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During this time, the BrainEx system not only preserved brain cell structure and reduced cell death, but also restored some cellular activity.

For example, although scientists are a long way from being able to restore brain function in people with severe brain injuries, if some restoration of brain activity is possible, "then we would have to change our definition of brain death," Singhal told Live Science.

The work also could stimulate research on ways to promote brain recovery after loss of blood flow to the brain, such as during a heart attack.

They later claimed that Merritte was neurologically impaired, which if true would only add to the unethical nature of the original research.

In the late 1900s, researchers discovered that mitochondria were free-living bacteria at some point in the past. Somehow they were drawn inside another cell, providing new fuel for their host. In 2015, Thijs Ettema of Uppsala University in Sweden and his colleagues discovered fragments of DNA in sediments retrieved from the Arctic Ocean. The fragments contained genes from a species of archaea that seemed to be closely related to eukaryotes.Dr. Ettema and his colleagues named them Asgard archaea. (Asgard is the home of the Norse gods.) DNA from these mystery microbes turned up in a river in North Carolina, hot springs in New Zealand and other places around the world.

Masaru K. Nobu, a microbiologist at the National Institute of Advanced Industrial Science and Technology in Tsukuba, Japan, and his colleagues managed to grow these organisms in a lab. The effort took more than a decade.The microbes, which are adapted to life in the cold seafloor, have a slow-motion existence. Prometheoarchaeum can take as long as 25 days to divide. By contrast, E. coli divides once every 20 minutes.

In the lab, the researchers mimicked the conditions in the seafloor by putting the sediment in a chamber without any oxygen. They pumped in methane and extracted deadly waste gases that might kill the resident microbes.The mud contained many kinds of microbes. But by 2015, the researchers had isolated an intriguing new species of archaea. And when Dr. Ettema and colleagues announced the discovery of Asgard archaea DNA, the Japanese researchers were shocked. Their new, living microbe belonged to that group.The researchers then undertook more painstaking research to understand the new species and link it to the evolution of eukaryotes.The researchers named the microbe Prometheoarchaeum syntrophicum, in honor of Prometheus, the Greek god who gave humans fire — after fashioning them from clay.

This finding suggests that the proteins that eukaryotes used to build complex cells started out doing other things, and only later were assigned new jobs.Dr. Nobu and his colleagues are now trying to figure out what those original jobs were. It’s possible, he said, that Prometheoarchaeum creates its tentacles with genes later used by eukaryotes to build cellular skeletons.

Before the discovery of Prometheoarchaeum, some researchers suspected that the ancestors of eukaryotes lived as predators, swallowing up smaller microbes. They might have engulfed the first mitochondria this way.

Instead of hunting prey, Prometheoarchaeum seems to make its living by slurping up fragments of proteins floating by. Its partners feed on its waste. They, in turn, provide Prometheoarchaeum with vitamins and other essential compounds.

It isn’t clear how the American public-school system will survive the COVID years. Teachers, whose relative pay and status have been in decline for decades, are fleeing the field. In 2021, buckling under the stresses of the pandemic, nearly 1 million people quit jobs in public education, a 40 percent increase over the previous year.

These kids, and the investments that come with them, may never return—the beginning of a cycle of attrition that could continue long after the pandemic ends and leave public schools even more underfunded and dilapidated than before. “It’s an open question whether the public-school system will recover,” Steiner said. “That is a real concern for democratic education.”

The high-profile failings of public schools during the pandemic have become a political problem for Democrats, because of their association with unions, prolonged closures, and the pedagogy of social justice, which can become a form of indoctrination.

The party that stands for strong government services in the name of egalitarian principles supported the closing of schools far longer than either the science or the welfare of children justified, and it has been woefully slow to acknowledge how much this damaged the life chances of some of America’s most disadvantaged students.

Public education is too important to be left to politicians and ideologues. Public schools still serve about 90 percent of children across red and blue America.

Since the common-school movement in the early 19th century, the public school has had an exalted purpose in this country. It’s our core civic institution—not just because, ideally, it brings children of all backgrounds together in a classroom, but because it prepares them for the demands and privileges of democratic citizenship. Or at least, it needs to.

What is school for? This is the kind of foundational question that arises when a crisis shakes the public’s faith in an essential institution. “The original thinkers about public education were concerned almost to a point of paranoia about creating self-governing citizens,”

“Horace Mann went to his grave having never once uttered the phrase college- and career-ready. We’ve become more accustomed to thinking about the private ends of education. We’ve completely lost the habit of thinking about education as citizen-making.”

School can’t just be an economic sorting system. One reason we have a stake in the education of other people’s children is that they will grow up to be citizens.

Public education is meant not to mirror the unexamined values of a particular family or community, but to expose children to ways that other people, some of them long dead, think.

If the answer were simply to push more and more kids into college, the United States would be entering its democratic prime

So the question isn’t just how much education, but what kind. Is it quaint, or utopian, to talk about teaching our children to be capable of governing themselves?

The COVID era, with Donald Trump out of office but still in power and with battles over mask mandates and critical race theory convulsing Twitter and school-board meetings, shows how badly Americans are able to think about our collective problems—let alone read, listen, empathize, debate, reconsider, and persuade in the search for solutions.

democratic citizenship can, at least in part, be learned.

The history warriors build their metaphysics of national good or evil on a foundation of ignorance. In a 2019 survey, only 40 percent of Americans were able to pass the test that all applicants for U.S. citizenship must take, which asks questions like “Who did the United States fight in World War II?” and “We elect a President for how many years?” The only state in which a majority passed was Vermont.

he orthodoxies currently fighting for our children’s souls turn the teaching of U.S. history into a static and morally simple quest for some American essence. They proceed from celebration or indictment toward a final judgment—innocent or guilty—and bury either oppression or progress in a subordinate clause. The most depressing thing about this gloomy pedagogy of ideologies in service to fragile psyches is how much knowledge it takes away from students who already have so little

A central goal for history, social-studies, and civics instruction should be to give students something more solid than spoon-fed maxims—to help them engage with the past on its own terms, not use it as a weapon in the latest front of the culture wars.

Releasing them to do “research” in the vast ocean of the internet without maps and compasses, as often happens, guarantees that they will drown before they arrive anywhere.

The truth requires a grounding in historical facts, but facts are quickly forgotten without meaning and context

The goal isn’t just to teach students the origins of the Civil War, but to give them the ability to read closely, think critically, evaluate sources, corroborate accounts, and back up their claims with evidence from original documents.

This kind of instruction, which requires teachers to distinguish between exposure and indoctrination, isn’t easy; it asks them to be more sophisticated professionals than their shabby conditions and pay (median salary: $62,000, less than accountants and transit police) suggest we are willing to support.

To do that, we’ll need to help kids restore at least part of their crushed attention spans.

staring at a screen for hours is a heavy depressant, especially for teenagers.

we’ll look back on the amount of time we let our children spend online with the same horror that we now feel about earlier generations of adults who hooked their kids on smoking.

“It’s not a choice between tech or no tech,” Bill Tally, a researcher with the Education Development Center, told me. “The question is what tech infrastructure best enables the things we care about,” such as deep engagement with instructional materials, teachers, and other students.

The pandemic should have forced us to reassess what really matters in public school; instead, it’s a crisis that we’ve just about wasted.

Like learning to read as historians, learning to sift through the tidal flood of memes for useful, reliable information can emancipate children who have been heedlessly hooked on screens by the adults in their lives

Finally, let’s give children a chance to read books—good books. It’s a strange feature of all the recent pedagogical innovations that they’ve resulted in the gradual disappearance of literature from many classrooms.

The best way to interest young people in literature is to have them read good literature, and not just books that focus with grim piety on the contemporary social and psychological problems of teenagers.

We sell them insultingly short in thinking that they won’t read unless the subject is themselves. Mirrors are ultimately isolating; young readers also need windows, even if the view is unfamiliar, even if it’s disturbing

connection through language to universal human experience and thought is the reward of great literature, a source of empathy and wisdom.

The culture wars, with their atmosphere of resentment, fear, and petty faultfinding, are hostile to the writing and reading of literature.

W. E. B. Du Bois wrote: “Nations reel and stagger on their way; they make hideous mistakes; they commit frightful wrongs; they do great and beautiful things. And shall we not best guide humanity by telling the truth about all this, so far as the truth is ascertainable?”

The classroom has become a half-abandoned battlefield, where grown-ups who claim to be protecting students from the virus, from books, from ideologies and counter-ideologies end up using children to protect themselves and their own entrenched camps.

American democracy can’t afford another generation of adults who don’t know how to talk and listen and think. We owe our COVID-scarred children the means to free themselves from the failures of the past and the present.

Students are leaving as well. Since 2020, nearly 1.5 million children have been removed from public schools to attend private or charter schools or be homeschooled.

“COVID has encouraged poor parents to question the quality of public education. We are seeing diminished numbers of children in our public schools, particularly our urban public schools.” In New York, more than 80,000 children have disappeared from city schools; in Los Angeles, more than 26,000; in Chicago, more than 24,000.

That the use of standard algorithms isn’t merely mechanical is not by itself a reason to teach them. It is important to teach them because, as we already noted, they are also the most elegant and powerful methods for specific operations. This means that they are our best representations of connections among mathematical concepts. Math instruction that does not teach both that these algorithms work and why they do is denying students insight into the very discipline it is supposed to be about.

There is a moral here for progressive education that reaches beyond the case of math. Even if we sympathize with progressivists in wanting schools to foster independence of mind, we shouldn’t assume that it is obvious how best to do this. Original thought ranges over many different domains, and it imposes divergent demands as it does so. Just as there is good reason to believe that in biology and history such thought requires significant factual knowledge, there is good reason to believe that in mathematics it requires understanding of and facility with the standard algorithms.

there is also good reason to believe that when we examine further areas of discourse we will come across yet further complexities. The upshot is that it would be naïve to assume that we can somehow promote original thinking in specific areas simply by calling for subject-related creative reasoning

Barrett is a professor of psychology at Northeastern

her research has led her to conclude that each of us constructs them in our own individual ways, from a diversity of sources: our internal sensations, our reactions to the environments we live in, our ever-evolving bodies of experience and learning, our cultures.

if Barrett is correct, we’ll need to rethink how we interpret mental illness, how we understand the mind and self, and even what psychology as a whole should become in the 21st century.

The problem was the options that Ekman had given his subjects when asking them to identify the emotions shown on the faces they were presented with. Those options, Barrett discovered, had limited the ways in which people allowed themselves to think. Barrett explained the problem to me this way: “I can break that experiment really easily, just by removing the words. I can just show you a face and ask how this person feels. Or I can show you two faces, two scowling faces, and I can say, ‘Do these people feel the same thing?’ And agreement drops into the toilet.”

Just as that first picture of the bee actually wasn’t a picture of a bee for me until I taught myself that it was, my emotions aren’t actually emotions until I’ve taught myself to think of them that way. Without that, I have only a meaningless mishmash of information about what I’m feeling.

emotion isn’t a simple reflex or a bodily state that’s hard-wired into our DNA, and it’s certainly not universally expressed. It’s a contingent act of perception that makes sense of the information coming in from the world around you, how your body is feeling in the moment, and everything you’ve ever been taught to understand as emotion. Culture to culture, person to person even, it’s never quite the same. What’s felt as sadness in one person might as easily be felt as weariness in another, or frustration in someone else.

The brain, it turns out, doesn’t consciously process every single piece of information that comes its way. Think of how impossibly distracting the regular act of blinking would be if it did. Instead, it pays attention to what you need to pay attention to, then raids your memory stores to fill in the blanks.

In many quarters, Barrett was angrily attacked for her ideas, and she’s been the subject of criticism ever since. “I think Lisa does a disservice to the actual empirical progress that we’re making,” says Dacher Keltner, a Berkeley psychologist

Keltner told me that he himself has coded thousands of facial expressions using Ekman’s system, and the results are strikingly consistent: Certain face-emotion combinations recur regularly, and others never occur. “That tells me, ‘Wow, this approach to distinct emotions has real power,’” he says.

Ekman reached the peak of his fame in the years following 2001. That’s the year the American Psychological Association named him one of the most influential psychologists of the 20th century. The next year, Malcolm Gladwell wrote an article about him in the New Yorker, and in 2003 he began working pro bono for the TSA. A year later, riding the updraft of success, he left his university post and started the Paul Ekman Group,

a small research team to visit the isolated Himba tribe in Namibia, in southern Africa. The plan was this: The team, led by Maria Gendron, would do a study similar to Ekman’s original cross-cultural one, but without providing any of the special words or context-heavy stories that Ekman had used to guide his subjects’ answers. Barrett’s researchers would simply hand a jumbled pile of different expressions (happy, sad, fearful, angry, disgusted, and neutral) to their subjects, and would ask them to sort them into six piles. If emotional expressions are indeed universal, they reasoned, then the Himba would put all low-browed, tight-lipped expressions into an anger pile, all wrinkled-nose faces into a disgust pile, and so on.

It didn’t happen that way. The Himba sorted some of the faces in ways that aligned with Ekman’s theory: smiling faces went into one pile, wide-eyed fearful faces went into another, and affectless faces went mostly into a third. But in the other three piles, the Himba mixed up angry scowls, disgusted grimaces, and sad frowns. Without any suggestive context, of the kind that Ekman had originally provided, they simply didn’t recognize the differences that leap out so naturally to Westerners.

“What we’re trying to do,” she told me, “is to just get people to pay attention to the fact that there’s a mountain of evidence that does not support the idea that facial expressions are universally recognized as emotional expressions.” That’s the crucial point, of course, because if we acknowledge that, then the entire edifice that Paul Ekman and others have been constructing for the past half-century comes tumbling down. And all sorts of things that we take for granted today—how we understand ourselves and our relationships with others, how we practice psychology

Barrett’s theory is still only in its infancy. But other researchers are beginning to take up her ideas, sometimes in part, sometimes in full, and where the science will take us as it expands is impossible to predict. It’s even possible that Barrett will turn out to be wrong, as she herself acknowledges. “Every scientist has to face that,” she says. Still, if she is right, then perhaps the most important change we’ll need to make is in our own heads. If our emotions are not universal physiological responses but concepts we’ve constructed from various biological signals and stashed memories, then perhaps we can exercise more control over our emotional lives than we’ve assumed.

“Every experience you have now is seeding your experience for the future,” Barrett told me. “Knowing that, would you choose to do what you’re doing now?” She paused a beat and looked me in the eye. “Well? Would you? You are the architect of your own experience.”

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.

A working paper published this summer has caused a stir by proposing that a classic body of research disproving the existence of the hot hand in basketball is flawed by a subtle misperception about randomness. If the analysis is correct, the possibility remains that the hot hand is real.

We mortals can benefit, at least in theory, from islands of predictability — a barely perceptible tilt of a roulette table that makes the ball slightly more likely to land on one side of the wheel than the other

The same is true for the random walk of the stock market. Becoming aware of information before it has propagated worldwide can give a speculator a tiny, temporary edge. Some traders pay a premium to locate their computer servers as close as possible to Lower Manhattan, gaining advantages measured in microseconds.

Taken to extremes, seeing connections that don’t exist can be a symptom of a psychiatric condition called apophenia. In less pathological forms, the brain’s hunger for pattern gives rise to superstitions (astrology, numerology) and is a driving factor in what has been called a replication crisis in science

I know it sounds crazy but when you average the scores together the answer is not 50-50, as most people would expect, but about 40-60 in favor of tails.

There is not, as Guildenstern might imagine, a tear in the fabric of space-time. It remains as true as ever that each flip is independent, with even odds that the coin will land one way or the other. But by concentrating on only some of the data — the flips that follow heads — a gambler falls prey to a selection bias.

basketball is no streakier than a coin toss. For a 50 percent shooter, for example, the odds of making a basket are supposed to be no better after a hit — still 50-50. But in a purely random situation, according to the new analysis, a hit would be expected to be followed by another hit less than half the time. Finding 50 percent would actually be evidence in favor of the hot hand

Dr. Gilovich is withholding judgment. “The larger the sample of data for a given player, the less of an issue this is,” he wrote in an email. “Because our samples were fairly large, I don’t believe this changes the original conclusions about the hot hand. ”

Take a fair coin — one as likely to land on heads as tails — and flip it four times. How often was heads followed by another head?

For all their care to be objective, scientists are as prone as anyone to valuing data that support their hypothesis over those that contradict it. Sometimes this results in experiments that succeed only under very refined conditions, in certain labs with special reagents and performed by a scientist with a hot hand.

We’re all in the same boat. We evolved with this uncanny ability to find patterns. The difficulty lies in separating what really exists from what is only in our minds.

Haidt’s experimentalist critique of Plato misses its mark because he ignores what Plato actually thought in favor of an oversimplification of his “rationalism.” He does something similar in suggesting that Kant’s ethics reflects a personality within the autism spectrum. Likewise, he implausibly suggests that John Rawls can be refuted by surveys showing that people do not share the judgments Rawls thinks we would make in the fictional situation of his “original position.”

Haidt’s own discussion requires him to move beyond empirical studies and in the direction of traditional philosophy.

But the great philosophers — Plato, Aristotle, Hume, Spinoza, Hegel, Nietzsche — describe moral experiences far more carefully and subtly than most of us can, and moreover, they provide historical perspectives that can help offset the limitations of our own limited viewpoint.

Haidt acknowledges that his concern as a psychologist is overwhelmingly descriptive.  But he says almost nothing about how to connect his work with the compelling normative questions of human life.  Engaging with the extensive philosophical discussions of Hume’s distinction between “is” and “ought” could help fill this major gap in Haidt’s account of ethics

I begin by reflecting on Haidt’s effort to refute Plato’s central argument in “The Republic.”  This is where Plato tries to show why a just (morally good) life is superior to an unjust (immoral) life.

Haidt pithily summarizes Socrates’ argument: “Reason must rule the happy person. And if reason rules, then it cares about what is truly good, not just about the appearance of virtue.” He maintains that Socrates goes wrong because he assumes a false view of the role of reason in human life. ”Reason is not fit to rule; it was designed to seek justification, not truth,” where justification means pursuing “socially strategic goals, such as guarding our reputations and convincing other people to support us.”

Haidt supports his claim about the actual role of reason with an array of fascinating psychological experiments cumulatively showing that “Glaucon was right: people care a great deal more about appearance and reputation than about reality,” and use reason accordingly.

Haidt’s psychological studies count against Plato only if we take them as denying any chance of rational control and allowing no alternative to a life dominated by our immediate inclinations — our “gut reactions,” as Haidt puts it. But Haidt makes no such claim, saying only, “we should not expect individuals to produce good, open-minded, truth-seeking reasoning, particularly when self-interest or reputational concerns are in play.”

Nevertheless, he adds, “if you put individuals together in the right way … you can create a group that ends up producing good reasoning as an emergent product of the social system.”

Mark Zuckerberg is 3.17 degrees of separation from all Facebook users.

The typical Facebook user has 155 friends, but only describes 50 of them as friends in real life, according to a 2014 study from the Pew Research Center. Thirty-five percent of people have Facebook friends they've never met in person.

The original "six degrees of separation" experiment required people to know each other fairly well: They had to be on a first-name basis, at a time when society was slightly more formal, in order for the connection to count.

About one-third of the documents eventually reached the stockbroker, after a chain of, on average, six people — the six degrees of separation. It's a small world after all, Milgram concluded.

She found instead that Milgram's conclusions rested on a shaky foundation, and that class and race divided Americans more than his original paper admitted. The majority of Milgram's letters didn't make it to the Boston stockbroker. And further experiments that factored in class and race suggested that making connections across those barriers was even more challenging

While middle- and high-income people were able to find their targets regardless of their household income, low-income people could only connect with other low-income families, Kleinfeld wrote in a 2002 article in the journal Society.

The correct interpretation of Milgram, she argued, was not the optimistic conclusion that we're all only a few degrees of separation away. Instead, it's that there are still barriers that are insurmountable.

But the real divide is between people who are on Facebook and those who aren't on the internet at all. Facebook users make up about 62 percent of American adults but 72 percent of all internet users. Americans without the internet are disproportionately older, rural, and less educated. As Facebook users get closer, they might be becoming ever more isolated.

But Verrilli countered that the federal government retains authority to review on a "case-by-case basis" significant drug trafficking crimes.

Young people, who have no place in this dead-eyed, sanitized landscape, scarcely venture from their bedrooms. Political freedom now means choosing between alternative versions of market fundamentalism.

Even the freedoms we do possess we tend not to exercise. We spend hours every day watching other people doing what we might otherwise be doing: dancing, singing, playing sports, even cooking. We venture outdoors to seek marginally different varieties of stuff we already possess

We entertain the illusion that we have chosen our lives. Why, if this is the case, do our apparent choices differ so little from those of other people? Why do we live and work and travel and eat and dress and entertain ourselves in almost identical fashion? It’s no wonder, when we possess and use it so little, that we make a fetish out of freedom.Continue reading the main story

our survival in the modern economy requires the use of few of the mental and physical capacities we possess. Sometimes it feels like a small and shuffling life. Our humdrum, humiliating lives leave us, I believe, ecologically bored.

Across many rich nations, especially the United States, global competition is causing the abandonment of farming on less fertile land. Rather than trying to tame and hold back the encroaching wilds, I believe we should help to accelerate the process of reclamation, removing redundant roads and fences, helping to re-establish missing species, such as wolves and cougars and bears, building bridges between recovering habitats to create continental-scale wildlife corridors, such as those promoted by the Rewilding Institute.

This rewilding of the land permits, if we choose, a partial rewilding of our own lives. It allows us to step into a world that is not controlled and regulated, to imagine ourselves back into the rawer life from which we came

My main question was what to call this subject, in view of the confusions wrought by its current name and the ancient origin of the word.

The general reaction to my original essay from people not professionally involved in philosophy rather proves my point about the need for linguistic reform. There is precious little understanding of what the subject is really like, but a lot of opinion about its demerits and betrayals of its historical ideals. To be sure, we will not cure such ignorance and hostility — either from the dogmatists of empirical science or the disappointed fringe mystics — by simply relabeling the subject; but we should at least forestall some of the ire that stems from the etymology and popular meaning of the word “philosophy”

She became a science journalist. At first it was a lark, a way to get free press passes to conferences where she and her father could ask questions of the greatest minds in quantum mechanics, string theory and cosmology. But within a short time, as she started getting assignments, journalism became a calling, and an identity.

“If observers create reality, where do the observers come from?” But the great man responded in riddles. “The universe is a self-­excited circuit,” Wheeler said. “The boundary of a boundary is zero.” The unraveling of these mysteries propels the next 400 or so pages.

she has an epiphany — that for something to be real, it must be invariant — she flies home to share it with her father. They discuss her insight over breakfast at a neighborhood haunt, where they make a list on what they will affectionately call “the IHOP napkin.” They list all the possible “ingredients of ultimate reality,” planning to test each item for whether it is “real,” that is whether it is invariant and can exist in the absence of an observer.

their readings and interviews reveal that each item in turn is observer-dependent. Space? Observer-dependent, and therefore not real. Gravity, electromagnetism, angular momentum? No, no, and no. In the end, every putative “ingredient of ultimate reality” is eliminated, including one they hadn’t even bothered to put on the list because it seemed weird to: reality itself

What remained was an unsettling and essential insight: that “physics isn’t the machinery behind the workings of the world; physics is the machinery behind the illusion that there is a world.”

In the proposal, she clarifies how cosmology and quantum mechanics have evolved as scientists come to grips with the fact that things they had taken to be real — quantum particles, space-time, gravity, dimension — turn out to be ­observer-dependent.

appeals to “a Christian audience as well as a scientific audience,"

“For the scientific community, it presents something that they can take to the laboratory and test for themselves.

Those with a “biased” mind might find the book “controversial," he added

In the process, fit has become a catchall used to justify hiring people who are similar to decision makers and rejecting people who are not.

The concept of fit first gained traction in the 1980s. The original idea was that if companies hired individuals whose personalities and values — and not just their skills — meshed with an organization’s strategy, workers would feel more attached to their jobs, work harder and stay longer.

in many organizations, fit has gone rogue. I saw this firsthand while researching the hiring practices of the country’s top investment banks, management consultancies and law firms. I interviewed 120 decision makers and spent nine months observing

While résumés (and connections) influenced which applicants made it into the interview room, interviewers’ perceptions of fit strongly shaped who walked out with job offers.

Crucially, though, for these gatekeepers, fit was not about a match with organizational values. It was about personal fit. In these time- and team-intensive jobs, professionals at all levels of seniority reported wanting to hire people with whom they enjoyed hanging out and could foresee developing close relationships with

To judge fit, interviewers commonly relied on chemistry. “

Many used the “airport test.” As a managing director at an investment bank put it, “Would I want to be stuck in an airport in Minneapolis in a snowstorm with them?”

interviewers were primarily interested in new hires whose hobbies, hometowns and biographies matched their own. Bonding over rowing college crew, getting certified in scuba, sipping single-malt Scotches in the Highlands or dining at Michelin-starred restaurants was evidence of fit; sharing a love of teamwork or a passion for pleasing clients was not

it has become a common feature of American corporate culture. Employers routinely ask job applicants about their hobbies and what they like to do for fun, while a complementary self-help industry informs white-collar job seekers that chemistry, not qualifications, will win them an offer.

Selection based on personal fit can keep demographic and cultural diversity low

In the elite firms I studied, the types of shared experiences associated with fit typically required large investments of time and money.

Class-biased definitions of fit are one reason investment banks, management consulting firms and law firms are dominated by people from the highest socioeconomic backgrounds

Also, whether the industry is finance, high-tech or fashion, a good fit in most American corporations still tends to be stereotypically masculine.

Perhaps most important, it is easy to mistake rapport for skill. Just as they erroneously believe that they can accurately tell when someone is lying, people tend to be overly confident in their ability to spot talent. Unstructured interviews, which are the most popular hiring tools for American managers and the primary way they judge fit, are notoriously poor predictors of job performance.

Organizations that use cultural fit for competitive advantage tend to favor concrete tools like surveys and structured interviews that systematically test behaviors associated with increased performance and employee retention.

For managers who want to use cultural fit in a more productive way, I have several suggestions.

First, communicate a clear and consistent idea of what the organization’s culture is (and is not) to potential employees. Second, make sure the definition of cultural fit is closely aligned with business goals. Ideally, fit should be based on data-driven analysis of what types of values, traits and behaviors actually predict on-the-job success. Third, create formal procedures like checklists for measuring fit, so that assessment is not left up to the eyes (and extracurriculars) of the beholder.

But cultural fit has become a new form of discrimination that keeps demographic and cultural diversity down