics is probably better than anybody else’s, and the company has been changing its hiring and management practices as a result of its ongoing analyses. (Brainteasers are no longer used in interviews, because they do not correlate with job success; GPA is not considered for anyone more than two years out of school, for the same reason—the list goes on.) But for all of Google’s technological enthusiasm, these same practices are still deeply human. A real, live person looks at every résumé the company receives. Hiring decisions are made by committee and are based in no small part on opinions formed during structured interviews.
Emily Horwitz

Pigeon Code Baffles British Cryptographers - NYTimes.com - 0 views

www.nytimes.com/...es-british-cryptographers.html

knowledge WWII carrier pigeons cryptography british nytimes

shared by Emily Horwitz on 25 Nov 12 - No Cached
  • They have eavesdropped on the enemy for decades, tracking messages from Hitler’s high command and the Soviet K.G.B. and on to the murky, modern world of satellites and cyberspace. But a lowly and yet mysterious carrier pigeon may have them baffled.
  • igeon specialists said they believed it may have been flying home from British units in France around the time of the D-Day landing in 1944 when it somehow expired in the chimney at the 17th-century home where it was found in the village of Bletchingley, south of London.
  • “Unless we get rather more idea than we have about who sent this message and who it was sent to, we are not going to be able to find out what the underlying code was,” said the historian, who was identified only as Tony under the organization’s secrecy protocols.
  • ...3 more annotations...
  • s code-breaking and communications interception unit in Gloucestershire, agreed to try to crack the code. But on Friday the secretive organization acknowledged that it had been unable to do so.
  • “Without access to the relevant code books and details of any additional encryption used, it will remain impossible to decrypt,” the Government Communications Headquarters said in a news release.
  • Mr. Martin said he was skeptical of the idea that the agency had been unable to crack the code. “I think there’s something about that message that is either sensitive or does not reflect well” on British special forces operating behind enemy lines in wartime France, he said in a telephone interview. “I’m convinced that it’s an important message and a secret message.”
Javier E

The Limits of Empathy - NYTimes.com - 0 views

www.nytimes.com/...oks-the-limits-of-empathy.html

empathy morality honor shame

shared by Javier E on 01 Oct 11 - No Cached
  • People who are empathetic are more sensitive to the perspectives and sufferings of others. They are more likely to make compassionate moral judgments.
  • The problem comes when we try to turn feeling into action. Empathy makes you more aware of other people’s suffering, but it’s not clear it actually motivates you to take moral action or prevents you from taking immoral action. In the early days of the Holocaust, Nazi prison guards sometimes wept as they mowed down Jewish women and children, but they still did it.
  • Empathy orients you toward moral action, but it doesn’t seem to help much when that action comes at a personal cost. You may feel a pang for the homeless guy on the other side of the street, but the odds are that you are not going to cross the street to give him a dollar.
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  • “These studies suggest that empathy is not a major player when it comes to moral motivation. Its contribution is negligible in children, modest in adults, and nonexistent when costs are significant.” Other scholars have called empathy a “fragile flower,” easily crushed by self-concern.
  • empathy often leads people astray. It influences people to care more about cute victims than ugly victims. It leads to nepotism. It subverts justice; juries give lighter sentences to defendants that show sadness.
  • These days empathy has become a shortcut. It has become a way to experience delicious moral emotions without confronting the weaknesses in our nature that prevent us from actually acting upon them
  • It has become a way to experience the illusion of moral progress without having to do the nasty work of making moral judgments. In a culture that is inarticulate about moral categories and touchy about giving offense, teaching empathy is a safe way for schools and other institutions to seem virtuous without risking controversy or hurting anybody’s feelings.
  • People who actually perform pro-social action don’t only feel for those who are suffering, they feel compelled to act by a sense of duty. Their lives are structured by sacred codes.
  • Think of anybody you admire. They probably have some talent for fellow-feeling, but it is overshadowed by their sense of obligation to some religious, military, social or philosophic code. They would feel a sense of shame or guilt if they didn’t live up to the code. The code tells them when they deserve public admiration or dishonor.
  • The code isn’t just a set of rules. It’s a source of identity. It’s pursued with joy. It arouses the strongest emotions and attachments. Empathy is a sideshow. If you want to make the world a better place, help people debate, understand, reform, revere and enact their codes. Accept that codes conflict.
Javier E

AOC Isn't Using 'Verbal Blackface'-She's Code-Switching - The Atlantic - 0 views

www.theatlantic.com/...586723

language code black english

shared by Javier E on 09 Apr 19 - No Cached
  • another misimpression about Black English: that only uneducated people can be considered “authentic” in using it. This partly reflects a sense that Black English is a mere matter of grammatical flubs, a legacy of inadequate education. That analysis of Black English has been resoundingly refuted by shelves and shelves of research by linguists. Yet even someone who acknowledges that Black English is not broken language might suppose that it is rooted solely in being black and, roughly, poor.
  • poor black people are by no means the only ones who code-switch into Black English. Worldwide, people code-switch into nonstandard dialects as part of the general palette of human expression: The nonstandard dialect can connote warmth, surprise, anger, flirtation, intimacy. Obama and Ocasio-Cortez are no less authentic in their use of Black English than people such as Cornel West and Keegan-Michael Key, educated black people who code-switch constantly and beautifully.
  • Code-switching, however, is often about seasoning, sprinkling, decoration
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  • why would it be wrong for a politician to seek to connect to black audiences by sprinkling her speech with some of their dialect, which she grew up hearing and using herself? After all, language is fundamentally designed for connection. People often note that their speech tends to meld itself to the speech of those around them, such that they end up having a multilayered linguistic identity. Ocasio-Cortez has one.
Javier E

Opinion | Harris Gonna Code Switch - The New York Times - 0 views

www.nytimes.com/...harris-code-switch.html

code-switching harris language

shared by Javier E on 15 Aug 24 - No Cached
  • language is about reaching into another mind. It’s about connecting.
  • Code-switching is one of the ways that humans use language to connect. Using the colloquial dialect of a language serves the same function as drinking or getting a mani-pedi together. It says, “We’re all the same.” It is especially natural, and common, when seeking connection about folksier things or summoning a note of cutting through the nonsense and getting to the heart of things in a “Let’s face it” way.
  • This is why many of us readily say “Ain’t gonna happen” even if we aren’t given to saying “ain’t” regularly.
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  • Closer to home, Maya Angelou deftly explained how Black Americans code-switch when she wrote: “We learned to slide out of one language and into another without being conscious of the effort. At school, in a given situation, we might respond with, ‘That’s not unusual.’ But in the street, meeting the same situation, we easily said, ‘It be’s like that sometimes.’”
  • It is in this light that we must evaluate an X post like “It’s pretty weird to change your accent on the fly depending on which audience you’re speaking to.” Wrong. This is like saying it’s pretty weird to dress according to what your plans for the day are.
Javier E

Technology's Man Problem - NYTimes.com - 0 views

www.nytimes.com/...technologys-man-problem.html

women tech industry silicon valley

shared by Javier E on 22 May 15 - No Cached
  • computer engineering, the most innovative sector of the economy, remains behind. Many women who want to be engineers encounter a field where they not only are significantly underrepresented but also feel pushed away.
  • Among the women who join the field, 56 percent leave by midcareer, a startling attrition rate that is double that for men, according to research from the Harvard Business School.
  • A culprit, many people in the field say, is a sexist, alpha-male culture that can make women and other people who don’t fit the mold feel unwelcome, demeaned or even endangered.
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  • “I’ve been a programmer for 13 years, and I’ve always been one of the only women and queer people in the room. I’ve been harassed, I’ve had people make suggestive comments to me, I’ve had people basically dismiss my expertise. I’ve gotten rape and death threats just for speaking out about this stuff.”
  • “We see these stories, ‘Why aren’t there more women in computer science and engineering?’ and there’s all these complicated answers like, ‘School advisers don’t have them take math and physics,’ and it’s probably true,” said Lauren Weinstein, a man who has spent his four-decade career in tech working mostly with other men, and is currently a consultant for Google.“But I think there’s probably a simpler reason,” he said, “which is these guys are just jerks, and women know it.”
  • once programming gained prestige, women were pushed out. Over the decades, the share of women in computing has continued to decline. In 2012, just 18 percent of computer-science college graduates were women, down from 37 percent in 1985, according to the National Center for Women & Information Technology.
  • Some 1.2 million computing jobs will be available in 2022, yet United States universities are producing only 39 percent of the graduates needed to fill them, the N.C.W.I.T. estimates.
  • Twenty percent of software developers are women, according to the Labor Department, and fewer than 6 percent of engineers are black or Hispanic. Comparatively, 56 percent of people in business and financial-operations jobs are women, as are 36 percent of physicians and surgeons and one-third of lawyers.
  • an engineer at Pinterest has collected data from people at 133 start-ups and found that an average of 12 percent of the engineers are women.
  • “It makes a hostile environment for me,” she said. “But I don’t want to raise my hand and call negative attention toward myself, and become the woman who is the problem — ‘that woman.’ In start-up culture they protect their own tribe, so by putting my hand up, I’m saying I’m an ‘other,’ I shouldn’t be there, so for me that’s an economic threat.”
  • “Many women have come to me and said they basically have had to hide on the Net now,” said Mr. Weinstein, who works on issues of identity and anonymity online. “They use male names, they don’t put their real photos up, because they are immediately targeted and harassed.”
  • “It’s a boys’ club, and you have to try to get into it, and they’re trying as hard as they can to prove you can’t,” said Ephrat Bitton, the director of algorithms at FutureAdvisor, an online investment start-up that she says has a better culture because almost half the engineers are women.
  • Writing code is a high-pressure job with little room for error, as are many jobs. But coding can be stressful in a different way, women interviewed for this article said, because code reviews — peer reviews to spot mistakes in software — can quickly devolve.
  • “Code reviews are brutal — ‘Mine is better than yours, I see flaws in yours’ — and they should be, for the creation of good software,” said Ellen Ullman, a software engineer and author. “I think when you add a drop of women into it, it just exacerbates the problem, because here’s a kind of foreigner.”
  • But some women argue that these kinds of initiatives are unhelpful.“My general issue with the coverage of women in tech is that women in the technology press are talked about in the context of being women, and men are talked about in the context of being in technology,” said a technical woman who would speak only on condition of anonymity because she did not want to be part of an article about women in tech.
runlai_jiang

Taking On Adam Smith (and Karl Marx) - The New York Times - 0 views

www.nytimes.com/...-adam-smith-and-karl-marx.html

capitalism

shared by runlai_jiang on 15 Jan 18 - No Cached
  • “This sort of vaccinated me for life against lazy, anticapitalist rhetoric, because when you see these empty shops, you see these people queuing for nothing in the street,” he said, “it became clear to me that we need private property and market institutions, not just for economic efficiency but for personal freedom.”
  • But his disenchantment with communism doesn’t mean that Mr. Piketty has turned his back on the intellectual heritage of Karl Marx, who sought to explain the “iron laws” of capitalism. Like Marx, he is fiercely critical of the economic and social inequalities that untrammeled capitalism produces — and, he concludes, will continue to worsen. “I belong to a generation that never had any temptation with the Communist Party; I was too young for that,” Mr. Piketty said, in
  • In his new book “Capital in the Twenty-First Century” (Harvard University Press), Mr. Piketty, 42, has written a blockbuster, at least in the world of economics. His book punctures earlier assumptions about the benevolence of advanced capitalism and forecasts sharply increasing inequality of wealth in industrialized countries, with deep and deleterious impact on democratic values of justice and fairness.
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  • Branko Milanovic, a former economist at the World Bank, called it “one of the watershed books in economic thinking.
  • “Capital in the Twenty-First Century,” with its title echoing Marx’s “Das Kapital,” is meant to be a return to the kind of economic history, of political economy, written by predecessors like Marx and Adam Smith. It is nothing less than a broad effort to understand Western societies and the economic rules that underpin them.
  • he said, are his generation’s “founding experiences”: the collapse of Communism, the economic degradation of Eastern Europe and the first Gulf War, in 1991.
  • Those events motivated him to try to understand a world where economic ideas had such bad consequences. As for the Gulf War, it showed him that “governments can do a lot in terms of redistribution of wealth when they want.” The rapid intervention to fo
  • The reason that postwar economies looked different — that inequality fell — was historical catastrophe. World War I, the Depression and World War II destroyed huge accumulations of private capital, especially in Europe. What the French call “les
  • In 2012 the top 1 percent of American households collected 22.5 percent of the nation’s income, the highest total since 1928. The richest 10 percent of Americans now take a larger slice of the pie than in 1913, at the close of the Gilded Age, owning more than 70 percent of the nation’s wealth. And half of that is owned by the top 1 percent. Advertisement Continue reading the main story Mr. Piketty, father of three daughters — 11, 13 and 16 — is no revolutionary. He is a member of no political party, and says he never served as an economic adviser to any politician. He calls himself a pragmatist, who simply follows the data.
  • Net wealth is a better indicator of ability to pay than income alone, he said. “All I’m proposing is to reduce the property tax on half or three-quarters of the population who have very little wealth,” he said. Write A Comment Published a year ago in French, the book is not without critics, especially of Mr. Piketty’s policy prescriptions, which have been called politically naïve. Others point out that some of the increase in capital is because of aging populations and postwar pension plans, which are not necessarily inherited.More criticism is sure to come, and Mr. Piketty says he welcomes it. “I’m certainly looking forward to the debate.”
Javier E

The Chatbots Are Here, and the Internet Industry Is in a Tizzy - The New York Times - 0 views

www.nytimes.com/...disrupt-internet-industry.html

chatbot AI industry effects business internet companies technology

shared by Javier E on 10 Mar 23 - No Cached
  • He cleared his calendar and asked employees to figure out how the technology, which instantly provides comprehensive answers to complex questions, could benefit Box, a cloud computing company that sells services that help businesses manage their online data.
  • Mr. Levie’s reaction to ChatGPT was typical of the anxiety — and excitement — over Silicon Valley’s new new thing. Chatbots have ignited a scramble to determine whether their technology could upend the economics of the internet, turn today’s powerhouses into has-beens or create the industry’s next giants.
  • Cloud computing companies are rushing to deliver chatbot tools, even as they worry that the technology will gut other parts of their businesses. E-commerce outfits are dreaming of new ways to sell things. Social media platforms are being flooded with posts written by bots. And publishing companies are fretting that even more dollars will be squeezed out of digital advertising.
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  • The volatility of chatbots has made it impossible to predict their impact. In one second, the systems impress by fielding a complex request for a five-day itinerary, making Google’s search engine look archaic. A moment later, they disturb by taking conversations in dark directions and launching verbal assaults.
  • The result is an industry gripped with the question: What do we do now?
  • The A.I. systems could disrupt $100 billion in cloud spending, $500 billion in digital advertising and $5.4 trillion in e-commerce sales,
  • As Microsoft figures out a chatbot business model, it is forging ahead with plans to sell the technology to others. It charges $10 a month for a cloud service, built in conjunction with the OpenAI lab, that provides developers with coding suggestions, among other things.
  • Smaller companies like Box need help building chatbot tools, so they are turning to the giants that process, store and manage information across the web. Those companies — Google, Microsoft and Amazon — are in a race to provide businesses with the software and substantial computing power behind their A.I. chatbots.
  • “The cloud computing providers have gone all in on A.I. over the last few months,
  • “They are realizing that in a few years, most of the spending will be on A.I., so it is important for them to make big bets.”
  • Yusuf Mehdi, the head of Bing, said the company was wrestling with how the new version would make money. Advertising will be a major driver, he said, but the company expects fewer ads than traditional search allows.
  • Google, perhaps more than any other company, has reason to both love and hate the chatbots. It has declared a “code red” because their abilities could be a blow to its $162 billion business showing ads on searches.
  • “The discourse on A.I. is rather narrow and focused on text and the chat experience,” Mr. Taylor said. “Our vision for search is about understanding information and all its forms: language, images, video, navigating the real world.”
  • Sridhar Ramaswamy, who led Google’s advertising division from 2013 to 2018, said Microsoft and Google recognized that their current search business might not survive. “The wall of ads and sea of blue links is a thing of the past,” said Mr. Ramaswamy, who now runs Neeva, a subscription-based search engine.
  • As that underlying tech, known as generative A.I., becomes more widely available, it could fuel new ideas in e-commerce. Late last year, Manish Chandra, the chief executive of Poshmark, a popular online secondhand store, found himself daydreaming during a long flight from India about chatbots building profiles of people’s tastes, then recommending and buying clothes or electronics. He imagined grocers instantly fulfilling orders for a recipe.
  • “It becomes your mini-Amazon,” said Mr. Chandra, who has made integrating generative A.I. into Poshmark one of the company’s top priorities over the next three years. “That layer is going to be very powerful and disruptive and start almost a new layer of retail.”
  • In early December, users of Stack Overflow, a popular social network for computer programmers, began posting substandard coding advice written by ChatGPT. Moderators quickly banned A.I.-generated text
  • t people could post this questionable content far faster than they could write posts on their own, said Dennis Soemers, a moderator for the site. “Content generated by ChatGPT looks trustworthy and professional, but often isn’t,”
  • When websites thrived during the pandemic as traffic from Google surged, Nilay Patel, editor in chief of The Verge, a tech news site, warned publishers that the search giant would one day turn off the spigot. He had seen Facebook stop linking out to websites and foresaw Google following suit in a bid to boost its own business.
  • He predicted that visitors from Google would drop from a third of websites’ traffic to nothing. He called that day “Google zero.”
  • Because chatbots replace website search links with footnotes to answers, he said, many publishers are now asking if his prophecy is coming true.
  • , strategists and engineers at the digital advertising company CafeMedia have met twice a week to contemplate a future where A.I. chatbots replace search engines and squeeze web traffic.
  • The group recently discussed what websites should do if chatbots lift information but send fewer visitors. One possible solution would be to encourage CafeMedia’s network of 4,200 websites to insert code that limited A.I. companies from taking content, a practice currently allowed because it contributes to search rankings.
  • Courts are expected to be the ultimate arbiter of content ownership. Last month, Getty Images sued Stability AI, the start-up behind the art generator tool Stable Diffusion, accusing it of unlawfully copying millions of images. The Wall Street Journal has said using its articles to train an A.I. system requires a license.
  • In the meantime, A.I. companies continue collecting information across the web under the “fair use” doctrine, which permits limited use of material without permission.
Javier E

English Is a Dialect With an Army - Ta-Nehisi Coates - The Atlantic - 0 views

www.theatlantic.com/...278300

language English African-American culture imperialism bilingualism multiculturalism

shared by Javier E on 04 Aug 13 - No Cached
  • I am getting some small notion of what it feels like to be white in America. What my classmates are telling me is that the Anglophone world is the international power. It dominates. Thus knowledge is tangibly necessary for them in a way that it is not for me
  • Of course the flip-side of this calculus is that power enables ignorance. Black people know this well.
  • I think this is the seed of the "We don't have any white history month!" syndrome. Through conquest the ways of whiteness become the air.
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  • But once those ways are apprehended by the conquered--as they must be--they are no longer the strict property of the conqueror. On the contrary you find the conquered mixing, cutting, folding, and flipping the ways of the conqueror into something that he barely recognizes and yet finds oddly compelling. And all the while the conquered still enjoys her own private home. She need not be amnesiac, only bilingual
  • . The phrase "code-switching" is overdone, but there is no cultural code from which all white people can "switch" from. It's not even a code. It's just the world. 
  • In the context of France, je suis américan. I am an aspect of the great power.
  • There is no "nigger" for me, no private language, no private way of being all my own. And with that comes a great feeling of weakness and shame.
  • the literature of slavemasters is filled with exasperation over their slaves laughing at invisible jokes.
Javier E

Regulating Sex - The New York Times - 0 views

www.nytimes.com/...-shulevitz-regulating-sex.html

sexual ethics law consent psychology rape

shared by Javier E on 29 Jun 15 - No Cached
  • THIS is a strange moment for sex in America. We’ve detached it from pregnancy, matrimony and, in some circles, romance. At least, we no longer assume that intercourse signals the start of a relationship.
  • But the more casual sex becomes, the more we demand that our institutions and government police the line between what’s consensual and what isn’t. And we wonder how to define rape. Is it a violent assault or a violation of personal autonomy? Is a person guilty of sexual misconduct if he fails to get a clear “yes” through every step of seduction and consummation?
  • According to the doctrine of affirmative consent — the “yes means yes” rule — the answer is, well, yes, he is.
  • ...22 more annotations...
  • if one person can think he’s hooking up while the other feels she’s being raped, it makes sense to have a law that eliminates the possibility of misunderstanding. “You shouldn’t be allowed to make the assumption that if you find someone lying on a bed, they’re free for sexual pleasure,”
  • About a quarter of all states, and the District of Columbia, now say sex isn’t legal without positive agreement,
  • And though most people think of “yes means yes” as strictly for college students, it is actually poised to become the law of the land.
  • Some new crimes outlined in the proposed code, for example, assume consent to be meaningless under conditions of unequal power. Consensual sex between professionals (therapists, lawyers and the like) and their patients and clients, for instance, would be a fourth-degree felony, punishable by significant time in prison.
  • Should we really put people in jail for not doing what most people aren’t doing? (Or at least, not yet?)
  • It’s one thing to teach college students to talk frankly about sex and not to have it without demonstrable pre-coital assent. Colleges are entitled to uphold their own standards of comportment, even if enforcement of that behavior is spotty or indifferent to the rights of the accused. It’s another thing to make sex a crime under conditions of poor communication.
  • Most people just aren’t very talkative during the delicate tango that precedes sex, and the re-education required to make them more forthcoming would be a very big project. Nor are people unerringly good at decoding sexual signals. If they were, we wouldn’t have romantic comedies.
  • “If there’s no social consensus about what the lines are,” says Nancy Gertner, a senior lecturer at Harvard Law School and a retired judge, then affirmative consent “has no business being in the criminal law.”
  • The example points to a trend evident both on campuses and in courts: the criminalization of what we think of as ordinary sex and of sex previously considered unsavory but not illegal.
  • But criminal law is a very powerful instrument for reshaping sexual mores.
  • most of these occupations already have codes of professional conduct, and victims also have recourse in the civil courts. Miscreants, she says, “should be drummed out of the profession or sued for malpractice.”
  • It’s important to remember that people convicted of sex crimes may not only go to jail, they can wind up on a sex-offender registry, with dire and lasting consequences.
  • We shouldn’t forget the harm done to American communities by the national passion for incarceration, either. In a letter to the American Law Institute, Ms. Smith listed several disturbing statistics: roughly one person in 100 behind bars, one in 31 under correctional supervision
  • the case for affirmative consent is “compelling,” he says. Mr. Schulhofer has argued that being raped is much worse than having to endure that awkward moment when one stops to confirm that one’s partner is happy to continue. Silence or inertia, often interpreted as agreement, may actually reflect confusion, drunkenness or “frozen fright,” a documented physiological response in which a person under sexual threat is paralyzed by terror
  • To critics who object that millions of people are having sex without getting unqualified assent and aren’t likely to change their ways, he’d reply that millions of people drive 65 miles per hour despite a 55-mile-per-hour speed limit, but the law still saves lives. As long as “people know what the rules of the road are,” he says, “the overwhelming majority will comply with them.”
  • He understands that the law will have to bring a light touch to the refashioning of sexual norms, which is why the current draft of the model code suggests classifying penetration without consent as a misdemeanor, a much lesser crime than a felony.
  • This may all sound reasonable, but even a misdemeanor conviction goes on the record as a sexual offense and can lead to registration
  • An affirmative consent standard also shifts the burden of proof from the accuser to the accused, which represents a real departure from the traditions of criminal law in the United States. Affirmative consent effectively means that the accused has to show that he got the go-ahead
  • if the law requires a “no,” then the jury will likely perceive any uncertainty about that “no” as a weakness in the prosecution’s case and not convict. But if the law requires a “yes,” then ambiguity will bolster the prosecutor’s argument: The guy didn’t get unequivocal consent, therefore he must be guilty of rape.
  • “It’s an unworkable standard,” says the Harvard law professor Jeannie C. Suk. “It’s only workable if we assume it’s not going to be enforced, by and large.” But that’s worrisome too. Selectively enforced laws have a nasty history of being used to harass people deemed to be undesirable, because of their politics, race or other reasons.
  • it’s probably just a matter of time before “yes means yes” becomes the law in most states. Ms. Suk told me that she and her colleagues have noticed a generational divide between them and their students. As undergraduates, they’re learning affirmative consent in their mandatory sexual-respect training sessions, and they come to “believe that this really is the best way to define consent, as positive agreement,” she says. When they graduate and enter the legal profession, they’ll probably reshape the law to reflect that belief.
  • Sex may become safer for some, but it will be a whole lot more anxiety-producing for others.
Javier E

Opinion | Is Computer Code a Foreign Language? - The New York Times - 1 views

www.nytimes.com/...code-foreign-language.html

language computer knowledge psychology humanity social

shared by Javier E on 18 Mar 19 - No Cached
  • the proposal that foreign language learning can be replaced by computer coding knowledge is misguided:
  • It stems from a widely held but mistaken belief that science and technology education should take precedence over subjects like English, history and foreign languages.
  • more urgent is my alarm at the growing tendency to accept and even foster the decline of the sort of interpersonal human contact that learning languages both requires and cultivates.
  • ...6 more annotations...
  • Language is an essential — perhaps the essential — marker of our species. We learn in and through natural languages; we develop our most fundamental cognitive skills by speaking and hearing languages; and we ultimately assume our identities as human beings and members of communities by exercising those languages
  • Our profound and impressive ability to create complex tools with which to manipulate our environments is secondary to our ability to conceptualize and communicate about those environments in natural languages.
  • Natural languages aren’t just more complex versions of the algorithms with which we teach machines to do tasks; they are also the living embodiments of our essence as social animals.
  • We express our love and our losses, explore beauty, justice and the meaning of our existence, and even come to know ourselves all though natural languages.
  • we are fundamentally limited in how much we can know about another’s thoughts and feelings, and that this limitation and the desire to transcend it is essential to our humanity
  • or us humans, communication is about much more than getting information or following instructions; it’s about learning who we are by interacting with others.
Javier E

The War in Ukraine Has Unleashed a New Word - The New York Times - 0 views

www.nytimes.com/...uscism-ukraine-russia-war.html

ukraine language code code-switching russia russian

shared by Javier E on 24 Apr 22 - No Cached
  • As I read about Irpin, about Bucha, about Trostyanets, of the bodies crushed by tanks, of the bicyclists shot on the street, of the desecrated corpses, there it was, “рашизм,” again and again
  • Grasping its meaning requires crossing differences in alphabet and pronunciation, thinking our way into the experience of a bilingual society at war with a fascist empire.
  • “Pашизм” sounds like “fascism,” but with an “r” sound instead of an “f” at the beginning; it means, roughly, “Russian fascism.”
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  • The aggressor in this war keeps trying to push back toward a past as it never happened, toward nonsensical and necrophiliac accounts of history. Russia must conquer Ukraine, Vladimir Putin says, because of a baptism a thousand years ago, or because of bloodshed during World War II.
  • The new word “рашизм” is a useful conceptualization of Putin’s worldview. Far more than Western analysts, Ukrainians have noticed the Russian tilt toward fascism in the last decade.
  • Undistracted by Putin’s operational deployment of genocide talk, they have seen fascist practices in Russia: the cults of the leader and of the dead, the corporatist state, the mythical past, the censorship, the conspiracy theories, the centralized propaganda and now the war of destruction
  • we have tended to overlook the central example of fascism’s revival, which is the Putin regime in the Russian Federation.
  • A bilingual nation like Ukraine is not just a collection of bilingual individuals; it is an unending set of encounters in which people habitually adjust the language they use to other people and new settings, manipulating language in ways that are foreign to monolingual nations
  • I have gone on Ukrainian television and radio, taken questions in Russian and answered them in Ukrainian, without anyone for a moment finding that switch worthy of mention.
  • Ukrainians change languages effortlessly — not just as situations change, but also to make situations change, sometimes in the middle of a sentence, or even in the middle of a word.
  • “Pашизм” is a word built up from the inside, from several languages, as a complex of puns and references that reveal a bilingual society thinking out its predicament and communicating to itself.
  • Putin’s ethnic imperialism insists that Ukrainians must be Russians because they speak Russian. They do — and they speak Ukrainian. But Ukrainian identity has as much to do with an ability to live between languages than it does with the use of any one of them
  • Those six Cyrillic letters contain references to Italian, Russian and English, all of which a mechanical, letter-by-letter transliteration would block
  • The best (if imperfect) way I have found to render “рашизм” from Ukrainian into English is “ruscism”
  • When we see “ruscism” we might guess this word has to do with Russia (“rus”), with politics (“ism”) and with the extreme right (“ascism”) — as, indeed, it does
  • I have had to spell “рашизм” as “ruscism” in English because we need “rus,” with a “u,” to see the reference to Russia. In losing the original Ukrainian “a,” though, we weaken a multilayered reference — because the “a” in “рашизм,” conveniently, allows the Ukrainian word to associate Russia and fascism in a way English cannot.
  • If you don’t know either language, you might think that Russian and Ukrainian are very similar. They are pretty close — much as, say, Spanish and Italian are.
  • the semantics are not that close
  • From a Russian perspective, the false friends are legion. There is an elegant four-syllable Ukrainian word that simply means “soon” or “without delay,” but to a Russian it sounds like “not behind the bar.” The Ukrainian word for “cat” sounds like the Russian for “whale,” while the Ukrainian for “female cats” sounds like Russian for “intestines.”
  • Russians do not understand Ukrainian, because they have not learned it. Ukrainians do understand Russian, because they have learned it.
  • Ukrainian soldiers often speak Russian, though they are instructed to use Ukrainian to spot infiltrators and spies. This is a drastic example of a general practice of code-switching.
  • Ukrainians are perfectly capable of writing Russian correctly, but during the war some internet commentators have spelled the occasional Russian word using the Ukrainian writing system, leaving it looking unmoored and pitiable. Writing in Ukrainian, you might spell “oсвобождение” as “aсвобaждениe,” the way it is pronounced — a bit of lexicographic alchemy that makes it (and, by extension, Russians) look silly, and mocks the political concepts being used to justify a war. In a larger sense, such efforts are a means of displacing Russia from its central position in regional culture.
Javier E

Whistleblower: Twitter misled investors, FTC and underplayed spam issues - Washington Post - 0 views

www.washingtonpost.com/...twitter-whistleblower-sec-spam

twitter whistleblower security social media technology

shared by Javier E on 27 Aug 22 - No Cached
  • Twitter executives deceived federal regulators and the company’s own board of directors about “extreme, egregious deficiencies” in its defenses against hackers, as well as its meager efforts to fight spam, according to an explosive whistleblower complaint from its former security chief.
  • The complaint from former head of security Peiter Zatko, a widely admired hacker known as “Mudge,” depicts Twitter as a chaotic and rudderless company beset by infighting, unable to properly protect its 238 million daily users including government agencies, heads of state and other influential public figures.
  • Among the most serious accusations in the complaint, a copy of which was obtained by The Washington Post, is that Twitter violated the terms of an 11-year-old settlement with the Federal Trade Commission by falsely claiming that it had a solid security plan. Zatko’s complaint alleges he had warned colleagues that half the company’s servers were running out-of-date and vulnerable software and that executives withheld dire facts about the number of breaches and lack of protection for user data, instead presenting directors with rosy charts measuring unimportant changes.
  • ...56 more annotations...
  • The complaint — filed last month with the Securities and Exchange Commission and the Department of Justice, as well as the FTC — says thousands of employees still had wide-ranging and poorly tracked internal access to core company software, a situation that for years had led to embarrassing hacks, including the commandeering of accounts held by such high-profile users as Elon Musk and former presidents Barack Obama and Donald Trump.
  • the whistleblower document alleges the company prioritized user growth over reducing spam, though unwanted content made the user experience worse. Executives stood to win individual bonuses of as much as $10 million tied to increases in daily users, the complaint asserts, and nothing explicitly for cutting spam.
  • Chief executive Parag Agrawal was “lying” when he tweeted in May that the company was “strongly incentivized to detect and remove as much spam as we possibly can,” the complaint alleges.
  • Zatko described his decision to go public as an extension of his previous work exposing flaws in specific pieces of software and broader systemic failings in cybersecurity. He was hired at Twitter by former CEO Jack Dorsey in late 2020 after a major hack of the company’s systems.
  • “I felt ethically bound. This is not a light step to take,” said Zatko, who was fired by Agrawal in January. He declined to discuss what happened at Twitter, except to stand by the formal complaint. Under SEC whistleblower rules, he is entitled to legal protection against retaliation, as well as potential monetary rewards.
  • “Security and privacy have long been top companywide priorities at Twitter,” said Twitter spokeswoman Rebecca Hahn. She said that Zatko’s allegations appeared to be “riddled with inaccuracies” and that Zatko “now appears to be opportunistically seeking to inflict harm on Twitter, its customers, and its shareholders.” Hahn said that Twitter fired Zatko after 15 months “for poor performance and leadership.” Attorneys for Zatko confirmed he was fired but denied it was for performance or leadership.
  • A person familiar with Zatko’s tenure said the company investigated Zatko’s security claims during his time there and concluded they were sensationalistic and without merit. Four people familiar with Twitter’s efforts to fight spam said the company deploys extensive manual and automated tools to both measure the extent of spam across the service and reduce it.
  • Overall, Zatko wrote in a February analysis for the company attached as an exhibit to the SEC complaint, “Twitter is grossly negligent in several areas of information security. If these problems are not corrected, regulators, media and users of the platform will be shocked when they inevitably learn about Twitter’s severe lack of security basics.”
  • Zatko’s complaint says strong security should have been much more important to Twitter, which holds vast amounts of sensitive personal data about users. Twitter has the email addresses and phone numbers of many public figures, as well as dissidents who communicate over the service at great personal risk.
  • This month, an ex-Twitter employee was convicted of using his position at the company to spy on Saudi dissidents and government critics, passing their information to a close aide of Crown Prince Mohammed bin Salman in exchange for cash and gifts.
  • Zatko’s complaint says he believed the Indian government had forced Twitter to put one of its agents on the payroll, with access to user data at a time of intense protests in the country. The complaint said supporting information for that claim has gone to the National Security Division of the Justice Department and the Senate Select Committee on Intelligence. Another person familiar with the matter agreed that the employee was probably an agent.
  • “Take a tech platform that collects massive amounts of user data, combine it with what appears to be an incredibly weak security infrastructure and infuse it with foreign state actors with an agenda, and you’ve got a recipe for disaster,” Charles E. Grassley (R-Iowa), the top Republican on the Senate Judiciary Committee,
  • Many government leaders and other trusted voices use Twitter to spread important messages quickly, so a hijacked account could drive panic or violence. In 2013, a captured Associated Press handle falsely tweeted about explosions at the White House, sending the Dow Jones industrial average briefly plunging more than 140 points.
  • After a teenager managed to hijack the verified accounts of Obama, then-candidate Joe Biden, Musk and others in 2020, Twitter’s chief executive at the time, Jack Dorsey, asked Zatko to join him, saying that he could help the world by fixing Twitter’s security and improving the public conversation, Zatko asserts in the complaint.
  • In 1998, Zatko had testified to Congress that the internet was so fragile that he and others could take it down with a half-hour of concentrated effort. He later served as the head of cyber grants at the Defense Advanced Research Projects Agency, the Pentagon innovation unit that had backed the internet’s invention.
  • But at Twitter Zatko encountered problems more widespread than he realized and leadership that didn’t act on his concerns, according to the complaint.
  • Twitter’s difficulties with weak security stretches back more than a decade before Zatko’s arrival at the company in November 2020. In a pair of 2009 incidents, hackers gained administrative control of the social network, allowing them to reset passwords and access user data. In the first, beginning around January of that year, hackers sent tweets from the accounts of high-profile users, including Fox News and Obama.
  • Several months later, a hacker was able to guess an employee’s administrative password after gaining access to similar passwords in their personal email account. That hacker was able to reset at least one user’s password and obtain private information about any Twitter user.
  • Twitter continued to suffer high-profile hacks and security violations, including in 2017, when a contract worker briefly took over Trump’s account, and in the 2020 hack, in which a Florida teen tricked Twitter employees and won access to verified accounts. Twitter then said it put additional safeguards in place.
  • This year, the Justice Department accused Twitter of asking users for their phone numbers in the name of increased security, then using the numbers for marketing. Twitter agreed to pay a $150 million fine for allegedly breaking the 2011 order, which barred the company from making misrepresentations about the security of personal data.
  • After Zatko joined the company, he found it had made little progress since the 2011 settlement, the complaint says. The complaint alleges that he was able to reduce the backlog of safety cases, including harassment and threats, from 1 million to 200,000, add staff and push to measure results.
  • But Zatko saw major gaps in what the company was doing to satisfy its obligations to the FTC, according to the complaint. In Zatko’s interpretation, according to the complaint, the 2011 order required Twitter to implement a Software Development Life Cycle program, a standard process for making sure new code is free of dangerous bugs. The complaint alleges that other employees had been telling the board and the FTC that they were making progress in rolling out that program to Twitter’s systems. But Zatko alleges that he discovered that it had been sent to only a tenth of the company’s projects, and even then treated as optional.
  • “If all of that is true, I don’t think there’s any doubt that there are order violations,” Vladeck, who is now a Georgetown Law professor, said in an interview. “It is possible that the kinds of problems that Twitter faced eleven years ago are still running through the company.”
  • The complaint also alleges that Zatko warned the board early in his tenure that overlapping outages in the company’s data centers could leave it unable to correctly restart its servers. That could have left the service down for months, or even have caused all of its data to be lost. That came close to happening in 2021, when an “impending catastrophic” crisis threatened the platform’s survival before engineers were able to save the day, the complaint says, without providing further details.
  • One current and one former employee recalled that incident, when failures at two Twitter data centers drove concerns that the service could have collapsed for an extended period. “I wondered if the company would exist in a few days,” one of them said.
  • The current and former employees also agreed with the complaint’s assertion that past reports to various privacy regulators were “misleading at best.”
  • For example, they said the company implied that it had destroyed all data on users who asked, but the material had spread so widely inside Twitter’s networks, it was impossible to know for sure
  • As the head of security, Zatko says he also was in charge of a division that investigated users’ complaints about accounts, which meant that he oversaw the removal of some bots, according to the complaint. Spam bots — computer programs that tweet automatically — have long vexed Twitter. Unlike its social media counterparts, Twitter allows users to program bots to be used on its service: For example, the Twitter account @big_ben_clock is programmed to tweet “Bong Bong Bong” every hour in time with Big Ben in London. Twitter also allows people to create accounts without using their real identities, making it harder for the company to distinguish between authentic, duplicate and automated accounts.
  • In the complaint, Zatko alleges he could not get a straight answer when he sought what he viewed as an important data point: the prevalence of spam and bots across all of Twitter, not just among monetizable users.
  • Zatko cites a “sensitive source” who said Twitter was afraid to determine that number because it “would harm the image and valuation of the company.” He says the company’s tools for detecting spam are far less robust than implied in various statements.
  • “Agrawal’s Tweets and Twitter’s previous blog posts misleadingly imply that Twitter employs proactive, sophisticated systems to measure and block spam bots,” the complaint says. “The reality: mostly outdated, unmonitored, simple scripts plus overworked, inefficient, understaffed, and reactive human teams.”
  • The four people familiar with Twitter’s spam and bot efforts said the engineering and integrity teams run software that samples thousands of tweets per day, and 100 accounts are sampled manually.
  • Some employees charged with executing the fight agreed that they had been short of staff. One said top executives showed “apathy” toward the issue.
  • Zatko’s complaint likewise depicts leadership dysfunction, starting with the CEO. Dorsey was largely absent during the pandemic, which made it hard for Zatko to get rulings on who should be in charge of what in areas of overlap and easier for rival executives to avoid collaborating, three current and former employees said.
  • For example, Zatko would encounter disinformation as part of his mandate to handle complaints, according to the complaint. To that end, he commissioned an outside report that found one of the disinformation teams had unfilled positions, yawning language deficiencies, and a lack of technical tools or the engineers to craft them. The authors said Twitter had no effective means of dealing with consistent spreaders of falsehoods.
  • Dorsey made little effort to integrate Zatko at the company, according to the three employees as well as two others familiar with the process who spoke on the condition of anonymity to describe sensitive dynamics. In 12 months, Zatko could manage only six one-on-one calls, all less than 30 minutes, with his direct boss Dorsey, who also served as CEO of payments company Square, now known as Block, according to the complaint. Zatko allegedly did almost all of the talking, and Dorsey said perhaps 50 words in the entire year to him. “A couple dozen text messages” rounded out their electronic communication, the complaint alleges.
  • Faced with such inertia, Zatko asserts that he was unable to solve some of the most serious issues, according to the complaint.
  • Some 30 percent of company laptops blocked automatic software updates carrying security fixes, and thousands of laptops had complete copies of Twitter’s source code, making them a rich target for hackers, it alleges.
  • A successful hacker takeover of one of those machines would have been able to sabotage the product with relative ease, because the engineers pushed out changes without being forced to test them first in a simulated environment, current and former employees said.
  • “It’s near-incredible that for something of that scale there would not be a development test environment separate from production and there would not be a more controlled source-code management process,” said Tony Sager, former chief operating officer at the cyberdefense wing of the National Security Agency, the Information Assurance divisio
  • Sager is currently senior vice president at the nonprofit Center for Internet Security, where he leads a consensus effort to establish best security practices.
  • Zatko stopped the material from being presented at the Dec. 9, 2021 meeting, the complaint said. But over his continued objections, Agrawal let it go to the board’s smaller Risk Committee a week later.
  • “A best practice is that you should only be authorized to see and access what you need to do your job, and nothing else,” said former U.S. chief information security officer Gregory Touhill. “If half the company has access to and can make configuration changes to the production environment, that exposes the company and its customers to significant risk.”
  • The complaint says Dorsey never encouraged anyone to mislead the board about the shortcomings, but that others deliberately left out bad news.
  • The complaint says that about half of Twitter’s roughly 7,000 full-time employees had wide access to the company’s internal software and that access was not closely monitored, giving them the ability to tap into sensitive data and alter how the service worked. Three current and former employees agreed that these were issues.
  • An unnamed executive had prepared a presentation for the new CEO’s first full board meeting, according to the complaint. Zatko’s complaint calls the presentation deeply misleading.
  • The presentation showed that 92 percent of employee computers had security software installed — without mentioning that those installations determined that a third of the machines were insecure, according to the complaint.
  • Another graphic implied a downward trend in the number of people with overly broad access, based on the small subset of people who had access to the highest administrative powers, known internally as “God mode.” That number was in the hundreds. But the number of people with broad access to core systems, which Zatko had called out as a big problem after joining, had actually grown slightly and remained in the thousands.
  • The presentation included only a subset of serious intrusions or other security incidents, from a total Zatko estimated as one per week, and it said that the uncontrolled internal access to core systems was responsible for just 7 percent of incidents, when Zatko calculated the real proportion as 60 percent.
  • When Dorsey left in November 2021, a difficult situation worsened under Agrawal, who had been responsible for security decisions as chief technology officer before Zatko’s hiring, the complaint says.
  • Agrawal didn’t respond to requests for comment. In an email to employees after publication of this article, obtained by The Post, he said that privacy and security continues to be a top priority for the company, and he added that the narrative is “riddled with inconsistences” and “presented without important context.”
  • On Jan. 4, Zatko reported internally that the Risk Committee meeting might have been fraudulent, which triggered an Audit Committee investigation.
  • Agarwal fired him two weeks later. But Zatko complied with the company’s request to spell out his concerns in writing, even without access to his work email and documents, according to the complaint.
  • Since Zatko’s departure, Twitter has plunged further into chaos with Musk’s takeover, which the two parties agreed to in May. The stock price has fallen, many employees have quit, and Agrawal has dismissed executives and frozen big projects.
  • Zatko said he hoped that by bringing new scrutiny and accountability, he could improve the company from the outside.
  • “I still believe that this is a tremendous platform, and there is huge value and huge risk, and I hope that looking back at this, the world will be a better place, in part because of this.”
Javier E

The Psychopath Makeover - The Chronicle Review - The Chronicle of Higher Education - 0 views

chronicle.com/...135160

psychopathy psychology brain science reading historical development

shared by Javier E on 10 Nov 12 - No Cached
  • The eminent criminal psychologist and creator of the widely used Psychopathy Checklist paused before answering. "I think, in general, yes, society is becoming more psychopathic," he said. "I mean, there's stuff going on nowadays that we wouldn't have seen 20, even 10 years ago. Kids are becoming anesthetized to normal sexual behavior by early exposure to pornography on the Internet. Rent-a-friend sites are getting more popular on the Web, because folks are either too busy or too techy to make real ones. ... The recent hike in female criminality is particularly revealing. And don't even get me started on Wall Street."
  • in a survey that has so far tested 14,000 volunteers, Sara Konrath and her team at the University of Michigan's Institute for Social Research has found that college students' self-reported empathy levels (as measured by the Interpersonal Reactivity Index, a standardized questionnaire containing such items as "I often have tender, concerned feelings for people less fortunate than me" and "I try to look at everybody's side of a disagreement before I make a decision") have been in steady decline over the past three decades—since the inauguration of the scale, in fact, back in 1979. A particularly pronounced slump has been observed over the past 10 years. "College kids today are about 40 percent lower in empathy than their counterparts of 20 or 30 years ago," Konrath reports.
  • Imagining, it would seem, really does make it so. Whenever we read a story, our level of engagement is such that we "mentally simulate each new situation encountered in a narrative," according to one of the researchers, Nicole Speer. Our brains then interweave these newly encountered situations with knowledge and experience gleaned from our own lives to create an organic mosaic of dynamic mental syntheses.
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  • during this same period, students' self-reported narcissism levels have shot through the roof. "Many people see the current group of college students, sometimes called 'Generation Me,' " Konrath continues, "as one of the most self-centered, narcissistic, competitive, confident, and individualistic in recent history."
  • Reading a book carves brand-new neural pathways into the ancient cortical bedrock of our brains. It transforms the way we see the world—makes us, as Nicholas Carr puts it in his recent essay, "The Dreams of Readers," "more alert to the inner lives of others." We become vampires without being bitten—in other words, more empathic. Books make us see in a way that casual immersion in the Internet, and the quicksilver virtual world it offers, doesn't.
  • if society really is becoming more psychopathic, it's not all doom and gloom. In the right context, certain psychopathic characteristics can actually be very constructive. A neurosurgeon I spoke with (who rated high on the psychopathic spectrum) described the mind-set he enters before taking on a difficult operation as "an intoxication that sharpens rather than dulls the senses." In fact, in any kind of crisis, the most effective individuals are often those who stay calm—who are able to respond to the exigencies of the moment while at the same time maintaining the requisite degree of detachment.
  • mental toughness isn't the only characteristic that Special Forces soldiers have in common with psychopaths. There's also fearlessness.
  • I ask Andy whether he ever felt any regret over anything he'd done. Over the lives he'd taken on his numerous secret missions around the world. "No," he replies matter-of-factly, his arctic-blue eyes showing not the slightest trace of emotion. "You seriously don't think twice about it. When you're in a hostile situation, the primary objective is to pull the trigger before the other guy pulls the trigger. And when you pull it, you move on. Simple as that. Why stand there, dwelling on what you've done? Go down that route and chances are the last thing that goes through your head will be a bullet from an M16. "The regiment's motto is 'Who Dares Wins.' But sometimes it can be shortened to 'F--- It.' "
  • one of the things that we know about psychopaths is that the light switches of their brains aren't wired up in quite the same way as the rest of ours are—and that one area particularly affected is the amygdala, a peanut-size structure located right at the center of the circuit board. The amygdala is the brain's emotion-control tower. It polices our emotional airspace and is responsible for the way we feel about things. But in psychopaths, a section of this airspace, the part that corresponds to fear, is empty.
  • Turn down the signals to the amygdala, of course, and you're well on the way to giving someone a psychopath makeover. Indeed, Liane Young and her team in Boston have since kicked things up a notch and demonstrated that applying TMS to the right temporoparietal junction—a neural ZIP code within that neighborhood—has significant effects not just on lying ability but also on moral-reasoning ability: in particular, ascribing intentionality to others' actions.
  • at an undisclosed moment sometime within the next 60 seconds, the image you see at the present time will change, and images of a different nature will appear on the screen. These images will be violent. And nauseating. And of a graphic and disturbing nature. "As you view these images, changes in your heart rate, skin conductance, and EEG activity will be monitored and compared with the resting levels that are currently being recorded
  • "OK," says Nick. "Let's get the show on the road." He disappears behind us, leaving Andy and me merrily soaking up the incontinence ad. Results reveal later that, at this point, as we wait for something to happen, our physiological output readings are actually pretty similar. Our pulse rates are significantly higher than our normal resting levels, in anticipation of what's to come. But with the change of scene, an override switch flips somewhere in Andy's brain. And the ice-cold Special Forces soldier suddenly swings into action. As vivid, florid images of dismemberment, mutilation, torture, and execution flash up on the screen in front of us (so vivid, in fact, that Andy later confesses to actually being able to "smell" the blood: a "kind of sickly-sweet smell that you never, ever forget"), accompanied not by the ambient spa music of before but by blaring sirens and hissing white noise, his physiological readings start slipping into reverse. His pulse rate begins to slow. His GSR begins to drop, his EEG to quickly and dramatically attenuate. In fact, by the time the show is over, all three of Andy's physiological output measures are pooling below his baseline.
  • Nick has seen nothing like it. "It's almost as if he was gearing himself up for the challenge," he says. "And then, when the challenge eventually presented itself, his brain suddenly responded by injecting liquid nitrogen into his veins. Suddenly implemented a blanket neural cull of all surplus feral emotion. Suddenly locked down into a hypnotically deep code red of extreme and ruthless focus." He shakes his head, nonplused. "If I hadn't recorded those readings myself, I'm not sure I would have believed them," he continues. "OK, I've never tested Special Forces before. And maybe you'd expect a slight attenuation in response. But this guy was in total and utter control of the situation. So tuned in, it looked like he'd completely tuned out."
  • My physiological output readings, in contrast, went through the roof. Exactly like Andy's, they were well above baseline as I'd waited for the carnage to commence. But that's where the similarity ended. Rather than go down in the heat of battle, in the midst of the blood and guts, mine had appreciated exponentially. "At least it shows that the equipment is working properly," comments Nick. "And that you're a normal human being."
  • TMS can't penetrate far enough into the brain to reach the emotion and moral-reasoning precincts directly. But by damping down or turning up the regions of the cerebral cortex that have links with such areas, it can simulate the effects of deeper, more incursive influence.
  • Before the experiment, I'd been curious about the time scale: how long it would take me to begin to feel the rush. Now I had the answer: about 10 to 15 minutes. The same amount of time, I guess, that it would take most people to get a buzz out of a beer or a glass of wine.
  • The effects aren't entirely dissimilar. An easy, airy confidence. A transcendental loosening of inhibition. The inchoate stirrings of a subjective moral swagger: the encroaching, and somehow strangely spiritual, realization that hell, who gives a s---, anyway? There is, however, one notable exception. One glaring, unmistakable difference between this and the effects of alcohol. That's the lack of attendant sluggishness. The enhancement of attentional acuity and sharpness. An insuperable feeling of heightened, polished awareness. Sure, my conscience certainly feels like it's on ice, and my anxieties drowned with a half-dozen shots of transcranial magnetic Jack Daniel's. But, at the same time, my whole way of being feels as if it's been sumptuously spring-cleaned with light. My soul, or whatever you want to call it, immersed in a spiritual dishwasher.
  • So this, I think to myself, is how it feels to be a psychopath. To cruise through life knowing that no matter what you say or do, guilt, remorse, shame, pity, fear—all those familiar, everyday warning signals that might normally light up on your psychological dashboard—no longer trouble you.
  • I suddenly get a flash of insight. We talk about gender. We talk about class. We talk about color. And intelligence. And creed. But the most fundamental difference between one individual and another must surely be that of the presence, or absence, of conscience. Conscience is what hurts when everything else feels good. But what if it's as tough as old boots? What if one's conscience has an infinite, unlimited pain threshold and doesn't bat an eye when others are screaming in agony?
Javier E

Moral code | Rough Type - 0 views

www.roughtype.com/?p=2173

morality technology robotics conscience

shared by Javier E on 30 Nov 12 - No Cached
  • So you’re happily tweeting away as your Google self-driving car crosses a bridge, its speed precisely synced to the 50 m.p.h. limit. A group of frisky schoolchildren is also heading across the bridge, on the pedestrian walkway. Suddenly, there’s a tussle, and three of the kids are pushed into the road, right in your vehicle’s path. Your self-driving car has a fraction of a second to make a choice: Either it swerves off the bridge, possibly killing you, or it runs over the children. What does the Google algorithm tell it to do?
  • As we begin to have computer-controlled cars, robots, and other machines operating autonomously out in the chaotic human world, situations will inevitably arise in which the software has to choose between a set of bad, even horrible, alternatives. How do you program a computer to choose the lesser of two evils? What are the criteria, and how do you weigh them?
  • Since we humans aren’t very good at codifying responses to moral dilemmas ourselves, particularly when the precise contours of a dilemma can’t be predicted ahead of its occurrence, programmers will find themselves in an extraordinarily difficult situation. And one assumes that they will carry a moral, not to mention a legal, burden for the code they write.
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  • We don’t even really know what a conscience is, but somebody’s going to have to program one nonetheless.
Javier E

Freedom Loses One - NYTimes.com - 0 views

www.nytimes.com/...brooks-freedom-loses-one.html

freedom values cultural

shared by Javier E on 02 Apr 13 - No Cached
  • we’ve had everything from jeans commercials to rock anthems to political conventions celebrating freedom as the highest ideal.
  • People are much more at liberty these days to follow their desires, unhampered by social convention, religious and ethnic traditions and legal restraints.
  • big thinkers down through the ages warned us this was going to have downsides. Alexis de Tocqueville and Emile Durkheim thought that if people are left perfectly free to pursue their individual desires, they will discover their desires are unlimited and unquenchable. They’ll turn inward and become self-absorbed. Society will become atomized. You’ll end up with more loneliness and less community.
  • ...4 more annotations...
  • Other big thinkers believed that if people are left perfectly free to follow their desires, their baser ones will end up dominating their nobler ones. For these writers, the goal in life is not primarily to be free but to be good. Being virtuous often means thwarting your inclinations, obeying a power outside yourself. It means maintaining a balance between liberty and restraint, restricting freedom for the sake of an ordered existence.
  • Recently, the balance between freedom and restraint has been thrown out of whack. People no longer even have a language to explain why freedom should sometimes be limited. The results are as predicted. A decaying social fabric, especially among the less fortunate. Decline in marriage. More children raised in unsteady homes. Higher debt levels as people spend to satisfy their cravings.
  • who knows, maybe we’ll see other spheres in life where restraints are placed on maximum personal choice. Maybe there will be sumptuary codes that will make lavish spending and C.E.O. salaries unseemly. Maybe there will be social codes so that people understand that the act of creating a child includes a lifetime commitment to give him or her an organized home. Maybe voters will restrain their appetite for their grandchildren’s money. Maybe more straight people will marry.
  • The proponents of same-sex marriage used the language of equality and rights in promoting their cause, because that is the language we have floating around. But, if it wins, same-sex marriage will be a victory for the good life, which is about living in a society that induces you to narrow your choices and embrace your obligations.
oliviaodon

How Do We Learn Languages? | Brain Blogger - 0 views

brainblogger.com/...how-do-we-learn-languages

knowledge languages brain

shared by oliviaodon on 31 Oct 16 - No Cached
  • The use of sound is one of the most common methods of communication both in the animal kingdom and between humans.
  • human speech is a very complex process and therefore needs intensive postnatal learning to be used effectively. Furthermore, to be effective the learning phase should happen very early in life and it assumes a normally functioning hearing and brain systems.
  • Nowadays, scientists and doctors are discovering the important brain zones involved in the processing of language information. Those zones are reassembled in a number of a language networks including the Broca, the Wernicke, the middle temporal, the inferior parietal and the angular gyrus. The variety of such brain zones clearly shows that the language processing is a very complex task. On the functional level, decoding a language begins in the ear where the incoming sounds are summed in the auditory nerve as an electrical signal and delivered to the auditory cortex where neurons extract auditory objects from that signal.
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  • The effectiveness of this process is so great that human brain is able to accurately identify words and whole phrases from a noisy background. This power of analysis brings to minds the great similarity between the brain and powerful supercomputers.
  • Until the last decade few studies compared the language acquisition in adults and children. Thanks to modern imaging and electroencephalography we are now able to address this question.
  • infants begin their lives with a very flexible brain that allows them to acquire virtually any language they are exposed to. Moreover, they can learn a language words almost equally by listening or by visual coding. This brain plasticity is the motor drive of the children capability of “cracking the speech code” of a language. With time, this ability is dramatically decreased and adults find it harder to acquire a new language.
  • clearly demonstrated that there are anatomical brain differences between fast and slow learners of foreign languages. By analyzing a group of people having a homogenous language background, scientists found that differences in specific brain regions can predict the capacity of a person to learn a second language.
  • Functional imaging of the brain revealed that activated brain parts are different between native and non-native speakers. The superior temporal gyrus is an important brain region involved in language learning. For a native speaker this part is responsible for automated processing of lexical retrieval and the build of phrase structure. In native speakers this zone is much more activated than in non-native ones.
  • Language acquisition is a long-term process by which information are stored in the brain unconsciously making them appropriate to oral and written usage. In contrast, language learning is a conscious process of knowledge acquisition that needs supervision and control by the person.
  • oliviaodon on 31 Oct 16
     
    Another cool article about how the brain works and language (inductive reasoning). 
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