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The study, published in Science, began with two Pavlovian-style conditioning exercises designed to counter race and gender biases.

However, they caution that the use of the technique in future would need strict ethical guidelines. “Sleep is a state in which the individual is without wilful consciousness and therefore vulnerable to suggestion,” they add.

Scientists believe the technique works because we consolidate memories by replaying them during sleep and transferring the information from the brain’s temporary storage to long-term memory. Hearing the distinctive sound would trigger the memory to be replayed repeatedly, the scientists said, enhancing the learning process.

“We call this Targeted Memory Reactivation, because the sounds played during sleep could produce relatively better memory for information cued during sleep compared to information not cued during sleep.

the human ability to remember colors over any period of time, or even from room to room, is extremely poor.

“Based on memory alone, we can probably reliably identify tens of colors, with some people perhaps able to study hard and get up to a hundred or so,

Almost everyone can distinguish tones when they are compared in close succession, he said, but only a very small percentage of people have what is called perfect pitch or absolute pitch: the ability to recall and identify tones after a considerable period of time, without a reference tone for comparison.

we don’t speak of anyone as having perfect hue.”

“we can identify the tones in a chord, but we cannot identify the wavelength makeup of a color.”

Pythagoras believed that “all things are number”: things come into existence when mathematical order is imposed on the formless stuff of the universe. He is believed to have come to this idea after discovering the importance of mathematics in music.

Musical order and beauty are similarly the result of order and harmony being carved out of cacophonous noise. Pythagoras also originated the idea of the heavenly ‘music of the spheres’, inaudible to us, made by the movement of the planets around the earth.

In his La Monadologie (Monadology, 1714), Gottfried Leibniz explained our response to art through subconscious perceptions (“les petites sensations”) of “the secret arithmetic” of intervals and other relationships in music and painting.

Immanuel Kant wrote a book on aesthetics, The Critique of Judgment (1790), in which he described aesthetic qualities as those which give us “disinterested pleasure”. They do this through their beauty, which Kant, as a classically-inclined thinker, saw in their harmony of form; or through their sublimity – meaning a perceived grandeur or power that does not threaten us.

Friedrich Schelling was the first of these transcendental idealists, and the first philosopher who thought that instrumental (as distinct from vocal) music was the purest and most disembodied of the arts, and enabled us not only to glimpse the Absolute – a word he coined, although Kant had talked about absolute truth being found in the Ding an Sich [‘the thing-in-itself’] – but during that experience, to see ourselves as an integral part of it. This idea would be taken much further still by:

it is as if two magic coins, flipped at different corners of the cosmos, always came up heads or tails together. (The spooky action takes place only in the context of simultaneous measurement. The particles share states, but they don’t send signals.)

fashion, temperament, zeitgeist, and sheer tenacity affected the debate, along with evidence and argument.

The certainty that spooky action at a distance takes place, Musser says, challenges the very notion of “locality,” our intuitive sense that some stuff happens only here, and some stuff over there. What’s happening isn’t really spooky action at a distance; it’s spooky distance, revealed through an action.

Why, then, did Einstein’s question get excluded for so long from reputable theoretical physics? The reasons, unfolding through generations of physicists, have several notable social aspects,

What started out as a reductio ad absurdum became proof that the cosmos is in certain ways absurd. What began as a bug became a feature and is now a fact.

“If poetry is emotion recollected in tranquility, then science is tranquility recollected in emotion.” The seemingly neutral order of the natural world becomes the sounding board for every passionate feeling the physicist possesses.

Musser explains that the big issue was settled mainly by being pushed aside. Generational imperatives trumped evidentiary ones. The things that made Einstein the lovable genius of popular imagination were also the things that made him an easy object of condescension. The hot younger theorists patronized him,

There was never a decisive debate, never a hallowed crucial experiment, never even a winning argument to settle the case, with one physicist admitting, “Most physicists (including me) accept that Bohr won the debate, although like most physicists I am hard pressed to put into words just how it was done.”

Arguing about non-locality went out of fashion, in this account, almost the way “Rock Around the Clock” displaced Sinatra from the top of the charts.

The same pattern of avoidance and talking-past and taking on the temper of the times turns up in the contemporary science that has returned to the possibility of non-locality.

the revival of “non-locality” as a topic in physics may be due to our finding the metaphor of non-locality ever more palatable: “Modern communications technology may not technically be non-local but it sure feels that it is.”

Living among distant connections, where what happens in Bangalore happens in Boston, we are more receptive to the idea of such a strange order in the universe.

The “indeterminacy” of the atom was, for younger European physicists, “a lesson of modernity, an antidote to a misplaced Enlightenment trust in reason, which German intellectuals in the 1920’s widely held responsible for their country’s defeat in the First World War.” The tonal and temperamental difference between the scientists was as great as the evidence they called on.

Science isn’t a slot machine, where you drop in facts and get out truths. But it is a special kind of social activity, one where lots of different human traits—obstinacy, curiosity, resentment of authority, sheer cussedness, and a grudging readiness to submit pet notions to popular scrutiny—end by producing reliable knowledge

What was magic became mathematical and then mundane. “Magical” explanations, like spooky action, are constantly being revived and rebuffed, until, at last, they are reinterpreted and accepted. Instead of a neat line between science and magic, then, we see a jumpy, shifting boundary that keeps getting redrawn

Real-world demarcations between science and magic, Musser’s story suggests, are like Bugs’s: made on the move and as much a trap as a teaching aid.

In the past several decades, certainly, the old lines between the history of astrology and astronomy, and between alchemy and chemistry, have been blurred; historians of the scientific revolution no longer insist on a clean break between science and earlier forms of magic.

Where once logical criteria between science and non-science (or pseudo-science) were sought and taken seriously—Karl Popper’s criterion of “falsifiability” was perhaps the most famous, insisting that a sound theory could, in principle, be proved wrong by one test or another—many historians and philosophers of science have come to think that this is a naïve view of how the scientific enterprise actually works.

They see a muddle of coercion, old magical ideas, occasional experiment, hushed-up failures—all coming together in a social practice that gets results but rarely follows a definable logic.

Yet the old notion of a scientific revolution that was really a revolution is regaining some credibility.

David Wootton, in his new, encyclopedic history, “The Invention of Science” (Harper), recognizes the blurred lines between magic and science but insists that the revolution lay in the public nature of the new approach.

What killed alchemy was the insistence that experiments must be openly reported in publications which presented a clear account of what had happened, and they must then be replicated, preferably before independent witnesses.

Wootton, while making little of Popper’s criterion of falsifiability, makes it up to him by borrowing a criterion from his political philosophy. Scientific societies are open societies. One day the lunar tides are occult, the next day they are science, and what changes is the way in which we choose to talk about them.

Wootton also insists, against the grain of contemporary academia, that single observed facts, what he calls “killer facts,” really did polish off antique authorities

once we agree that the facts are facts, they can do amazing work. Traditional Ptolemaic astronomy, in place for more than a millennium, was destroyed by what Galileo discovered about the phases of Venus. That killer fact “serves as a single, solid, and strong argument to establish its revolution around the Sun, such that no room whatsoever remains for doubt,” Galileo wrote, and Wootton adds, “No one was so foolish as to dispute these claims.

everal things flow from Wootton’s view. One is that “group think” in the sciences is often true think. Science has always been made in a cloud of social networks.

There has been much talk in the pop-sci world of “memes”—ideas that somehow manage to replicate themselves in our heads. But perhaps the real memes are not ideas or tunes or artifacts but ways of making them—habits of mind rather than products of mind

science, then, a club like any other, with fetishes and fashions, with schemers, dreamers, and blackballed applicants? Is there a real demarcation to be made between science and every other kind of social activity

The claim that basic research is valuable because it leads to applied technology may be true but perhaps is not at the heart of the social use of the enterprise. The way scientists do think makes us aware of how we can think

a newly emerging model of how the brain focuses attention on a particular task, using neurons in the thalamic reticular nucleus as a switchboard to control the amount of information the brain receives, limiting and filtering out sensory information that we don't want to pay attention to

People need to be able to focus on one thing and suppress other distractions to perform everyday functions such as driving, talking on the phone, and socializing

sets the stage for ever more detailed studies on the complex behavior involved in how the mammalian brain pays attention to what's important, and especially how those neural circuits are broken in cases of attention-deficit diseases, such as ADHD, autism, and schizophrenia

its individual neurons as possible regulators of the brain's ability to multitask

The test, they say, was designed to gauge how well the area of the brain known to control higher behavioral functions, the prefrontal cortex, could direct the focus on one sense over another

researchers distracted the mice with opposing stimuli: If the mouse was expecting a flash of light to guide it to the milk reward, the researchers distracted it with a sound, and vice versa. Distracting the mice decreased their ability to collect the food reward to 70 percent from nearly 90 percent, even if the distracting stimulus was removed later

found that inactivating the prefrontal cortex region of the brain, which is believed responsible for decision-making in complex behaviors, disrupted TRN neural signaling and reduced mice to only random success in obtaining a milk reward when presented with specifically cued light or sound signals

Inactivating the TRN, while leaving the cortical regions intact, also diminished success with obtaining the prompted food reward

prefrontal cortex is essential to performing such behavioral tasks

this part of the brain "stores the knowledge ultimately communicated to the TRN to control how much visual or auditory sensory information is suppressed or not, and how the brain ultimately multitasks

The agency also relies on industry data to develop rules on chemical safety that is often kept confidential for business reasons.

So why would he want to prohibit his own agency from using these studies? It’s not a mystery. Time and again the Trump administration has put the profits of regulated industries over the health of the American people. Fundamental research on the effects of air pollution on public health has long been a target of those who oppose the E.P.A.’s air quality regulations, like the rule that requires power plants to reduce their mercury emissions.

By the end of World War II, however, American corporations were facing severe talent shortages. Their senior executives were growing old, and a dearth of hiring from the Depression through the war had resulted in a shortfall of able, well-trained managers. Finding people who had the potential to rise quickly through the ranks became an overriding preoccupation of American businesses. They began to devise a formal hiring-and-management system based in part on new studies of human behavior, and in part on military techniques developed during both world wars, when huge mobilization efforts and mass casualties created the need to get the right people into the right roles as efficiently as possible. By the 1950s, it was not unusual for companies to spend days with young applicants for professional jobs, conducting a battery of tests, all with an eye toward corner-office potential.

But companies abandoned their hard-edged practices for another important reason: many of their methods of evaluation turned out not to be very scientific.

this regime, so widespread in corporate America at mid-century, had almost disappeared by 1990. “I think an HR person from the late 1970s would be stunned to see how casually companies hire now,”

Many factors explain the change, he said, and then he ticked off a number of them: Increased job-switching has made it less important and less economical for companies to test so thoroughly. A heightened focus on short-term financial results has led to deep cuts in corporate functions that bear fruit only in the long term. The Civil Rights Act of 1964, which exposed companies to legal liability for discriminatory hiring practices, has made HR departments wary of any broadly applied and clearly scored test that might later be shown to be systematically biased.

about a quarter of the country’s corporations were using similar tests to evaluate managers and junior executives, usually to assess whether they were ready for bigger roles.

He has encouraged the company’s HR executives to think about applying the games to the recruitment and evaluation of all professional workers.

Knack makes app-based video games, among them Dungeon Scrawl, a quest game requiring the player to navigate a maze and solve puzzles, and Wasabi Waiter, which involves delivering the right sushi to the right customer at an increasingly crowded happy hour. These games aren’t just for play: they’ve been designed by a team of neuroscientists, psychologists, and data scientists to suss out human potential. Play one of them for just 20 minutes, says Guy Halfteck, Knack’s founder, and you’ll generate several megabytes of data, exponentially more than what’s collected by the SAT or a personality test. How long you hesitate before taking every action, the sequence of actions you take, how you solve problems—all of these factors and many more are logged as you play, and then are used to analyze your creativity, your persistence, your capacity to learn quickly from mistakes, your ability to prioritize, and even your social intelligence and personality. The end result, Halfteck says, is a high-resolution portrait of your psyche and intellect, and an assessment of your potential as a leader or an innovator.

When the results came back, Haringa recalled, his heart began to beat a little faster. Without ever seeing the ideas, without meeting or interviewing the people who’d proposed them, without knowing their title or background or academic pedigree, Knack’s algorithm had identified the people whose ideas had panned out. The top 10 percent of the idea generators as predicted by Knack were in fact those who’d gone furthest in the process.

What Knack is doing, Haringa told me, “is almost like a paradigm shift.” It offers a way for his GameChanger unit to avoid wasting time on the 80 people out of 100—nearly all of whom look smart, well-trained, and plausible on paper—whose ideas just aren’t likely to work out.

Aptitude, skills, personal history, psychological stability, discretion, loyalty—companies at the time felt they had a need (and the right) to look into them all. That ambit is expanding once again, and this is undeniably unsettling. Should the ideas of scientists be dismissed because of the way they play a game? Should job candidates be ranked by what their Web habits say about them? Should the “data signature” of natural leaders play a role in promotion? These are all live questions today, and they prompt heavy concerns: that we will cede one of the most subtle and human of skills, the evaluation of the gifts and promise of other people, to machines; that the models will get it wrong; that some people will never get a shot in the new workforce.

scoring distance from work could violate equal-employment-opportunity standards. Marital status? Motherhood? Church membership? “Stuff like that,” Meyerle said, “we just don’t touch”—at least not in the U.S., where the legal environment is strict. Meyerle told me that Evolv has looked into these sorts of factors in its work for clients abroad, and that some of them produce “startling results.”

consider the alternative. A mountain of scholarly literature has shown that the intuitive way we now judge professional potential is rife with snap judgments and hidden biases, rooted in our upbringing or in deep neurological connections that doubtless served us well on the savanna but would seem to have less bearing on the world of work.

We may like to think that society has become more enlightened since those days, and in many ways it has, but our biases are mostly unconscious, and they can run surprisingly deep. Consider race. For a 2004 study called “Are Emily and Greg More Employable Than Lakisha and Jamal?,” the economists Sendhil Mullainathan and Marianne Bertrand put white-sounding names (Emily Walsh, Greg Baker) or black-sounding names (Lakisha Washington, Jamal Jones) on similar fictitious résumés, which they then sent out to a variety of companies in Boston and Chicago. To get the same number of callbacks, they learned, they needed to either send out half again as many résumés with black names as those with white names, or add eight extra years of relevant work experience to the résumés with black names.

a sociologist at Northwestern, spent parts of the three years from 2006 to 2008 interviewing professionals from elite investment banks, consultancies, and law firms about how they recruited, interviewed, and evaluated candidates, and concluded that among the most important factors driving their hiring recommendations were—wait for it—shared leisure interests.

Lacking “reliable predictors of future performance,” Rivera writes, “assessors purposefully used their own experiences as models of merit.” Former college athletes “typically prized participation in varsity sports above all other types of involvement.” People who’d majored in engineering gave engineers a leg up, believing they were better prepared.

the prevailing system of hiring and management in this country involves a level of dysfunction that should be inconceivable in an economy as sophisticated as ours. Recent survey data collected by the Corporate Executive Board, for example, indicate that nearly a quarter of all new hires leave their company within a year of their start date, and that hiring managers wish they’d never extended an offer to one out of every five members on their team

In the late 1990s, as these assessments shifted from paper to digital formats and proliferated, data scientists started doing massive tests of what makes for a successful customer-support technician or salesperson. This has unquestionably improved the quality of the workers at many firms.

In 2010, however, Xerox switched to an online evaluation that incorporates personality testing, cognitive-skill assessment, and multiple-choice questions about how the applicant would handle specific scenarios that he or she might encounter on the job. An algorithm behind the evaluation analyzes the responses, along with factual information gleaned from the candidate’s application, and spits out a color-coded rating: red (poor candidate), yellow (middling), or green (hire away). Those candidates who score best, I learned, tend to exhibit a creative but not overly inquisitive personality, and participate in at least one but not more than four social networks, among many other factors. (Previous experience, one of the few criteria that Xerox had explicitly screened for in the past, turns out to have no bearing on either productivity or retention

When Xerox started using the score in its hiring decisions, the quality of its hires immediately improved. The rate of attrition fell by 20 percent in the initial pilot period, and over time, the number of promotions rose. Xerox still interviews all candidates in person before deciding to hire them, Morse told me, but, she added, “We’re getting to the point where some of our hiring managers don’t even want to interview anymore”

Gone are the days, Ostberg told me, when, say, a small survey of college students would be used to predict the statistical validity of an evaluation tool. “We’ve got a data set of 347,000 actual employees who have gone through these different types of assessments or tools,” he told me, “and now we have performance-outcome data, and we can split those and slice and dice by industry and location.”

Evolv’s tests allow companies to capture data about everybody who applies for work, and everybody who gets hired—a complete data set from which sample bias, long a major vexation for industrial-organization psychologists, simply disappears. The sheer number of observations that this approach makes possible allows Evolv to say with precision which attributes matter more to the success of retail-sales workers (decisiveness, spatial orientation, persuasiveness) or customer-service personnel at call centers (rapport-building)

There are some data that Evolv simply won’t use, out of a concern that the information might lead to systematic bias against whole classes of people

the idea that hiring was a science fell out of favor. But now it’s coming back, thanks to new technologies and methods of analysis that are cheaper, faster, and much-wider-ranging than what we had before

what most excites him are the possibilities that arise from monitoring the entire life cycle of a worker at any given company.

Now the two companies are working together to marry pre-hire assessments to an increasing array of post-hire data: about not only performance and duration of service but also who trained the employees; who has managed them; whether they were promoted to a supervisory role, and how quickly; how they performed in that role; and why they eventually left.

What begins with an online screening test for entry-level workers ends with the transformation of nearly every aspect of hiring, performance assessment, and management.

I turned to Sandy Pentland, the director of the Human Dynamics Laboratory at MIT. In recent years, Pentland has pioneered the use of specialized electronic “badges” that transmit data about employees’ interactions as they go about their days. The badges capture all sorts of information about formal and informal conversations: their length; the tone of voice and gestures of the people involved; how much those people talk, listen, and interrupt; the degree to which they demonstrate empathy and extroversion; and more. Each badge generates about 100 data points a minute.

he tried the badges out on about 2,500 people, in 21 different organizations, and learned a number of interesting lessons. About a third of team performance, he discovered, can usually be predicted merely by the number of face-to-face exchanges among team members. (Too many is as much of a problem as too few.) Using data gathered by the badges, he was able to predict which teams would win a business-plan contest, and which workers would (rightly) say they’d had a “productive” or “creative” day. Not only that, but he claimed that his researchers had discovered the “data signature” of natural leaders, whom he called “charismatic connectors” and all of whom, he reported, circulate actively, give their time democratically to others, engage in brief but energetic conversations, and listen at least as much as they talk.

His group is developing apps to allow team members to view their own metrics more or less in real time, so that they can see, relative to the benchmarks of highly successful employees, whether they’re getting out of their offices enough, or listening enough, or spending enough time with people outside their own team.

Torrents of data are routinely collected by American companies and now sit on corporate servers, or in the cloud, awaiting analysis. Bloomberg reportedly logs every keystroke of every employee, along with their comings and goings in the office. The Las Vegas casino Harrah’s tracks the smiles of the card dealers and waitstaff on the floor (its analytics team has quantified the impact of smiling on customer satisfaction). E‑mail, of course, presents an especially rich vein to be mined for insights about our productivity, our treatment of co-workers, our willingness to collaborate or lend a hand, our patterns of written language, and what those patterns reveal about our intelligence, social skills, and behavior.

people analytics will ultimately have a vastly larger impact on the economy than the algorithms that now trade on Wall Street or figure out which ads to show us. He reminded me that we’ve witnessed this kind of transformation before in the history of management science. Near the turn of the 20th century, both Frederick Taylor and Henry Ford famously paced the factory floor with stopwatches, to improve worker efficiency.

“The quantities of data that those earlier generations were working with,” he said, “were infinitesimal compared to what’s available now. There’s been a real sea change in the past five years, where the quantities have just grown so large—petabytes, exabytes, zetta—that you start to be able to do things you never could before.”

People analytics will unquestionably provide many workers with more options and more power. Gild, for example, helps companies find undervalued software programmers, working indirectly to raise those people’s pay. Other companies are doing similar work. One called Entelo, for instance, specializes in using algorithms to identify potentially unhappy programmers who might be receptive to a phone cal

He sees it not only as a boon to a business’s productivity and overall health but also as an important new tool that individual employees can use for self-improvement: a sort of radically expanded The 7 Habits of Highly Effective People, custom-written for each of us, or at least each type of job, in the workforce.

the most exotic development in people analytics today is the creation of algorithms to assess the potential of all workers, across all companies, all the time.

The way Gild arrives at these scores is not simple. The company’s algorithms begin by scouring the Web for any and all open-source code, and for the coders who wrote it. They evaluate the code for its simplicity, elegance, documentation, and several other factors, including the frequency with which it’s been adopted by other programmers. For code that was written for paid projects, they look at completion times and other measures of productivity. Then they look at questions and answers on social forums such as Stack Overflow, a popular destination for programmers seeking advice on challenging projects. They consider how popular a given coder’s advice is, and how widely that advice ranges.

The algorithms go further still. They assess the way coders use language on social networks from LinkedIn to Twitter; the company has determined that certain phrases and words used in association with one another can distinguish expert programmers from less skilled ones. Gild knows these phrases and words are associated with good coding because it can correlate them with its evaluation of open-source code, and with the language and online behavior of programmers in good positions at prestigious companies.

having made those correlations, Gild can then score programmers who haven’t written open-source code at all, by analyzing the host of clues embedded in their online histories. They’re not all obvious, or easy to explain. Vivienne Ming, Gild’s chief scientist, told me that one solid predictor of strong coding is an affinity for a particular Japanese manga site.

Gild’s CEO, Sheeroy Desai, told me he believes his company’s approach can be applied to any occupation characterized by large, active online communities, where people post and cite individual work, ask and answer professional questions, and get feedback on projects. Graphic design is one field that the company is now looking at, and many scientific, technical, and engineering roles might also fit the bill. Regardless of their occupation, most people leave “data exhaust” in their wake, a kind of digital aura that can reveal a lot about a potential hire.

professionally relevant personality traits can be judged effectively merely by scanning Facebook feeds and photos. LinkedIn, of course, captures an enormous amount of professional data and network information, across just about every profession. A controversial start-up called Klout has made its mission the measurement and public scoring of people’s online social influence.

Mullainathan expressed amazement at how little most creative and professional workers (himself included) know about what makes them effective or ineffective in the office. Most of us can’t even say with any certainty how long we’ve spent gathering information for a given project, or our pattern of information-gathering, never mind know which parts of the pattern should be reinforced, and which jettisoned. As Mullainathan put it, we don’t know our own “production function.”

Over time, better job-matching technologies are likely to begin serving people directly, helping them see more clearly which jobs might suit them and which companies could use their skills. In the future, Gild plans to let programmers see their own profiles and take skills challenges to try to improve their scores. It intends to show them its estimates of their market value, too, and to recommend coursework that might allow them to raise their scores even more. Not least, it plans to make accessible the scores of typical hires at specific companies, so that software engineers can better see the profile they’d need to land a particular job

Knack, for its part, is making some of its video games available to anyone with a smartphone, so people can get a better sense of their strengths, and of the fields in which their strengths would be most valued. (Palo Alto High School recently adopted the games to help students assess careers.) Ultimately, the company hopes to act as matchmaker between a large network of people who play its games (or have ever played its games) and a widening roster of corporate clients, each with its own specific profile for any given type of job.

When I began my reporting for this story, I was worried that people analytics, if it worked at all, would only widen the divergent arcs of our professional lives, further gilding the path of the meritocratic elite from cradle to grave, and shutting out some workers more definitively. But I now believe the opposite is likely to happen, and that we’re headed toward a labor market that’s fairer to people at every stage of their careers

For decades, as we’ve assessed people’s potential in the professional workforce, the most important piece of data—the one that launches careers or keeps them grounded—has been educational background: typically, whether and where people went to college, and how they did there. Over the past couple of generations, colleges and universities have become the gatekeepers to a prosperous life. A degree has become a signal of intelligence and conscientiousness, one that grows stronger the more selective the school and the higher a student’s GPA, that is easily understood by employers, and that, until the advent of people analytics, was probably unrivaled in its predictive powers.

the limitations of that signal—the way it degrades with age, its overall imprecision, its many inherent biases, its extraordinary cost—are obvious. “Academic environments are artificial environments,” Laszlo Bock, Google’s senior vice president of people operations, told The New York Times in June. “People who succeed there are sort of finely trained, they’re conditioned to succeed in that environment,” which is often quite different from the workplace.

because one’s college history is such a crucial signal in our labor market, perfectly able people who simply couldn’t sit still in a classroom at the age of 16, or who didn’t have their act together at 18, or who chose not to go to graduate school at 22, routinely get left behind for good. That such early factors so profoundly affect career arcs and hiring decisions made two or three decades later is, on its face, absurd.

I spoke with managers at a lot of companies who are using advanced analytics to reevaluate and reshape their hiring, and nearly all of them told me that their research is leading them toward pools of candidates who didn’t attend college—for tech jobs, for high-end sales positions, for some managerial roles. In some limited cases, this is because their analytics revealed no benefit whatsoever to hiring people with college degrees; in other cases, and more often, it’s because they revealed signals that function far better than college history,

Google, too, is hiring a growing number of nongraduates. Many of the people I talked with reported that when it comes to high-paying and fast-track jobs, they’re reducing their preference for Ivy Leaguers and graduates of other highly selective schools.

This process is just beginning. Online courses are proliferating, and so are online markets that involve crowd-sourcing. Both arenas offer new opportunities for workers to build skills and showcase competence. Neither produces the kind of instantly recognizable signals of potential that a degree from a selective college, or a first job at a prestigious firm, might. That’s a problem for traditional hiring managers, because sifting through lots of small signals is so difficult and time-consuming.

all of these new developments raise philosophical questions. As professional performance becomes easier to measure and see, will we become slaves to our own status and potential, ever-focused on the metrics that tell us how and whether we are measuring up? Will too much knowledge about our limitations hinder achievement and stifle our dreams? All I can offer in response to these questions, ironically, is my own gut sense, which leads me to feel cautiously optimistic.

Google’s understanding of the promise of analytics is probably better than anybody else’s, and the company has been changing its hiring and management practices as a result of its ongoing analyses. (Brainteasers are no longer used in interviews, because they do not correlate with job success; GPA is not considered for anyone more than two years out of school, for the same reason—the list goes on.) But for all of Google’s technological enthusiasm, these same practices are still deeply human. A real, live person looks at every résumé the company receives. Hiring decisions are made by committee and are based in no small part on opinions formed during structured interviews.

Taste does not simply equal your taste buds. It draws on information from all our senses as well as context. As a result, food is susceptible to the same trickery as wine. Adding yellow food dye to vanilla pudding leads people to experience a lemony taste. Diners eating in the dark at a chic concept restaurant confuse veal for tuna. Branding, packaging, and price tags are equally important to enjoyment. Cheap fish is routinely passed off as its pricier cousins at seafood and sushi restaurants. 

Just like with wine and classical music, we often judge food based on very different criteria than what we claim. The result is that our perceptions are easily skewed in ways we don’t anticipate. 

What does it mean for wine that presentation so easily trumps the quality imbued by being grown on premium Napa land or years of fruitful aging? Is it comforting that the same phenomenon is found in food and classical music, or is it a strike against the authenticity of our enjoyment of them as well? How common must these manipulations be until we concede that the influence of the price tag of a bottle of wine or the visual appearance of a pianist is not a trick but actually part of the quality?

To answer these questions, we need to investigate the underlying mechanism that leads us to judge wine, food, and music by criteria other than what we claim to value. And that mechanism seems to be the quick, intuitive judgments our minds unconsciously make

this unknowability also makes it easy to be led astray when our intuition makes a mistake. We may often be able to count on the price tag or packaging of food and wine for accurate information about quality. But as we believe that we’re judging based on just the product, we fail to recognize when presentation manipulates our snap judgments.

Participants were just as effective when watching 6 second video clips and when comparing their ratings to ratings of teacher effectiveness as measured by actual student test performance. 

The power of intuitive first impressions has been demonstrated in a variety of other contexts. One experiment found that people predicted the outcome of political elections remarkably well based on silent 10 second video clips of debates - significantly outperforming political pundits and predictions made based on economic indicators.

In a real world case, a number of art experts successfully identified a 6th century Greek statue as a fraud. Although the statue had survived a 14 month investigation by a respected museum that included the probings of a geologist, they instantly recognized something was off. They just couldn’t explain how they knew.

Cases like this represent the canon behind the idea of the “adaptive unconscious,” a concept made famous by journalist Malcolm Gladwell in his book Blink. The basic idea is that we constantly, quickly, and unconsciously do the equivalent of judging a book by its cover. After all, a cover provides a lot of relevant information in a world in which we don’t have time to read every page.

Gladwell describes the adaptive unconscious as “a kind of giant computer that quickly and quietly processes a lot of the data we need in order to keep functioning as human beings.”

In a famous experiment, psychologist Nalini Ambady provided participants in an academic study with 30 second silent video clips of a college professor teaching a class and asked them to rate the effectiveness of the professor.

In follow up experiments, Chia-Jung Tsay found that those judging musicians’ auditions based on visual cues were not giving preference to attractive performers. Rather, they seemed to look for visual signs of relevant characteristics like passion, creativity, and uniqueness. Seeing signs of passion is valuable information. But in differentiating between elite performers, it gives an edge to someone who looks passionate over someone whose play is passionate

Outside of these more eccentric examples, it’s our reliance on quick judgments, and ignorance of their workings, that cause people to act on ugly, unconscious biases

It’s also why - from a business perspective - packaging and presentation is just as important as the good or service on offer. Why marketing is just as important as product. 

Gladwell ends Blink optimistically. By paying closer attention to our powers of rapid cognition, he argues, we can avoid its pitfalls and harness its powers. We can blindly audition musicians behind a screen, look at a piece of art devoid of other context, and pay particular attention to possible unconscious bias in our performance reports.

But Gladwell’s success in demonstrating how the many calculations our adaptive unconscious performs without our awareness undermines his hopeful message of consciously harnessing its power.

As a former world-class tennis player and coach of over 50 years, Braden is a perfect example of the ideas behind thin slicing. But if he can’t figure out what his unconscious is up to when he recognizes double faults, why should anyone else expect to be up to the task?

flawed judgment in fields like medicine and investing has more serious consequences. The fact that expertise is so tricky leads psychologist Daniel Kahneman to assert that most experts should seek the assistance of statistics and algorithms in making decisions.

In his book Thinking, Fast and Slow, he describes our two modes of thought: System 1, like the adaptive unconscious, is our “fast, instinctive, and emotional” intuition. System 2 is our “slower, more deliberative, and more logical” conscious thought. Kahneman believes that we often leave decisions up to System 1 and generally place far “too much confidence in human judgment” due to the pitfalls of our intuition described above.

Not every judgment will be made in a field that is stable and regular enough for an algorithm to help us make judgments or predictions. But in those cases, he notes, “Hundreds of studies have shown that wherever we have sufficient information to build a model, it will perform better than most people.”

Experts can avoid the pitfalls of intuition more easily than laypeople. But they need help too, especially as our collective confidence in expertise leads us to overconfidence in their judgments. 

This article has referred to the influence of price tags and context on products and experiences like wine and classical music concerts as tricks that skew our perception. But maybe we should consider them a real, actual part of the quality.

Losing ourselves in a universe of relativism, however, will lead us to miss out on anything new or unique. Take the example of the song “Hey Ya!” by Outkast. When the music industry heard it, they felt sure it would be a hit. When it premiered on the radio, however, listeners changed the channel. The song sounded too dissimilar from songs people liked, so they responded negatively. 

It took time for people to get familiar with the song and realize that they enjoyed it. Eventually “Hey Ya!” became the hit of the summer.

Many boorish people talking about the ethereal qualities of great wine probably can't even identify cork taint because their impressions are dominated by the price tag and the wine label. But the classic defense of wine - that you need to study it to appreciate it - is also vindicated. The open question - which is both editorial and empiric - is what it means for the industry that constant vigilance and substantial study is needed to dependably appreciate wine for the product quality alone. But the questions is relevant to the enjoyment of many other products and experiences that we enjoy in life.

Maybe the most important conclusion is to not only recognize the fallibility of our judgments and impressions, but to recognize when it matters, and when it doesn’t

the really painful message our daughter will receive is that we're embarrassing. For most people who aren't New Atheists, or old atheists, and have no passion invested in the subject, either negative or positive, believers aren't weird because we're wicked. We're weird because we're inexplicable; because, when there's no necessity for it that anyone sensible can see, we've committed ourselves to a set of awkward and absurd attitudes that obtrude, that stick out against the background of modern life, and not in some important or respectworthy or principled way, either.

Believers are people who try to insert Jee-zus into conversations at parties; who put themselves down, with writhings of unease, for perfectly normal human behaviour; who are constantly trying to create a solemn hush that invites a fart, a hiccup, a bit of subversion. Believers are people who, on the rare occasions when you have to listen to them, like at a funeral or a wedding, seize the opportunity to pour the liquidised content of a primary-school nativity play into your earhole, apparently not noticing that childhood is over.

What goes on inside believers is mysterious. So far as it can be guessed at it appears to be a kind of anxious pretending, a kind of continual, nervous resistance to reality.

to me, it's belief that involves the most uncompromising attention to the nature of things of which you are capable. Belief demands that you dispense with illusion after illusion, while contemporary common sense requires continual, fluffy pretending – pretending that might as well be systematic, it's so thoroughly incentivised by our culture.

The atheist bus says: "There's probably no God. So stop worrying and enjoy your life."

the word that offends against realism here is "enjoy". I'm sorry – enjoy your life?

If you based your knowledge of the human species exclusively on adverts, you'd think that the normal condition of humanity was to be a good-looking single person between 20 and 35, with excellent muscle-definition and/or an excellent figure, and a large disposable income. And you'd think the same thing if you got your information exclusively from the atheist bus

The implication of the bus slogan is that enjoyment would be your natural state if you weren't being "worried" by us believers and our hellfire preaching. Take away the malignant threat of God-talk, and you would revert to continuous pleasure

What's so wrong with this, apart from it being total bollocks? Well, in the first place, that it buys a bill of goods, sight unseen, from modern marketing. Given that human life isn't and can't be made up of enjoyment, it is in effect accepting a picture of human life in which those pieces of living where easy enjoyment is more likely become the only pieces that are visible.

But then, like every human being, I am not in the habit of entertaining only those emotions I can prove. I'd be an unrecognisable oddity if I did. Emotions can certainly be misleading: they can fool you into believing stuff that is definitely, demonstrably untrue. Yet emotions are also our indispensable tool for navigating, for feeling our way through, the much larger domain of stuff that isn't susceptible to proof or disproof, that isn't checkable against the physical universe. We dream, hope, wonder, sorrow, rage, grieve, delight, surmise, joke, detest; we form such unprovable conjectures as novels or clarinet concertos; we imagine. And religion is just a part of that, in one sense. It's just one form of imagining, absolutely functional, absolutely human-normal. It would seem perverse, on the face of it, to propose that this one particular manifestation of imagining should be treated as outrageous, should be excised if (which is doubtful) we can manage it.

suppose, as the atheist bus goes by, you are povertystricken, or desperate for a job, or a drug addict, or social services have just taken away your child. The bus tells you that there's probably no God so you should stop worrying and enjoy your life, and now the slogan is not just bitterly inappropriate in mood. What it means, if it's true, is that anyone who isn't enjoying themselves is entirely on their own. What the bus says is: there's no help coming.

Enjoyment is great. The more enjoyment the better. But enjoyment is one emotion. To say that life is to be enjoyed (just enjoyed) is like saying that mountains should only have summits, or that all colours should be purple, or that all plays should be by Shakespeare. This really is a bizarre category error.

A consolation you could believe in would be one that wasn't in danger of popping like a soap bubble on contact with the ordinary truths about us. A consolation you could trust would be one that acknowledged the difficult stuff rather than being in flight from it, and then found you grounds for hope in spite of it, or even because of it

The novelist Richard Powers has written that the Clarinet Concerto sounds the way mercy would sound, and that's exactly how I experienced it in 1997. Mercy, though, is one of those words that now requires definition. It does not only mean some tyrant's capacity to suspend a punishment he has himself inflicted. It can mean – and does mean in this case – getting something kind instead of the sensible consequences of an action, or as well as the sensible consequences of an action.

from outside, belief looks like a series of ideas about the nature of the universe for which a truth-claim is being made, a set of propositions that you sign up to; and when actual believers don't talk about their belief in this way, it looks like slipperiness, like a maddening evasion of the issue.

I am a fairly orthodox Christian. Every Sunday I say and do my best to mean the whole of the Creed, which is a series of propositions. But it is still a mistake to suppose that it is assent to the propositions that makes you a believer. It is the feelings that are primary. I assent to the ideas because I have the feelings; I don't have the feelings because I've assented to the ideas.

what I felt listening to Mozart in 1997 is not some wishy-washy metaphor for an idea I believe in, and it's not a front behind which the real business of belief is going on: it's the thing itself. My belief is made of, built up from, sustained by, emotions like that. That's what makes it real.

I think that Mozart, two centuries earlier, had succeeded in creating a beautiful and accurate report of an aspect of reality. I think that the reason reality is that way – that it is in some ultimate sense merciful as well as being a set of physical processes all running along on their own without hope of appeal, all the way up from quantum mechanics to the relative velocity of galaxies by way of "blundering, low and horridly cruel" biology (Darwin) – is that the universe is sustained by a continual and infinitely patient act of love. I think that love keeps it in being.

That's what I think. But it's all secondary. It all comes limping along behind my emotional assurance that there was mercy, and I felt it. And so the argument about whether the ideas are true or not, which is the argument that people mostly expect to have about religion, is also secondary for me.

No, I can't prove it. I don't know that any of it is true. I don't know if there's a God. (And neither do you, and neither does Professor Dawkins, and neither does anybody. It isn't the kind of thing you can know. It isn't a knowable item.)

let's be clear about the emotional logic of the bus's message. It amounts to a denial of hope or consolation on any but the most chirpy, squeaky, bubble-gummy reading of the human situation

It's got itself established in our culture, relatively recently, that the emotions involved in religious belief must be different from the ones involved in all the other kinds of continuous imagining, hoping, dreaming, and so on, that humans do. These emotions must be alien, freakish, sad, embarrassing, humiliating, immature, pathetic. These emotions must be quite separate from commonsensical us. But they aren't

The emotions that sustain religious belief are all, in fact, deeply ordinary and deeply recognisable to anybody who has ever made their way across the common ground of human experience as an adult.

It's just that the emotions in question are rarely talked about apart from their rationalisation into ideas. This is what I have tried to do in my new book, Unapologetic.

You can easily look up what Christians believe in. You can read any number of defences of Christian ideas. This, however, is a defence of Christian emotions – of their intelligibility, of their grown-up dignity.

poor readers can sound out words from print, so in that sense, they can read. Yet they are functionally illiterate — they comprehend very little of what they can sound out. So what does comprehension require? Broad vocabulary, obviously. Equally important, but more subtle, is the role played by factual knowledge.

All prose has factual gaps that must be filled by the reader.

Knowledge also provides context.

You might think, then, that authors should include all the information needed to understand what they write.

Current education practices show that reading comprehension is misunderstood. It’s treated like a general skill that can be applied with equal success to all texts. Rather, comprehension is intimately intertwined with knowledge.

students who score well on reading tests are those with broad knowledge; they usually know at least a little about the topics of the passages on the test.

One experiment tested 11th graders’ general knowledge with questions from science (“pneumonia affects which part of the body?”), history (“which American president resigned because of the Watergate scandal?”), as well as the arts, civics, geography, athletics and literature. Scores on this general knowledge test were highly associated with reading test scores.

But those details would make prose long and tedious for readers who already know the information. “Write for your audience” means, in part, gambling on what they know.

That suggests three significant changes in schooling.

First, it points to decreasing the time spent on literacy instruction in early grades.

Third-graders spend 56 percent of their time on literacy activities but 6 percent each on science and social studies. This disproportionate emphasis on literacy backfires in later grades, when children’s lack of subject matter knowledge impedes comprehension.

Another positive step would be to use high-information texts in early elementary grades. Historically, they have been light in content.

Second, understanding the importance of knowledge to reading ought to make us think differently about year-end standardized tests. If a child has studied New Zealand, she ought to be good at reading and thinking about passages on New Zealand. Why test her reading with a passage about spiders, or the Titanic?

Third, the systematic building of knowledge must be a priority in curriculum design.

The Common Core Standards for reading specify nearly nothing by way of content that children are supposed to know — the document valorizes reading skills. State officials should go beyond the Common Core Standards by writing content-rich grade-level standards

Don’t blame the internet, or smartphones, or fake news for Americans’ poor reading. Blame ignorance. Turning the tide will require profound changes in how reading is taught, in standardized testing and in school curriculums. Underlying all these changes must be a better understanding of how the mind comprehends what it reads.

Daniel T. Willingham (@DTWillingham) is a professor of psychology at the University of Virginia and the author, most recently, of “The Reading Mind: A Cognitive Approach to Understanding How the Mind Reads.”

If there were a prize for the busiest language, then a language like Kabardian, also known as Circassian and spoken in the Caucasus, would win

The prize for most economical language could go to certain colloquial dialects of Indonesian that are rarely written but represent the daily reality of Indonesian in millions of mouths

Experiments have shown that this is often true to a faint, flickering degree a psychologist can detect in the artifice of experimental conditions

In a language where final sounds take the accent, such sounds tend to hold on longer because they are so loud and clear—you’re less likely to mumble it and people listening are more likely to hear it

When a language seems especially telegraphic, usually another factor has come into play: Enough adults learned it at a certain stage in its history that, given the difficulty of learning a new language after childhood, it became a kind of stripped-down “schoolroom” version of itself

Even if languages’ differences in busyness can’t be taken as windows on psychological alertness, the differences remain awesome

It also has to do with language; you can't just add a random stroke to a Chinese character and create a new surname, the way you can add a letter to an English name.

people with rare characters in their names, which aren't compatible with existing computer systems, can get left behind -- pushing many to change their names for the sake of convenience, even if it means abandoning centuries of heritage and language.

China's history, full of migration, political turmoil and warfare, meant people's names were often in flux -- which is partly why many have since vanished.

People sometimes changed their names for convenience, too -- for instance, simplifying complex characters by adopting similar-sounding ones with fewer strokes. Other times they did it out of superstition, abandoning a name believed to bring ill fortune, said Chen, the associate professor.

surnames are lost or die out over time with each new generation as women take on their husbands' surnames.

With China roaring into the digital age, nearly everything -- from making appointments to buying train tickets -- has moved online. That meant a world of trouble if you happened to have a rare character in your name, that might not be in the database.

China's digitized ID cards made the problem even more pressing. The first generation of these cards allowed people to hand-write their names on -- but the second-generation cards, launched in 2004 and dubbed "smart cards" for their digital features, exclusively used computer-printed text.

Another factor exacerbating the increasing commonness of Chinese names is the government's efforts to standardize and regulate the language.

Various dialects of Mandarin are spoken between the provinces, with some so different that speakers are unintelligible to each other.

To try to address this, experts have increased the database from 32,000 characters to 70,000 characters, according to the government. They're still working to expand it to include more than 90,000 character

This struggle, and the cost of adapting to the modern age, was exemplified in a village in the eastern Shandong province in the late 2000s. Many villagers shared the ancestral name "Shan" -- but when they began applying for the digitized ID cards, local officials advised them to change their surnames to "Xian," a similar-sounding but more common character, according to state-owned news service CNTV.

In the end, more than 200 villagers were forced to change their surnames, a source of sorrow for many.

I learned something more useful: the existence of non-fiction literature that can teach you anything.

something felt odd. Whenever a conversation revolved around a serious non-fiction book I read, such as ‘Sapiens’ or ‘Thinking Fast and Slow,’ I could never remember much. Turns out, I hadn’t absorbed as much information as I’d believed. Since I couldn’t remember much, I felt as though reading wasn’t an investment in knowledge but mere entertainment.

When I opened up about my struggles, many others confessed they also can’t remember most of what they read, as if forgetting is a character flaw. But it isn’t.

It’s the way we work with books that’s flawed.

there’s a better way to read. Most people rely on techniques like highlighting, rereading, or, worst of all, completely passive reading, which are highly ineffective.

Since I started applying evidence-based learning strategies to reading non-fiction books, many things have changed. I can explain complex ideas during dinner conversations. I can recall interesting concepts and link them in my writing or podcasts. As a result, people come to me for all kinds of advice.

What’s the Architecture of Human Learning and Memory?

Human brains don’t work like recording devices. We don’t absorb information and knowledge by reading sentences.

we store new information in terms of its meaning to our existing memory

we give new information meaning by actively participating in the learning process — we interpret, connect, interrelate, or elaborate

To remember new information, we not only need to know it but also to know how it relates to what we already know.

Learning is dependent on memory processes because previously-stored knowledge functions as a framework in which newly learned information can be linked.”

Human memory works in three stages: acquisition, retention, and retrieval. In the acquisition phase, we link new information to existing knowledge; in the retention phase, we store it, and in the retrieval phase, we get information out of our memory.

Retrieval, the third stage, is cue dependent. This means the more mental links you’re generating during stage one, the acquisition phase, the easier you can access and use your knowledge.

we need to understand that the three phases interrelate

creating durable and flexible access to to-be-learned information is partly a matter of achieving a meaningful encoding of that information and partly a matter of exercising the retrieval process.”

Next, we’ll look at the learning strategies that work best for our brains (elaboration, retrieval, spaced repetition, interleaving, self-testing) and see how we can apply those insights to reading non-fiction books.

The strategies that follow are rooted in research from professors of Psychological & Brain Science around Henry Roediger and Mark McDaniel. Both scientists spent ten years bridging the gap between cognitive psychology and education fields. Harvard University Press published their findings in the book ‘Make It Stick.

#1 Elaboration

“Elaboration is the process of giving new material meaning by expressing it in your own words and connecting it with what you already know.”

Why elaboration works: Elaborative rehearsal encodes information into your long-term memory more effectively. The more details and the stronger you connect new knowledge to what you already know, the better because you’ll be generating more cues. And the more cues they have, the easier you can retrieve your knowledge.

How I apply elaboration: Whenever I read an interesting section, I pause and ask myself about the real-life connection and potential application. The process is invisible, and my inner monologues sound like: “This idea reminds me of…, This insight conflicts with…, I don’t really understand how…, ” etc.

For example, when I learned about A/B testing in ‘The Lean Startup,’ I thought about applying this method to my startup. I added a note on the site stating we should try it in user testing next Wednesday. Thereby the book had an immediate application benefit to my life, and I will always remember how the methodology works.

How you can apply elaboration: Elaborate while you read by asking yourself meta-learning questions like “How does this relate to my life? In which situation will I make use of this knowledge? How does it relate to other insights I have on the topic?”

While pausing and asking yourself these questions, you’re generating important memory cues. If you take some notes, don’t transcribe the author’s words but try to summarize, synthesize, and analyze.

#2 Retrieval

With retrieval, you try to recall something you’ve learned in the past from your memory. While retrieval practice can take many forms — take a test, write an essay, do a multiple-choice test, practice with flashcards

the authors of ‘Make It Stick’ state: “While any kind of retrieval practice generally benefits learning, the implication seems to be that where more cognitive effort is required for retrieval, greater retention results.”

Whatever you settle for, be careful not to copy/paste the words from the author. If you don’t do the brain work yourself, you’ll skip the learning benefits of retrieval

Retrieval strengthens your memory and interrupts forgetting and, as other researchers replicate, as a learning event, the act of retrieving information is considerably more potent than is an additional study opportunity, particularly in terms of facilitating long-term recall.

How I apply retrieval: I retrieve a book’s content from my memory by writing a book summary for every book I want to remember. I ask myself questions like: “How would you summarize the book in three sentences? Which concepts do you want to keep in mind or apply? How does the book relate to what you already know?”

I then publish my summaries on Goodreads or write an article about my favorite insights

How you can apply retrieval: You can come up with your own questions or use mine. If you don’t want to publish your summaries in public, you can write a summary into your journal, start a book club, create a private blog, or initiate a WhatsApp group for sharing book summaries.

a few days after we learn something, forgetting sets in

#3 Spaced Repetition

With spaced repetition, you repeat the same piece of information across increasing intervals.

The harder it feels to recall the information, the stronger the learning effect. “Spaced practice, which allows some forgetting to occur between sessions, strengthens both the learning and the cues and routes for fast retrieval,”

Why it works: It might sound counterintuitive, but forgetting is essential for learning. Spacing out practice might feel less productive than rereading a text because you’ll realize what you forgot. Your brain has to work harder to retrieve your knowledge, which is a good indicator of effective learning.

How I apply spaced repetition: After some weeks, I revisit a book and look at the summary questions (see #2). I try to come up with my answer before I look up my actual summary. I can often only remember a fraction of what I wrote and have to look at the rest.

“Knowledge trapped in books neatly stacked is meaningless and powerless until applied for the betterment of life.”

How you can apply spaced repetition: You can revisit your book summary medium of choice and test yourself on what you remember. What were your action points from the book? Have you applied them? If not, what hindered you?

By testing yourself in varying intervals on your book summaries, you’ll strengthen both learning and cues for fast retrieval.

Why interleaving works: Alternate working on different problems feels more difficult as it, again, facilitates forgetting.

How I apply interleaving: I read different books at the same time.

1) Highlight everything you want to remember

#5 Self-Testing

While reading often falsely tricks us into perceived mastery, testing shows us whether we truly mastered the subject at hand. Self-testing helps you identify knowledge gaps and brings weak areas to the light

“It’s better to solve a problem than to memorize a solution.”

Why it works: Self-testing helps you overcome the illusion of knowledge. “One of the best habits a learner can instill in herself is regular self-quizzing to recalibrate her understanding of what she does and does not know.”

How I apply self-testing: I explain the key lessons from non-fiction books I want to remember to others. Thereby, I test whether I really got the concept. Often, I didn’t

instead of feeling frustrated, cognitive science made me realize that identifying knowledge gaps are a desirable and necessary effect for long-term remembering.

How you can apply self-testing: Teaching your lessons learned from a non-fiction book is a great way to test yourself. Before you explain a topic to somebody, you have to combine several mental tasks: filter relevant information, organize this information, and articulate it using your own vocabulary.

Now that I discovered how to use my Kindle as a learning device, I wouldn’t trade it for a paper book anymore. Here are the four steps it takes to enrich your e-reading experience

How you can apply interleaving: Your brain can handle reading different books simultaneously, and it’s effective to do so. You can start a new book before you finish the one you’re reading. Starting again into a topic you partly forgot feels difficult first, but as you know by now, that’s the effect you want to achieve.

it won’t surprise you that researchers proved highlighting to be ineffective. It’s passive and doesn’t create memory cues.

2) Cut down your highlights in your browser

After you finished reading the book, you want to reduce your highlights to the essential part. Visit your Kindle Notes page to find a list of all your highlights. Using your desktop browser is faster and more convenient than editing your highlights on your e-reading device.

Now, browse through your highlights, delete what you no longer need, and add notes to the ones you really like. By adding notes to the highlights, you’ll connect the new information to your existing knowledge

3) Use software to practice spaced repetitionThis part is the main reason for e-books beating printed books. While you can do all of the above with a little extra time on your physical books, there’s no way to systemize your repetition praxis.

Readwise is the best software to combine spaced repetition with your e-books. It’s an online service that connects to your Kindle account and imports all your Kindle highlights. Then, it creates flashcards of your highlights and allows you to export your highlights to your favorite note-taking app.

Common Learning Myths DebunkedWhile reading and studying evidence-based learning techniques I also came across some things I wrongly believed to be true.

#2 Effective learning should feel easyWe think learning works best when it feels productive. That’s why we continue to use ineffective techniques like rereading or highlighting. But learning works best when it feels hard, or as the authors of ‘Make It Stick’ write: “Learning that’s easy is like writing in sand, here today and gone tomorrow.”

In Conclusion

I developed and adjusted these strategies over two years, and they’re still a work in progress.

Try all of them but don’t force yourself through anything that doesn’t feel right for you. I encourage you to do your own research, add further techniques, and skip what doesn’t serve you

“In the case of good books, the point is not to see how many of them you can get through, but rather how many can get through to you.”— Mortimer J. Adler

now, after a year of pandemic, I realize that wasn’t the problem. The rubble was real, all right. It just wasn’t normal.

it always, somehow, came back to that essential human craving for things to be normal, and our inability to believe that they are not, even when presented with compelling evidence.

This phenomenon is well-known to cognitive scientists, who have dubbed it “normalcy bias.”

the greater risk is more often the opposite: People can’t quite believe. They ignore the fire alarm, defy the order to evacuate ahead of the hurricane, or pause to grab their luggage when exiting the crashed plane. Too often, they die.

Calling the quest for normalcy a bias makes it sound bad, but most of the time this tendency is a good thing. The world is full of aberrations, most of them meaningless. If we aimed for maximal reaction to every anomaly we encountered, we’d break down from sheer nervous exhaustion.

But when things go disastrously wrong, our optimal response is at war with the part of our brain that insists things are fine. We try to reoccupy the old normal even if it’s become radioactive and salted with mines. We still resist the new normal — even when it’s staring us in the face.

Nine months into our current disaster, I now see that our bitter divides over pandemic response were most fundamentally a contest between two ideas of what it meant to get “back to normal.”

One group wanted to feel as safe as they had before a virus invaded our shores; the other wanted to feel as unfettered

he disputes that followed weren’t just a fight to determine whose idea of normal would prevail. They were a battle against an unthinkable reality, which was that neither kind of normalcy was fully possible anymore.

I suspect we all might have been less willing to make war on our opponents if only we’d believed that we were fighting people not very different from how we were — exhausted by the whole thing and frantic to feel like themselves again

Some catastrophes are simply too big to be understood except in the smallest way, through their most ordinary human details

A valid argument is one where if all the premises are true, so that the conclusion necessarily follows

A non-valid argument is one where even if the premises are true, the conclusion does not necessarily follow

Argumentation is the staple of most, if not all, academic writing

Example of a non-valid argument: If Dr. Litfin were Catholic, he would pray in chapel. Dr. Litfin does pray in chapel. Therefore, Dr. Litfin is Catholic.

Invalidity and unsoundness are often difficult to spot at first glance.

Begging the Question: the conclusion assumes or restates what is explicitly stated in the premise.

Appeal to Ignorance: argues that, since a certain statement or point has not been shown to be false, it must be true—or vice versa.

Not only is the language system thoroughly interactive with a high degree of co-activation across words and concepts, but it also impacts our processing in other domains such as vision, attention and cognitive control.

In other words, it is safe to say that the language you speak influences how you see the world not only figuratively but also quite literally, down to the mechanics of your eye movements.