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Javier E

The Bilingual Advantage - NYTimes.com - 0 views

www.nytimes.com/...31conversation.html

bilingual education language

shared by Javier E on 02 Jun 11 - No Cached
  • We found that if you gave 5- and 6-year-olds language problems to solve, monolingual and bilingual children knew, pretty much, the same amount of language.
  • The bilinguals, we found, manifested a cognitive system with the ability to attend to important information and ignore the less important.
  • There’s a system in your brain, the executive control system. It’s a general manager. Its job is to keep you focused on what is relevant, while ignoring distractions. It’s what makes it possible for you to hold two different things in your mind at one time and switch between them. If you have two languages and you use them regularly, the way the brain’s networks work is that every time you speak, both languages pop up and the executive control system has to sort through everything and attend to what’s relevant in the moment. Therefore the bilinguals use that system more, and it’s that regular use that makes that system more efficient.
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  • we found that normally aging bilinguals had better cognitive functioning than normally aging monolinguals. Bilingual older adults performed better than monolingual older adults on executive control tasks.
  • On average, the bilinguals showed Alzheimer’s symptoms five or six years later than those who spoke only one language. This didn’t mean that the bilinguals didn’t have Alzheimer’s. It meant that as the disease took root in their brains, they were able to continue functioning at a higher level. They could cope with the disease for longer.
  • You have to use both languages all the time. You won’t get the bilingual benefit from occasional use.
  • One would think bilingualism might help with multitasking — does it? A. Yes, multitasking is one of the things the executive control system handles.
  • One of the things we’ve seen is that on certain kinds of even nonverbal tests, bilingual people are faster. Why? Well, when we look in their brains through neuroimaging, it appears like they’re using a different kind of a network that might include language centers to solve a completely nonverbal problem. Their whole brain appears to rewire because of bilingualism.
sissij

YouTube Filtering Draws Ire of Gay and Transgender Creators - The New York Times - 0 views

www.nytimes.com/...youtube-lgbt-videos.html

new york times bias social media research

shared by sissij on 20 Mar 17 - No Cached
  • YouTube said on Sunday that it was investigating the simmering complaints by some users that its family-friendly “restricted mode” wrongly filters out some lesbian, gay, bisexual and transgender videos.
  • In a statement, YouTube said that many videos featuring lesbian, gay, bisexual and transgender content were unaffected by the filter, an optional parental-control setting, and that it only targeted those that discussed sensitive topics such as politics, health and sexuality.
  • In a statement, YouTube described restricted mode as “an optional feature used by a very small subset of users who want to have a more limited YouTube experience.”
  • ...2 more annotations...
  • the system is “not 100 percent accurate.”
  • Over the weekend, many video creators and users complained on Twitter, recycling the hashtag #YouTubeIsOverParty, which was trending worldwide by Sunday night.
  • sissij on 20 Mar 17
     
    Restriction in social media has always been a controversial issue. I think this problem in the system filtering the videos of gay and transgender creator shouldn't be all blamed on Youtube. I think the system Youtube used to filter the video is not based on the sexuality information of the creators. It think the system might take in the comments and survey results from the viewer. I think this reflects that the mainstream community and mindset still reject and repel transgenders and gays. People don't want to be sensitive topics. --Sissi (3/20/2017)
caelengrubb

What Johannes Kepler Got Wrong - 0 views

www.thegreatcoursesdaily.com/what-johannes-kepler-got-wrong

shared by caelengrubb on 17 Jan 21 - No Cached
  • ohannes Kepler was one of the leading characters in the history of astronomy. His most famous achievement was the three laws of planetary motion, still taught in courses today. However, like all other human beings, he was not perfect and made mistakes
  • Johannes Kepler was one of the most influential figures in the history of astronomy. His three laws of planetary movement changed the world of science significantly and became a foundation for other scientists to build theories upon.
  • Nonetheless, there are theories in his past that are not even close to reality.
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  • In 1609, Kepler published a book containing the first two laws. The book also revealed his new model of the solar system, which was against what most scientists back then believed.
  • He stated that planets moved in elliptical orbits through the solar system, with the Sun located at one focus of the ellipse. Before Kepler, they believed that all orbits in the solar system were perfectly circular.
  • About ten years later, Kepler added his third law: that square of the orbital period divided by the cube of orbit’s semi-major axis is the same for all planets. Although not immediately accepted, his three laws took science to the next level. Why was he initially not appreciated?
  • Kepler applied this to the planets and stated that the solar system was built upon geometrical objects called Platonic solids that are a specific type of three-dimensional shape. They have identical sides or surfaces, edges of equal length, and angles of equal extent.
  • The model Kepler presented was based on a sequence of six spheres and the five Platonic solids, each located between two spheres. Back then, only six planets were discovered as Uranus and Neptune’s discovery took until the 18th and 19th centuries. Thus, each sphere represented one planet.
  • nitially, it seemed to explain the approximate ratios of the orbits of the six planets. It also gave a reason why there are only six planets—because there are only five Platonic shapes, each of which needs to fit between the orbit of two planets, only once
  • Kepler published this theory in detail, in his book Mysterium Cosmographicum. Despite all the value he gave to this theory, we now know how wrong it was.
  • Kepler cherished the theory as his most significant work, long after he had discovered the three laws.
  • However, the number of planets in the solar system or any other system in the universe is not predictable. Many of the numbers appearing everywhere are out of a mere accident, just like the number of planets.
  • Kepler thought his greatest achievement was the wrong solar system he drew, but it was the three laws that were so right to survive to date.
huffem4

Dual Process Theory - Explanation and examples - Conceptually - 1 views

conceptually.org/...dual-processing-theory

dual process knowledge reasoning thinking

shared by huffem4 on 15 Jul 20 - No Cached
  • When we’re making decisions, we use two different systems of thinking. System 1 is our intuition or gut-feeling: fast, automatic, emotional, and subconscious. System 2 is slower and more deliberate: consciously working through different considerations, applying different concepts and models and weighing them all up.
  • One takeaway from the psychological research on dual process theory is that our System 1 (intuition) is more accurate in areas where we’ve gathered a lot of data with reliable and fast feedback, like social dynamics.
  • our System 2 tends to be better for decisions where we don’t have a lot of experience; involving numbers, statistics, logic, abstractions, or models; and phenomena our ancestors never dealt with.
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  • You can also use both systems, acknowledging that you have an intuition, and feeding it into your System 2 model.
Javier E

Cognitive Biases and the Human Brain - The Atlantic - 1 views

www.theatlantic.com/...565775

cognitive bias psychology research knowledge bias

shared by Javier E on 28 Mar 21 - No Cached
  • Present bias shows up not just in experiments, of course, but in the real world. Especially in the United States, people egregiously undersave for retirement—even when they make enough money to not spend their whole paycheck on expenses, and even when they work for a company that will kick in additional funds to retirement plans when they contribute.
  • hen people hear the word bias, many if not most will think of either racial prejudice or news organizations that slant their coverage to favor one political position over another. Present bias, by contrast, is an example of cognitive bias—the collection of faulty ways of thinking that is apparently hardwired into the human brain. The collection is large. Wikipedia’s “List of cognitive biases” contains 185 entries, from actor-observer bias (“the tendency for explanations of other individuals’ behaviors to overemphasize the influence of their personality and underemphasize the influence of their situation … and for explanations of one’s own behaviors to do the opposite”) to the Zeigarnik effect (“uncompleted or interrupted tasks are remembered better than completed ones”)
  • If I had to single out a particular bias as the most pervasive and damaging, it would probably be confirmation bias. That’s the effect that leads us to look for evidence confirming what we already think or suspect, to view facts and ideas we encounter as further confirmation, and to discount or ignore any piece of evidence that seems to support an alternate view
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  • Confirmation bias shows up most blatantly in our current political divide, where each side seems unable to allow that the other side is right about anything.
  • The whole idea of cognitive biases and faulty heuristics—the shortcuts and rules of thumb by which we make judgments and predictions—was more or less invented in the 1970s by Amos Tversky and Daniel Kahneman
  • versky died in 1996. Kahneman won the 2002 Nobel Prize in Economics for the work the two men did together, which he summarized in his 2011 best seller, Thinking, Fast and Slow. Another best seller, last year’s The Undoing Project, by Michael Lewis, tells the story of the sometimes contentious collaboration between Tversky and Kahneman
  • Another key figure in the field is the University of Chicago economist Richard Thaler. One of the biases he’s most linked with is the endowment effect, which leads us to place an irrationally high value on our possessions.
  • In an experiment conducted by Thaler, Kahneman, and Jack L. Knetsch, half the participants were given a mug and then asked how much they would sell it for. The average answer was $5.78. The rest of the group said they would spend, on average, $2.21 for the same mug. This flew in the face of classic economic theory, which says that at a given time and among a certain population, an item has a market value that does not depend on whether one owns it or not. Thaler won the 2017 Nobel Prize in Economics.
  • “The question that is most often asked about cognitive illusions is whether they can be overcome. The message … is not encouraging.”
  • that’s not so easy in the real world, when we’re dealing with people and situations rather than lines. “Unfortunately, this sensible procedure is least likely to be applied when it is needed most,” Kahneman writes. “We would all like to have a warning bell that rings loudly whenever we are about to make a serious error, but no such bell is available.”
  • At least with the optical illusion, our slow-thinking, analytic mind—what Kahneman calls System 2—will recognize a Müller-Lyer situation and convince itself not to trust the fast-twitch System 1’s perception
  • Kahneman and others draw an analogy based on an understanding of the Müller-Lyer illusion, two parallel lines with arrows at each end. One line’s arrows point in; the other line’s arrows point out. Because of the direction of the arrows, the latter line appears shorter than the former, but in fact the two lines are the same length.
  • Because biases appear to be so hardwired and inalterable, most of the attention paid to countering them hasn’t dealt with the problematic thoughts, judgments, or predictions themselves
  • Is it really impossible, however, to shed or significantly mitigate one’s biases? Some studies have tentatively answered that question in the affirmative.
  • what if the person undergoing the de-biasing strategies was highly motivated and self-selected? In other words, what if it was me?
  • Over an apple pastry and tea with milk, he told me, “Temperament has a lot to do with my position. You won’t find anyone more pessimistic than I am.”
  • I met with Kahneman
  • “I see the picture as unequal lines,” he said. “The goal is not to trust what I think I see. To understand that I shouldn’t believe my lying eyes.” That’s doable with the optical illusion, he said, but extremely difficult with real-world cognitive biases.
  • In this context, his pessimism relates, first, to the impossibility of effecting any changes to System 1—the quick-thinking part of our brain and the one that makes mistaken judgments tantamount to the Müller-Lyer line illusion
  • he most effective check against them, as Kahneman says, is from the outside: Others can perceive our errors more readily than we can.
  • “slow-thinking organizations,” as he puts it, can institute policies that include the monitoring of individual decisions and predictions. They can also require procedures such as checklists and “premortems,”
  • A premortem attempts to counter optimism bias by requiring team members to imagine that a project has gone very, very badly and write a sentence or two describing how that happened. Conducting this exercise, it turns out, helps people think ahead.
  • “My position is that none of these things have any effect on System 1,” Kahneman said. “You can’t improve intuition.
  • Perhaps, with very long-term training, lots of talk, and exposure to behavioral economics, what you can do is cue reasoning, so you can engage System 2 to follow rules. Unfortunately, the world doesn’t provide cues. And for most people, in the heat of argument the rules go out the window.
  • Kahneman describes an even earlier Nisbett article that showed subjects’ disinclination to believe statistical and other general evidence, basing their judgments instead on individual examples and vivid anecdotes. (This bias is known as base-rate neglect.)
  • over the years, Nisbett had come to emphasize in his research and thinking the possibility of training people to overcome or avoid a number of pitfalls, including base-rate neglect, fundamental attribution error, and the sunk-cost fallacy.
  • Nisbett’s second-favorite example is that economists, who have absorbed the lessons of the sunk-cost fallacy, routinely walk out of bad movies and leave bad restaurant meals uneaten.
  • When Nisbett asks the same question of students who have completed the statistics course, about 70 percent give the right answer. He believes this result shows, pace Kahneman, that the law of large numbers can be absorbed into System 2—and maybe into System 1 as well, even when there are minimal cues.
  • about half give the right answer: the law of large numbers, which holds that outlier results are much more frequent when the sample size (at bats, in this case) is small. Over the course of the season, as the number of at bats increases, regression to the mean is inevitabl
  • When Nisbett has to give an example of his approach, he usually brings up the baseball-phenom survey. This involved telephoning University of Michigan students on the pretense of conducting a poll about sports, and asking them why there are always several Major League batters with .450 batting averages early in a season, yet no player has ever finished a season with an average that high.
  • we’ve tested Michigan students over four years, and they show a huge increase in ability to solve problems. Graduate students in psychology also show a huge gain.”
  • , “I know from my own research on teaching people how to reason statistically that just a few examples in two or three domains are sufficient to improve people’s reasoning for an indefinitely large number of events.”
  • isbett suggested another factor: “You and Amos specialized in hard problems for which you were drawn to the wrong answer. I began to study easy problems, which you guys would never get wrong but untutored people routinely do … Then you can look at the effects of instruction on such easy problems, which turn out to be huge.”
  • Nisbett suggested that I take “Mindware: Critical Thinking for the Information Age,” an online Coursera course in which he goes over what he considers the most effective de-biasing skills and concepts. Then, to see how much I had learned, I would take a survey he gives to Michigan undergraduates. So I did.
  • he course consists of eight lessons by Nisbett—who comes across on-screen as the authoritative but approachable psych professor we all would like to have had—interspersed with some graphics and quizzes. I recommend it. He explains the availability heuristic this way: “People are surprised that suicides outnumber homicides, and drownings outnumber deaths by fire. People always think crime is increasing” even if it’s not.
  • When I finished the course, Nisbett sent me the survey he and colleagues administer to Michigan undergrads
  • It contains a few dozen problems meant to measure the subjects’ resistance to cognitive biases
  • I got it right. Indeed, when I emailed my completed test, Nisbett replied, “My guess is that very few if any UM seniors did as well as you. I’m sure at least some psych students, at least after 2 years in school, did as well. But note that you came fairly close to a perfect score.”
  • Nevertheless, I did not feel that reading Mindware and taking the Coursera course had necessarily rid me of my biases
  • For his part, Nisbett insisted that the results were meaningful. “If you’re doing better in a testing context,” he told me, “you’ll jolly well be doing better in the real world.”
  • The New York–based NeuroLeadership Institute offers organizations and individuals a variety of training sessions, webinars, and conferences that promise, among other things, to use brain science to teach participants to counter bias. This year’s two-day summit will be held in New York next month; for $2,845, you could learn, for example, “why are our brains so bad at thinking about the future, and how do we do it better?”
  • Philip E. Tetlock, a professor at the University of Pennsylvania’s Wharton School, and his wife and research partner, Barbara Mellers, have for years been studying what they call “superforecasters”: people who manage to sidestep cognitive biases and predict future events with far more accuracy than the pundits
  • One of the most important ingredients is what Tetlock calls “the outside view.” The inside view is a product of fundamental attribution error, base-rate neglect, and other biases that are constantly cajoling us into resting our judgments and predictions on good or vivid stories instead of on data and statistics
  • In 2006, seeking to prevent another mistake of that magnitude, the U.S. government created the Intelligence Advanced Research Projects Activity (iarpa), an agency designed to use cutting-edge research and technology to improve intelligence-gathering and analysis. In 2011, iarpa initiated a program, Sirius, to fund the development of “serious” video games that could combat or mitigate what were deemed to be the six most damaging biases: confirmation bias, fundamental attribution error, the bias blind spot (the feeling that one is less biased than the average person), the anchoring effect, the representativeness heuristic, and projection bias (the assumption that everybody else’s thinking is the same as one’s own).
  • most promising are a handful of video games. Their genesis was in the Iraq War
  • Together with collaborators who included staff from Creative Technologies, a company specializing in games and other simulations, and Leidos, a defense, intelligence, and health research company that does a lot of government work, Morewedge devised Missing. Some subjects played the game, which takes about three hours to complete, while others watched a video about cognitive bias. All were tested on bias-mitigation skills before the training, immediately afterward, and then finally after eight to 12 weeks had passed.
  • “The literature on training suggests books and classes are fine entertainment but largely ineffectual. But the game has very large effects. It surprised everyone.”
  • he said he saw the results as supporting the research and insights of Richard Nisbett. “Nisbett’s work was largely written off by the field, the assumption being that training can’t reduce bias,
  • even the positive results reminded me of something Daniel Kahneman had told me. “Pencil-and-paper doesn’t convince me,” he said. “A test can be given even a couple of years later. But the test cues the test-taker. It reminds him what it’s all about.”
  • Morewedge told me that some tentative real-world scenarios along the lines of Missing have shown “promising results,” but that it’s too soon to talk about them.
  • In the future, I will monitor my thoughts and reactions as best I can
Javier E

Noam Chomsky on Where Artificial Intelligence Went Wrong - Yarden Katz - The Atlantic - 0 views

www.theatlantic.com/...261637

chomsky ai language brain science computer research methods science history

shared by Javier E on 30 Jun 13 - No Cached
  • If you take a look at the progress of science, the sciences are kind of a continuum, but they're broken up into fields. The greatest progress is in the sciences that study the simplest systems. So take, say physics -- greatest progress there. But one of the reasons is that the physicists have an advantage that no other branch of sciences has. If something gets too complicated, they hand it to someone else.
  • If a molecule is too big, you give it to the chemists. The chemists, for them, if the molecule is too big or the system gets too big, you give it to the biologists. And if it gets too big for them, they give it to the psychologists, and finally it ends up in the hands of the literary critic, and so on.
  • neuroscience for the last couple hundred years has been on the wrong track. There's a fairly recent book by a very good cognitive neuroscientist, Randy Gallistel and King, arguing -- in my view, plausibly -- that neuroscience developed kind of enthralled to associationism and related views of the way humans and animals work. And as a result they've been looking for things that have the properties of associationist psychology.
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  • in general what he argues is that if you take a look at animal cognition, human too, it's computational systems. Therefore, you want to look the units of computation. Think about a Turing machine, say, which is the simplest form of computation, you have to find units that have properties like "read", "write" and "address." That's the minimal computational unit, so you got to look in the brain for those. You're never going to find them if you look for strengthening of synaptic connections or field properties, and so on. You've got to start by looking for what's there and what's working and you see that from Marr's highest level.
  • it's basically in the spirit of Marr's analysis. So when you're studying vision, he argues, you first ask what kind of computational tasks is the visual system carrying out. And then you look for an algorithm that might carry out those computations and finally you search for mechanisms of the kind that would make the algorithm work. Otherwise, you may never find anything.
  • "Good Old Fashioned AI," as it's labeled now, made strong use of formalisms in the tradition of Gottlob Frege and Bertrand Russell, mathematical logic for example, or derivatives of it, like nonmonotonic reasoning and so on. It's interesting from a history of science perspective that even very recently, these approaches have been almost wiped out from the mainstream and have been largely replaced -- in the field that calls itself AI now -- by probabilistic and statistical models. My question is, what do you think explains that shift and is it a step in the right direction?
  • AI and robotics got to the point where you could actually do things that were useful, so it turned to the practical applications and somewhat, maybe not abandoned, but put to the side, the more fundamental scientific questions, just caught up in the success of the technology and achieving specific goals.
  • The approximating unanalyzed data kind is sort of a new approach, not totally, there's things like it in the past. It's basically a new approach that has been accelerated by the existence of massive memories, very rapid processing, which enables you to do things like this that you couldn't have done by hand. But I think, myself, that it is leading subjects like computational cognitive science into a direction of maybe some practical applicability... ..in engineering? Chomsky: ...But away from understanding.
  • I was very skeptical about the original work. I thought it was first of all way too optimistic, it was assuming you could achieve things that required real understanding of systems that were barely understood, and you just can't get to that understanding by throwing a complicated machine at it.
  • if success is defined as getting a fair approximation to a mass of chaotic unanalyzed data, then it's way better to do it this way than to do it the way the physicists do, you know, no thought experiments about frictionless planes and so on and so forth. But you won't get the kind of understanding that the sciences have always been aimed at -- what you'll get at is an approximation to what's happening.
  • Suppose you want to predict tomorrow's weather. One way to do it is okay I'll get my statistical priors, if you like, there's a high probability that tomorrow's weather here will be the same as it was yesterday in Cleveland, so I'll stick that in, and where the sun is will have some effect, so I'll stick that in, and you get a bunch of assumptions like that, you run the experiment, you look at it over and over again, you correct it by Bayesian methods, you get better priors. You get a pretty good approximation of what tomorrow's weather is going to be. That's not what meteorologists do -- they want to understand how it's working. And these are just two different concepts of what success means, of what achievement is.
  • if you get more and more data, and better and better statistics, you can get a better and better approximation to some immense corpus of text, like everything in The Wall Street Journal archives -- but you learn nothing about the language.
  • the right approach, is to try to see if you can understand what the fundamental principles are that deal with the core properties, and recognize that in the actual usage, there's going to be a thousand other variables intervening -- kind of like what's happening outside the window, and you'll sort of tack those on later on if you want better approximations, that's a different approach.
  • take a concrete example of a new field in neuroscience, called Connectomics, where the goal is to find the wiring diagram of very complex organisms, find the connectivity of all the neurons in say human cerebral cortex, or mouse cortex. This approach was criticized by Sidney Brenner, who in many ways is [historically] one of the originators of the approach. Advocates of this field don't stop to ask if the wiring diagram is the right level of abstraction -- maybe it's no
  • if you went to MIT in the 1960s, or now, it's completely different. No matter what engineering field you're in, you learn the same basic science and mathematics. And then maybe you learn a little bit about how to apply it. But that's a very different approach. And it resulted maybe from the fact that really for the first time in history, the basic sciences, like physics, had something really to tell engineers. And besides, technologies began to change very fast, so not very much point in learning the technologies of today if it's going to be different 10 years from now. So you have to learn the fundamental science that's going to be applicable to whatever comes along next. And the same thing pretty much happened in medicine.
  • that's the kind of transition from something like an art, that you learn how to practice -- an analog would be trying to match some data that you don't understand, in some fashion, maybe building something that will work -- to science, what happened in the modern period, roughly Galilean science.
  • it turns out that there actually are neural circuits which are reacting to particular kinds of rhythm, which happen to show up in language, like syllable length and so on. And there's some evidence that that's one of the first things that the infant brain is seeking -- rhythmic structures. And going back to Gallistel and Marr, its got some computational system inside which is saying "okay, here's what I do with these things" and say, by nine months, the typical infant has rejected -- eliminated from its repertoire -- the phonetic distinctions that aren't used in its own language.
  • people like Shimon Ullman discovered some pretty remarkable things like the rigidity principle. You're not going to find that by statistical analysis of data. But he did find it by carefully designed experiments. Then you look for the neurophysiology, and see if you can find something there that carries out these computations. I think it's the same in language, the same in studying our arithmetical capacity, planning, almost anything you look at. Just trying to deal with the unanalyzed chaotic data is unlikely to get you anywhere, just like as it wouldn't have gotten Galileo anywhere.
  • with regard to cognitive science, we're kind of pre-Galilean, just beginning to open up the subject
  • You can invent a world -- I don't think it's our world -- but you can invent a world in which nothing happens except random changes in objects and selection on the basis of external forces. I don't think that's the way our world works, I don't think it's the way any biologist thinks it is. There are all kind of ways in which natural law imposes channels within which selection can take place, and some things can happen and other things don't happen. Plenty of things that go on in the biology in organisms aren't like this. So take the first step, meiosis. Why do cells split into spheres and not cubes? It's not random mutation and natural selection; it's a law of physics. There's no reason to think that laws of physics stop there, they work all the way through. Well, they constrain the biology, sure. Chomsky: Okay, well then it's not just random mutation and selection. It's random mutation, selection, and everything that matters, like laws of physics.
  • What I think is valuable is the history of science. I think we learn a lot of things from the history of science that can be very valuable to the emerging sciences. Particularly when we realize that in say, the emerging cognitive sciences, we really are in a kind of pre-Galilean stage. We don't know wh
  • at we're looking for anymore than Galileo did, and there's a lot to learn from that.
oliviaodon

NASA Just Discovered Seven New Exoplanets... So What? - 0 views

www.forbes.com/...d-seven-new-exoplanets-so-what

science

shared by oliviaodon on 28 Feb 17 - No Cached
  • On Wednesday, the scientists at NASA kind of freaked out. They announced the discovery of some seemingly Earth-like planets outside of our solar system, a group of rocky globes they're calling 'TRAPPIST-1.'
  • To be completely blunt, the most exiting thing for actual scientists is that these planets are close enough that we're actually going to be able to study them – particularly when the James Webb Space Telescope launches (October 2018.) When that launches, it will have a real shot at actually taking a look at the atmospheres of these planets – or if they have atmospheres at all. So it's like a promise of future excitement
  • The closer the system is to our solar system – the more the star is like the Sun and the planet is like the Earth, the more likely we are to understand what we're looking at. That's what makes it exciting.
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  • At the moment, all you really tell from the transits is these are small black dots. We just get a radius – and if we're super lucky – as they were in the case of this system, they can get masses. The sizes and masses of these planets is really valuable information though, because it does suggests that most of them are rocky. Six of the seven planets look like they're rocky.  And being Earth-sized, we think it's a good place: an atmosphere thick enough to keep you warm and last for billions of years, but not so thick that you end up being a gas giant planet.
  • Most of them are the right distance from a star that maybe they could have liquid water on their surfaces. But that's a huge maybe
  • o it's not really that we think Earth-like life is the only life that can be out there. It's just the only life we can detect.
  • oliviaodon on 28 Feb 17
     
    This article discusses the potential of a new scientific discovery: seven exoplanets outside of our solar system. This article does a great job in mentioning the limitations of science, however.
Javier E

Coursera Plans to Announce University Partners for Online Classes - NYTimes.com - 0 views

www.nytimes.com/...rtners-for-online-classes.html

university online classes courses system startups education

shared by Javier E on 20 Apr 12 - No Cached
  • John Doerr, a Kleiner investment partner, said via e-mail that he saw a clear business model: “Yes. Even with free courses. From a community of millions of learners some should ‘opt in’ for valuable, premium services. Those revenues should fund investment in tools, technology and royalties to faculty and universities.”
  • Previously he said he had been involved with Stanford’s effort to put academic lectures online for viewing. But he noted that there was evidence that the newer interactive systems provided much more effective learning experiences.
  • Coursera and Udacity are not alone in the rush to offer mostly free online educational alternatives. Start-up companies like Minerva and Udemy, and, separately, the Massachusetts Institute of Technology, have recently announced similar platforms.
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  • Unlike previous video lectures, which offered a “static” learning model, the Coursera system breaks lectures into segments as short as 10 minutes and offers quick online quizzes as part of each segment.
  • Where essays are required, especially in the humanities and social sciences, the system relies on the students themselves to grade their fellow students’ work, in effect turning them into teaching assistants.
  • The Coursera system also offers an online feature that allows students to get support from a global student community. Dr. Ng said an early test of the system found that questions were typically answered within 22 minutes.
  • Dr. Koller said the educational approach was similar to that of the “flipped classroom,” pioneered by the Khan Academy, a creation of the educator Salman Khan. Students watch lectures at home and then work on problem-solving or “homework” in the classroom, either one-on-one with the teacher or in small groups.
grayton downing

How the Brain Creates Personality: A New Theory - Stephen M. Kosslyn and G. Wayne Mille... - 0 views

www.theatlantic.com/...281287

brain personality research science brain science

shared by grayton downing on 12 Nov 13 - No Cached
  • It is possible to examine any object—including a brain—at different levels
  • if we want to know how the brain gives rise to thoughts, feelings, and behaviors, we want to focus on the bigger picture of how its structure allows it to store and process information—the architecture, as it were. To understand the brain at this level, we don’t have to know everything about the individual connections among brain cells or about any other biochemical process.
  • top parts and the bottom parts of the brain have differ­ent functions. The top brain formulates and executes plans (which often involve deciding where to move objects or how to move the body in space), whereas the bottom brain classifies and interprets incoming information about the world. The two halves always work together;
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  • You have probably heard of this theory, in which the left and right halves of the brain are characterized, respectively, as logical versus intuitive, verbal versus perceptual, analytic versus synthetic, and so forth. The trouble is that none of these sweeping generalizations has stood up to careful scientific scrutiny. The dif­ferences between the left and right sides of the brain are nuanced, and simple, sweeping dichotomies do not in fact explain how the two sides function.
  • top and bottom portions of the brain have very different functions. This fact was first discovered in the context of visual perception, and it was supported in 1982 in a landmark report by National Medal of Science winner Mortimer Mishkin and Leslie G. Ungerleider, of the National Institute of Mental Health.
  • scientists trained monkeys to perform two tasks. In the first task, the monkeys had to learn to recognize which of two shapes concealed a bit of food.
  • These functions occur relatively close to where neural connec­tions deliver inputs from the eyes and ears—but processing doesn’t just stop there.
  • top parts of our frontal lobe can take into account the confluence of information about “what’s out there,” our emo­tional reactions to it, and our goals.
  • Four distinct cognitive modes emerge from how the top-brain and bottom-brain systems can interac
  • The two systems always work together. You use the top brain to decide to walk over to talk to your friend only after you know who she is (courtesy of the bottom brain). And after talking to her, you formulate another plan, to enter the date and time in your calendar, and then you need to monitor what hap­pens (again using the bottom brain) as you try to carry out this plan (a top-brain activity).
  • speak of differences in the degree to which a person relies on the top-brain and bottom-brain systems, we are speaking of differences in this second kind of utilization, in the kind of processing that’s not simply dictated by a given situation. In this sense, you can rely on one or the other brain system to a greater or lesser degree.
  • The degree to which you tend to use each system will affect your thoughts, feel­ings, and behavior in profound ways. The notion that each system can be more or less highly utilized, in this sense is the foundation of the Theory of Cognitive Modes. 
Javier E

Read this if you want to be happy in 2014 - The Washington Post - 2 views

www.washingtonpost.com/...3-9389-09ef9944065e_story.html

diet exercise happiness health freedom knowledge willpower system goal

shared by Javier E on 03 Jan 14 - No Cached
  • people usually experience the sensation of happiness whenever they have both health and freedom. It’s a simple formula: Happiness = Health + Freedom
  • I’m talking about the everyday freedom of being able to do what you want when you want to do it, at work and elsewhere. For happiness, timing is as important as the thing you’re doing
  • Matching your mood to your activity is a baseline requirement for happiness
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  • The good news is that timing is relatively controllable, especially in the long run.
  • If you’re just starting out in your career, it won’t be easy to find a job that gives you a flexible schedule. The best approach is a strategy of moving toward more flexibility over the course of your life.
  • There isn’t one formula for finding schedule flexibility. Just make sure all of your important decisions are consistent with an end game of a more flexible schedule. Otherwise you are shutting yourself off from the most accessible lever for happiness — timing.
  • if you knew that pasta is far lower on the glycemic index than a white potato, you would make a far healthier choice that requires no willpower at all. All it took was knowledge.
  • The most important thing to know about staying fit is this: If it takes willpower, you’re doing it wrong. Anything that requires willpower is unsustainable in the long run.
  • studies show that using willpower in one area diminishes how much willpower you have in reserve for other areas. You need to get willpower out of the system
  • My observation is that you can usually replace willpower with knowledge.
  • the trick for avoiding unhealthy foods is to make sure you always have access to healthy options that you enjoy eating. Your knowledge of this trick, assuming you use it, makes willpower far less necessary.
  • don’t give up too much income potential just to get a flexible schedule. There’s no point in having a flexible schedule if you can’t afford to do anything.
  • the fittest people have systems, not goals, unless they are training for something specific. A sensible system is to continuously learn more about the science of diet and the methods for making healthy food taste great. With that system, weight management will feel automatic. Goals aren’t needed.
  • Did you know that sleepiness causes you to feel hungry?
  • Did you know that eating peanuts is a great way to suppress appetite?
  • Did you know that eating mostly protein instead of simple carbs for lunch will help you avoid the afternoon energy slump?
  • Cheese adds calories, but the fat content will help suppress your appetite, so you probably come out ahead. If you didn’t already know that, you might end up using willpower to avoid cheese at dinner and willpower again later that night to resist snacking. A little knowledge replaces a lot of willpower.
  • Did you know that exercise has only a small impact on your weight?
  • after I started noticing how drained and useless I felt after eating simple carbs, french fries became easy to resist.
  • I also learned that I can remove problem foods from my diet if I target them for extinction one at a time. It was easy to stop eating three large Snickers every day (which I was doing) when I realized I could eat anything else I wanted whenever I wanted
  • If you’re on a diet, you’re probably trying to avoid certain types of food, but you’re also trying to limit your portions. Instead of waging war on two fronts, try allowing yourself to eat as much as you want of anything that is healthy.
  • healthier food is almost self-regulating in the sense that you don’t have an insatiable desire to keep eating it the way you might with junk food. With healthy food, you tend to stop when you feel full
  • One of the biggest obstacles to healthy eating is the impression that healthy food generally tastes like cardboard. So consider making it a lifelong system to learn how to season and prepare healthy foods
  • Did you know that eating simple carbs can make you hungrier?
  • ’m limiting my portion size. You only need to do that if you are eating the wrong foods. Eating half of your cake still keeps you addicted to cake. And portion control takes a lot of willpower. You’ll find that healthy food satisfies you sooner, so you don’t crave large portions.
  • No one can exercise enough to overcome a bad diet. Diet is the right button to push for losing weight, so long as you are active. People who eat right and stay active usually have no problems with weight.
  • I’m about to share with you the simplest and potentially most effective exercise plan in the world. Here it is: Be active every day.
  • When you’re active, and you don’t overdo it, you’ll find yourself in a good mood afterward. That reward becomes addictive over time.
  • After a few months of being moderately active every day, you’ll discover that it is harder to sit and do nothing than it is to get up and do something. That’s the frame of mind you want. You want exercise to become a habit with a reward so it evolves into a useful addiction
  • the intensity of your workout has a surprisingly small impact on your weight unless you’re running half-marathons every week. If your diet is right, moderate exercise is all you need.
  • When your body is feeling good, and you have some flexibility in your schedule, you’ll find that the petty annoyances that plague your life become nothing but background noise. And that’s a great launch pad for happiness.
  • As you find yourself getting healthier and happier, the people in your life will view you differently too. Healthy-looking people generally earn more money, get more offers and enjoy a better social life. All of that will help your happiness.
  • Keep in mind that happiness is a directional phenomenon. We feel happy when things are moving in the right direction no matter where we are at the moment.
Javier E

The Bilingual Advantage - NYTimes.com - 0 views

www.nytimes.com/...31conversation.html

bilingual advantage research cognitive

shared by Javier E on 02 Jul 11 - No Cached
  • As we did our research, you could see there was a big difference in the way monolingual and bilingual children processed language.
  • The bilinguals, we found, manifested a cognitive system with the ability to attend to important information and ignore the less important.
  • If you have two languages and you use them regularly, the way the brain’s networks work is that every time you speak, both languages pop up and the executive control system has to sort through everything and attend to what’s relevant in the moment. Therefore the bilinguals use that system more, and it’s that regular use that makes that system more efficient.
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  • On average, the bilinguals showed Alzheimer’s symptoms five or six years later than those who spoke only one language. This didn’t mean that the bilinguals didn’t have Alzheimer’s. It meant that as the disease took root in their brains, they were able to continue functioning at a higher level. They could cope with the disease for longer.
  • One would think bilingualism might help with multitasking — does it? A. Yes, multitasking is one of the things the executive control system handles
  • In terms of monolinguals and bilinguals, the big thing that we have found is that the connections are different. So we have monolinguals solving a problem, and they use X systems, but when bilinguals solve the same problem, they use others. One of the things we’ve seen is that on certain kinds of even nonverbal tests, bilingual people are faster. Why? Well, when we look in their brains through neuroimaging, it appears like they’re using a different kind of a network that might include language centers to solve a completely nonverbal problem. Their whole brain appears to rewire because of bilingualism.
Javier E

Ivy League Schools Are Overrated. Send Your Kids Elsewhere. | New Republic - 1 views

www.thenewrepublic.com/...rated-send-your-kids-elsewhere

inequality ivy league admissions university education elite success leadership class

shared by Javier E on 22 Jul 14 - No Cached
  • a blizzard of admissions jargon that I had to pick up on the fly. “Good rig”: the transcript exhibits a good degree of academic rigor. “Ed level 1”: parents have an educational level no higher than high school, indicating a genuine hardship case. “MUSD”: a musician in the highest category of promise. Kids who had five or six items on their list of extracurriculars—the “brag”—were already in trouble, because that wasn’t nearly enough.
  • With so many accomplished applicants to choose from, we were looking for kids with something special, “PQs”—personal qualities—that were often revealed by the letters or essays. Kids who only had the numbers and the résumé were usually rejected: “no spark,” “not a team-builder,” “this is pretty much in the middle of the fairway for us.” One young person, who had piled up a truly insane quantity of extracurriculars and who submitted nine letters of recommendation, was felt to be “too intense.”
  • On the other hand, the numbers and the résumé were clearly indispensable. I’d been told that successful applicants could either be “well-rounded” or “pointy”—outstanding in one particular way—but if they were pointy, they had to be really pointy: a musician whose audition tape had impressed the music department, a scientist who had won a national award.
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  • When I speak of elite education, I mean prestigious institutions like Harvard or Stanford or Williams as well as the larger universe of second-tier selective schools, but I also mean everything that leads up to and away from them—the private and affluent public high schools; the ever-growing industry of tutors and consultants and test-prep courses; the admissions process itself, squatting like a dragon at the entrance to adulthood; the brand-name graduate schools and employment opportunities that come after the B.A.; and the parents and communities, largely upper-middle class, who push their children into the maw of this machine.
  • Our system of elite education manufactures young people who are smart and talented and driven, yes, but also anxious, timid, and lost, with little intellectual curiosity and a stunted sense of purpose: trapped in a bubble of privilege, heading meekly in the same direction, great at what they’re doing but with no idea why they’re doing it.
  • “Super People,” the writer James Atlas has called them—the stereotypical ultra-high-achieving elite college students of today. A double major, a sport, a musical instrument, a couple of foreign languages, service work in distant corners of the globe, a few hobbies thrown in for good measure: They have mastered them all, and with a serene self-assurance
  • Like so many kids today, I went off to college like a sleepwalker. You chose the most prestigious place that let you in; up ahead were vaguely understood objectives: status, wealth—“success.” What it meant to actually get an education and why you might want one—all this was off the table.
  • It was only after 24 years in the Ivy League—college and a Ph.D. at Columbia, ten years on the faculty at Yale—that I started to think about what this system does to kids and how they can escape from it, what it does to our society and how we can dismantle it.
  • I taught many wonderful young people during my years in the Ivy League—bright, thoughtful, creative kids whom it was a pleasure to talk with and learn from. But most of them seemed content to color within the lines that their education had marked out for them. Very few were passionate about ideas. Very few saw college as part of a larger project of intellectual discovery and development. Everyone dressed as if they were ready to be interviewed at a moment’s notice.
  • Look beneath the façade of seamless well-adjustment, and what you often find are toxic levels of fear, anxiety, and depression, of emptiness and aimlessness and isolation. A large-scale survey of college freshmen recently found that self-reports of emotional well-being have fallen to their lowest level in the study’s 25-year history.
  • So extreme are the admission standards now that kids who manage to get into elite colleges have, by definition, never experienced anything but success. The prospect of not being successful terrifies them, disorients them. The cost of falling short, even temporarily, becomes not merely practical, but existential. The result is a violent aversion to risk.
  • There are exceptions, kids who insist, against all odds, on trying to get a real education. But their experience tends to make them feel like freaks. One student told me that a friend of hers had left Yale because she found the school “stifling to the parts of yourself that you’d call a soul.”
  • What no one seems to ask is what the “return” is supposed to be. Is it just about earning more money? Is the only purpose of an education to enable you to get a job? What, in short, is college for?
  • The first thing that college is for is to teach you to think.
  • College is an opportunity to stand outside the world for a few years, between the orthodoxy of your family and the exigencies of career, and contemplate things from a distance.
  • it is only through the act of establishing communication between the mind and the heart, the mind and experience, that you become an individual, a unique being—a soul. The job of college is to assist you to begin to do that. Books, ideas, works of art and thought, the pressure of the minds around you that are looking for their own answers in their own ways.
  • College is not the only chance to learn to think, but it is the best. One thing is certain: If you haven’t started by the time you finish your B.A., there’s little likelihood you’ll do it later. That is why an undergraduate experience devoted exclusively to career preparation is four years largely wasted.
  • Elite schools like to boast that they teach their students how to think, but all they mean is that they train them in the analytic and rhetorical skills that are necessary for success in business and the professions.
  • Everything is technocratic—the development of expertise—and everything is ultimately justified in technocratic terms.
  • Religious colleges—even obscure, regional schools that no one has ever heard of on the coasts—often do a much better job in that respect.
  • At least the classes at elite schools are academically rigorous, demanding on their own terms, no? Not necessarily. In the sciences, usually; in other disciplines, not so much
  • professors and students have largely entered into what one observer called a “nonaggression pact.”
  • higher marks for shoddier work.
  • today’s young people appear to be more socially engaged than kids have been for several decades and that they are more apt to harbor creative or entrepreneurial impulses
  • they tend to be played out within the same narrow conception of what constitutes a valid life: affluence, credentials, prestige.
  • Experience itself has been reduced to instrumental function, via the college essay. From learning to commodify your experiences for the application, the next step has been to seek out experiences in order to have them to commodify
  • there is now a thriving sector devoted to producing essay-ready summers
  • To be a high-achieving student is to constantly be urged to think of yourself as a future leader of society.
  • what these institutions mean by leadership is nothing more than getting to the top. Making partner at a major law firm or becoming a chief executive, climbing the greasy pole of whatever hierarchy you decide to attach yourself to. I don’t think it occurs to the people in charge of elite colleges that the concept of leadership ought to have a higher meaning, or, really, any meaning.
  • The irony is that elite students are told that they can be whatever they want, but most of them end up choosing to be one of a few very similar things
  • As of 2010, about a third of graduates went into financing or consulting at a number of top schools, including Harvard, Princeton, and Cornell.
  • Whole fields have disappeared from view: the clergy, the military, electoral politics, even academia itself, for the most part, including basic science
  • It’s considered glamorous to drop out of a selective college if you want to become the next Mark Zuckerberg, but ludicrous to stay in to become a social worker. “What Wall Street figured out,” as Ezra Klein has put it, “is that colleges are producing a large number of very smart, completely confused graduates. Kids who have ample mental horsepower, an incredible work ethic and no idea what to do next.”
  • t almost feels ridiculous to have to insist that colleges like Harvard are bastions of privilege, where the rich send their children to learn to walk, talk, and think like the rich. Don’t we already know this? They aren’t called elite colleges for nothing. But apparently we like pretending otherwise. We live in a meritocracy, after all.
  • Visit any elite campus across our great nation, and you can thrill to the heart-warming spectacle of the children of white businesspeople and professionals studying and playing alongside the children of black, Asian, and Latino businesspeople and professionals
  • That doesn’t mean there aren’t a few exceptions, but that is all they are. In fact, the group that is most disadvantaged by our current admissions policies are working-class and rural whites, who are hardly present
  • The college admissions game is not primarily about the lower and middle classes seeking to rise, or even about the upper-middle class attempting to maintain its position. It is about determining the exact hierarchy of status within the upper-middle class itself.
  • This system is exacerbating inequality, retarding social mobility, perpetuating privilege, and creating an elite that is isolated from the society that it’s supposed to lead. The numbers are undeniable. In 1985, 46 percent of incoming freshmen at the 250 most selective colleges came from the top quarter of the income distribution. By 2000, it was 55 percent
  • The major reason for the trend is clear. Not increasing tuition, though that is a factor, but the ever-growing cost of manufacturing children who are fit to compete in the college admissions game
  • Wealthy families start buying their children’s way into elite colleges almost from the moment they are born: music lessons, sports equipment, foreign travel (“enrichment” programs, to use the all-too-perfect term)—most important, of course, private-school tuition or the costs of living in a place with top-tier public schools.
  • s there anything that I can do, a lot of young people have written to ask me, to avoid becoming an out-of-touch, entitled little shit? I don’t have a satisfying answer, short of telling them to transfer to a public university. You cannot cogitate your way to sympathy with people of different backgrounds, still less to knowledge of them. You need to interact with them directly, and it has to be on an equal footing
  • Elite private colleges will never allow their students’ economic profile to mirror that of society as a whole. They can’t afford to—they need a critical mass of full payers and they need to tend to their donor base—and it’s not even clear that they’d want to.
  • Elite colleges are not just powerless to reverse the movement toward a more unequal society; their policies actively promote it.
  • The SAT is supposed to measure aptitude, but what it actually measures is parental income, which it tracks quite closely
  • U.S. News and World Report supplies the percentage of freshmen at each college who finished in the highest 10 percent of their high school class. Among the top 20 universities, the number is usually above 90 percent. I’d be wary of attending schools like that. Students determine the level of classroom discussion; they shape your values and expectations, for good and ill. It’s partly because of the students that I’d warn kids away from the Ivies and their ilk. Kids at less prestigious schools are apt to be more interesting, more curious, more open, and far less entitled and competitive.
  • The best option of all may be the second-tier—not second-rate—colleges, like Reed, Kenyon, Wesleyan, Sewanee, Mount Holyoke, and others. Instead of trying to compete with Harvard and Yale, these schools have retained their allegiance to real educational values.
  • Not being an entitled little shit is an admirable goal. But in the end, the deeper issue is the situation that makes it so hard to be anything else. The time has come, not simply to reform that system top to bottom, but to plot our exit to another kind of society altogether.
  • The education system has to act to mitigate the class system, not reproduce it. Affirmative action should be based on class instead of race, a change that many have been advocating for years. Preferences for legacies and athletes ought to be discarded. SAT scores should be weighted to account for socioeconomic factors. Colleges should put an end to résumé-stuffing by imposing a limit on the number of extracurriculars that kids can list on their applications. They ought to place more value on the kind of service jobs that lower-income students often take in high school and that high achievers almost never do. They should refuse to be impressed by any opportunity that was enabled by parental wealth
  • More broadly, they need to rethink their conception of merit. If schools are going to train a better class of leaders than the ones we have today, they’re going to have to ask themselves what kinds of qualities they need to promote. Selecting students by GPA or the number of extracurriculars more often benefits the faithful drudge than the original mind.
  • reforming the admissions process. That might address the problem of mediocrity, but it won’t address the greater one of inequality
  • The problem is the Ivy League itself. We have contracted the training of our leadership class to a set of private institutions. However much they claim to act for the common good, they will always place their interests first.
  • I’ve come to see that what we really need is to create one where you don’t have to go to the Ivy League, or any private college, to get a first-rate education.
  • High-quality public education, financed with public money, for the benefit of all
  • Everybody gets an equal chance to go as far as their hard work and talent will take them—you know, the American dream. Everyone who wants it gets to have the kind of mind-expanding, soul-enriching experience that a liberal arts education provides.
  • We recognize that free, quality K–12 education is a right of citizenship. We also need to recognize—as we once did and as many countries still do—that the same is true of higher education. We have tried aristocracy. We have tried meritocracy. Now it’s time to try democracy.
Javier E

The Irrational Consumer: Why Economics Is Dead Wrong About How We Make Choices - Derek ... - 4 views

www.theatlantic.com/...267255

rational choice rationality psychology consumer economics

shared by Javier E on 20 May 15 - No Cached
  • Atlantic.displayRandomElement('#header li.business .sponsored-dropdown-item'); Derek Thompson - Derek Thompson is a senior editor at The Atlantic, where he oversees business coverage for the website. More Derek has also written for Slate, BusinessWeek, and the Daily Beast. He has appeared as a guest on radio and television networks, including NPR, the BBC, CNBC, and MSNBC. All Posts RSS feed Share Share on facebook Share on linkedin Share on twitter « Previous Thompson Email Print Close function plusOneCallback () { $(document).trigger('share'); } $(document).ready(function() { var iframeUrl = "\/ad\/thanks-iframe\/TheAtlanticOnline\/channel_business;src=blog;by=derek-thompson;title=the-irrational-consumer-why-economics-is-dead-wrong-about-how-we-make-choices;pos=sharing;sz=640x480,336x280,300x250"; var toolsClicked = false; $('#toolsTop').click(function() { toolsClicked = 'top'; }); $('#toolsBottom').click(function() { toolsClicked = 'bottom'; }); $('#thanksForSharing a.hide').click(function() { $('#thanksForSharing').hide(); }); var onShareClickHandler = function() { var top = parseInt($(this).css('top').replace(/px/, ''), 10); toolsClicked = (top > 600) ? 'bottom' : 'top'; }; var onIframeReady = function(iframe) { var win = iframe.contentWindow; // Don't show the box if there's no ad in it if (win.$('.ad').children().length == 1) { return; } var visibleAds = win.$('.ad').filter(function() { return !($(this).css('display') == 'none'); }); if (visibleAds.length == 0) { // Ad is hidden, so don't show return; } if (win.$('.ad').hasClass('adNotLoaded')) { // Ad failed to load so don't show return; } $('#thanksForSharing').css('display', 'block'); var top; if(toolsClicked == 'bottom' && $('#toolsBottom').length) { top = $('#toolsBottom')[0].offsetTop + $('#toolsBottom').height() - 310; } else { top = $('#toolsTop')[0].offsetTop + $('#toolsTop').height() + 10; } $('#thanksForSharing').css('left', (-$('#toolsTop').offset().left + 60) + 'px'); $('#thanksForSharing').css('top', top + 'px'); }; var onShare = function() { // Close "Share successful!" AddThis plugin popup if (window._atw && window._atw.clb && $('#at15s:visible').length) { _atw.clb(); } if (iframeUrl == null) { return; } $('#thanksForSharingIframe').attr('src', "\/ad\/thanks-iframe\/TheAtlanticOnline\/channel_business;src=blog;by=derek-thompson;title=the-irrational-consumer-why-economics-is-dead-wrong-about-how-we-make-choices;pos=sharing;sz=640x480,336x280,300x250"); $('#thanksForSharingIframe').load(function() { var iframe = this; var win = iframe.contentWindow; if (win.loaded) { onIframeReady(iframe); } else { win.$(iframe.contentDocument).ready(function() { onIframeReady(iframe); }) } }); }; if (window.addthis) { addthis.addEventListener('addthis.ready', function() { $('.articleTools .share').mouseover(function() { $('#at15s').unbind('click', onShareClickHandler); $('#at15s').bind('click', onShareClickHandler); }); }); addthis.addEventListener('addthis.menu.share', function(evt) { onShare(); }); } // This 'share' event is used for testing, so one can call // $(document).trigger('share') to get the thank you for // sharing box to appear. $(document).bind('share', function(event) { onShare(); }); if (!window.FB || (window.FB && !window.FB._apiKey)) { // Hook into the fbAsyncInit function and register our listener there var oldFbAsyncInit = (window.fbAsyncInit) ? window.fbAsyncInit : (function() { }); window.fbAsyncInit = function() { oldFbAsyncInit(); FB.Event.subscribe('edge.create', function(response) { // to hide the facebook comments box $('#facebookLike span.fb_edge_comment_widget').hide(); onShare(); }); }; } else if (window.FB) { FB.Event.subscribe('edge.create', function(response) { // to hide the facebook comments box $('#facebookLike span.fb_edge_comment_widget').hide(); onShare(); }); } }); The Irrational Consumer: Why Economics Is Dead Wrong About How We Make Choices By Derek Thompson he
  • First, making a choice is physically exhausting, literally, so that somebody forced to make a number of decisions in a row is likely to get lazy and dumb.
  • Second, having too many choices can make us less likely to come to a conclusion. In a famous study of the so-called "paradox of choice", psychologists Mark Lepper and Sheena Iyengar found that customers presented with six jam varieties were more likely to buy one than customers offered a choice of 24.
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  • Many of our mistakes stem from a central "availability bias." Our brains are computers, and we like to access recently opened files, even though many decisions require a deep body of information that might require some searching. Cheap example: We remember the first, last, and peak moments of certain experiences.
  • The third check against the theory of the rational consumer is the fact that we're social animals. We let our friends and family and tribes do our thinking for us
  • neurologists are finding that many of the biases behavioral economists perceive in decision-making start in our brains. "Brain studies indicate that organisms seem to be on a hedonic treadmill, quickly habituating to homeostasis," McFadden writes. In other words, perhaps our preference for the status quo isn't just figuratively our heads, but also literally sculpted by the hand of evolution inside of our brains.
  • The popular psychological theory of "hyperbolic discounting" says people don't properly evaluate rewards over time. The theory seeks to explain why many groups -- nappers, procrastinators, Congress -- take rewards now and pain later, over and over again. But neurology suggests that it hardly makes sense to speak of "the brain," in the singular, because it's two very different parts of the brain that process choices for now and later. The choice to delay gratification is mostly processed in the frontal system. But studies show that the choice to do something immediately gratifying is processed in a different system, the limbic system, which is more viscerally connected to our behavior, our "reward pathways," and our feelings of pain and pleasure.
  • the final message is that neither the physiology of pleasure nor the methods we use to make choices are as simple or as single-minded as the classical economists thought. A lot of behavior is consistent with pursuit of self-interest, but in novel or ambiguous decision-making environments there is a good chance that our habits will fail us and inconsistencies in the way we process information will undo us.
  • Our brains seem to operate like committees, assigning some tasks to the limbic system, others to the frontal system. The "switchboard" does not seem to achieve complete, consistent communication between different parts of the brain. Pleasure and pain are experienced in the limbic system, but not on one fixed "utility" or "self-interest" scale. Pleasure and pain have distinct neural pathways, and these pathways adapt quickly to homeostasis, with sensation coming from changes rather than levels
  • Social networks are sources of information, on what products are available, what their features are, and how your friends like them. If the information is accurate, this should help you make better choices. On the other hand, it also makes it easier for you to follow the crowd rather than engaging in the due diligence of collecting and evaluating your own information and playing it against your own preferences
Javier E

Why Baseball Is Obsessed With the Book 'Thinking, Fast and Slow' - The New York Times - 0 views

www.nytimes.com/...inking-fast-and-slow-book.html

baseball cognitive bias cognitive psychology knowledge

shared by Javier E on 24 Feb 21 - No Cached
  • In Teaford’s case, the scouting evaluation was predisposed to a mental shortcut called the representativeness heuristic, which was first defined by the psychologists Daniel Kahneman and Amos Tversky. In such cases, an assessment is heavily influenced by what is believed to be the standard or the ideal.
  • Kahneman, a professor emeritus at Princeton University and a winner of the Nobel Prize in economics in 2002, later wrote “Thinking, Fast and Slow,” a book that has become essential among many of baseball’s front offices and coaching staffs.
  • “Pretty much wherever I go, I’m bothering people, ‘Have you read this?’” said Mejdal, now an assistant general manager with the Baltimore Orioles.
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  • There aren’t many explicit references to baseball in “Thinking, Fast and Slow,” yet many executives swear by it
  • “From coaches to front office people, some get back to me and say this has changed their life. They never look at decisions the same way.
  • A few, though, swear by it. Andrew Friedman, the president of baseball operations for the Dodgers, recently cited the book as having “a real profound impact,” and said he reflects back on it when evaluating organizational processes. Keith Law, a former executive for the Toronto Blue Jays, wrote the book “Inside Game” — an examination of bias and decision-making in baseball — that was inspired by “Thinking, Fast and Slow.”
  • “As the decision tree in baseball has changed over time, this helps all of us better understand why it needed to change,” Mozeliak wrote in an email. He said that was especially true when “working in a business that many decisions are based on what we see, what we remember, and what is intuitive to our thinking.”
  • The central thesis of Kahneman’s book is the interplay between each mind’s System 1 and System 2, which he described as a “psychodrama with two characters.”
  • System 1 is a person’s instinctual response — one that can be enhanced by expertise but is automatic and rapid. It seeks coherence and will apply relevant memories to explain events.
  • System 2, meanwhile, is invoked for more complex, thoughtful reasoning — it is characterized by slower, more rational analysis but is prone to laziness and fatigue.
  • Kahneman wrote that when System 2 is overloaded, System 1 could make an impulse decision, often at the expense of self-control
  • No area of baseball is more susceptible to bias than scouting, in which organizations aggregate information from disparate sources:
  • “The independent opinion aspect is critical to avoid the groupthink and be aware of momentum,”
  • Matt Blood, the director of player development for the Orioles, first read “Thinking, Fast and Slow” as a Cardinals area scout nine years ago and said that he still consults it regularly. He collaborated with a Cardinals analyst to develop his own scouting algorithm as a tripwire to mitigate bias
  • Mejdal himself fell victim to the trap of the representativeness heuristic when he started with the Cardinals in 2005
Javier E

The Brain Has a Special Kind of Memory for Past Infections - Scientific American - 0 views

www.scientificamerican.com/...-of-memory-for-past-infections

infection memory brain science research

shared by Javier E on 09 Nov 21 - No Cached
  • immune cells from the periphery routinely patrol the central nervous system and support its function. In a new study, researchers showed for the first time that—just as the brain remembers people, places, smells, and so on—it also stores what they call “memory traces” of the body’s past infections. Reactivating the same brain cells that encode this information is enough to swiftly summon the peripheral immune system to defend at-risk tissues.
  • It is clear the peripheral immune system is capable of retaining information about past infections to fight off future ones—otherwise, vaccines would not work. But Asya Rolls, a neuroimmunologist at Technion–Israel Institute of Technology and the paper’s senior author, says the study expands this concept of classical immunologic memory. Initially, she was taken aback that the brain could store traces of immune activity and use them to trigger such a precise response. “I was amazed,” she says.
  • After the infection and immune response dissipated, the researchers injected the mice with a drug that artificially reactivated those same groups of brain cells. They were stunned by what they saw: upon reactivation, the insular cortex directed the immune system to mount a targeted response in the gut at the site of the original inflammation—even though, by that time, there was no infection, tissue damage or pathogen-initiated local inflammation to be found. The brain had retained some sort of memory of the infection and was prepared to reinitiate the fight.
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  • The new study provides “unassailable” evidence that the central nervous system can control the peripheral immune system, Tracey says. “It’s an incredibly important contribution to the fields of neuroscience and immunology.”
  • Just as researchers have traced sensory and motor processing to specific brain regions, Tracey suspects that a similar neurological “map” of immunologic information also exists. This new study, he says, is the first direct evidence of that map. “It’s going to be really exciting to see what comes next,” he adds.
Javier E

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

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

twitter whistleblower security social media technology

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

For Chat-Based AI, We Are All Once Again Tech Companies' Guinea Pigs - WSJ - 0 views

www.wsj.com/...-are-tech-guinea-pigs-647d827b

ai chatbot generative experiment evaluation justification debate

shared by Javier E on 27 Feb 23 - No Cached
  • The companies touting new chat-based artificial-intelligence systems are running a massive experiment—and we are the test subjects.
  • In this experiment, Microsoft, MSFT -2.18% OpenAI and others are rolling out on the internet an alien intelligence that no one really understands, which has been granted the ability to influence our assessment of what’s true in the world. 
  • Companies have been cautious in the past about unleashing this technology on the world. In 2019, OpenAI decided not to release an earlier version of the underlying model that powers both ChatGPT and the new Bing because the company’s leaders deemed it too dangerous to do so, they said at the time.
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  • Microsoft leaders felt “enormous urgency” for it to be the company to bring this technology to market, because others around the world are working on similar tech but might not have the resources or inclination to build it as responsibly, says Sarah Bird, a leader on Microsoft’s responsible AI team.
  • One common starting point for such models is what is essentially a download or “scrape” of most of the internet. In the past, these language models were used to try to understand text, but the new generation of them, part of the revolution in “generative” AI, uses those same models to create texts by trying to guess, one word at a time, the most likely word to come next in any given sequence.
  • Wide-scale testing gives Microsoft and OpenAI a big competitive edge by enabling them to gather huge amounts of data about how people actually use such chatbots. Both the prompts users input into their systems, and the results their AIs spit out, can then be fed back into a complicated system—which includes human content moderators paid by the companies—to improve it.
  • , being first to market with a chat-based AI gives these companies a huge initial lead over companies that have been slower to release their own chat-based AIs, such as Google.
  • rarely has an experiment like Microsoft and OpenAI’s been rolled out so quickly, and at such a broad scale.
  • Among those who build and study these kinds of AIs, Mr. Altman’s case for experimenting on the global public has inspired responses ranging from raised eyebrows to condemnation.
  • The fact that we’re all guinea pigs in this experiment doesn’t mean it shouldn’t be conducted, says Nathan Lambert, a research scientist at the AI startup Huggingface.
  • “I would kind of be happier with Microsoft doing this experiment than a startup, because Microsoft will at least address these issues when the press cycle gets really bad,” says Dr. Lambert. “I think there are going to be a lot of harms from this kind of AI, and it’s better people know they are coming,” he adds.
  • Others, particularly those who study and advocate for the concept of “ethical AI” or “responsible AI,” argue that the global experiment Microsoft and OpenAI are conducting is downright dangerous
  • Celeste Kidd, a professor of psychology at University of California, Berkeley, studies how people acquire knowledge
  • Her research has shown that people learning about new things have a narrow window in which they form a lasting opinion. Seeing misinformation during this critical initial period of exposure to a new concept—such as the kind of misinformation that chat-based AIs can confidently dispense—can do lasting harm, she says.
  • Dr. Kidd likens OpenAI’s experimentation with AI to exposing the public to possibly dangerous chemicals. “Imagine you put something carcinogenic in the drinking water and you were like, ‘We’ll see if it’s carcinogenic.’ After, you can’t take it back—people have cancer now,”
  • Part of the challenge with AI chatbots is that they can sometimes simply make things up. Numerous examples of this tendency have been documented by users of both ChatGPT and OpenA
  • These models also tend to be riddled with biases that may not be immediately apparent to users. For example, they can express opinions gleaned from the internet as if they were verified facts
  • When millions are exposed to these biases across billions of interactions, this AI has the potential to refashion humanity’s views, at a global scale, says Dr. Kidd.
  • OpenAI has talked publicly about the problems with these systems, and how it is trying to address them. In a recent blog post, the company said that in the future, users might be able to select AIs whose “values” align with their own.
  • “We believe that AI should be a useful tool for individual people, and thus customizable by each user up to limits defined by society,” the post said.
  • Eliminating made-up information and bias from chat-based search engines is impossible given the current state of the technology, says Mark Riedl, a professor at Georgia Institute of Technology who studies artificial intelligence
  • He believes the release of these technologies to the public by Microsoft and OpenAI is premature. “We are putting out products that are still being actively researched at this moment,” he adds. 
  • in other areas of human endeavor—from new drugs and new modes of transportation to advertising and broadcast media—we have standards for what can and cannot be unleashed on the public. No such standards exist for AI, says Dr. Riedl.
  • To modify these AIs so that they produce outputs that humans find both useful and not-offensive, engineers often use a process called “reinforcement learning through human feedback.
  • that’s a fancy way of saying that humans provide input to the raw AI algorithm, often by simply saying which of its potential responses to a query are better—and also which are not acceptable at all.
  • Microsoft’s and OpenAI’s globe-spanning experiments on millions of people are yielding a fire hose of data for both companies. User-entered prompts and the AI-generated results are fed back through a network of paid human AI trainers to further fine-tune the models,
  • Huggingface’s Dr. Lambert says that any company, including his own, that doesn’t have this river of real-world usage data helping it improve its AI is at a huge disadvantage
  • In chatbots, in some autonomous-driving systems, in the unaccountable AIs that decide what we see on social media, and now, in the latest applications of AI, again and again we are the guinea pigs on which tech companies are testing new technology.
  • It may be the case that there is no other way to roll out this latest iteration of AI—which is already showing promise in some areas—at scale. But we should always be asking, at times like these: At what price?
Javier E

GPT-4 has arrived. It will blow ChatGPT out of the water. - The Washington Post - 0 views

www.washingtonpost.com/...it-will-blow-chatgpt-out-water

AI chatbot evolution assessment

shared by Javier E on 15 Mar 23 - No Cached
  • GPT-4, in contrast, is a state-of-the-art system capable of creating not just words but describing images in response to a person’s simple written commands.
  • When shown a photo of a boxing glove hanging over a wooden seesaw with a ball on one side, for instance, a person can ask what will happen if the glove drops, and GPT-4 will respond that it would hit the seesaw and cause the ball to fly up.
  • an AI program, known as a large language model, that early testers had claimed was remarkably advanced in its ability to reason and learn new things
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  • hose promises have also fueled anxiety over how people will be able to compete for jobs outsourced to eerily refined machines or trust the accuracy of what they see online.
  • Officials with the San Francisco lab said GPT-4’s “multimodal” training across text and images would allow it to escape the chat box and more fully emulate a world of color and imagery, surpassing ChatGPT in its “advanced reasoning capabilities.”
  • A person could upload an image and GPT-4 could caption it for them, describing the objects and scene.
  • AI language models often confidently offer wrong answers because they are designed to spit out cogent phrases, not actual facts. And because they have been trained on internet text and imagery, they have also learned to emulate human biases of race, gender, religion and class.
  • GPT-4 still makes many of the errors of previous versions, including “hallucinating” nonsense, perpetuating social biases and offering bad advice. It also lacks knowledge of events that happened after about September 2021, when its training data was finalized, and “does not learn from its experience,” limiting people’s ability to teach it new things.
  • Microsoft has invested billions of dollars in OpenAI in the hope its technology will become a secret weapon for its workplace software, search engine and other online ambitions. It has marketed the technology as a super-efficient companion that can handle mindless work and free people for creative pursuits, helping one software developer to do the work of an entire team or allowing a mom-and-pop shop to design a professional advertising campaign without outside help.
  • it could lead to business models and creative ventures no one can predict.
  • sparked criticism that the companies are rushing to exploit an untested, unregulated and unpredictable technology that could deceive people, undermine artists’ work and lead to real-world harm.
  • the company held back the feature to better understand potential risks. As one example, she said, the model might be able to look at an image of a big group of people and offer up known information about them, including their identities — a possible facial recognition use case that could be used for mass surveillance.
  • OpenAI researchers wrote, “As GPT-4 and AI systems like it are adopted more widely,” they “will have even greater potential to reinforce entire ideologies, worldviews, truths and untruths, and to cement them or lock them in.”
  • “We can agree as a society broadly on some harms that a model should not contribute to,” such as building a nuclear bomb or generating child sexual abuse material, she said. “But many harms are nuanced and primarily affect marginalized groups,” she added, and those harmful biases, especially across other languages, “cannot be a secondary consideration in performance.”
  • OpenAI said its new model would be able to handle more than 25,000 words of text, a leap forward that could facilitate longer conversations and allow for the searching and analysis of long documents.
  • OpenAI developers said GPT-4 was more likely to provide factual responses and less likely to refuse harmless requests
  • Duolingo, the language learning app, has already used GPT-4 to introduce new features, such as an AI conversation partner and a tool that tells users why an answer was incorrect.
  • The company did not share evaluations around bias that have become increasingly common after pressure from AI ethicists.
  • GPT-4 will have competition in the growing field of multisensory AI. DeepMind, an AI firm owned by Google’s parent company Alphabet, last year released a “generalist” model named Gato that can describe images and play video games. And Google this month released a multimodal system, PaLM-E, that folded AI vision and language expertise into a one-armed robot on wheels: If someone told it to go fetch some chips, for instance, it could comprehend the request, wheel over to a drawer and choose the right bag.
  • The systems, though — as critics and the AI researchers are quick to point out — are merely repeating patterns and associations found in their training data without a clear understanding of what it’s saying or when it’s wrong.
  • GPT-4, the fourth “generative pre-trained transformer” since OpenAI’s first release in 2018, relies on a breakthrough neural-network technique in 2017 known as the transformer that rapidly advanced how AI systems can analyze patterns in human speech and imagery.
  • The systems are “pre-trained” by analyzing trillions of words and images taken from across the internet: news articles, restaurant reviews and message-board arguments; memes, family photos and works of art.
  • Giant supercomputer clusters of graphics processing chips are mapped out their statistical patterns — learning which words tended to follow each other in phrases, for instance — so that the AI can mimic those patterns, automatically crafting long passages of text or detailed images, one word or pixel at a time.
  • In 2019, the company refused to publicly release GPT-2, saying it was so good they were concerned about the “malicious applications” of its use, from automated spam avalanches to mass impersonation and disinformation campaigns.
  • Altman has also marketed OpenAI’s vision with the aura of science fiction come to life. In a blog post last month, he said the company was planning for ways to ensure that “all of humanity” benefits from “artificial general intelligence,” or AGI — an industry term for the still-fantastical idea of an AI superintelligence that is generally as smart as, or smarter than, the humans themselves.
sissij

The Danger of Only Seeing What You Already Believe | Big Think - 0 views

bigthink.com/...eeing-what-you-already-believe

research psychology bias social media

shared by sissij on 24 Mar 17 - No Cached
  • the blank canvas, an empty page, the unfilled columns in ProTools awaiting sonic imagination. Once completed, another journey begins. The distance between zero and popularity is complex. 
  • The creator is always in a relationship with their audience.
  • Humans are neopholic, by which Thompson means we are “curious to discover new things” as well as neophobic, “afraid of anything that’s too new.” 
  • ...2 more annotations...
  • For example, my dopamine receptors tingled when Thompson mentioned Joseph Campbell and Jeff Buckley, given that they’re both huge inspirations to me.
  • Thompson notes that as we age our explicit memory system wanes. We become more susceptible to confuse a statement that “feels right” with one that is correct.
  • sissij on 24 Mar 17
     
    I found this article very interesting as it discussed the logic fallacy and confirmation bias in humane mind.The danger of only seeing what they already believe is especially obvious in the era of Internet. More and more social medias use filter system to give viewers what they like to see based on their viewing history. Although this filter system can satisfy the viewers, viewers get a limited range of information. I think it limits the mindset of the viewers. --Sissi (3/23/2017)
grayton downing

Newborn Immune Systems Suppressed | The Scientist Magazine® - 0 views

www.the-scientist.com/?articles.view/articleNo/38187/title/Newborn-Immune-Systems-Suppressed/

newborn immune systems science research

shared by grayton downing on 13 Nov 13 - No Cached
  • sterile world of the womb, at birth babies are thrust into an environment full of bacteria, viruses, and parasites. They are very vulnerable to these infections for their first months of life—a trait that has long been blamed on their immature immune systems.
  • “This more intricate regulation of immune responses makes more sense than immaturity,” said Sing Sing Way, who led the study, “because it allows a protective response to be mounted if needed.” This may explain why newborn immune responses, though generally weak, also vary wildly between different babies and across different studies.
  • njecting 6-day-old mice with splenocytes (a type of white blood cell) from adults. Newborn mice are normally 1,000 times more suspectible to bacterial infections than adults, but despite receiving working immune cells, they became no less vulnerable.
  • ...3 more annotations...
  • Way added that there might be other reasons why newborns should carry immunosuppressive cells
  • Baby formulas contain small amounts of arginine. Sidney Morris, a biochemist from the University of Pittsburgh, said that it may be important to avoid fortifying them with extra arginine, lest it swamps the arginase activity of CD71+ cells, releases the immune system, and causes problems for the developing infants’ guts.
  • “Whether the precise mechanism of immunosuppression is the same or different in each of these circumstances remains to be determined,” he said.
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