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oliviaodon

Neil deGrasse Tyson: Science Deniers In Power Are A Profound Threat To Democracy | The Huffington Post - 0 views

www.huffingtonpost.com/...rs_us_58f99e89e4b06b9cb91572a1

science

shared by oliviaodon on 21 Apr 17 - No Cached
  • The U.S. grew from a “backwoods country” to one of “greatest nations the world has ever known” thanks to science — but that pillar of America is eroding, astrophysicist Neil deGrasse Tyson warns.
  • Science deniers “rising to power” now create a “recipe for the complete dismantling of our informed democracy,”
  • “People have lost the ability to judge what is true and what is not, what is reliable, what is not reliable,” he says in the above video, which he posted to Facebook Wednesday. “That’s not the country I remember growing up in. I don’t remember any other time where people were standing in denial of what science was.”
  • ...2 more annotations...
  • Tyson praises science as an “exercise in finding what is true” that’s based on peer-reviewed experimentation backed by other experiments and counter-experiments that gives birth to an “emergent truth.” He points out that science is “not something to toy with.” “You can’t say, ‘I chose not to believe in E=mc2,’” he says, referring to physicist Albert Einstein’s corroborated theory of special relativity. “You don’t have that option. It is true, whether or not you believe in it.”
  • Tyson warns that every minute someone is in denial of a scientific truth delays the “political solution that should have been established years ago.”  “Recognize what science is, and allow to be what it can and should be: In the service of civilization,” he says. “It’s in our hands.”
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 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.
  • ...52 more annotations...
  • 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 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.
  • 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.
  • “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.
  • 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.
  • 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.”
  • 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.
  • 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.
  • “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.
  • “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.
  • 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.
caelengrubb

Looking inward in an era of 'fake news': Addressing cognitive bias | YLAI Network - 0 views

ylai.state.gov/news-addressing-cognitive-bias

shared by caelengrubb on 07 Jun 21 - No Cached
  • In an era when everyone seems eager to point out instances of “fake news,” it is easy to forget that knowing how we make sense of the news is as important as knowing how to spot incorrect or biased content
  • While the ability to analyze the credibility of a source and the veracity of its content remains an essential and often-discussed aspect of news literacy, it is equally important to understand how we as news consumers engage with and react to the information we find online, in our feeds, and on our apps
  • People process information they receive from the news in the same way they process all information around them — in the shortest, quickest way possible
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  • When we consider how we engage with the news, some shortcuts we may want to pay close attention to, and reflect carefully on, are cognitive biases.
  • In fact, without these heuristics, it would be impossible for us to process all the information we receive daily. However, the use of these shortcuts can lead to “blind spots,” or unintentional ways we respond to information that can have negative consequences for how we engage with, digest, and share the information we encounter
  • These shortcuts, also called heuristics, streamline our problem-solving process and help us make relatively quick decisions.
  • Confirmation bias is the tendency to seek out and value information that confirms our pre-existing beliefs while discarding information that proves our ideas wrong.
  • Cognitive biases are best described as glitches in how we process information
  • Echo chamber effect refers to a situation in which we are primarily exposed to information, people, events, and ideas that already align with our point of view.
  • Anchoring bias, also known as “anchoring,” refers to people’s tendency to consider the first piece of information they receive about a topic as the most reliable
  • The framing effect is what happens when we make decisions based on how information is presented or discussed, rather than its actual substance.
  • Fluency heuristic occurs when a piece of information is deemed more valuable because it is easier to process or recall
  • Everyone operates under one or more cognitive biases. So, when searching for and reading the news (or other information), it is important to be aware of how these biases might shape how we make sense of this information.
  • In conclusion, we may not be able to control the content of the news — whether it is fake, reliable, or somewhere in between — but we can learn to be aware of how we respond to it and adjust our evaluations of the news accordingly.
pier-paolo

Reasons for Reason - The New York Times - 0 views

opinionator.blogs.nytimes.com/...reasons-for-reason

shared by pier-paolo on 02 Nov 20 - No Cached
  • How do we rationally defend our most fundamental epistemic principles? Like many of the best philosophical mysteries, this a problem that can seem both unanswerable and yet extremely important to solve.
  • Any way you go, it seems you must admit you can give no reason for trusting your methods, and hence can give no reason to defend your most fundamental epistemic principles.
  • A legitimate challenge is presumably a rational challenge. Disagreements over epistemic principles are disagreements over which methods and sources to trus
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  • That is, whether I can give reasons for them that can be appreciated from what Hume called a “common point of view” — reasons that can “move some universal principle of the human frame, and touch a string, to which all mankind have an accord and symphony.”
  • Democracies are, or should be, spaces of reasons.
  • we should take the project of defending our epistemic principles seriously is that the ideal of civility demands it.
  • We need to justify our epistemic principles from a common point of view because we need shared epistemic principles in order to even have a common point of view.
  • Without a common background of standards against which we measure what counts as a reliable source of information, or a reliable method of inquiry, and what doesn’t, we won’t be able to agree on the facts, let alone values.
  • But we can’t decide every issue that way, and we certainly can’t decide on our epistemic principles — which methods and sources are actually rationally worthy of trust — by voting
  • They are valuable because almost everyone can appeal to them. They have roots in our natural instincts, as Hume might have said. If so, then perhaps we can hope to give reasons for our epistemic principles. Such reasons will be “merely” practical, but reasons — reasons for reason, as it were — all the same.
peterconnelly

Meet the Wikipedia editor who published the Buffalo shooting entry minutes after it started - CNN - 0 views

www.cnn.com/...index.html

CNN.com

shared by peterconnelly on 03 Jun 22 - No Cached
  • After Jason Moore, from Portland, Oregon, saw headlines from national news sources on Google News about the Buffalo shooting at a local supermarket on Saturday afternoon, he did a quick search for the incident on Wikipedia. When no results appeared, he drafted a single sentence: "On May 14, 2022, 10 people were killed in a mass shooting in Buffalo, New York." He hit save and published the entry on Wikipedia in less than a minute.
  • That article, which as of Friday has been viewed more than 900,000 times, has since undergone 1,071 edits by 223 editors who've voluntarily updated the page on the internet's free and largest crowdsourced encyclopedia.
  • He's credited with creating 50,000 entries
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  • In the middle of breaking news, when people are searching for information, some platforms can present more questions than answers. Although Wikipedia is not staffed with professional journalists, it is viewed as an authoritative source by much of the public, for better or for worse. Its entries are also used for fact-checking purposes by some of the biggest social platforms, adding to the stakes and reach of the work from Moore and others.
  • "Editing Wikipedia can absolutely take an emotional toll on me, especially when working on difficult topics such as the COVID-19 pandemic, mass shootings, terrorist attacks, and other disasters," he said.
  • "I like the instant gratification of making the internet better," he said.
  • "I want to direct people to something that is going to provide them with much more reliable information at a time when it's very difficult for people to understand what sources they can trust."
  • "It is considered cool if you're the first person who creates an article, especially if you do it well with high-quality contributions," said Rasberry.
  • To help patrol incoming edits and predict misconduct or errors, Wikipedia -- like Twitter -- uses artificial intelligence bots that can escalate suspicious content to human reviewers who monitor content.
  • Rasberry, who also wrote the Wikipedia page on the platform's fact checking processes, said Wikipedia does not employ paid staff to monitor anything unless it involves "strange and unusual serious crimes like terrorism or real world violence, such as using Wikipedia to make threats, plan to commit suicide, or when Wikipedia itself is part of a crime.
  • Rasberry said flaws range from a geographical bias, which is related to challenges with communicating across languages; access to internet in lower and middle income countries; and barriers to freedom of journalism around the world.
  • "I've got many other editors that I'm working with who will back me, so when we encounter vandalism or trolls or misinformation or disinformation, editors are very quick to revert inappropriate edits or remove inappropriate content or poorly sourced content," Moore said.
  • While "edit wars" can happen on pages, Rasberry said this tends to occur more often over social issues rather than news.
  • Wikipedia also publicly displays who edits each version of an article via its history page, along with a "talk" page for each post that allows editors to openly discuss edits.
  • "If no reliable sources can be found on a topic, Wikipedia should not have an article on it," the page said.
  • "If it was a paid advertising site or if it had a different mission, I wouldn't waste my time."
criscimagnael

Understanding Science: An overview - 0 views

undsci.berkeley.edu/...intro_01

shared by criscimagnael on 30 May 22 - No Cached
  • Science is, in one sense, our knowledge of all that — all the stuff that is in the universe
  • But just as importantly, science is also a reliable process by which we learn about all that stuff in the universe. However, science is different from many other ways of learning because of the way it is done. Science relies on testing ideas with evidence gathered from the natural world.
  • Science helps satisfy the natural curiosity with which we are all born: why is the sky blue, how did the leopard get its spots, what is a solar eclipse? With science, we can answer such questions without resorting to magical explanations.
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  • Without science, the modern world would not be modern at all, and we still have much to learn.
  • does not deal with supernatural explanations.
  • it is a path to understanding.
  • all science relies on testing ideas by figuring out what expectations are generated by an idea and making observations to find out whether those expectations hold true.
  • Accepted scientific ideas are reliable because they have been subjected to rigorous testing,
  • It relies on a system of checks and balances, which helps ensure that science moves in the direction of greater accuracy and understanding. This system is facilitated by diversity within the scientific community, which offers a broad range of perspectives on scientific ideas.
criscimagnael

Can Forensic Science Be Trusted? - The Atlantic - 0 views

www.theatlantic.com/...629632

shared by criscimagnael on 30 May 22 - No Cached
  • When asked, years later, why she had failed to photograph what she said she’d seen on the enhanced bedsheet, Yezzo replied, “This is one time that I didn’t manage to get it soon enough.” She added: “Operator error.”
  • The words were deployed as definitive by prosecutors—“the evidence is uncontroverted by the scientist, totally uncontroverted”
  • Michael Donnelly, now a justice on the Ohio Supreme Court, did not preside over this case, but he has had ample exposure to the use of forensic evidence. “As a trial judge,” he told me, “I sat there for 14 years. And when forensics experts testified, the jury hung on their every word.”
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  • Forensic science, which drives the plots of movies and television shows, is accorded great respect by the public. And in the proper hands, it can provide persuasive insight. But in the wrong hands, it can trap innocent people in a vise of seeming inerrancy—and it has done so far too often. What’s more, although some forensic disciplines, such as DNA analysis, are reliable, others have been shown to have serious limitations.
  • Yezzo is not like Annie Dookhan, a chemist in a Massachusetts crime laboratory who boosted her productivity by falsifying reports and by “dry labbing”—that is, reporting results without actually conducting any tests.
  • Nor is Yezzo like Michael West, a forensic odontologist who claimed that he could identify bite marks on a victim and then match those marks to a specific person.
  • The deeper issue with forensic science lies not in malfeasance or corruption—or utter incompetence—but in the gray area where Yezzo can be found. Her alleged personal problems are unusual: Only because of them did the details of her long career come to light.
  • to the point of alignment; how rarely an analyst’s skills are called into question in court; and how seldom the performance of crime labs is subjected to any true oversight.
  • More than half of those exonerated by post-conviction DNA testing had been wrongly convicted based on flawed forensic evidence.
  • The quality of the work done in crime labs is almost never audited.
  • Even the best forensic scientists can fall prey to unintentional bias.
  • Study after study has demonstrated the power of cognitive bias.
  • Cognitive bias can of course affect anyone, in any circumstance—but it is particularly dangerous in a criminal-justice system where forensic scientists have wide latitude as well as some incentive to support the views of prosecutors and the police.
Javier E

Tips for Keeping the Peace and Making a Difference Around Politics at Thanksgiving - Ad Fontes Media - 1 views

www.adfontesmedia.com/round-politics-at-thanksgiving

politics bias psychology knowledge persuasion

shared by Javier E on 30 Nov 19 - No Cached
  • Creating more peace, rather than more polarization
  • Avoid starting out with “you’re wrong.” The result of starting out that way is rarely that the other person ends up saying “oh, yes, you are totally right and I AM wrong!” Even if it’s true, it’s usually not effective.
  • If you really plan to get deep into political discussions, I recommend reading up on news sources from the side opposite your views. Really read them closely and deeply. This will familiarize you with the arguments that convince your opposite-side relative and reduce your shock when you hear them repeat those arguments. It will allow you to react with more peace and less anger, and will allow you to prepare your arguments better. Remember, the arguments that convince you (that you read in your news sources) are not the same ones that convince them. Address the arguments that convince them.
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  • Find out exactly what news sources your relatives read and watch and how they access those sources. Do they click on Facebook links, read just the headlines, use apps, visit sites, or watch TV? Inquire with the intent to really understand their habits.
  • If your opposite-side relative flat-out refuses to read any sources outside their own low-reliability, highly biased ones and dismisses sources you find credible out-of-hand, that might be a sign that discussing politics with that relative is not an effective use of your time or energy. In such an instance, I’d just encourage compassion toward them.
  • Share authentically about something that affects you personally. When discussing politics, sharing authentically about something you have experienced is usually much more effective than sharing something abstract about a policy or politician.
  • Avoid starting out with “you’re wrong.” The result of starting out that way is rarely that the other person ends up saying “oh, yes, you are totally right and I AM wrong!” Even if it’s true, it’s usually not effective.
  • Creating more peace, rather than more polarization
  • If you really plan to get deep into political discussions, I recommend reading up on news sources from the side opposite your views. Really read them closely and deeply. This will familiarize you with the arguments that convince your opposite-side relative and reduce your shock when you hear them repeat those arguments. It will allow you to react with more peace and less anger, and will allow you to prepare your arguments better. Remember, the arguments that convince you (that you read in your news sources) are not the same ones that convince them. Address the arguments that convince them.
  • Find out exactly what news sources your relatives read and watch and how they access those sources. Do they click on Facebook links, read just the headlines, use apps, visit sites, or watch TV? Inquire with the intent to really understand their habits.
  • If your opposite-side relative flat-out refuses to read any sources outside their own low-reliability, highly biased ones and dismisses sources you find credible out-of-hand, that might be a sign that discussing politics with that relative is not an effective use of your time or energy. In such an instance, I’d just encourage compassion toward them.
  • Share authentically about something that affects you personally. When discussing politics, sharing authentically about something you have experienced is usually much more effective than sharing something abstract about a policy or politician.
Javier E

His Job Was to Make Instagram Safe for Teens. His 14-Year-Old Showed Him What the App Was Really Like. - WSJ - 0 views

www.wsj.com/...ens-harassment-safety-5d991be1

social media bias technology psychology meta facebook instagram

shared by Javier E on 05 Nov 23 - No Cached
  • The experience of young users on Meta’s Instagram—where Bejar had spent the previous two years working as a consultant—was especially acute. In a subsequent email to Instagram head Adam Mosseri, one statistic stood out: One in eight users under the age of 16 said they had experienced unwanted sexual advances on the platform over the previous seven days.
  • For Bejar, that finding was hardly a surprise. His daughter and her friends had been receiving unsolicited penis pictures and other forms of harassment on the platform since the age of 14, he wrote, and Meta’s systems generally ignored their reports—or responded by saying that the harassment didn’t violate platform rules.
  • “I asked her why boys keep doing that,” Bejar wrote to Zuckerberg and his top lieutenants. “She said if the only thing that happens is they get blocked, why wouldn’t they?”
  • ...39 more annotations...
  • For the well-being of its users, Bejar argued, Meta needed to change course, focusing less on a flawed system of rules-based policing and more on addressing such bad experiences
  • The company would need to collect data on what upset users and then work to combat the source of it, nudging those who made others uncomfortable to improve their behavior and isolating communities of users who deliberately sought to harm others.
  • “I am appealing to you because I believe that working this way will require a culture shift,” Bejar wrote to Zuckerberg—the company would have to acknowledge that its existing approach to governing Facebook and Instagram wasn’t working.
  • During and after Bejar’s time as a consultant, Meta spokesman Andy Stone said, the company has rolled out several product features meant to address some of the Well-Being Team’s findings. Those features include warnings to users before they post comments that Meta’s automated systems flag as potentially offensive, and reminders to be kind when sending direct messages to users like content creators who receive a large volume of messages. 
  • Meta’s classifiers were reliable enough to remove only a low single-digit percentage of hate speech with any degree of precision.
  • Bejar was floored—all the more so when he learned that virtually all of his daughter’s friends had been subjected to similar harassment. “DTF?” a user they’d never met would ask, using shorthand for a vulgar proposition. Instagram acted so rarely on reports of such behavior that the girls no longer bothered reporting them. 
  • Meta’s own statistics suggested that big problems didn’t exist. 
  • Meta had come to approach governing user behavior as an overwhelmingly automated process. Engineers would compile data sets of unacceptable content—things like terrorism, pornography, bullying or “excessive gore”—and then train machine-learning models to screen future content for similar material.
  • While users could still flag things that upset them, Meta shifted resources away from reviewing them. To discourage users from filing reports, internal documents from 2019 show, Meta added steps to the reporting process. Meta said the changes were meant to discourage frivolous reports and educate users about platform rules. 
  • The outperformance of Meta’s automated enforcement relied on what Bejar considered two sleights of hand. The systems didn’t catch anywhere near the majority of banned content—only the majority of what the company ultimately removed
  • “Please don’t talk about my underage tits,” Bejar’s daughter shot back before reporting his comment to Instagram. A few days later, the platform got back to her: The insult didn’t violate its community guidelines.
  • Also buttressing Meta’s statistics were rules written narrowly enough to ban only unambiguously vile material. Meta’s rules didn’t clearly prohibit adults from flooding the comments section on a teenager’s posts with kiss emojis or posting pictures of kids in their underwear, inviting their followers to “see more” in a private Facebook Messenger group. 
  • “Mark personally values freedom of expression first and foremost and would say this is a feature and not a bug,” Rosen responded
  • Narrow rules and unreliable automated enforcement systems left a lot of room for bad behavior—but they made the company’s child-safety statistics look pretty good according to Meta’s metric of choice: prevalence.
  • Defined as the percentage of content viewed worldwide that explicitly violates a Meta rule, prevalence was the company’s preferred measuring stick for the problems users experienced.
  • According to prevalence, child exploitation was so rare on the platform that it couldn’t be reliably estimated, less than 0.05%, the threshold for functional measurement. Content deemed to encourage self-harm, such as eating disorders, was just as minimal, and rule violations for bullying and harassment occurred in just eight of 10,000 views. 
  • “There’s a grading-your-own-homework problem,”
  • Meta defines what constitutes harmful content, so it shapes the discussion of how successful it is at dealing with it.”
  • It could reconsider its AI-generated “beauty filters,” which internal research suggested made both the people who used them and those who viewed the images more self-critical
  • the team built a new questionnaire called BEEF, short for “Bad Emotional Experience Feedback.
  • A recurring survey of issues 238,000 users had experienced over the past seven days, the effort identified problems with prevalence from the start: Users were 100 times more likely to tell Instagram they’d witnessed bullying in the last week than Meta’s bullying-prevalence statistics indicated they should.
  • “People feel like they’re having a bad experience or they don’t,” one presentation on BEEF noted. “Their perception isn’t constrained by policy.
  • they seemed particularly common among teens on Instagram.
  • Among users under the age of 16, 26% recalled having a bad experience in the last week due to witnessing hostility against someone based on their race, religion or identity
  • More than a fifth felt worse about themselves after viewing others’ posts, and 13% had experienced unwanted sexual advances in the past seven days. 
  • The vast gap between the low prevalence of content deemed problematic in the company’s own statistics and what users told the company they experienced suggested that Meta’s definitions were off, Bejar argued
  • To minimize content that teenagers told researchers made them feel bad about themselves, Instagram could cap how much beauty- and fashion-influencer content users saw.
  • Proving to Meta’s leadership that the company’s prevalence metrics were missing the point was going to require data the company didn’t have. So Bejar and a group of staffers from the Well-Being Team started collecting it
  • And it could build ways for users to report unwanted contacts, the first step to figuring out how to discourage them.
  • One experiment run in response to BEEF data showed that when users were notified that their comment or post had upset people who saw it, they often deleted it of their own accord. “Even if you don’t mandate behaviors,” said Krieger, “you can at least send signals about what behaviors aren’t welcome.”
  • But among the ranks of Meta’s senior middle management, Bejar and Krieger said, BEEF hit a wall. Managers who had made their careers on incrementally improving prevalence statistics weren’t receptive to the suggestion that the approach wasn’t working. 
  • After three decades in Silicon Valley, he understood that members of the company’s C-Suite might not appreciate a damning appraisal of the safety risks young users faced from its product—especially one citing the company’s own data. 
  • “This was the email that my entire career in tech trained me not to send,” he says. “But a part of me was still hoping they just didn’t know.”
  • “Policy enforcement is analogous to the police,” he wrote in the email Oct. 5, 2021—arguing that it’s essential to respond to crime, but that it’s not what makes a community safe. Meta had an opportunity to do right by its users and take on a problem that Bejar believed was almost certainly industrywide.
  • fter Haugen’s airing of internal research, Meta had cracked down on the distribution of anything that would, if leaked, cause further reputational damage. With executives privately asserting that the company’s research division harbored a fifth column of detractors, Meta was formalizing a raft of new rules for employees’ internal communication.
  • Among the mandates for achieving “Narrative Excellence,” as the company called it, was to keep research data tight and never assert a moral or legal duty to fix a problem.
  • “I had to write about it as a hypothetical,” Bejar said. Rather than acknowledging that Instagram’s survey data showed that teens regularly faced unwanted sexual advances, the memo merely suggested how Instagram might help teens if they faced such a problem.
  • The hope that the team’s work would continue didn’t last. The company stopped conducting the specific survey behind BEEF, then laid off most everyone who’d worked on it as part of what Zuckerberg called Meta’s “year of efficiency.
  • If Meta was to change, Bejar told the Journal, the effort would have to come from the outside. He began consulting with a coalition of state attorneys general who filed suit against the company late last month, alleging that the company had built its products to maximize engagement at the expense of young users’ physical and mental health. Bejar also got in touch with members of Congress about where he believes the company’s user-safety efforts fell short. 
karenmcgregor

Decoding the Investment: Cost Analysis of CCNA Assignment Writing Help - 1 views

Embarking on the journey towards Cisco Certified Network Associate (CCNA) certification is both commendable and challenging. As students navigate through the intricacies of CCNA coursework, the nee...

#ccnaassignmentwritinghelp #ccna #chargesforccnaassignment #affordableassignmenthelp education

started by karenmcgregor on 09 Jan 24 no follow-up yet
Javier E

Holly the Cat's Incredible Journey - NYTimes.com - 0 views

well.blogs.nytimes.com/...one-cats-incredible-journey

sense perception animal

shared by Javier E on 21 Jan 13 - No Cached
  • “I really believe these stories, but they’re just hard to explain,” said Marc Bekoff, a behavioral ecologist at the University of Colorado. “Maybe being street-smart, maybe reading animal cues, maybe being able to read cars, maybe being a good hunter. I have no data for this.”There is, in fact, little scientific dogma on cat navigation. Migratory animals like birds, turtles and insects have been studied more closely, and use magnetic fields, olfactory cues, or orientation by the sun.
  • Strange, faraway locations would seem problematic, although he and Patrick Bateson, a behavioral biologist at Cambridge University, say that cats can sense smells across long distances. “Let’s say they associate the smell of pine with wind coming from the north, so they move in a southerly direction,”
  • Professor Tabor cited longer-distance reports he considered credible: Murka, a tortoiseshell in Russia, traveling about 325 miles home to Moscow from her owner’s mother’s house in Voronezh in 1989; Ninja, who returned to Farmington, Utah, in 1997, a year after her family moved from there to Mill Creek, Wash.; and Howie, an indoor Persian cat in Australia who in 1978 ran away from relatives his vacationing family left him with and eventually traveled 1,000 miles to his family’s home.
  • ...3 more annotations...
  • The closest, said Roger Tabor, a British cat biologist, may have been a 1954 study in Germany which cats placed in a covered circular maze with exits every 15 degrees most often exited in the direction of their homes, but more reliably if their homes were less than five kilometers away.
  • “We haven’t the slightest idea how they do this,” Mr. Galaxy said. “Anybody who says they do is lying, and, if you find it, please God, tell me what it is.”
  • Nobody knows how it happened: an indoor housecat who got lost on a family excursion managing, after two months and about 200 miles, to return to her hometown.
Javier E

The Future of Sex - The European - 1 views

www.theeuropean-magazine.com/...6576-the-future-of-sex

sex trends mechanistic reproduction intimacy

shared by Javier E on 17 Mar 13 - No Cached
  • Consider the most likely scenario for how human sexual behavior will develop over the next hundred years or so in the absence of cataclysm. Here’s what I see if we continue on our current path:
  • Like every other aspect of human life, our sexuality will become increasingly mediated by technology. The technology of pornography will become ever more sophisticated—even if the subject matter of porn itself will remain as primal as ever.
  • As the technology improves, society continues to grow ever more fragmented, and hundreds of millions of Chinese men with no hope of marrying a bona-fide, flesh-and-blood woman come of age, sex robots will become as common and acceptable as dildos and vibrators are today. After all, the safest sex is that which involves no other living things…
  • ...4 more annotations...
  • As our sexuality becomes ever more divorced from emotion and intimacy, a process already well underway, sex will increasingly be seen as simply a matter of provoking orgasm in the most efficient, reliable ways possible.
  • Human sexuality will continue to be subjected to the same commodification and mechanization as other aspects of our lives. Just as the 21st century saw friends replaced by Facebook friends, nature replaced by parks, ocean fisheries replaced by commercially farmed seafood, and sunshine largely supplanted by tanning salons, we’ll see sexual interaction reduced to mechanically provoked orgasm as human beings become ever more dominated by the machines and mechanistic thought processes that developed in our brains and societies like bacteria in a petri dish.
  • Gender identity will fade away as sexual interaction becomes less “human” and we grow less dependent upon binary interactions with other people. As more and more of our interactions take place with non-human partners, others’ expectations and judgments will become less relevant to the development of sexual identity, leading to greater fluidity and far less urgency and passion concerning sexual expression.
  • the collapse of western civilization may well be the best thing that could happen for human sexuality. Following the collapse of the consumerist, competitive mind-set that now dominates so much of human thought, we’d possibly be free to rebuild a social world more in keeping with our preagricultural origins, characterized by economies built upon sharing rather than hoarding, a politics of respect rather than of power, and a sexuality of intimacy rather than alienation.
Javier E

The Dark Age Of Journalism « The Dish - 0 views

dish.andrewsullivan.com/...the-dark-age-of-journalism

journalism media industry propaganda information ethics

shared by Javier E on 27 Mar 13 - No Cached
  • Anyone who cares deeply about quality, independent journalism should pray for paywalls and other subscription models to take hold. Because in the world of the smart and the desperate, desperate always has the last word.
  • it matters that the industry that is responsible for the dissemination of information is increasingly ceding editorial control to PR firms simply to stay afloat
  • Democracy is a market in which politicians design policies to get votes. Like any market, it relies on information and signals being reliably transmitted from producer to consumer and vice versa. In a situation where the producer can effectively block the signals that actually their policies are designed simply to siphon wealth from everyone else into the pockets of the rich, what do you think happens to that market? Yep, that’s right, you get a choice between red, blue and yellow versions of producers all with the same agenda.
  • ...1 more annotation...
  • We’ve gone from advertizing supporting journalism to journalism supporting corporate propaganda. At the rate we’re going, as the line between church and state is deliberately blurred by desperate media companies, we may end up with a handful of actual independent online magazines and newspapers and a vast industry of corporate propaganda designed to look like the real thing. If we’re lucky.
Javier E

Can Just Anyone Claim to Be a TV Meteorologist? - NYTimes.com - 0 views

www.nytimes.com/...-to-be-a-tv-meteorologist.html

profession self-portrayal reliability

shared by Javier E on 23 Apr 13 - No Cached
  • Does an individual have the right to professionally define who she is, or is that designation dictated by other people? Is there an ethical responsibility to describe oneself in a standardized, universally accepted context?
  • Most titles are self-applied. This is generally fine, because most titles are meaningless. If you declare yourself a futurist or a farmer or a musician (or an ethicist), that’s what you are, even if reasonable people can disagree. Most titles indicate only intent (“I call myself a ____ because that is what I aspire to do”). Failure to fulfill that intent has no significant impact on other people; as such, ethics aren’t really in play
  • But this is not the case for those rarefied professions in which strangers rely on someone they’ve never met to possess essential, functional, nonnegotiable knowledge that no normal person could attain without intense schooling or specialized experience. I would place neurosurgeon near the top of this tier.
Javier E

The Philosophy of Data - NYTimes.com - 0 views

www.nytimes.com/...ks-the-philosophy-of-data.html

data analysis trend

shared by Javier E on 05 Feb 13 - No Cached
  • the rising philosophy of the day, I’d say it is data-ism.
  • We now have the ability to gather huge amounts of data. This ability seems to carry with it certain cultural assumptions — that everything that can be measured should be measured; that data is a transparent and reliable lens that allows us to filter out emotionalism and ideology; that data will help us do remarkable things — like foretell the future.
  • In what situations should we rely on intuitive pattern recognition and in which situations should we ignore intuition and follow the data?
  • ...3 more annotations...
  • two things data does really well.
  • it’s really good at exposing when our intuitive view of reality is wrong
  • data can illuminate patterns of behavior we haven’t yet noticed
Grace Carey

News at Tipitaka Network - 0 views

www.tipitaka.net/...news.php

dogmatism falsification religion ignorance bias faith dual-causation logic Quantum-Physics measurement Reality Heisenberg uncertainty 5-senses perception

shared by Grace Carey on 27 Jan 13 - No Cached
  • Grace Carey on 27 Jan 13
     
    Finding some interesting and very much TOK articles while I'm working on my religious investigation about the science behind Buddhist beliefs. I found this one particularly intriguing as it discusses why the theory of reincarnation is scientifically sound and why scientists are often narrow-minded and overly trusted. "I was once told by a Buddhist G.P. that, on his first day at a medical school in Sydney, the famous Professor, head of the Medical School, began his welcoming address by stating "Half of what we are going to teach you in the next few years is wrong. Our problem is that we do not know which half it is!" Those were the words of a real scientist." "Logic is only as reliable as the assumptions on which it is based." "Objective experience is that which is free from all bias. In Buddhism, the three types of bias are desire, ill-will and skeptical doubt. Desire makes one see only what one wants to see, it bends the truth to fit one's preferences." "Reality, according to pure science, does not consist of well ordered matter with precise massed, energies and positions in space, all just waiting to be measured. Reality is the broadest of smudges of all possibilities, only some being more probable than others." "At a recent seminar on Science and Religion, at which I was a speaker, a Catholic in the audience bravely announced that whenever she looks through a telescope at the stars, she feels uncomfortable because her religion is threatened. I commented that whenever a scientist looks the other way round through a telescope, to observe the one who is watching, then they feel uncomfortable because their science is threatened by what is doing the seeing! "
Javier E

Haidt's Problem With Plato - NYTimes.com - 0 views

opinionator.blogs.nytimes.com/...jonathan-haidts-plato-problem

moral reasoning emotion reason Plato Haidt

shared by Javier E on 05 Oct 12 - No Cached
  • Haidt’s view here is not at all alien to Plato, who saw truth arising only from the right sort of discussion among inquirers accountable to one another. Nor would Plato object to Haidt’s claim that ethics is based on intuition — direct moral judgments — rather than on reasoning. Haidt’s “reasoning” corresponds to what Plato calls dianoia, the process of logically deriving conclusions from given premises.
  • Such logic yields merely hypothetical knowledge (if p, then q), since logic cannot prove the truth of its premises.  Reasoning, therefore, will reliably yield truth only when it is completed by acts of intuition (noesis) that justify the premises from which we reason.
  • Plato’s intuitions are not like the snap judgments of everyday life, driven by genes and social conditioning. But nor are they the insights of individuals meditating in isolation.
  • ...9 more annotations...
  • Haidt’s experimentalist critique of Plato misses its mark because he ignores what Plato actually thought in favor of an oversimplification of his “rationalism.” He does something similar in suggesting that Kant’s ethics reflects a personality within the autism spectrum. Likewise, he implausibly suggests that John Rawls can be refuted by surveys showing that people do not share the judgments Rawls thinks we would make in the fictional situation of his “original position.”
  • Haidt’s own discussion requires him to move beyond empirical studies and in the direction of traditional philosophy.
  • But the great philosophers — Plato, Aristotle, Hume, Spinoza, Hegel, Nietzsche — describe moral experiences far more carefully and subtly than most of us can, and moreover, they provide historical perspectives that can help offset the limitations of our own limited viewpoint.
  • Haidt acknowledges that his concern as a psychologist is overwhelmingly descriptive.  But he says almost nothing about how to connect his work with the compelling normative questions of human life.  Engaging with the extensive philosophical discussions of Hume’s distinction between “is” and “ought” could help fill this major gap in Haidt’s account of ethics
  • I begin by reflecting on Haidt’s effort to refute Plato’s central argument in “The Republic.”  This is where Plato tries to show why a just (morally good) life is superior to an unjust (immoral) life.
  • Haidt pithily summarizes Socrates’ argument: “Reason must rule the happy person. And if reason rules, then it cares about what is truly good, not just about the appearance of virtue.” He maintains that Socrates goes wrong because he assumes a false view of the role of reason in human life. ”Reason is not fit to rule; it was designed to seek justification, not truth,” where justification means pursuing “socially strategic goals, such as guarding our reputations and convincing other people to support us.”
  • Haidt supports his claim about the actual role of reason with an array of fascinating psychological experiments cumulatively showing that “Glaucon was right: people care a great deal more about appearance and reputation than about reality,” and use reason accordingly.
  • Haidt’s psychological studies count against Plato only if we take them as denying any chance of rational control and allowing no alternative to a life dominated by our immediate inclinations — our “gut reactions,” as Haidt puts it. But Haidt makes no such claim, saying only, “we should not expect individuals to produce good, open-minded, truth-seeking reasoning, particularly when self-interest or reputational concerns are in play.”
  • Nevertheless, he adds, “if you put individuals together in the right way … you can create a group that ends up producing good reasoning as an emergent product of the social system.”
carolinewren

Playing Dumb on Climate Change - NYTimes.com - 1 views

www.nytimes.com/...ng-dumb-on-climate-change.html

nytimes com climate change science global warming

shared by carolinewren on 24 Feb 15 - No Cached
  • SCIENTISTS have often been accused of exaggerating the threat of climate change,
  • The year just concluded is about to be declared the hottest one on record,
  • Science is conservative, and new claims of knowledge are greeted with high degrees of skepticism.
  • ...14 more annotations...
  • if there’s more than even a scant 5 percent possibility that an event occurred by chance, scientists will reject the causal claim.
  • correlation is not necessarily causation, because we need to rule out the possibility that we are just observing a coincidence.
  • . In the 18th and 19th centuries, this conservatism generally took the form of a demand for a large amount of evidence; in the 20th century, it took on the form of a demand for statistical significance
  • scientists place the burden of proof on the person making an affirmative claim.
  • the 95 percent level has no actual basis in nature. It is a convention, a value judgment.
  • The 95 percent confidence level is generally credited to the British statistician R. A. Fisher, who was interested in the problem of how to be sure an observed effect of an experiment was not just the result of chance.
  • It places the burden of proof on the victim rather than, for example, on the manufacturer of a harmful product.
  • it might be reasonable to accept a lower statistical threshold when examining effects in people, because you already have reason to believe that the observed effect is not just chance.
  • WHY don’t scientists pick the standard that is appropriate to the case at hand, instead of adhering to an absolutist one?
  • the history of science in relation to religion.
  • long tradition in the history of science that valorizes skepticism as an antidote to religious faith
  • scientists consciously rejected religion as a basis of natural knowledge, they held on to certain cultural presumptions about what kind of person had access to reliable knowledge.
  • they do practice a form of self-denial, denying themselves the right to believe anything that has not passed very high intellectual hurdles.
  • vigorously denying its relation to religion, modern science retains symbolic vestiges of prophetic tradition, so many scientists bend over backward to avoid these associations.
Javier E

Science and gun violence: why is the research so weak? [Part 2] - Boing Boing - 1 views

boingboing.net/...guns.html

social science results methods experiment test research modeling assumption global warming guns public policy

shared by Javier E on 10 Mar 13 - No Cached
  • Scientists are missing some important bits of data that would help them better understand the effects of gun policy and the causes of gun-related violence. But that’s not the only reason why we don’t have solid answers. Once you have the data, you still have to figure out what it means. This is where the research gets complicated, because the problem isn’t simply about what we do and don’t know right now. The problem, say some scientists, is that we —from the public, to politicians, to even scientists themselves—may be trying to force research to give a type of answer that we can’t reasonably expect it to offer. To understand what science can do for the gun debates, we might have to rethink what “evidence-based policy” means to us.
  • For the most part, there aren’t a lot of differences in the data that these studies are using. So how can they reach such drastically different conclusions? The issue is in the kind of data that exists, and what you have to do to understand it, says Charles Manski, professor of economics at Northwestern University. Manski studies the ways that other scientists do research and how that research translates into public policy.
  • Even if we did have those gaps filled in, Manski said, what we’d have would still just be observational data, not experimental data. “We don’t have randomized, controlled experiments, here,” he said. “The only way you could do that, you’d have to assign a gun to some people randomly at birth and follow them throughout their lives. Obviously, that’s not something that’s going to work.”
  • ...14 more annotations...
  • This means that, even under the best circumstances, scientists can’t directly test what the results of a given gun policy are. The best you can do is to compare what was happening in a state before and after a policy was enacted, or to compare two different states, one that has the policy and one that doesn’t. And that’s a pretty inexact way of working.
  • Add in enough assumptions, and you can eventually come up with an estimate. But is the estimate correct? Is it even close to reality? That’s a hard question to answer, because the assumptions you made—the correlations you drew between cause and effect, what you know and what you assume to be true because of that—might be totally wrong.
  • It’s hard to tease apart the effect of one specific change, compared to the effects of other things that could be happening at the same time.
  • This process of taking the observational data we do have and then running it through a filter of assumptions plays out in the real world in the form of statistical modeling. When the NAS report says that nobody yet knows whether more guns lead to more crime, or less crime, what they mean is that the models and the assumptions built into those models are all still proving to be pretty weak.
  • From either side of the debate, he said, scientists continue to produce wildly different conclusions using the same data. On either side, small shifts in the assumptions lead the models to produce different results. Both factions continue to choose sets of assumptions that aren’t terribly logical. It’s as if you decided that anybody with blue shoes probably had a belly-button piercing. There’s not really a good reason for making that correlation. And if you change the assumption—actually, belly-button piercings are more common in people who wear green shoes—you end up with completely different results.
  • The Intergovernmental Panel on Climate Change (IPCC) produces these big reports periodically, which analyze lots of individual papers. In essence, they’re looking at lots of trees and trying to paint you a picture of the forest. IPCC reports are available for free online, you can go and read them yourself. When you do, you’ll notice something interesting about the way that the reports present results. The IPCC never says, “Because we burned fossil fuels and emitted carbon dioxide into the atmosphere then the Earth will warm by x degrees.” Instead, those reports present a range of possible outcomes … for everything. Depending on the different models used, different scenarios presented, and the different assumptions made, the temperature of the Earth might increase by anywhere between 1.5 and 4.5 degrees Celsius.
  • What you’re left with is an environment where it’s really easy to prove that your colleague’s results are probably wrong, and it’s easy for him to prove that yours are probably wrong. But it’s not easy for either of you to make a compelling case for why you’re right.
  • Statistical modeling isn’t unique to gun research. It just happens to be particularly messy in this field. Scientists who study other topics have done a better job of using stronger assumptions and of building models that can’t be upended by changing one small, seemingly randomly chosen detail. It’s not that, in these other fields, there’s only one model being used, or even that all the different models produce the exact same results. But the models are stronger and, more importantly, the scientists do a better job of presenting the differences between models and drawing meaning from them.
  • “Climate change is one of the rare scientific literatures that has actually faced up to this,” Charles Manski said. What he means is that, when scientists model climate change, they don’t expect to produce exact, to-the-decimal-point answers.
  • “It’s been a complete waste of time, because we can’t validate one model versus another,” Pepper said. Most likely, he thinks that all of them are wrong. For instance, all the models he’s seen assume that a law will affect every state in the same way, and every person within that state in the same way. “But if you think about it, that’s just nonsensical,” he said.
  • On the one hand, that leaves politicians in a bit of a lurch. The response you might mount to counteract a 1.5 degree increase in global average temperature is pretty different from the response you’d have to 4.5 degrees. On the other hand, the range does tell us something valuable: the temperature is increasing.
  • The problem with this is that it flies in the face of what most of us expect science to do for public policy. Politics is inherently biased, right? The solutions that people come up with are driven by their ideologies. Science is supposed to cut that Gordian Knot. It’s supposed to lay the evidence down on the table and impartially determine who is right and who is wrong.
  • Manski and Pepper say that this is where we need to rethink what we expect science to do. Science, they say, isn’t here to stop all political debate in its tracks. In a situation like this, it simply can’t provide a detailed enough answer to do that—not unless you’re comfortable with detailed answers that are easily called into question and disproven by somebody else with a detailed answer.
  • Instead, science can reliably produce a range of possible outcomes, but it’s still up to the politicians (and, by extension, up to us) to hash out compromises between wildly differing values on controversial subjects. When it comes to complex social issues like gun ownership and gun violence, science doesn’t mean you get to blow off your political opponents and stake a claim on truth. Chances are, the closest we can get to the truth is a range that encompasses the beliefs of many different groups.
Javier E

Coping with Chaos in the White House - Medium - 0 views

medium.com/...n-the-white-house-697fa2ca3ddf

Trump narcissism character psychology

shared by Javier E on 03 Dec 16 - No Cached
  • I am not a professional and this is not a diagnosis. My post is not intended to persuade anyone or provide a comprehensive description of NPD. I am speaking purely from decades of dealing with NPD and sharing strategies that were helpful for me in coping and predicting behavior.
  • Here are a few things to keep in mind:
  • 1) It’s not curable and it’s barely treatable. He is who he is. There is no getting better, or learning, or adapting. He’s not going to “rise to the occasion” for more than maybe a couple hours. So just put that out of your mind.
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  • 2) He will say whatever feels most comfortable or good to him at any given time. He will lie a lot, and say totally different things to different people. Stop being surprised by this. While it’s important to pretend “good faith” and remind him of promises, as Bernie Sanders and others are doing, that’s for his supporters, so *they* can see the inconsistency as it comes. He won’t care. So if you’re trying to reconcile or analyze his words, don’t. It’s 100% not worth your time. Only pay attention to and address his actions.
  • 3) You can influence him by making him feel good. There are already people like Bannon who appear ready to use him for their own ends. The GOP is excited to try. Watch them, not him.
  • 4) Entitlement is a key aspect of the disorder. As we are already seeing, he will likely not observe traditional boundaries of the office. He has already stated that rules don’t apply to him. This particular attribute has huge implications for the presidency and it will be important for everyone who can to hold him to the same standards as previous presidents.
  • 5) We should expect that he only cares about himself and those he views as extensions of himself, like his children. (People with NPD often can’t understand others as fully human or distinct.) He desires accumulation of wealth and power because it fills a hole.
  • He will have no qualms *at all* about stealing everything he can from the country, and he’ll be happy to help others do so, if they make him feel good. He won’t view it as stealing but rather as something he’s entitled to do. This is likely the only thing he will intentionally accomplish.
  • 6) It’s very, very confusing for non-disordered people to experience a disordered person with NPD. While often intelligent, charismatic and charming, they do not reliably observe social conventions or demonstrate basic human empathy. It’s very common for non-disordered people to lower their own expectations and try to normalize the behavior. DO NOT DO THIS
  • 7) People with NPD often recruit helpers, referred to in the literature as “enablers” when they allow or cover for bad behavior and “flying monkeys” when they perpetrate bad behavior
  • 8) People with NPD often foster competition for sport in people they control. Expect lots of chaos, firings and recriminations. He will probably behave worst toward those closest to him, but that doesn’t mean (obviously) that his actions won’t have consequences for the rest of us. He will punish enemies.
  • 9) Gaslighting — where someone tries to convince you that the reality you’ve experienced isn’t true — is real and torturous. He will gaslight, his followers will gaslight.
  • Learn the signs and find ways to stay focused on what you know to be true. Note: it is typically not helpful to argue with people who are attempting to gaslight. You will only confuse yourself. Just walk away.
  • 10) Whenever possible, do not focus on the narcissist or give him attention. Unfortunately we can’t and shouldn’t ignore the president, but don’t circulate his tweets or laugh at him — you are enabling him and getting his word out.
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