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Javier E

Why it's as hard to escape an echo chamber as it is to flee a cult | Aeon Essays - 0 views

aeon.co/...hamber-as-it-is-to-flee-a-cult

echo-chamber epistemic bubble trust goodwill Descartes network information truth rationality cult filter reliability corroborated bias psychology

shared by Javier E on 29 Jul 22 - No Cached
  • there are two very different phenomena at play here, each of which subvert the flow of information in very distinct ways. Let’s call them echo chambers and epistemic bubbles. Both are social structures that systematically exclude sources of information. Both exaggerate their members’ confidence in their beliefs.
  • they work in entirely different ways, and they require very different modes of intervention
  • An epistemic bubble is when you don’t hear people from the other side. An echo chamber is what happens when you don’t trust people from the other side.
  • ...90 more annotations...
  • start with epistemic bubbles
  • That omission might be purposeful
  • But that omission can also be entirely inadvertent. Even if we’re not actively trying to avoid disagreement, our Facebook friends tend to share our views and interests
  • An ‘echo chamber’ is a social structure from which other relevant voices have been actively discredited. Where an epistemic bubble merely omits contrary views, an echo chamber brings its members to actively distrust outsiders.
  • an echo chamber is something like a cult. A cult isolates its members by actively alienating them from any outside sources. Those outside are actively labelled as malignant and untrustworthy.
  • In epistemic bubbles, other voices are not heard; in echo chambers, other voices are actively undermined.
  • The way to break an echo chamber is not to wave “the facts” in the faces of its members. It is to attack the echo chamber at its root and repair that broken trust.
  • Looking to others for corroboration is a basic method for checking whether one has reasoned well or badly
  • They have been in the limelight lately, most famously in Eli Pariser’s The Filter Bubble (2011) and Cass Sunstein’s #Republic: Divided Democracy in the Age of Social Media (2017).
  • The general gist: we get much of our news from Facebook feeds and similar sorts of social media. Our Facebook feed consists mostly of our friends and colleagues, the majority of whom share our own political and cultural views
  • various algorithms behind the scenes, such as those inside Google search, invisibly personalise our searches, making it more likely that we’ll see only what we want to see. These processes all impose filters on information.
  • Such filters aren’t necessarily bad. The world is overstuffed with information, and one can’t sort through it all by oneself: filters need to be outsourced.
  • That’s why we all depend on extended social networks to deliver us knowledge
  • any such informational network needs the right sort of broadness and variety to work
  • Each individual person in my network might be superbly reliable about her particular informational patch but, as an aggregate structure, my network lacks what Sanford Goldberg in his book Relying on Others (2010) calls ‘coverage-reliability’. It doesn’t deliver to me a sufficiently broad and representative coverage of all the relevant information.
  • Epistemic bubbles also threaten us with a second danger: excessive self-confidence.
  • An ‘epistemic bubble’ is an informational network from which relevant voices have been excluded by omission
  • Suppose that I believe that the Paleo diet is the greatest diet of all time. I assemble a Facebook group called ‘Great Health Facts!’ and fill it only with people who already believe that Paleo is the best diet. The fact that everybody in that group agrees with me about Paleo shouldn’t increase my confidence level one bit. They’re not mere copies – they actually might have reached their conclusions independently – but their agreement can be entirely explained by my method of selection.
  • Luckily, though, epistemic bubbles are easily shattered. We can pop an epistemic bubble simply by exposing its members to the information and arguments that they’ve missed.
  • echo chambers are a far more pernicious and robust phenomenon.
  • amieson and Cappella’s book is the first empirical study into how echo chambers function
  • echo chambers work by systematically alienating their members from all outside epistemic sources.
  • Their research centres on Rush Limbaugh, a wildly successful conservative firebrand in the United States, along with Fox News and related media
  • His constant attacks on the ‘mainstream media’ are attempts to discredit all other sources of knowledge. He systematically undermines the integrity of anybody who expresses any kind of contrary view.
  • outsiders are not simply mistaken – they are malicious, manipulative and actively working to destroy Limbaugh and his followers. The resulting worldview is one of deeply opposed force, an all-or-nothing war between good and evil
  • The result is a rather striking parallel to the techniques of emotional isolation typically practised in cult indoctrination
  • cult indoctrination involves new cult members being brought to distrust all non-cult members. This provides a social buffer against any attempts to extract the indoctrinated person from the cult.
  • The echo chamber doesn’t need any bad connectivity to function. Limbaugh’s followers have full access to outside sources of information
  • As Elijah Millgram argues in The Great Endarkenment (2015), modern knowledge depends on trusting long chains of experts. And no single person is in the position to check up on the reliability of every member of that chain
  • Their worldview can survive exposure to those outside voices because their belief system has prepared them for such intellectual onslaught.
  • exposure to contrary views could actually reinforce their views. Limbaugh might offer his followers a conspiracy theory: anybody who criticises him is doing it at the behest of a secret cabal of evil elites, which has already seized control of the mainstream media.
  • Perversely, exposure to outsiders with contrary views can thus increase echo-chamber members’ confidence in their insider sources, and hence their attachment to their worldview.
  • ‘evidential pre-emption’. What’s happening is a kind of intellectual judo, in which the power and enthusiasm of contrary voices are turned against those contrary voices through a carefully rigged internal structure of belief.
  • One might be tempted to think that the solution is just more intellectual autonomy. Echo chambers arise because we trust others too much, so the solution is to start thinking for ourselves.
  • that kind of radical intellectual autonomy is a pipe dream. If the philosophical study of knowledge has taught us anything in the past half-century, it is that we are irredeemably dependent on each other in almost every domain of knowledge
  • Limbaugh’s followers regularly read – but do not accept – mainstream and liberal news sources. They are isolated, not by selective exposure, but by changes in who they accept as authorities, experts and trusted sources.
  • we depend on a vastly complicated social structure of trust. We must trust each other, but, as the philosopher Annette Baier says, that trust makes us vulnerable. Echo chambers operate as a kind of social parasite on that vulnerability, taking advantage of our epistemic condition and social dependency.
  • I am quite confident that there are plenty of echo chambers on the political Left. More importantly, nothing about echo chambers restricts them to the arena of politics
  • The world of anti-vaccination is clearly an echo chamber, and it is one that crosses political lines. I’ve also encountered echo chambers on topics as broad as diet (Paleo!), exercise technique (CrossFit!), breastfeeding, some academic intellectual traditions, and many, many more
  • Here’s a basic check: does a community’s belief system actively undermine the trustworthiness of any outsiders who don’t subscribe to its central dogmas? Then it’s probably an echo chamber.
  • much of the recent analysis has lumped epistemic bubbles together with echo chambers into a single, unified phenomenon. But it is absolutely crucial to distinguish between the two.
  • Epistemic bubbles are rather ramshackle; they go up easily, and they collapse easily
  • Echo chambers are far more pernicious and far more robust. They can start to seem almost like living things. Their belief systems provide structural integrity, resilience and active responses to outside attacks
  • the two phenomena can also exist independently. And of the events we’re most worried about, it’s the echo-chamber effects that are really causing most of the trouble.
  • new data does, in fact, seem to show that people on Facebook actually do see posts from the other side, or that people often visit websites with opposite political affiliation.
  • their basis for evaluation – their background beliefs about whom to trust – are radically different. They are not irrational, but systematically misinformed about where to place their trust.
  • Many people have claimed that we have entered an era of ‘post-truth’.
  • Not only do some political figures seem to speak with a blatant disregard for the facts, but their supporters seem utterly unswayed by evidence. It seems, to some, that truth no longer matters.
  • This is an explanation in terms of total irrationality. To accept it, you must believe that a great number of people have lost all interest in evidence or investigation, and have fallen away from the ways of reason.
  • echo chambers offers a less damning and far more modest explanation. The apparent ‘post-truth’ attitude can be explained as the result of the manipulations of trust wrought by echo chambers.
  • We don’t have to attribute a complete disinterest in facts, evidence or reason to explain the post-truth attitude. We simply have to attribute to certain communities a vastly divergent set of trusted authorities.
  • An echo chamber doesn’t destroy their members’ interest in the truth; it merely manipulates whom they trust and changes whom they accept as trustworthy sources and institutions.
  • in many ways, echo-chamber members are following reasonable and rational procedures of enquiry. They’re engaging in critical reasoning. They’re questioning, they’re evaluating sources for themselves, they’re assessing different pathways to information. They are critically examining those who claim expertise and trustworthiness, using what they already know about the world
  • none of this weighs against the existence of echo chambers. We should not dismiss the threat of echo chambers based only on evidence about connectivity and exposure.
  • Notice how different what’s going on here is from, say, Orwellian doublespeak, a deliberately ambiguous, euphemism-filled language designed to hide the intent of the speaker.
  • echo chambers don’t trade in vague, ambiguous pseudo-speech. We should expect that echo chambers would deliver crisp, clear, unambiguous claims about who is trustworthy and who is not
  • clearly articulated conspiracy theories, and crisply worded accusations of an outside world rife with untrustworthiness and corruption.
  • Once an echo chamber starts to grip a person, its mechanisms will reinforce themselves.
  • In an epistemically healthy life, the variety of our informational sources will put an upper limit to how much we’re willing to trust any single person. Everybody’s fallible; a healthy informational network tends to discover people’s mistakes and point them out. This puts an upper ceiling on how much you can trust even your most beloved leader
  • nside an echo chamber, that upper ceiling disappears.
  • Being caught in an echo chamber is not always the result of laziness or bad faith. Imagine, for instance, that somebody has been raised and educated entirely inside an echo chamber
  • when the child finally comes into contact with the larger world – say, as a teenager – the echo chamber’s worldview is firmly in place. That teenager will distrust all sources outside her echo chamber, and she will have gotten there by following normal procedures for trust and learning.
  • It certainly seems like our teenager is behaving reasonably. She could be going about her intellectual life in perfectly good faith. She might be intellectually voracious, seeking out new sources, investigating them, and evaluating them using what she already knows.
  • The worry is that she’s intellectually trapped. Her earnest attempts at intellectual investigation are led astray by her upbringing and the social structure in which she is embedded.
  • Echo chambers might function like addiction, under certain accounts. It might be irrational to become addicted, but all it takes is a momentary lapse – once you’re addicted, your internal landscape is sufficiently rearranged such that it’s rational to continue with your addiction
  • Similarly, all it takes to enter an echo chamber is a momentary lapse of intellectual vigilance. Once you’re in, the echo chamber’s belief systems function as a trap, making future acts of intellectual vigilance only reinforce the echo chamber’s worldview.
  • There is at least one possible escape route, however. Notice that the logic of the echo chamber depends on the order in which we encounter the evidence. An echo chamber can bring our teenager to discredit outside beliefs precisely because she encountered the echo chamber’s claims first. Imagine a counterpart to our teenager who was raised outside of the echo chamber and exposed to a wide range of beliefs. Our free-range counterpart would, when she encounters that same echo chamber, likely see its many flaws
  • Those caught in an echo chamber are giving far too much weight to the evidence they encounter first, just because it’s first. Rationally, they should reconsider their beliefs without that arbitrary preference. But how does one enforce such informational a-historicity?
  • The escape route is a modified version of René Descartes’s infamous method.
  • Meditations on First Philosophy (1641). He had come to realise that many of the beliefs he had acquired in his early life were false. But early beliefs lead to all sorts of other beliefs, and any early falsehoods he’d accepted had surely infected the rest of his belief system.
  • The only solution, thought Descartes, was to throw all his beliefs away and start over again from scratch.
  • He could start over, trusting nothing and no one except those things that he could be entirely certain of, and stamping out those sneaky falsehoods once and for all. Let’s call this the Cartesian epistemic reboot.
  • Notice how close Descartes’s problem is to our hapless teenager’s, and how useful the solution might be. Our teenager, like Descartes, has problematic beliefs acquired in early childhood. These beliefs have infected outwards, infesting that teenager’s whole belief system. Our teenager, too, needs to throw everything away, and start over again.
  • Let’s call the modernised version of Descartes’s methodology the social-epistemic reboot.
  • when she starts from scratch, we won’t demand that she trust only what she’s absolutely certain of, nor will we demand that she go it alone
  • For the social reboot, she can proceed, after throwing everything away, in an utterly mundane way – trusting her senses, trusting others. But she must begin afresh socially – she must reconsider all possible sources of information with a presumptively equanimous eye. She must take the posture of a cognitive newborn, open and equally trusting to all outside sources
  • we’re not asking people to change their basic methods for learning about the world. They are permitted to trust, and trust freely. But after the social reboot, that trust will not be narrowly confined and deeply conditioned by the particular people they happened to be raised by.
  • Such a profound deep-cleanse of one’s whole belief system seems to be what’s actually required to escape. Look at the many stories of people leaving cults and echo chambers
  • Take, for example, the story of Derek Black in Florida – raised by a neo-Nazi father, and groomed from childhood to be a neo-Nazi leader. Black left the movement by, basically, performing a social reboot. He completely abandoned everything he’d believed in, and spent years building a new belief system from scratch. He immersed himself broadly and open-mindedly in everything he’d missed – pop culture, Arabic literature, the mainstream media, rap – all with an overall attitude of generosity and trust.
  • It was the project of years and a major act of self-reconstruction, but those extraordinary lengths might just be what’s actually required to undo the effects of an echo-chambered upbringing.
  • we need to attack the root, the systems of discredit themselves, and restore trust in some outside voices.
  • Stories of actual escapes from echo chambers often turn on particular encounters – moments when the echo-chambered individual starts to trust somebody on the outside.
  • Black’s is case in point. By high school, he was already something of a star on neo-Nazi media, with his own radio talk-show. He went on to college, openly neo-Nazi, and was shunned by almost every other student in his community college. But then Matthew Stevenson, a Jewish fellow undergraduate, started inviting Black to Stevenson’s Shabbat dinners. In Black’s telling, Stevenson was unfailingly kind, open and generous, and slowly earned Black’s trust. This was the seed, says Black, that led to a massive intellectual upheaval – a slow-dawning realisation of the depths to which he had been misled
  • Similarly, accounts of people leaving echo-chambered homophobia rarely involve them encountering some institutionally reported fact. Rather, they tend to revolve around personal encounters – a child, a family member, a close friend coming out.
  • hese encounters matter because a personal connection comes with a substantial store of trust.
  • We don’t simply trust people as educated experts in a field – we rely on their goodwill. And this is why trust, rather than mere reliability, is the key concept
  • goodwill is a general feature of a person’s character. If I demonstrate goodwill in action, then you have some reason to think that I also have goodwill in matters of thought and knowledge.
  • f one can demonstrate goodwill to an echo-chambered member – as Stevenson did with Black – then perhaps one can start to pierce that echo chamber.
  • the path I’m describing is a winding, narrow and fragile one. There is no guarantee that such trust can be established, and no clear path to its being established systematically.
  • what we’ve found here isn’t an escape route at all. It depends on the intervention of another. This path is not even one an echo-chamber member can trigger on her own; it is only a whisper-thin hope for rescue from the outside.
dicindioha

Daniel Kahneman On Hiring Decisions - Business Insider - 0 views

www.businessinsider.com/man-on-hiring-decisions-2013-1

shared by dicindioha on 03 May 17 - No Cached
  • Most hiring decisions come down to a gut decision. According to Nobel laureate Daniel Kahneman, however, this process is extremely flawed and there's a much better way.
    • dicindioha
      dicindioha on 03 May 17
       
      hiring comes down to 'gut feeling'
  • Kahneman asked interviewers to put aside personal judgments and limit interviews to a series of factual questions meant to generate a score on six separate personality traits. A few months later, it became clear that Kahneman's systematic approach was a vast improvement over gut decisions. It was so effective that the army would use his exact method for decades to come. Why you should care is because this superior method can be copied by any organization — and really, by anyone facing a hard decision.
  • First, select a few traits that are prerequisites for success in this position (technical proficiency, engaging personality, reliability, and so on. Don't overdo it — six dimensions is a good number. The traits you choose should be as independent as possible from each other, and you should feel that you can assess them reliably by asking a few factual questions. Next, make a list of those questions for each trait and think about how you will score it, say on a 1-5 scale. You should have an idea of what you will call "very weak" or "very strong."
    • dicindioha
      dicindioha on 03 May 17
       
      WHAT YOU SHOULD DO IN AN INTERVIEW
  • ...2 more annotations...
  • Do not skip around. To evaluate each candidate add up the six scores ... Firmly resolve that you will hire the candidate whose final score is the highest, even if there is another one whom you like better — try to resist your wish to invent broken legs to change the ranking.
  • than if you do what people normally do in such situations, which is to go into the interview unprepared and to make choices by an overall intuitive judgment such as "I looked into his eyes and liked what I saw."
  • dicindioha on 03 May 17
     
    we cannot always use simply a 'gut feeling' from our so called 'reasoning' and emotional response to make big decisions like job hiring, which is what happens much of the time. this is a really interesting way to do it systematically. you still use your own perspective, but the questions asked will hopefully lead you to a better outcome
peterconnelly

AI model's insight helps astronomers propose new theory for observing far-off worlds | ... - 0 views

techcrunch.com/...y-for-observing-far-off-worlds

techcrunch

shared by peterconnelly on 03 Jun 22 - No Cached
  • Machine learning models are increasingly augmenting human processes, either performing repetitious tasks faster or providing some systematic insight that helps put human knowledge in perspective.
  • Astronomers at UC Berkeley were surprised to find both happen after modeling gravitational microlensing events, leading to a new unified theory for the phenomenon.
  • Gravitational lensing occurs when light from far-off stars and other stellar objects bends around a nearer one directly between it and the observer, briefly giving a brighter — but distorted — view of the farther one.
  • ...7 more annotations...
  • Ambiguities are often reconciled with other observed data, such as that we know by other means that the planet is too small to cause the scale of distortion seen.
  • “The two previous theories of degeneracy deal with cases where the background star appears to pass close to the foreground star or the foreground planet. The AI algorithm showed us hundreds of examples from not only these two cases, but also situations where the star doesn’t pass close to either the star or planet and cannot be explained by either previous theory,” said Zhang in a Berkeley news release.
  • But without the systematic and confident calculations of the AI, it’s likely the simplified, less correct theory would have persisted for many more years.
  • As a result — and after some convincing, since a grad student questioning established doctrine is tolerated but perhaps not encouraged — they ended up proposing a new, “unified” theory of how degeneracy in these observations can be explained, of which the two known theories were simply the most common cases.
  • “People were seeing these microlensing events, which actually were exhibiting this new degeneracy but just didn’t realize it. It was really just the machine learning looking at thousands of events where it became impossible to miss,” said Scott Gaudi
  • But Zhang seemed convinced that the AI had clocked something that human observers had systematically overlooked.
  • Just as people learned to trust calculators and later computers, we are learning to trust some AI models to output an interesting truth clear of preconceptions and assumptions — that is, if we haven’t just coded our own preconceptions and assumptions into them.
sissij

By Demanding Too Much from Science, We Became a Post-Truth Society | Big Think - 1 views

bigthink.com/...dont-trust-the-experts-anymore

society science brain science research

shared by sissij on 10 Feb 17 - No Cached
  • The number of people who today openly question reality are not the tin-foil hat-wearing kind. Increasingly they are our friends, and those who hold positions of power.
  • Indeed, the public understanding of what constitutes valid evidence, and a worthy expert opinion, seems to be at an all time low.
  • Well, a new study suggests that this wealth of information might be the problem.
  • ...6 more annotations...
  • A new study out of Germany has found that people are much more confident in the claims of a popular science article then they are in the claims of an academic article written for experts
  • It was also found that the subjects were more confident in their own judgments after reading a popular article, and that this was tied to a lessened desire to seek out more information from expert sources.
  • "easiness effect”
  • the issue arises from the manner in which popular science is presented; as opposed to how scientists themselves present data to each other and to the public.
  • This emboldens people to reject the ideas of experts who they see as superfluous to their understanding of an idea (which they have already grasped).
  • notably health
  • sissij on 10 Feb 17
     
    Although many people allege themselves being scientific when trying to convince others by using the scientific researches they read on the mass media, does that really make their points more reliable? Not really. The popular science is sometimes not as meticulous as the academic article article written for experts. In popular science articles, the authors often changed their writing style to favor the general population, like having a more certain tone. This appeals to readers' desire for simplicity and this tendency is called the "easiness effect", which I find is really similar to the logic fallacy we talked about in TOK. Science itself has more and more become a table that can make an argument seem more rational. However, science is all about the scientific method used in the research that is an art of systematic simplification. Without these element, the title "science" means nothing. --Sissi (2/10/2017)
abby deardorff

Musical Training Optimizes Brain Function | Psychology Today - 0 views

www.psychologytoday.com/...ining-optimizes-brain-function

brain psychology

shared by abby deardorff on 18 Nov 13 - No Cached
  • Three Brain Benefits of Musical Training:
  • musical training can have a huge impact on the developing brain
  • systematic training actually helped improve brain areas related to music improvisation.
  • ...3 more annotations...
  • training before the age of 7 years results in changes in white-matter connectivity that may serve as a solid scaffolding upon which ongoing experience can maintain a well-connected brain infrastructure into adulthood.
  • musical training improves the function and connectivity of different brain regions. Musical training increases brain volume and strengthens communication between brain areas. Playing an instrument changes how the brain interprets and integrates a wide range of sensory information, especially for those who start before age 7.
  • Musicians have an enhanced ability to integrate sensory information from hearing, touch, and sight.The age at which musical training begins affects brain anatomy as an adult; beginning training before the age of seven has the greatest impact.Brain circuits involved in musical improvisation are shaped by systematic training, leading to less reliance on working memory and more extensive connectivity within the brain.
jlessner

Straight Talk for White Men - NYTimes.com - 0 views

www.nytimes.com/...raight-talk-for-white-men.html

science Research bias

shared by jlessner on 22 Feb 15 - No Cached
  • SUPERMARKET shoppers are more likely to buy French wine when French music is playing, and to buy German wine when they hear German music. That’s true even though only 14 percent of shoppers say they noticed the music, a study finds.
  • Researchers discovered that candidates for medical school interviewed on sunny days received much higher ratings than those interviewed on rainy days. Being interviewed on a rainy day was a setback equivalent to having an MCAT score 10 percent lower, according to a new book called “Everyday Bias,” by Howard J. Ross.
  • Those studies are a reminder that we humans are perhaps less rational than we would like to think, and more prone to the buffeting of unconscious influences. That’s something for those of us who are white men to reflect on when we’re accused of “privilege.”
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  • When I wrote a series last year, “When Whites Just Don’t Get It,” the reaction from white men was often indignant: It’s an equal playing field now! Get off our case!
  • Yet the evidence is overwhelming that unconscious bias remains widespread in ways that systematically benefit both whites and men. So white men get a double dividend, a payoff from both racial and gender biases.
  • male professors are disproportionately likely to be described as a “star” or “genius.” Female professors are disproportionately described as “nasty,” “ugly,” “bossy” or “disorganized.”
  • When students were taking the class from someone they believed to be male, they rated the teacher more highly. The very same teacher, when believed to be female, was rated significantly lower.
  • The study found that a résumé with a name like Emily or Greg received 50 percent more callbacks than the same résumé with a name like Lakisha or Jamal. Having a white-sounding name was as beneficial as eight years’ work experience.
  • Then there was the study in which researchers asked professors to evaluate the summary of a supposed applicant for a post as laboratory manager, but, in some cases, the applicant was named John and in others Jennifer. Everything else was the same.“John” was rated an average of 4.0 on a 7-point scale for competence, “Jennifer” a 3.3. When asked to propose an annual starting salary for the applicant, the professors suggested on average a salary for “John” almost $4,000 higher than for “Jennifer.”Continue reading the main story Continue reading the main story
  • While we don’t notice systematic unfairness, we do observe specific efforts to redress it — such as affirmative action, which often strikes white men as profoundly unjust. Thus a majority of white Americans surveyed in a 2011 study said that there is now more racism against whites than against blacks.
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
  • ...52 more annotations...
  • 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.
katedriscoll

Frontiers | A Neural Network Framework for Cognitive Bias | Psychology - 0 views

www.frontiersin.org/...full

shared by katedriscoll on 28 Mar 21 - No Cached
  • Human decision-making shows systematic simplifications and deviations from the tenets of rationality (‘heuristics’) that may lead to suboptimal decisional outcomes (‘cognitive biases’). There are currently three prevailing theoretical perspectives on the origin of heuristics and cognitive biases: a cognitive-psychological, an ecological and an evolutionary perspective. However, these perspectives are mainly descriptive and none of them provides an overall explanatory framework for
  • the underlying mechanisms of cognitive biases. To enhance our understanding of cognitive heuristics and biases we propose a neural network framework for cognitive biases, which explains why our brain systematically tends to default to heuristic (‘Type 1’) decision making. We argue that many cognitive biases arise from intrinsic brain mechanisms that are fundamental for the working of biological neural networks. To substantiate our viewpoint, we discern and explain four basic neural network principles: (1) Association, (2) Compatibility, (3) Retainment, and (4) Focus. These principles are inherent to (all) neural networks which were originally optimized to perform concrete biological, perceptual, and motor functions. They form the basis for our inclinations to associate and combine (unrelated) information, to prioritize information that is compatible with our present state (such as knowledge, opinions, and expectations), to retain given information that sometimes could better be ignored, and to focus on dominant information while ignoring relevant information that is not directly activated. The supposed mechanisms are complementary and not mutually exclusive. For different cognitive biases they may all contribute in varying degrees to distortion of information. The present viewpoint not only complements the earlier three viewpoints, but also provides a unifying and binding framework for many cognitive bias phenomena.
  • The cognitive-psychological (or heuristics and biases) perspective (Evans, 2008; Kahneman and Klein, 2009) attributes cognitive biases to limitations in the available data and in the human information processing capacity (Simon, 1955; Broadbent, 1958; Kahneman, 1973, 2003; Norman and Bobrow, 1975)
katedriscoll

Fallacies | Internet Encyclopedia of Philosophy - 0 views

iep.utm.edu/fallacy

shared by katedriscoll on 03 Nov 20 - No Cached
  • A fallacy is a kind of error in reasoning. The list of fallacies  below contains 229 names of the most common fallacies, and it provides brief explanations and examples of each of them. Fallacious arguments should not be persuasive, but they too often are. Fallacies may be created unintentionally, or they may be created intentionally in order to deceive other people
  • The vast majority of the commonly identified fallacies involve arguments, although some involve only explanations, or definitions, or other products of reasoning. Sometimes the term “fallacy” is used even more broadly to indicate any false belief or cause of a false belief. The list below includes some fallacies of these sorts, but most are fallacies that involve kinds of errors made while arguing informally in natural language.
  • The first known systematic study of fallacies was due to Aristotle in his De Sophisticis Elenchis (Sophistical Refutations), an appendix to the Topics. He listed thirteen types. After the Dark Ages, fallacies were again studied systematically in Medieval Europe. This is why so many fallacies have Latin names. The third major period of study of the fallacies began in the later twentieth century due to renewed interest from the disciplines of philosophy, logic, communication studies, rhetoric, psychology, and artificial intelligence.
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  • The term “fallacy” is not a precise term. One reason is that it is ambiguous. It can refer either to (a) a kind of error in an argument, (b) a kind of error in reasoning (including arguments, definitions, explanations, and so forth), (c) a false belief, or (d) the cause of any of the previous errors including what are normally referred to as “rhetorical techniques.” Philosophers who are researchers in fallacy theory prefer to emphasize (a), but their lead is often not followed in textbooks and public discussion.
  • Consulting the list below will give a general idea of the kind of error involved in passages to which the fallacy name is applied. However, simply applying the fallacy name to a passage cannot substitute for a detailed examination of the passage and its context or circumstances because there are many instances of reasoning to which a fallacy name might seem to apply, yet, on further examination, it is found that in these circumstances the reasoning is really not fallacious.
  • katedriscoll on 03 Nov 20
     
    In TOK we talked about just a couple types of fallacies.Turns out there are hundreds of fallacies. This article explains what a fallacy, the history of it as well as a list of the most common fallacies.
Javier E

Grand Old Planet - NYTimes.com - 1 views

www.nytimes.com/...krugman-grand-old-planet.html

science bias partisan motivated reasoning knowledge evidence

shared by Javier E on 23 Nov 12 - No Cached
  • Mr. Rubio was asked how old the earth is. After declaring “I’m not a scientist, man,” the senator went into desperate evasive action, ending with the declaration that “it’s one of the great mysteries.”
  • Reading Mr. Rubio’s interview is like driving through a deeply eroded canyon; all at once, you can clearly see what lies below the superficial landscape. Like striated rock beds that speak of deep time, his inability to acknowledge scientific evidence speaks of the anti-rational mind-set that has taken over his political party.
  • that question didn’t come out of the blue. As speaker of the Florida House of Representatives, Mr. Rubio provided powerful aid to creationists trying to water down science education. In one interview, he compared the teaching of evolution to Communist indoctrination tactics — although he graciously added that “I’m not equating the evolution people with Fidel Castro.
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  • What was Mr. Rubio’s complaint about science teaching? That it might undermine children’s faith in what their parents told them to believe.
  • What accounts for this pattern of denial? Earlier this year, the science writer Chris Mooney published “The Republican Brain,” which was not, as you might think, a partisan screed. It was, instead, a survey of the now-extensive research linking political views to personality types. As Mr. Mooney showed, modern American conservatism is highly correlated with authoritarian inclinations — and authoritarians are strongly inclined to reject any evidence contradicting their prior beliefs
  • it’s not symmetric. Liberals, being human, often give in to wishful thinking — but not in the same systematic, all-encompassing way.
  • We are, after all, living in an era when science plays a crucial economic role. How are we going to search effectively for natural resources if schools trying to teach modern geology must give equal time to claims that the world is only 6.000 years old? How are we going to stay competitive in biotechnology if biology classes avoid any material that might offend creationists?
  • then there’s the matter of using evidence to shape economic policy. You may have read about the recent study from the Congressional Research Service finding no empirical support for the dogma that cutting taxes on the wealthy leads to higher economic growth. How did Republicans respond? By suppressing the report. On economics, as in hard science, modern conservatives don’t want to hear anything challenging their preconceptions — and they don’t want anyone else to hear about it, either.
Javier E

Is Confidence in Science as a Source of Progress Based on Faith or Fact? - NYTimes.com - 3 views

dotearth.blogs.nytimes.com/...rogress-based-on-faith-or-fact

science progress faith fact justification application ssss

shared by Javier E on 23 Dec 11 - No Cached
  • There’s been a range of interesting reactions to my piece on Pete Seeger’s question about whether confidence in science as a source of human progress is underpinned by fact or faith.
  • the discussion was not about confidence in science as an enterprise, but confidence that benefits would always accrue to society from applications of scientific knowledge
  • Theologically speaking, science constantly reminds us of the sense in which we are nearly – but clearly not quite – gods. Perhaps the trickiest value issues surrounding science are hidden behind the seemingly innocent metaphors of ‘getting into the mind of God’ (physics) and ‘playing God’ (biomedicine). Notwithstanding scientists’ own disclaimers, as a matter of fact science has done as well as it has because scientists have adopted a ‘godlike’ attitude toward nature. We have allowed ourselves to imagine and intervene in things at very high levels of abstraction and in ways that can only be justified in terms of the power unleashed by the resulting systematic view of things. The costs incurred have included devaluing our most immediate experiences of nature and subjecting things to quite artificial conditions in order to extract knowledge.
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  • For Francis Bacon and the other early Scientific Revolutionaries, this was a fair price to pay for doing divine work – God, after all, was thought to be himself transcendent and perhaps even alienated from nature. But without this theistic assumption, it becomes difficult to justify the unfettered pursuit of science, once both the costs and benefits are each given their due. Of course, we could simply say that science is what turns humans into gods. For all its hubris, this response would at least possess the virtues of candor and consistency. As it stands, scientists shy away from any such strong self-understandings, preferring to hide behind more passive accounts of their activities – e.g. they ‘describe’ rather than generate phenomena, they ‘explain’ rather than justify nature, etc. Lost in this secular translation of an originally sacred mission is the scientist’s sense of personal responsibility qua scientist.
  • Rather than thinking of science as a “force for good”, we should think of it as an inherent human activity, like com
  • merce.
mcginnisca

8 facts about the Armenian genocide 100 years ago - CNN.com - 0 views

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

Armenia genocide or mass killings language

shared by mcginnisca on 09 Dec 15 - No Cached
  • Turkish FM: Why we won't recognize Armenian killings as genocide 05:07
  • The mass killings of Armenians in the Ottoman Empire, which began 100 years ago Friday, is said by some scholars and others to have been the first genocide of the 20th century, even though the word "genocide" did not exist at the time.
  • The issue of whether to call the killings a genocide is emotional, both for Armenians, who are descended from those killed, and for Turks, the heirs to the Ottomans. For both groups, the question touches as much on national identity as on historical facts.
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  • Some Turks still view the Armenians as having been a threat to the Ottoman Empire in a time of war, and say many people of various ethnicities -- including Turks -- were killed in the chaos of war.
  • The Ottoman Turks, having recently entered World War I on the side of Germany and the Austro-Hungarian Empire, were worried that Armenians living in the Ottoman Empire would offer wartime assistance to Russia. Russia had long coveted control of Constantinople (now Istanbul), which controlled access to the Black Sea -- and therefore access to Russia's only year-round seaports.
  • How many Armenians lived in the Ottoman Empire at the start of the mass killings?Many historians agree that the number was about 2 million. However, victims of the mass killings also included some of the 1.8 million Armenians living in the Caucasus under Russian rule, some of whom were massacred by Ottoman forces in 1918 as they marched through East Armenia and Azerbaijan.
  • on the night of April 23-24, 1915, the authorities in Constantinople, the empire's capital, rounded up about 250 Armenian intellectuals and community leaders. Many of them ended up deported or assassinated.
  • Estimates range from 300,000 to 2 million deaths between 1914 and 1923, with not all of the victims in the Ottoman Empire
  • Some show Ottoman soldiers posing with severed heads, others with them standing amid skulls in the dirt.The victims are reported to have died in mass burnings and by drowning, torture, gas, poison, disease and starvation. Children were reported to have been loaded into boats, taken out to sea and thrown overboard. Rape, too, was frequently reported.
  • No. Genocide was not even a word at the time, much less a legally defined crime.The word "genocide" was invented in 1944 by a Polish lawyer named Raphael Lemkin to describe the Nazis' systematic attempt to eradicate Jews from Europe. He formed the word by combining the Greek word for race with the Latin word for killing.
  • Who calls the mass killings of Armenians a genocide?Armenia, the Vatican, the European Parliament, France, Russia and Canada. Germany is expected to join that group on Friday, the 100th anniversary of the start of the killings.
  • Who does not call the mass killings a genocide?Turkey, the United States, the European Commission, the United Kingdom and the United Nations. A U.N. subcommittee called the killings genocide in 1985, but current U.N. Secretary-General Ban Ki-moon declines to use the word.
  • While Turkey vehemently continues to reject the word "genocide,"
lenaurick

Why time seems to speed up as we get older - Vox - 0 views

www.vox.com/...-speed-accelerate-age-new-year

science research psychology knowledge brain science bias

shared by lenaurick on 31 May 16 - No Cached
  • As part of a lifelong experiment on circadian rhythms, Sothern, now 69, is trying to confirm or reject a widely held belief: Many people feel that time flies by more quickly as they age.
  • So far, Sothern's results are inconclusive
  • "I'm tending now to overestimate the minute more than I used to," he tells me. But then again, he had detected a similar pattern — more overestimates — in the 1990s, only to have his estimates fall in the 2000s. "Time estimation isn't a perfect science," he says.
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  • There's very little scientific evidence to suggest our perception of time changes as we age. And yet, we consistently report that the past felt longer — that time is flying by faster as we age. What's going on?
  • Scientists can look at time estimation, or our ability to estimate how long a minute passes, compared with a clock. (This is what Sothern is doing.) They can also look at time awareness, or the broad feeling that time is moving quickly or slowly. Finally there's time perspective, the sense of a past, present, and future as constructed by our memories.
  • What researchers have found out is that while time estimation and time awareness don't change much as we age, time perspective does. In other words: Our memories create the illusion time is accelerating.
  • There weren't many differences between the old and the young. "[C]hronological age showed no systematic influence on the perception of these brief intervals of time up," the authors wrote. (That said, the researchers did find that males overestimate time while females underestimate it, perhaps due to having slightly different circadian clocks and therefore slightly different metabolic rates
  • Here, too, age seemed not to matter. Older people didn't seem to be aware of time passing any faster than younger people. The only question that yielded a statistically significant difference was, "How fast did the last decade pass?" Even there, the reported differences were tiny, and the effect appeared to plateau around age 50.
  • psychologists William Friedman and Steve Janssen found scant evidence that the subjective experience of time speeds up with age. They write in their 2009 paper, "We can concluded that when adults report on their general impressions of the speed of time, age differences are very small."
  • One possibility is that participants were simply biased by the (incorrect) conventional wisdom — they reported their later years as flying by more quickly because that's what everyday lore says should happen.
  • When people reflect back on their own life, they feel like their early years went by very slowly and their later years go by more quickly. This could be the source of the belief that time goes more quickly as they age.
  •  "Most people feel that time is currently passing faster for them than it did in the past," Janssen writes me in an email. "They have forgotten how they experienced the passage of time when they were younger."
  • We use significant events as signposts to gauge the passage of time. The fewer events, the faster time seems to go by.
  • Childhood is full of big, memorable moments like learning to ride a bike or making first friends. By contrast, adult life becomes ordinary and mechanized, and ambles along by.
  • Each passing year converts some of this experience into automatic routine which we hardly notice at all, the days and weeks smooth themselves out in recollection, and the years grow hollow and collapse.
  • Each new minute represents a smaller fraction of our lives. One day as a 10 year old represents about .027 percent of the kid's life. A day for a 60 year old? .0045 percent. The kid's life is just... bigger.
  • Also, our ability to recall events declines with age. If we can't remember a time, it didn't happen.
  • "[F]inding that there is insufficient time to get things done may be reinterpreted as the feeling that time is passing quickly," they write. Deadlines always come sooner than we'd like.
  • Psychologists have long understood the phenomenon called "forward telescoping" — i.e., our tendency to underestimate how long ago very memorable events occurred. "Because we know that memories fade over time, we use the clarity of a memory as a guide to its recency," science writer Claudia Hammond writes in her book Time Warped. "So if a memory seems unclear we assumed it happened longer ago." But very clear memories are assumed to be more recent.
  • If our memories can trick us into thinking time is moving quickly, then maybe there are ways to trick our brains into thinking that time is slowing down — such as committing to breaking routines and learning new things. You're more likely to remember learning how to skydive than watching another hour of mindless television.
aliciathompson1

Decisions Are Emotional, not Logical: The Neuroscience behind Decision Making | Big Think - 0 views

bigthink.com/...science-behind-decision-making

decision making logic emotion

shared by aliciathompson1 on 04 Jun 16 - No Cached
  • decision-making isn’t logical, it’s emotional, according to the latest findings in neuroscience.
  • A few years ago, neuroscientist Antonio Damasio made a groundbreaking discovery
  • So at the point of decision, emotions are very important for choosing. In fact even with what we believe are logical decisions, the very point of choice is arguably always based on emotion.
  • ...1 more annotation...
  • There’s a detailed and systematic way to go about building vision the right way.
Javier E

What Gamergate should have taught us about the 'alt-right' | Technology | The Guardian - 0 views

www.theguardian.com/...gamergate-alt-right-hate-trump

post-truth disinformation fascism rationality far right social media manipulation press alt-right psychology

shared by Javier E on 02 Dec 16 - No Cached
  • Gamergate
  • The 2014 hashtag campaign, ostensibly founded to protest about perceived ethical failures in games journalism, clearly thrived on hate – even though many of those who aligned themselves with the movement either denied there was a problem with harassment, or wrote it off as an unfortunate side effect
  • ure, women, minorities and progressive voices within the industry were suddenly living in fear. Sure, those who spoke out in their defence were quickly silenced through exhausting bursts of online abuse. But that wasn’t why people supported it, right? They were disenfranchised, felt ignored, and wanted to see a systematic change.
  • ...23 more annotations...
  • Is this all sounding rather familiar now? Does it remind you of something?
  • it quickly became clear that the GamerGate movement was a mess – an undefined mission to Make Video Games Great Again via undecided means.
  • fter all, the culture war that began in games now has a senior representative in The White House. As a founder member and former executive chair of Brietbart News, Steve Bannon had a hand in creating media monster Milo Yiannopoulos, who built his fame and Twitter following by supporting and cheerleading Gamergate. This hashtag was the canary in the coalmine, and we ignored it.
  • Gamergate was an online movement that effectively began because a man wanted to punish his ex girlfriend. Its most notable achievement was harassing a large number of progressive figures - mostly women – to the point where they felt unsafe or considered leaving the industry
  • The similarities between Gamergate and the far-right online movement, the “alt-right”, are huge, startling and in no way a coincidence
  • no one in the movement was willing to be associated with the abuse being carried out in its name. Prominent supporters on Twitter, in subreddits and on forums like 8Chan, developed a range of pernicious rhetorical devices and defences to distance themselves from threats to women and minorities in the industry: the targets were lying or exaggerating, they were too precious; a language of dismissal and belittlement was formed against them. Safe spaces, snowflakes, unicorns, cry bullies. Even when abuse was proven, the usual response was that people on their side were being abused too. These techniques, forged in Gamergate, have become the standard toolset of far-right voices online
  • In 2016, new wave conservative media outlets like Breitbart have gained trust with their audience by painting traditional news sources as snooty and aloof. In 2014, video game YouTube stars, seeking to appear in touch with online gaming communities, unscrupulously proclaimed that traditional old-media sources were corrupt. Everything we’re seeing now, had its precedent two years ago.
  • With 2014’s Gamergate, Breitbart seized the opportunity to harness the pre-existing ignorance and anger among disaffected young white dudes. With Trump’s movement in 2016, the outlet was effectively running his campaign: Steve Bannon took leave of his role at the company in August 2016 when he was hired as chief executive of Trump’s presidential campaign
  • young men converted via 2014’s Gamergate, are being more widely courted now. By leveraging distrust and resentment towards women, minorities and progressives, many of Gamergate’s most prominent voices – characters like Mike Cernovich, Adam Baldwin, and Milo Yiannopoulos – drew power and influence from its chaos
  • These figures gave Gamergate a new sense of direction – generalising the rhetoric: this was now a wider war between “Social Justice Warriors” (SJWs) and everyday, normal, decent people. Games were simply the tip of the iceberg – progressive values, went the argument, were destroying everything
  • The same voices moved into other geek communities, especially comics, where Marvel and DC were criticised for progressive storylines and decisions. They moved into science fiction with the controversy over the Hugo awards. They moved into cinema with the revolting kickback against the all-female Ghostbusters reboot.
  • Using 4chan (and then the more sympathetic offshoot 8Chan) to plan their subversions and attacks made Gamergate a terribly sloppy operation, leaving a trail of evidence that made it quite clear the whole thing was purposefully, plainly nasty. But the video game industry didn’t have the spine to react, and allowed the movement to coagulate – forming a mass of spiteful disappointment that Breitbart was only more than happy to coddle
  • Historically, that seems to be Breitbart’s trick - strongly represent a single issue in order to earn trust, and then gradually indoctrinate to suit wider purposes. With Gamergate, they purposefully went fishing for anti-feminists. 2016’s batch of fresh converts – the white extremists – came from enticing conspiracy theories about the global neoliberal elite secretly controlling the world.
  • The greatest strength of Gamergate, though, was that it actually appeared to represent many left-leaning ideals: stamping out corruption in the press, pushing for better ethical practices, battling for openness.
  • There are similarities here with many who support Trump because of his promises to put an end to broken neo-liberalism, to “drain the swamp” of establishment corruption. Many left-leaning supporters of Gamergate sought to intellectualise their alignment with the hashtag, adopting familiar and acceptable labels of dissent – identifying as libertarian, egalitarian, humanist.
  • At best they unknowingly facilitated abuse, defending their own freedom of expression while those who actually needed support were threatened and attacked.
  • Genuine discussions over criticism, identity and censorship were paralysed and waylaid by Twitter voices obsessed with rhetorical fallacies and pedantic debating practices. While the core of these movements make people’s lives hell, the outer shell – knowingly or otherwise – protect abusers by insisting that the real problem is that you don’t want to talk, or won’t provide the ever-shifting evidence they politely require.
  • In 2017, the tactics used to discredit progressive game critics and developers will be used to discredit Trump and Bannon’s critics. There will be gaslighting, there will be attempts to make victims look as though they are losing their grip on reality, to the point that they gradually even start to believe it. The “post-truth” reality is not simply an accident – it is a concerted assault on the rational psyche.
  • The strangest aspect of Gamergate is that it consistently didn’t make any sense: people chose to align with it, and yet refused responsibility. It was constantly demanded that we debate the issues, but explanations and facts were treated with scorn. Attempts to find common ground saw the specifics of the demands being shifted: we want you to listen to us; we want you to change your ways; we want you to close your publication down. This movement that ostensibly wanted to protect free speech from cry bully SJWs simultaneously did what it could to endanger sites it disagreed with, encouraging advertisers to abandon support for media outlets that published stories critical of the hashtag. The petulance of that movement is disturbingly echoed in Trump’s own Twitter feed.
  • Looking back, Gamergate really only made sense in one way: as an exemplar of what Umberto Eco called “eternal fascism”, a form of extremism he believed could flourish at any point in, in any place – a fascism that would extol traditional values, rally against diversity and cultural critics, believe in the value of action above thought and encourage a distrust of intellectuals or experts – a fascism built on frustration and machismo. The requirement of this formless fascism would – above all else – be to remain in an endless state of conflict, a fight against a foe who must always be portrayed as impossibly strong and laughably weak
  • 2016 has presented us with a world in which our reality is being wilfully manipulated. Fake news, divisive algorithms, misleading social media campaigns.
  • The majority of people who voted for Trump will never take responsibility for his racist, totalitarian policies, but they’ll provide useful cover and legitimacy for those who demand the very worst from the President Elect. Trump himself may have disavowed the “alt-right”, but his rhetoric has led to them feeling legitimised. As with Gamergate, the press risks being manipulated into a position where it has to tread a respectful middle ground that doesn’t really exist.
  • Perhaps the true lesson of Gamergate was that the media is culturally unequipped to deal with the forces actively driving these online movements. The situation was horrifying enough two years ago, it is many times more dangerous now.
Javier E

The decline effect and the scientific method : The New Yorker - 3 views

www.newyorker.com/...101213fa_fact_lehrer

science empiricism philosophy scientific method decline research statistics method bias truth

shared by Javier E on 17 Jun 12 - Cached
  • The test of replicability, as it’s known, is the foundation of modern research. Replicability is how the community enforces itself. It’s a safeguard for the creep of subjectivity. Most of the time, scientists know what results they want, and that can influence the results they get. The premise of replicability is that the scientific community can correct for these flaws.
  • But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable.
  • This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology.
  • ...39 more annotations...
  • If replication is what separates the rigor of science from the squishiness of pseudoscience, where do we put all these rigorously validated findings that can no longer be proved? Which results should we believe?
  • Schooler demonstrated that subjects shown a face and asked to describe it were much less likely to recognize the face when shown it later than those who had simply looked at it. Schooler called the phenomenon “verbal overshadowing.”
  • The most likely explanation for the decline is an obvious one: regression to the mean. As the experiment is repeated, that is, an early statistical fluke gets cancelled out. The extrasensory powers of Schooler’s subjects didn’t decline—they were simply an illusion that vanished over time.
  • yet Schooler has noticed that many of the data sets that end up declining seem statistically solid—that is, they contain enough data that any regression to the mean shouldn’t be dramatic. “These are the results that pass all the tests,” he says. “The odds of them being random are typically quite remote, like one in a million. This means that the decline effect should almost never happen. But it happens all the time!
  • this is why Schooler believes that the decline effect deserves more attention: its ubiquity seems to violate the laws of statistics
  • In 2001, Michael Jennions, a biologist at the Australian National University, set out to analyze “temporal trends” across a wide range of subjects in ecology and evolutionary biology. He looked at hundreds of papers and forty-four meta-analyses (that is, statistical syntheses of related studies), and discovered a consistent decline effect over time, as many of the theories seemed to fade into irrelevance.
  • Jennions admits that his findings are troubling, but expresses a reluctance to talk about them
  • publicly. “This is a very sensitive issue for scientists,” he says. “You know, we’re supposed to be dealing with hard facts, the stuff that’s supposed to stand the test of time. But when you see these trends you become a little more skeptical of things.”
  • Sterling saw that if ninety-seven per cent of psychology studies were proving their hypotheses, either psychologists were extraordinarily lucky or they published only the outcomes of successful experiments.
  • Jennions, similarly, argues that the decline effect is largely a product of publication bias, or the tendency of scientists and scientific journals to prefer positive data over null results, which is what happens when no effect is found. The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for
  • While publication bias almost certainly plays a role in the decline effect, it remains an incomplete explanation. For one thing, it fails to account for the initial prevalence of positive results among studies that never even get submitted to journals. It also fails to explain the experience of people like Schooler, who have been unable to replicate their initial data despite their best efforts.
  • One of his most cited papers has a deliberately provocative title: “Why Most Published Research Findings Are False.”
  • suspects that an equally significant issue is the selective reporting of results—the data that scientists choose to document in the first place. Palmer’s most convincing evidence relies on a statistical tool known as a funnel graph. When a large number of studies have been done on a single subject, the data should follow a pattern: studies with a large sample size should all cluster around a common value—the true result—whereas those with a smaller sample size should exhibit a random scattering, since they’re subject to greater sampling error. This pattern gives the graph its name, since the distribution resembles a funnel.
  • after Palmer plotted every study of fluctuating asymmetry, he noticed that the distribution of results with smaller sample sizes wasn’t random at all but instead skewed heavily toward positive results. Palmer has since documented a similar problem in several other contested subject areas. “Once I realized that selective reporting is everywhere in science, I got quite depressed,” Palmer told me. “As a researcher, you’re always aware that there might be some nonrandom patterns, but I had no idea how widespread it is.”
  • Palmer summarized the impact of selective reporting on his field: “We cannot escape the troubling conclusion that some—perhaps many—cherished generalities are at best exaggerated in their biological significance and at worst a collective illusion nurtured by strong a-priori beliefs often repeated.”
  • Palmer emphasizes that selective reporting is not the same as scientific fraud. Rather, the problem seems to be one of subtle omissions and unconscious misperceptions, as researchers struggle to make sense of their results. Stephen Jay Gould referred to this as the “sho
  • horning” process.
  • “A lot of scientific measurement is really hard,” Simmons told me. “If you’re talking about fluctuating asymmetry, then it’s a matter of minuscule differences between the right and left sides of an animal. It’s millimetres of a tail feather. And so maybe a researcher knows that he’s measuring a good male”—an animal that has successfully mated—“and he knows that it’s supposed to be symmetrical. Well, that act of measurement is going to be vulnerable to all sorts of perception biases. That’s not a cynical statement. That’s just the way human beings work.”
  • One of the classic examples of selective reporting concerns the testing of acupuncture in different countries. While acupuncture is widely accepted as a medical treatment in various Asian countries, its use is much more contested in the West. These cultural differences have profoundly influenced the results of clinical trials.
  • John Ioannidis, an epidemiologist at Stanford University, argues that such distortions are a serious issue in biomedical research. “These exaggerations are why the decline has become so common,” he says. “It’d be really great if the initial studies gave us an accurate summary of things. But they don’t. And so what happens is we waste a lot of money treating millions of patients and doing lots of follow-up studies on other themes based on results that are misleading.”
  • In 2005, Ioannidis published an article in the Journal of the American Medical Association that looked at the forty-nine most cited clinical-research studies in three major medical journals.
  • the data Ioannidis found were disturbing: of the thirty-four claims that had been subject to replication, forty-one per cent had either been directly contradicted or had their effect sizes significantly downgraded.
  • the most troubling fact emerged when he looked at the test of replication: out of four hundred and thirty-two claims, only a single one was consistently replicable. “This doesn’t mean that none of these claims will turn out to be true,” he says. “But, given that most of them were done badly, I wouldn’t hold my breath.”
  • According to Ioannidis, the main problem is that too many researchers engage in what he calls “significance chasing,” or finding ways to interpret the data so that it passes the statistical test of significance—the ninety-five-per-cent boundary invented by Ronald Fisher.
  • For Simmons, the steep rise and slow fall of fluctuating asymmetry is a clear example of a scientific paradigm, one of those intellectual fads that both guide and constrain research: after a new paradigm is proposed, the peer-review process is tilted toward positive results. But then, after a few years, the academic incentives shift—the paradigm has become entrenched—so that the most notable results are now those that disprove the theory.
  • The problem of selective reporting is rooted in a fundamental cognitive flaw, which is that we like proving ourselves right and hate being wrong.
  • “It feels good to validate a hypothesis,” Ioannidis said. “It feels even better when you’ve got a financial interest in the idea or your career depends upon it. And that’s why, even after a claim has been systematically disproven”—he cites, for instance, the early work on hormone replacement therapy, or claims involving various vitamins—“you still see some stubborn researchers citing the first few studies
  • That’s why Schooler argues that scientists need to become more rigorous about data collection before they publish. “We’re wasting too much time chasing after bad studies and underpowered experiments,”
  • The current “obsession” with replicability distracts from the real problem, which is faulty design.
  • “Every researcher should have to spell out, in advance, how many subjects they’re going to use, and what exactly they’re testing, and what constitutes a sufficient level of proof. We have the tools to be much more transparent about our experiments.”
  • Schooler recommends the establishment of an open-source database, in which researchers are required to outline their planned investigations and document all their results. “I think this would provide a huge increase in access to scientific work and give us a much better way to judge the quality of an experiment,”
  • scientific research will always be shadowed by a force that can’t be curbed, only contained: sheer randomness. Although little research has been done on the experimental dangers of chance and happenstance, the research that exists isn’t encouraging.
  • The disturbing implication of the Crabbe study is that a lot of extraordinary scientific data are nothing but noise. The hyperactivity of those coked-up Edmonton mice wasn’t an interesting new fact—it was a meaningless outlier, a by-product of invisible variables we don’t understand.
  • The problem, of course, is that such dramatic findings are also the most likely to get published in prestigious journals, since the data are both statistically significant and entirely unexpected
  • This suggests that the decline effect is actually a decline of illusion. While Karl Popper imagined falsification occurring with a single, definitive experiment—Galileo refuted Aristotelian mechanics in an afternoon—the process turns out to be much messier than that.
  • Many scientific theories continue to be considered true even after failing numerous experimental tests.
  • Even the law of gravity hasn’t always been perfect at predicting real-world phenomena. (In one test, physicists measuring gravity by means of deep boreholes in the Nevada desert found a two-and-a-half-per-cent discrepancy between the theoretical predictions and the actual data.)
  • Such anomalies demonstrate the slipperiness of empiricism. Although many scientific ideas generate conflicting results and suffer from falling effect sizes, they continue to get cited in the textbooks and drive standard medical practice. Why? Because these ideas seem true. Because they make sense. Because we can’t bear to let them go. And this is why the decline effect is so troubling. Not because it reveals the human fallibility of science, in which data are tweaked and beliefs shape perceptions. (Such shortcomings aren’t surprising, at least for scientists.) And not because it reveals that many of our most exciting theories are fleeting fads and will soon be rejected. (That idea has been around since Thomas Kuhn.)
  • The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that’s often not the case. Just because an idea is true doesn’t mean it can be proved. And just because an idea can be proved doesn’t mean it’s true. When the experiments are done, we still have to choose what to believe. ♦
Emily Freilich

The Man Who Would Teach Machines to Think - James Somers - The Atlantic - 1 views

www.theatlantic.com/...309529

artificial intelligence science technology progression

shared by Emily Freilich on 08 Nov 13 - No Cached
  • Douglas Hofstadter, the Pulitzer Prize–winning author of Gödel, Escher, Bach, thinks we've lost sight of what artificial intelligence really means. His stubborn quest to replicate the human mind.
  • “If somebody meant by artificial intelligence the attempt to understand the mind, or to create something human-like, they might say—maybe they wouldn’t go this far—but they might say this is some of the only good work that’s ever been done
  • Their operating premise is simple: the mind is a very unusual piece of software, and the best way to understand how a piece of software works is to write it yourself.
  • ...43 more annotations...
  • “It depends on what you mean by artificial intelligence.”
  • Computers are flexible enough to model the strange evolved convolutions of our thought, and yet responsive only to precise instructions. So if the endeavor succeeds, it will be a double victory: we will finally come to know the exact mechanics of our selves—and we’ll have made intelligent machines.
  • Ever since he was about 14, when he found out that his youngest sister, Molly, couldn’t understand language, because she “had something deeply wrong with her brain” (her neurological condition probably dated from birth, and was never diagnosed), he had been quietly obsessed by the relation of mind to matter.
  • How could consciousness be physical? How could a few pounds of gray gelatin give rise to our very thoughts and selves?
  • Consciousness, Hofstadter wanted to say, emerged via just the same kind of “level-crossing feedback loop.”
  • In 1931, the Austrian-born logician Kurt Gödel had famously shown how a mathematical system could make statements not just about numbers but about the system itself.
  • But then AI changed, and Hofstadter didn’t change with it, and for that he all but disappeared.
  • By the early 1980s, the pressure was great enough that AI, which had begun as an endeavor to answer yes to Alan Turing’s famous question, “Can machines think?,” started to mature—or mutate, depending on your point of view—into a subfield of software engineering, driven by applications.
  • Take Deep Blue, the IBM supercomputer that bested the chess grandmaster Garry Kasparov. Deep Blue won by brute force.
  • Hofstadter wanted to ask: Why conquer a task if there’s no insight to be had from the victory? “Okay,” he says, “Deep Blue plays very good chess—so what? Does that tell you something about how we play chess? No. Does it tell you about how Kasparov envisions, understands a chessboard?”
  • AI started working when it ditched humans as a model, because it ditched them. That’s the thrust of the analogy: Airplanes don’t flap their wings; why should computers think?
  • It’s a compelling point. But it loses some bite when you consider what we want: a Google that knows, in the way a human would know, what you really mean when you search for something
  • Cognition is recognition,” he likes to say. He describes “seeing as” as the essential cognitive act: you see some lines a
  • How do you make a search engine that understands if you don’t know how you understand?
  • s “an A,” you see a hunk of wood as “a table,” you see a meeting as “an emperor-has-no-clothes situation” and a friend’s pouting as “sour grapes”
  • That’s what it means to understand. But how does understanding work?
  • analogy is “the fuel and fire of thinking,” the bread and butter of our daily mental lives.
  • there’s an analogy, a mental leap so stunningly complex that it’s a computational miracle: somehow your brain is able to strip any remark of the irrelevant surface details and extract its gist, its “skeletal essence,” and retrieve, from your own repertoire of ideas and experiences, the story or remark that best relates.
  • in Hofstadter’s telling, the story goes like this: when everybody else in AI started building products, he and his team, as his friend, the philosopher Daniel Dennett, wrote, “patiently, systematically, brilliantly,” way out of the light of day, chipped away at the real problem. “Very few people are interested in how human intelligence works,”
  • For more than 30 years, Hofstadter has worked as a professor at Indiana University at Bloomington
  • The quick unconscious chaos of a mind can be slowed down on the computer, or rewound, paused, even edited
  • project out of IBM called Candide. The idea behind Candide, a machine-translation system, was to start by admitting that the rules-based approach requires too deep an understanding of how language is produced; how semantics, syntax, and morphology work; and how words commingle in sentences and combine into paragraphs—to say nothing of understanding the ideas for which those words are merely conduits.
  • , Hofstadter directs the Fluid Analogies Research Group, affectionately known as FARG.
  • Parts of a program can be selectively isolated to see how it functions without them; parameters can be changed to see how performance improves or degrades. When the computer surprises you—whether by being especially creative or especially dim-witted—you can see exactly why.
  • When you read Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought, which describes in detail this architecture and the logic and mechanics of the programs that use it, you wonder whether maybe Hofstadter got famous for the wrong book.
  • ut very few people, even admirers of GEB, know about the book or the programs it describes. And maybe that’s because FARG’s programs are almost ostentatiously impractical. Because they operate in tiny, seemingly childish “microdomains.” Because there is no task they perform better than a human.
  • “The entire effort of artificial intelligence is essentially a fight against computers’ rigidity.”
  • “Nobody is a very reliable guide concerning activities in their mind that are, by definition, subconscious,” he once wrote. “This is what makes vast collections of errors so important. In an isolated error, the mechanisms involved yield only slight traces of themselves; however, in a large collection, vast numbers of such slight traces exist, collectively adding up to strong evidence for (and against) particular mechanisms.
  • So IBM threw that approach out the window. What the developers did instead was brilliant, but so straightforward,
  • The technique is called “machine learning.” The goal is to make a device that takes an English sentence as input and spits out a French sentence
  • What you do is feed the machine English sentences whose French translations you already know. (Candide, for example, used 2.2 million pairs of sentences, mostly from the bilingual proceedings of Canadian parliamentary debates.)
  • By repeating this process with millions of pairs of sentences, you will gradually calibrate your machine, to the point where you’ll be able to enter a sentence whose translation you don’t know and get a reasonable resul
  • Google Translate team can be made up of people who don’t speak most of the languages their application translates. “It’s a bang-for-your-buck argument,” Estelle says. “You probably want to hire more engineers instead” of native speakers.
  • But the need to serve 1 billion customers has a way of forcing the company to trade understanding for expediency. You don’t have to push Google Translate very far to see the compromises its developers have made for coverage, and speed, and ease of engineering. Although Google Translate captures, in its way, the products of human intelligence, it isn’t intelligent itself.
  • “Did we sit down when we built Watson and try to model human cognition?” Dave Ferrucci, who led the Watson team at IBM, pauses for emphasis. “Absolutely not. We just tried to create a machine that could win at Jeopardy.”
  • For Ferrucci, the definition of intelligence is simple: it’s what a program can do. Deep Blue was intelligent because it could beat Garry Kasparov at chess. Watson was intelligent because it could beat Ken Jennings at Jeopardy.
  • “There’s a limited number of things you can do as an individual, and I think when you dedicate your life to something, you’ve got to ask yourself the question: To what end? And I think at some point I asked myself that question, and what it came out to was, I’m fascinated by how the human mind works, it would be fantastic to understand cognition, I love to read books on it, I love to get a grip on it”—he called Hofstadter’s work inspiring—“but where am I going to go with it? Really what I want to do is build computer systems that do something.
  • Peter Norvig, one of Google’s directors of research, echoes Ferrucci almost exactly. “I thought he was tackling a really hard problem,” he told me about Hofstadter’s work. “And I guess I wanted to do an easier problem.”
  • Of course, the folly of being above the fray is that you’re also not a part of it
  • As our machines get faster and ingest more data, we allow ourselves to be dumber. Instead of wrestling with our hardest problems in earnest, we can just plug in billions of examples of them.
  • Hofstadter hasn’t been to an artificial-intelligence conference in 30 years. “There’s no communication between me and these people,” he says of his AI peers. “None. Zero. I don’t want to talk to colleagues that I find very, very intransigent and hard to convince of anything
  • Everything from plate tectonics to evolution—all those ideas, someone had to fight for them, because people didn’t agree with those ideas.
  • Academia is not an environment where you just sit in your bath and have ideas and expect everyone to run around getting excited. It’s possible that in 50 years’ time we’ll say, ‘We really should have listened more to Doug Hofstadter.’ But it’s incumbent on every scientist to at least think about what is needed to get people to understand the ideas.”
Javier E

Choose to Be Grateful. It Will Make You Happier. - The New York Times - 2 views

www.nytimes.com/...-it-will-make-you-happier.html

gratitude happiness authenticity psychology

shared by Javier E on 22 Nov 15 - No Cached
  • Building the best life does not require fealty to feelings in the name of authenticity, but rather rebelling against negative impulses and acting right even when we don’t feel like it. In a nutshell, acting grateful can actually make you grateful.
  • some people are just naturally more grateful than others. A 2014 article in the journal Social Cognitive and Affective Neuroscience identified a variation in a gene (CD38) associated with gratitude. Some people simply have a heightened genetic tendency to experience, in the researchers’ words, “global relationship satisfaction, perceived partner responsiveness and positive emotions (particularly love).” That is, those relentlessly positive people you know who seem grateful all the time may simply be mutants.
  • Evidence suggests that we can actively choose to practice gratitude — and that doing so raises our happiness.
  • ...11 more annotations...
  • , researchers in one 2003 study randomly assigned one group of study participants to keep a short weekly list of the things they were grateful for, while other groups listed hassles or neutral events. Ten weeks later, the first group enjoyed significantly greater life satisfaction than the others
  • acting happy, regardless of feelings, coaxes one’s brain into processing positive emotions. In one famous 1993 experiment, researchers asked human subjects to smile forcibly for 20 seconds while tensing facial muscles, notably the muscles around the eyes called the orbicularis oculi (which create “crow’s feet”). They found that this action stimulated brain activity associated with positive emotions.
  • gratitude stimulates the hypothalamus (a key part of the brain that regulates stress) and the ventral tegmental area (part of our “reward circuitry” that produces the sensation of pleasure).
  • In the slightly more elegant language of the Stoic philosopher Epictetus, “He is a man of sense who does not grieve for what he has not, but rejoices in what he has.”
  • In addition to building our own happiness, choosing gratitude can also bring out the best in those around us
  • when their competence was questioned, the subjects tended to lash out with aggression and personal denigration. When shown gratitude, however, they reduced the bad behavior. That is, the best way to disarm an angry interlocutor is with a warm “thank you.”
  • A new study in the Journal of Consumer Psychology finds evidence that people begin to crave sweets when they are asked to express gratitude.
  • There are concrete strategies that each of us can adopt. First, start with “interior gratitude,” the practice of giving thanks privately
  • he recommends that readers systematically express gratitude in letters to loved ones and colleagues. A disciplined way to put this into practice is to make it as routine as morning coffee. Write two short emails each morning to friends, family or colleagues, thanking them for what they do.
  • Finally, be grateful for useless things
  • think of the small, useless things you experience — the smell of fall in the air, the fragment of a song that reminds you of when you were a kid. Give thanks.
kushnerha

If Philosophy Won't Diversify, Let's Call It What It Really Is - The New York Times - 0 views

www.nytimes.com/...call-it-what-it-really-is.html

new york times epistemology philosophy diversity education bias

shared by kushnerha on 11 May 16 - No Cached
  • The vast majority of philosophy departments in the United States offer courses only on philosophy derived from Europe and the English-speaking world. For example, of the 118 doctoral programs in philosophy in the United States and Canada, only 10 percent have a specialist in Chinese philosophy as part of their regular faculty. Most philosophy departments also offer no courses on Africana, Indian, Islamic, Jewish, Latin American, Native American or other non-European traditions. Indeed, of the top 50 philosophy doctoral programs in the English-speaking world, only 15 percent have any regular faculty members who teach any non-Western philosophy.
  • Given the importance of non-European traditions in both the history of world philosophy and in the contemporary world, and given the increasing numbers of students in our colleges and universities from non-European backgrounds, this is astonishing. No other humanities discipline demonstrates this systematic neglect of most of the civilizations in its domain. The present situation is hard to justify morally, politically, epistemically or as good educational and research training practice.
  • While a few philosophy departments have made their curriculums more diverse, and while the American Philosophical Association has slowly broadened the representation of the world’s philosophical traditions on its programs, progress has been minimal.
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  • Many philosophers and many departments simply ignore arguments for greater diversity; others respond with arguments for Eurocentrism that we and many others have refuted elsewhere. The profession as a whole remains resolutely Eurocentric.
  • Instead, we ask those who sincerely believe that it does make sense to organize our discipline entirely around European and American figures and texts to pursue this agenda with honesty and openness. We therefore suggest that any department that regularly offers courses only on Western philosophy should rename itself “Department of European and American Philosophy.”
  • We see no justification for resisting this minor rebranding (though we welcome opposing views in the comments section to this article), particularly for those who endorse, implicitly or explicitly, this Eurocentric orientation.
  • Some of our colleagues defend this orientation on the grounds that non-European philosophy belongs only in “area studies” departments, like Asian Studies, African Studies or Latin American Studies. We ask that those who hold this view be consistent, and locate their own departments in “area studies” as well, in this case, Anglo-European Philosophical Studies.
  • Others might argue against renaming on the grounds that it is unfair to single out philosophy: We do not have departments of Euro-American Mathematics or Physics. This is nothing but shabby sophistry. Non-European philosophical traditions offer distinctive solutions to problems discussed within European and American philosophy, raise or frame problems not addressed in the American and European tradition, or emphasize and discuss more deeply philosophical problems that are marginalized in Anglo-European philosophy. There are no comparable differences in how mathematics or physics are practiced in other contemporary cultures.
  • Of course, we believe that renaming departments would not be nearly as valuable as actually broadening the philosophical curriculum and retaining the name “philosophy.” Philosophy as a discipline has a serious diversity problem, with women and minorities underrepresented at all levels among students and faculty, even while the percentage of these groups increases among college students. Part of the problem is the perception that philosophy departments are nothing but temples to the achievement of males of European descent. Our recommendation is straightforward: Those who are comfortable with that perception should confirm it in good faith and defend it honestly; if they cannot do so, we urge them to diversify their faculty and their curriculum.
  • This is not to disparage the value of the works in the contemporary philosophical canon: Clearly, there is nothing intrinsically wrong with philosophy written by males of European descent; but philosophy has always become richer as it becomes increasingly diverse and pluralistic.
  • We hope that American philosophy departments will someday teach Confucius as routinely as they now teach Kant, that philosophy students will eventually have as many opportunities to study the “Bhagavad Gita” as they do the “Republic,” that the Flying Man thought experiment of the Persian philosopher Avicenna (980-1037) will be as well-known as the Brain-in-a-Vat thought experiment of the American philosopher Hilary Putnam (1926-2016), that the ancient Indian scholar Candrakirti’s critical examination of the concept of the self will be as well-studied as David Hume’s, that Frantz Fanon (1925-1961), Kwazi Wiredu (1931- ), Lame Deer (1903-1976) and Maria Lugones will be as familiar to our students as their equally profound colleagues in the contemporary philosophical canon. But, until then, let’s be honest, face reality and call departments of European-American Philosophy what they really are.
  • For demographic, political and historical reasons, the change to a more multicultural conception of philosophy in the United States seems inevitable. Heed the Stoic adage: “The Fates lead those who come willingly, and drag those who do not.”
Javier E

Why Our Children Don't Think There Are Moral Facts - NYTimes.com - 1 views

opinionator.blogs.nytimes.com/...nt-think-there-are-moral-facts

morality fact truth relativism ethics

shared by Javier E on 02 Mar 15 - No Cached
  • I already knew that many college-aged students don’t believe in moral facts.
  • the overwhelming majority of college freshman in their classrooms view moral claims as mere opinions that are not true or are true only relative to a culture.
  • where is the view coming from?
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  • the Common Core standards used by a majority of K-12 programs in the country require that students be able to “distinguish among fact, opinion, and reasoned judgment in a text.”
  • So what’s wrong with this distinction and how does it undermine the view that there are objective moral facts?
  • For example, many people once thought that the earth was flat. It’s a mistake to confuse truth (a feature of the world) with proof (a feature of our mental lives)
  • Furthermore, if proof is required for facts, then facts become person-relative. Something might be a fact for me if I can prove it but not a fact for you if you can’t. In that case, E=MC2 is a fact for a physicist but not for me.
  • worse, students are taught that claims are either facts or opinions. They are given quizzes in which they must sort claims into one camp or the other but not both. But if a fact is something that is true and an opinion is something that is believed, then many claims will obviously be both
  • How does the dichotomy between fact and opinion relate to morality
  • Kids are asked to sort facts from opinions and, without fail, every value claim is labeled as an opinion.
  • Here’s a little test devised from questions available on fact vs. opinion worksheets online: are the following facts or opinions? — Copying homework assignments is wrong. — Cursing in school is inappropriate behavior. — All men are created equal. — It is worth sacrificing some personal liberties to protect our country from terrorism. — It is wrong for people under the age of 21 to drink alcohol. — Vegetarians are healthier than people who eat meat. — Drug dealers belong in prison.
  • The answer? In each case, the worksheets categorize these claims as opinions. The explanation on offer is that each of these claims is a value claim and value claims are not facts. This is repeated ad nauseum: any claim with good, right, wrong, etc. is not a fact.
  • In summary, our public schools teach students that all claims are either facts or opinions and that all value and moral claims fall into the latter camp. The punchline: there are no moral facts. And if there are no moral facts, then there are no moral truths.
  • It should not be a surprise that there is rampant cheating on college campuses: If we’ve taught our students for 12 years that there is no fact of the matter as to whether cheating is wrong, we can’t very well blame them for doing so later on.
  • If it’s not true that it’s wrong to murder a cartoonist with whom one disagrees, then how can we be outraged? If there are no truths about what is good or valuable or right, how can we prosecute people for crimes against humanity? If it’s not true that all humans are created equal, then why vote for any political system that doesn’t benefit you over others?
  • the curriculum sets our children up for doublethink. They are told that there are no moral facts in one breath even as the next tells them how they ought to behave.
  • Our children deserve a consistent intellectual foundation. Facts are things that are true. Opinions are things we believe. Some of our beliefs are true. Others are not. Some of our beliefs are backed by evidence. Others are not.
  • Value claims are like any other claims: either true or false, evidenced or not.
  • The hard work lies not in recognizing that at least some moral claims are true but in carefully thinking through our evidence for which of the many competing moral claims is correct.
  • Moral truths are not the same as scientific truths or mathematical truths. Yet they may still be used a guiding principle for our individual lives as well as our laws.But there is equal danger of giving moral judgments the designation of truth as there is in not doing so. Many people believe that abortion is murder on the same level as shooting someone with a gun. But many others do not. So is it true that abortion is murder?Moral principles can become generally accepted and then form the basis for our laws. But many long accepted moral principles were later rejected as being faulty. "Separate but equal" is an example. Judging homosexual relationships as immoral is another example.
  • Whoa! That Einstein derived an equation is a fact. But the equation represents a theory that may have to be tweaked at some point in the future. It may be a fact that the equation foretold the violence of atomic explosions, but there are aspects of nature that elude the equation. Remember "the theory of everything?"
  • Here is a moral fact, this is a sermon masquerading as a philosophical debate on facts, opinions and truth. This professor of religion is asserting that the government via common core is teaching atheism via the opinion vs fact.He is arguing, in a dishonest form, that public schools should be teaching moral facts. Of course moral facts is code for the Ten Commandments.
  • As a fourth grade teacher, I try to teach students to read critically, including distinguishing between facts and opinions as they read (and have been doing this long before the Common Core arrived, by the way). It's not always easy for children to grasp the difference. I can only imagine the confusion that would ensue if I introduced a third category -- moral "facts" that can't be proven but are true nonetheless!
  • horrible acts occur not because of moral uncertainty, but because people are too sure that their views on morality are 100% true, and anyone who fails to recognize and submit themselves are heathens who deserve death.I can't think of any case where a society has suffered because people are too thoughtful and open-minded to different perspectives on moral truth.In any case, it's not an elementary school's job to teach "moral truths."
  • The characterization of moral anti-realism as some sort of fringe view in philosophy is misleading. Claims that can be true or false are, it seems, 'made true' by features of the world. It's not clear to many in philosophy (like me) just what features of the world could make our moral claims true. We are more likely to see people's value claims as making claims about, and enforcing conformity to, our own (contingent) social norms. This is not to hold, as Mr. McBrayer seems to think follows, that there are no reasons to endorse or criticize these social norms.
  • This is nonsense. Giving kids the tools to distinguish between fact and opinion is hard enough in an age when Republicans actively deny reality on Fox News every night. The last thing we need is to muddy their thinking with the concept of "moral facts."A fact is a belief that everyone _should_ agree upon because it is observable and testable. Morals are not agreed upon by all. Consider the hot button issue of abortion.
  • Truthfully, I'm not terribly concerned that third graders will end up taking these lessons in the definition of fact versus opinion to the extremes considered here, or take them as a license to cheat. That will come much later, when they figure out, as people always have, what they can get a way with. But Prof. McBrayer, with his blithe expectation that all the grownups know that there moral "facts"? He scares the heck out of me.
  • I've long chafed at the language of "fact" v. "opinion", which is grounded in a very particular, limited view of human cognition. In my own ethics courses, I work actively to undermine the distinction, focusing instead on considered judgment . . . or even more narrowly, on consideration itself. (See http://wp.me/p5Ag0i-6M )
  • The real waffle here is the very concept of "moral facts." Our statements of values, even very important ones are, obviously, not facts. Trying to dress them up as if they are facts, to me, argues for a pretty serious moral weakness on the part of those advancing the idea.
  • Our core values are not important because they are facts. They are important because we collectively hold them and cherish them. To lean on the false crutch of "moral facts" to admit the weakness of your own moral convictions.
  • I would like to believe that there is a core of moral facts/values upon which all humanity can agree, but it would be tough to identify exactly what those are.
  • For the the ancient philosophers, reality comprised the Good, the True, and the Beautiful (what we might now call ethics, science and art), seeing these as complementary and inseparable, though distinct, realms. With the ascendency of science in our culture as the only valid measure of reality to the detriment of ethics and art (that is, if it is not observable and provable, it is not real), we have turned the good and the beautiful into mere "social constructs" that have no validity on their own. While I am sympathetic in many ways with Dr. McBrayer's objections, I think he falls into the trap of discounting the Good and The Beautiful as valid in and of themselves, and tries, instead, to find ways to give them validity through the True. I think his argument would have been stronger had he used the language of validity rather than the language of truth. Goodness, Truth and Beauty each have their own validity, though interdependent and inseparable. When we artificially extract one of these and give it primacy, we distort reality and alienate ourselves from it.
  • Professor McBrayer seems to miss the major point of the Common Core concern: can students distinguish between premises based on (reasonably construed) fact and premises based on emotion when evaluating conclusions? I would prefer that students learn to reason rather than be taught moral 'truth' that follows Professor McBrayer's logic.
  • Moral issues cannot scientifically be treated on the level that Prof. McBrayer is attempting to use in this column: true or false, fact or opinion or both. Instead, they should be treated as important characteristics of the systematic working of a society or of a group of people in general. One can compare the working of two groups of people: one in which e.g. cheating and lying is acceptable, and one in which they are not. One can use historical or model examples to show the consequences and the working of specific systems of morals. I think that this method - suitably adjusted - can be used even in second grade.
  • Relativism has nothing to do with liberalism. The second point is that I'm not sure it does all that much harm, because I have yet to encounter a student who thought that he or she had to withhold judgment on those who hold opposing political views!
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