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A new study out of Germany has found that people are much more confident in the claims of a popular science article then they are in the claims of an academic article written for experts

It was also found that the subjects were more confident in their own judgments after reading a popular article, and that this was tied to a lessened desire to seek out more information from expert sources.

"easiness effect”

the issue arises from the manner in which popular science is presented; as opposed to how scientists themselves present data to each other and to the public.

This emboldens people to reject the ideas of experts who they see as superfluous to their understanding of an idea (which they have already grasped).

notably health

He says readers no longer want an author to prove his or her assertions. They just want to know the author is giving legitimate answers to their questions.

"It's a paradox," he says. "We distrust authority if it's in the form of a major institution, like government, business or Wall Street. But if an individual claims authority in a given field, we assume the person must be telling the truth about his or her credentials. It's the natural trust we extend others -- we typically assume that people are who they say they are."

"But it's also a little bit of intellectual laziness," he adds. "That's what happens in an era when people are famous for being famous instead of famous for having accomplished something distinctive. If you and the media say you're special, you probably are."

With a printed book people feel more committed to reading the entire thing, but with a digital book not so much, which is another reason a lot of today's books are shorter.

Patterns that didn’t change one generation to the next, Dr. Conway called still lifes — such as the four-celled block, the six-celled beehive or the eight-celled pond. Patterns that took a long time to stabilize, he called methuselahs.

Life shows us complex virtual “organisms” arising out of the interaction of a few simple rules — so goodbye “Intelligent Design.”

I first encountered Life at the Exploratorium in San Francisco in 1978. I was hooked immediately by the thing that has always hooked me — watching complexity arise out of simplicity.

Life shows you two things. The first is sensitivity to initial conditions. A tiny change in the rules can produce a huge difference in the output, ranging from complete destruction (no dots) through stasis (a frozen pattern) to patterns that keep changing as they unfold.

The second thing Life shows us is something that Darwin hit upon when he was looking at Life, the organic version. Complexity arises from simplicity!

I’ve wondered for decades what one could learn from all that Life hacking. I recently realized it’s a great place to try to develop “meta-engineering” — to see if there are general principles that govern the advance of engineering and help us predict the overall future trajectory of technology.

Melanie Mitchell— Professor of complexity, Santa Fe Institute

Given that Conway’s proof that the Game of Life can be made to simulate a Universal Computer — that is, it could be “programmed” to carry out any computation that a traditional computer can do — the extremely simple rules can give rise to the most complex and most unpredictable behavior possible. This means that there are certain properties of the Game of Life that can never be predicted, even in principle!

I use the Game of Life to make vivid for my students the ideas of determinism, higher-order patterns and information. One of its great features is that nothing is hidden; there are no black boxes in Life, so you know from the outset that anything that you can get to happen in the Life world is completely unmysterious and explicable in terms of a very large number of simple steps by small items.

In Thomas Pynchon’s novel “Gravity’s Rainbow,” a character says, “But you had taken on a greater and more harmful illusion. The illusion of control. That A could do B. But that was false. Completely. No one can do. Things only happen.”This is compelling but wrong, and Life is a great way of showing this.

Brian Eno— Musician, London

Stephen Wolfram— Scientist and C.E.O., Wolfram Research

In Life, we might say, things only happen at the pixel level; nothing controls anything, nothing does anything. But that doesn’t mean that there is no such thing as action, as control; it means that these are higher-level phenomena composed (entirely, with no magic) from things that only happen.

Bert Chan— Artificial-life researcher and creator of the continuous cellular automaton “Lenia,” Hong Kong

it did have a big impact on beginner programmers, like me in the 90s, giving them a sense of wonder and a kind of confidence that some easy-to-code math models can produce complex and beautiful results. It’s like a starter kit for future software engineers and hackers, together with Mandelbrot Set, Lorenz Attractor, et cetera.

if we think about our everyday life, about corporations and governments, the cultural and technical infrastructures humans built for thousands of years, they are not unlike the incredible machines that are engineered in Life.

In normal times, they are stable and we can keep building stuff one component upon another, but in harder times like this pandemic or a new Cold War, we need something that is more resilient and can prepare for the unpreparable. That would need changes in our “rules of life,” which we take for granted.

Rudy Rucker— Mathematician and author of “Ware Tetralogy,” Los Gatos, Calif.

That’s what chaos is about. The Game of Life, or a kinky dynamical system like a pair of pendulums, or a candle flame, or an ocean wave, or the growth of a plant — they aren’t readily predictable. But they are not random. They do obey laws, and there are certain kinds of patterns — chaotic attractors — that they tend to produce. But again, unpredictable is not random. An important and subtle distinction which changed my whole view of the world.

William Poundstone— Author of “The Recursive Universe: Cosmic Complexity and the Limits of Scientific Knowledge,” Los Angeles, Calif.

The Game of Life’s pulsing, pyrotechnic constellations are classic examples of emergent phenomena, introduced decades before that adjective became a buzzword.

Fifty years later, the misfortunes of 2020 are the stuff of memes. The biggest challenges facing us today are emergent: viruses leaping from species to species; the abrupt onset of wildfires and tropical storms as a consequence of a small rise in temperature; economies in which billions of free transactions lead to staggering concentrations of wealth; an internet that becomes more fraught with hazard each year

Looming behind it all is our collective vision of an artificial intelligence-fueled future that is certain to come with surprises, not all of them pleasant.

The name Conway chose — the Game of Life — frames his invention as a metaphor. But I’m not sure that even he anticipated how relevant Life would become, and that in 50 years we’d all be playing an emergent game of life and death.

This suggests that we imagine a complex reality in which things might be true — materially, spiritually, psychologically

Westerners, by contrast, not only tolerate fantasy play but actively encourage it, for adults as well as for children. We are novel readers, movie watchers and game players.

“Inventive pretend,” in which children pretend the fantastic or impossible (enchanted princesses, dragon hunters) “is rarely — if ever — observed in non-industrialized or traditional cultures,”

Science leads us to draw a sharp line between what is real and what is unreal. At the same time, we live in an age in which we are exquisitely aware that there are many theories, both religious and scientific, to explain the world, and many ways to be human.

Probably fiction does for us what the vision of Aslan did for Bob: it helps us to learn what we find emotionally true in the face of irreconcilable contradictions.

fiction teaches us how to think about what we take to be true. In the cacophony of an information-soaked age, we need it.

But political puritans such as Cruz and Sanders tend to make policy the way they explain the world — with unwarranted, clumsy simplicity.

Authentically believing that the whole country secretly agrees with your agenda and will join you on the barricades is not a virtue, it is a fantasy. Sincerely proposing poorly thought-out policy does not change the fact that it is poorly thought-out policy.

Charting how exactly the heart and mind interact while forcing the body to move along, it’s Tegan and Sara’s current appeal distilled as if for an instruction manual on the art of joy

A woman named Diana, who wore star-and-flower earrings, said that before she tidied, her life was out of control. Her job had been recently eliminated when she found the book. “It’s a powerful message for women that you should be surrounded by things that make you happy,”

“I found the opposite of happiness is not sadness,” Diana told us. “It’s chaos.”

Another woman said she KonMaried a bad boyfriend. Having tidied everything in her home and finding she still distinctly lacked happiness, she held her boyfriend in her hands, realized he no longer sparked joy and got rid of him.

She realized that the work she was doing as a tidying consultant was far more psychological than it was practical. Tidying wasn’t just a function of your physical space; it was a function of your soul.

. She wants you to override the instinct to keep a certain thing because an HGTV show or a home-design magazine or a Pinterest page said it would brighten up your room or make your life better. She wants you to possess your possessions on your own terms, not theirs

she would say to him what she said to me, that yes, America is a little different from Japan, but ultimately it’s all the same. We’re all the same in that we’re enticed into the false illusion of happiness through material purchase.

each organizer I spoke with said that she had the same fundamental plan that Kondo did, that the client should purge (they cry “purge” for what Kondo gently calls “discarding”) what is no longer needed or wanted; somehow the extra step of thanking the object or folding it a little differently enrages them. This rage hides behind the notion that things are different here in America, that our lives are more complicated and our stuff is more burdensome and our decisions are harder to make.

Conference was different from the KonMari events that I attended. Whereas Kondo does not believe that you need to buy anything in order to organize and that storage systems provide only the illusion of tidiness, the women of Conference traded recon on timesaving apps, label makers, the best kind of Sharpie, the best tool they own (“supersticky notes,” “drawer dividers”)

They don’t like that you have to get rid of all of your papers, which is actually a misnomer: Kondo just says you should limit them because they’re incapable of sparking joy, and you should confine them to three folders: needs immediate attention, must be kept for now, must be kept forever.

She leaves room for something that people don’t often give her credit for: that the KonMari method might not be your speed. “I think it’s good to have different types of organizing methods,” she continued, “because my method might not spark joy with some people, but his method might.

Ultimately, the women of NAPO said that Kondo’s methods were too draconian and that the clients they knew couldn’t live in Kondo’s world. They had jobs and children, and they needed baby steps and hand-holding and maintenance plans. They needed someone to do for them what they couldn’t naturally do for themselves.

the most potent difference between Kondo and the NAPO women is that the NAPO women seek to make a client’s life good by organizing their stuff; Kondo, on the other hand, leads with her spiritual mission, to change their lives through magic.

She went to work in finance, but she found the work empty and meaningless. She would come home and find herself overwhelmed by her stuff. So she began searching for “minimalism” on the internet almost constantly, happening on Pinterest pages of beautiful, empty bathrooms and kitchens, and she began to imagine that it was her stuff that was weighing her down. She read philosophy blogs about materialism and the accumulation of objects. “They just all talked about feeling lighter,”

“I never knew how to get here from there,” she said. Ning looked around her apartment, which is spare. She loves it here now, but that seemed impossible just a couple of years ago.

She found Kondo’s book, and she felt better immediately, just having read it. She began tidying, and immediately she lost three pounds. She had been trying to lose weight forever, and then suddenly, without effort, three pounds, just gone.

when it comes to stuff, we are all the same. Once we’ve divided all the drawers and eliminated that which does not bring us joy and categorized ourselves within an inch of our lives, we’ll find that the person lying beneath all the stuff was still just plain old us. We are all a mess, even when we’re done tidying.

“In bad conditions, the only chance of success is to take a chance and hope it works out, and that’s what the plants are doing,

This complex behavior in a plant supports an idea, known as risk sensitivity theory, that scientists have long had trouble testing in insects and animals. It states that when choosing between stable and uncertain outcomes, an organism will play it safe when things are going well, and take risks when times are hard.

The simplicity of plants makes it much easier to create a proper test for at least one reason: Plants don’t worry about feelings.

“[Science] requires technical skill and it is a process of creating something new where you cannot always predict the outcome.”

Many scientists work under the principle that beauty and simplicity often underlie phenomena in nature,” says biophysicist Joshua Shaevitz. His work, “The history of gliding,”

is a dazzling array of colorful filaments made by tracking the paths of hundreds of thousands of the social bacterium Myxococcus xanthus. “The process of scientific research often seems dull from the outside, but on the inside there are stunningly beautiful elements to all aspects of nature,” says Shaevitz.

mobile payment system for its stores

And in a change of strategy for Walmart, its new payment app does not seek to bypass credit card companies.

“When you look at these things, the customer has constraints put upon them, and that creates frictions and seams in the shopping experience,” Mr. Eckert said. “But Walmart Pay works with any smartphone and almost any payment type.”

“And once that happens, literally, the customer is done,”

“They can put their phone away. Once the transaction’s complete, we total up the register, and the customer can leave.”

There are also concerns over security.

We insist that meritocracy works and combine it with a valorization of hard work (which itself stems from our country’s majority-Protestant roots). To maintain the story that success is accessible to all, we’ve developed a tendency to seek out and elevate simplistic formulas that we hope come with guarantees. Stay pure until marriage, and your marriage will flourish. Follow the “success sequence,” and you’ll never be poor. Go to the right school, and all career doors will open. Elect the right candidate, and America will be great once more.

More generative for him are the examples of artists who became known as Minimalists even as they disavowed the term.

What’s most striking about Chayka’s minimalist gestures is how frail they seem next to the larger upheavals that are taking place.

Discussing the renunciatory philosophy of the Stoics and Henry David Thoreau, he discerns “a strategy of avoidance, especially in moments when society feels chaotic or catastrophic.” There’s a strain of this in contemporary lifestyle minimalism, which offers self-protection and retreat: “Your bedroom might be cleaner, but the world stays bad.”

The minimalism that Chayka seeks encourages not an escape from the world but a deeper engagement with it

Chayka’s journey ends in a rock garden in Kyoto, where serene contemplation contends with jostling visitors.

“Up through the 20th century, material accumulation and stability made sense as forms of security,” Chayka writes. “Little of this feels true today.” Tangible goods now cost exceedingly less, and intangible “forms of security” cost exceedingly more.

After all, it’s unlikely that the tchotchkes or the new TV set will toss you into financial straits; it’s the college tuition that will put you into crushing debt, the very real possibility you’ll outlive your meager retirement account, or the medical treatment not covered by insurance.

Reading Chayka’s book put me in mind of a longing for less stuff, and a longing for more support.

Many biological ideas proposed during the past 150 years stood in stark conflict with what everybody assumed to be true. The acceptance of these ideas required an ideological revolution. And no biologist has been responsible for more—and for more drastic—modifications of the average person’s worldview than Charles Darwin

. Evolutionary biology, in contrast with physics and chemistry, is a historical science—the evolutionist attempts to explain events and processes that have already taken place. Laws and experiments are inappropriate techniques for the explication of such events and processes. Instead one constructs a historical narrative, consisting of a tentative reconstruction of the particular scenario that led to the events one is trying to explain.

The discovery of natural selection, by Darwin and Alfred Russel Wallace, must itself be counted as an extraordinary philosophical advance

The concept of natural selection had remarkable power for explaining directional and adaptive changes. Its nature is simplicity itself. It is not a force like the forces described in the laws of physics; its mechanism is simply the elimination of inferior individuals

A diverse population is a necessity for the proper working of natural selection

Because of the importance of variation, natural selection should be considered a two-step process: the production of abundant variation is followed by the elimination of inferior individuals

By adopting natural selection, Darwin settled the several-thousandyear- old argument among philosophers over chance or necessity. Change on the earth is the result of both, the first step being dominated by randomness, the second by necessity

Another aspect of the new philosophy of biology concerns the role of laws. Laws give way to concepts in Darwinism. In the physical sciences, as a rule, theories are based on laws; for example, the laws of motion led to the theory of gravitation. In evolutionary biology, however, theories are largely based on concepts such as competition, female choice, selection, succession and dominance. These biological concepts, and the theories based on them, cannot be reduced to the laws and theories of the physical sciences

Despite the initial resistance by physicists and philosophers, the role of contingency and chance in natural processes is now almost universally acknowledged. Many biologists and philosophers deny the existence of universal laws in biology and suggest that all regularities be stated in probabilistic terms, as nearly all so-called biological laws have exceptions. Philosopher of science Karl Popper’s famous test of falsification therefore cannot be applied in these cases.

To borrow Darwin’s phrase, there is grandeur in this view of life. New modes of thinking have been, and are being, evolved. Almost every component in modern man’s belief system is somehow affected by Darwinian principles

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.

This is a key point about language use: rarely is natural language ever limited to speech alone. When we are speaking, we constantly use gestures to illustrate what we mean. For this reason, linguists say that language is “multi-modal”. Writing takes away that extra non-verbal information, but emoji may allow us to re-incorporate it into our text.

Emoji are not always used as embellishments, however – sometimes, strings of the characters can themselves convey meaning in a longer sequence on their own. But to constitute their own language, they would need a key component: grammar.

A grammatical system is a set of constraints that governs how the meaning of an utterance is packaged in a coherent way. Natural language grammars have certain traits that distinguish them. For one, they have individual units that play different roles in the sequence – like nouns and verbs in a sentence. Also, grammar is different from meaning

When emoji are isolated, they are primarily governed by simple rules related to meaning alone, without these more complex rules. For instance, according to research by Tyler Schnoebelen, people often create strings of emoji that share a common meaning

This sequence has little internal structure; even when it is rearranged, it still conveys the same message. These images are connected solely by their broader meaning. We might consider them to be a visual list: “here are all things related to celebrations and birthdays.” Lists are certainly a conventionalised way of communicating, but they don’t have grammar the way that sentences do.

What if the order did matter though? What if they conveyed a temporal sequence of events? Consider this example, which means something like “a woman had a party where they drank, and then opened presents and then had cake”:

In all cases, the doer of the action (the agent) precedes the action. In fact, this pattern is commonly found in both full languages and simple communication systems. For example, the majority of the world’s languages place the subject before the verb of a sentence.

These rules may seem like the seeds of grammar, but psycholinguist Susan Goldin-Meadow and colleagues have found this order appears in many other systems that would not be considered a language. For example, this order appears when people arrange pictures to describe events from an animated cartoon, or when speaking adults communicate using only gestures. It also appears in the gesture systems created by deaf children who cannot hear spoken languages and are not exposed to sign languages.

describes the children as lacking exposure to a language and thus invent their own manual systems to communicate, called “homesigns”. These systems are limited in the size of their vocabularies and the types of sequences they can create. For this reason, the agent-act order seems not to be due to a grammar, but from basic heuristics – practical workarounds – based on meaning alone. Emoji seem to tap into this same system.

Nevertheless, some may argue that despite emoji’s current simplicity, this may be the groundwork for emerging complexity – that although emoji do not constitute a language at the present time, they could develop into one over time.

Could an emerging “emoji visual language” be developing in a similar way, with actual grammatical structure? To answer that question, you need to consider the intrinsic constraints on the technology itself.Emoji are created by typing into a computer like text. But, unlike text, most emoji are provided as whole units, except for the limited set of emoticons which convert to emoji, like :) or ;). When writing text, we use the building blocks (letters) to create the units (words), not by searching through a list of every whole word in the language.

emoji force us to convey information in a linear unit-unit string, which limits how complex expressions can be made. These constraints may mean that they will never be able to achieve even the most basic complexity that we can create with normal and natural drawings.

What’s more, these limits also prevent users from creating novel signs – a requisite for all languages, especially emerging ones. Users have no control over the development of the vocabulary. As the “vocab list” for emoji grows, it will become increasingly unwieldy: using them will require a conscious search process through an external list, not an easy generation from our own mental vocabulary, like the way we naturally speak or draw. This is a key point – it means that emoji lack the flexibility needed to create a new language.

we already have very robust visual languages, as can be seen in comics and graphic novels. As I argue in my book, The Visual Language of Comics, the drawings found in comics use a systematic visual vocabulary (such as stink lines to represent smell, or stars to represent dizziness). Importantly, the available vocabulary is not constrained by technology and has developed naturally over time, like spoken and written languages.

grammar of sequential images is more of a narrative structure – not of nouns and verbs. Yet, these sequences use principles of combination like any other grammar, including roles played by images, groupings of images, and hierarchic embedding.

measured participants’ brainwaves while they viewed sequences one image at a time where a disruption appeared either within the groupings of panels or at the natural break between groupings. The particular brainwave responses that we observed were similar to those that experimenters find when violating the syntax of sentences. That is, the brain responds the same way to violations of “grammar”, whether in sentences or sequential narrative images.

I would hypothesise that emoji can use a basic narrative structure to organise short stories (likely made up of agent-action sequences), but I highly doubt that they would be able to create embedded clauses like these. I would also doubt that you would see the same kinds of brain responses that we saw with the comic strip sequences.

But that blessed feeling evaporated in June of 2019, when I lost my daughter, Frankie, to suicide, three weeks before her high school graduation

Ever since that day, I have thought of little else except how I could help the next struggling teenager, the next Frankie.

Several days after her passing, we opened our home up to our community, including Frankie’s very large group of teenage friends

“What strength Frankie had. It must have taken enormous energy for her to do what she did each day.”

That was Frankie. She had the strength to engage in school and in theater, despite her anxiety and depression. She had an ability to connect — emotionally, profoundly — with others, even when she was struggling herself

“empathy personified, with quite the fabulous earring collection.”

Whether that strength came from her home or somewhere else, or both, Frankie just had a way of drawing out warmth wherever she went.

Just as my parents couldn’t predict in the 1980s what seatbelt safety would look like now, I am not sure what suicide prevention should look like in the future.

Suicidal thinking, whether it is the result of mental illness, stress, trauma or loss, is actually far more common and difficult to see than many of us realize

A June 2020 Centers for Disease Control survey found that one in four 18- to 24-year-olds reported that they had seriously thought about taking their lives in the past 30 days; prepandemic estimates found that just under one in five high schoolers had seriously considered suicide, and just under one in 10 had made at least one suicide attempt during the previous year.

Despite 50 years of research, predicting death by suicide is still nearly impossible

Like others who have lost a child to suicide, I have spent countless hours going over relentless “what ifs.”

Maybe what we need are seatbelts for suicide.

“Click it or Ticket” was born in part out of a concern in the 1980s about teenagers dying in car accidents. Just as with suicides today, adults couldn’t predict who would get into a car accident, and one of the best solutions we had — seatbelts — was used routinely, in some estimates, by only 15 percent of the population. Indeed, as children, my siblings and I used to make a game of rolling around in the back of our car, seatbelts ignored.

Three decades later, our world is unlike anything I could have imagined as a child. Putting on a seatbelt is the first lesson of driver’s education; cars get inspected annually for working seatbelts; car companies embed those annoying beeping sounds to remind you to buckle your seatbelt

But like many who struggle with suicidal thinking, she kept her own pain camouflaged for a long time, perhaps for too long.

Most of us (estimates range as high as 91 percent) now wear a seatbelt.

But I imagine a world in which every health worker, school professional, employer and religious leader can recognize the signs of suicidal thinking and know how to ask about it, respond to it and offer resources to someone who is struggling

When I told Frankie’s orthodontist about her suicide, his response surprised me: “We really don’t come across that in our practice.” Even though orthodontists don’t ask about it, they see children during their early teenage years, when suicidal thinking often begins to emerge. Can you imagine a world in which signs for the prevention hotline and text line are posted for kids to see as they get their braces adjusted?

What if the annual teenage pediatric checkup involved a discussion of one-at-a-time pill packaging and boxes to lock up lethal medications, the way there is a discussion of baby-proofing homes when children start to crawl? What if pediatricians handed each adolescent a card with the prevention hotline on it (or better yet, if companies preprogrammed that number into cellphones) and the pediatrician talked through what happens when a teenager calls? What if doctors coached parents on how to ask their teenager, “Are you thinking about suicide?”

What if we required and funded every school to put in place one of the existing programs that train teachers and other school professionals to be a resource for struggling students?

I recognize that despite progress identifying effective programs to combat suicidal thinking, their success rate and simplicity does not compare with what we see with seatbelts. But that doesn’t mean we shouldn’t do more.

Part of doing more also includes making the world more just and caring. To give one example, state-level same-sex-marriage policies that were in place before the Supreme Court legalized same-sex marriage nationally have been linked to reductions in suicide attempts among adolescents, especially among sexual minorities.

Just as safer highways and car models make seatbelts more effective, asking about and responding to suicidal thinking is only one part of a solution that also includes attention to societal injustices.

I understand, of course, that asking about suicidal thinking is scary. But if it is scary for you to ask about it, it is even scarier for the teenager who is thinking about it.

I will never forget sitting with Frankie in the waiting room in the pediatric psychiatric wing on the night I brought her to the inpatient unit, three months before she took her life

“You know, I am so glad you finally know.” I could hear the relief in her voice. I just nodded, understandingly, but it broke my heart that she held on to such a painful secret for so long.

I find myself inspired by Frankie’s teenage friends, who cared deeply for her and now support one another after her passing.

On good days, she would sit on the worn couch in that office, snuggle in a pile of teenagers and discuss plays, schoolwork and their lives.

And in that corner space, she would text a friend to help her get to class or, after she had opened up about her struggles, encourage others to open up as well.

The fall after Frankie left us, some students decided to remake that hidden corner, dotting the walls with colored Post-it notes. Scrawled on a pink Post-it were the words “you matter”; a yellow one read “it gets better”; an orange one shared a cellphone number to call for help. Tiny Post-it squares had transformed the corner into a space to comfort, heal and support the next struggling teenager.

I don’t know if a seatbelt approach would have saved Frankie. And I understand that all the details of such an approach aren’t fully worked out here. But I don’t want us to lose any more children because we weren’t brave enough to take on something that scares us, something we don’t fully understand, something that is much more prevalent than many of us realize.

If 17- and 18-year-olds who’ve lost a friend have the strength to imagine a world dotted with healing, then the least we can do as adults is design and build the structure to support them

Applied welfare economics is the fruition of microeconomics.

It is hard to imagine a basic course in microeconomics failing to include numerous cases and examples drawn from all of the fields listed above. This is because microeconomics is so basic. It represents the trunk of the tree from which all the listed subfields have branche

The specialization of production and the institutions of trade, commerce, and markets long antedated the science of economics. Indeed, one can fairly say that from the very outset the science of economics entailed the study of the market forms that arose quite naturally (and without any help from economists) out of human behavior

In microeconomics this is translated into the notion of people maximizing their personal “utility,” or welfare.

At the beginning of the process, those who adopted the new hybrids made handsome profits.

The economics of supply and demand has a sort of moral or normative overtone, at least when it comes to dealing with a wide range of market distortions. In an undistorted market, buyers pay the market price up to the point where they judge further units not to be worth that price, while competitive sellers supply added units as long as they can make money on each increment.

The strength of microeconomics comes from the simplicity of its underlying structure and its close touch with the real world. In a nutshell, microeconomics has to do with supply and demand, and with the way they interact in various markets.

If price controls keep bread (or anything else) artificially cheap, the predictable result is that less will be supplied than is demanded.

Had the government given wheat farmers coupons, each of which permitted the farmer to market one bushel of wheat, wheat marketings could have been cut by the desired amount. Production inefficiencies could be avoided by allowing the farmers to buy and sell coupons among themselves.

monopoly represents the artificial restriction of production by an entity having sufficient “market power” to do so.

Modern monopolies are a bit less transparent, for two reasons. First, even though governments still grant monopolies, they usually grant them to the producers. Second, some monopolies just happen without government creating them, although these are usually short-lived.

A final example of what occurs with official prices that are too high is the phenomenon of “rent seeking,” which occurs when someone enters a business to earn a profit that the government has tried to make unusually high.

If the wage does not adjust downward to equate supply and demand, the rate of urban unemployment will rise until further migration is deterred. Still other examples are in banking and drugs.

Rent seeking also occurs when something of value (like import licenses or radio/TV franchises) is being given away or sold below its true value

The great unifying principles of microeconomics are, ever and always, supply and demand. The normative overtone of microeconomics comes from the fact that competitive supply price represents value as seen by suppliers, and competitive demand price represents value as seen by demanders.

The faith of those who believed in Progress was based on the assumption that one could discern a purpose to the human enterprise, even without the theological scaffolding that supported the Christian edifice of belief. Science and technology were the chief instruments of Progress, and · i.Lac_cumulation of reliable in orma on a out nature _1b_n, would bring ignorance, superstition, and suffering to an end.

In T ~chnopoly, we are driven to fill our lives with the quesUo "accesTinformation.

But the genie that came out of the bottle proclaiming that information was the new god of culture was a deceiver. It solved the problez:n of information scarcity, the disadvantages o_f wh~s~ious. But it gave no wami g_ahout the dan_gers of information7rttn,

!:ion of what is called a_ curriculum was a logical step toward 1./ organizing, limiting, and discriminating among available sources of information. Schools became technocracy's first secular bureaucracies, structures for legitimizing some parts of the flow of infgrmatiQD and di"s.ci.e.diling other earts. School;;ere, in short, a ~eans of governing the ecology of information.

it is why in _a TechnoE,.oly there can be no transcendent sense of purpose or meaning, no cultural coherence.

There were several reasons for the rapid growth of the common school, but none was more obvious than that it was a necessary response to the anxiefies and confusion aroused by information on the loose. The inven-

The milieu in which T echnopoly flourishes is one in which the tie between information and human purpose has been severed, i.e., inf~rmation appears indiscriminately, directed at no one in particular, in enormous volume and at high speeds; and disconnected from theory, meaning, or purpose.

Abetted ~~orm of ed~~on that in itself has been em _lie~any co~e~ent world-view, Technopoly deprives us of the social, p·olitical, historical, mefaphys1cal, logical, or spiritual bases for knowing what is beyond belief.

There is not a single line written by Jefferson, Adams, Paine, Hamilton, or Franklin that does not take for granted that when information is made available to citizens they are capable of managing it. This is not to say that the Founding Fathers believed information could not be false, misleading, or irrelevant. But they believed that the marketplace of infonpation and ideas was sufficiently ordered so that citizens could make sense of what they read and heard and, through reason, judge ·its μsefulness to their lives. Jefferson's proposals for education, Paine'~ arguments for self-governance, Franklin's arrangements for community affairs assume coherent, commonly shared principles.that allow us to debate such questions as: What are the responsibilities of citizens? What is the nature of education? What constitutes human progress? What are the limitations of social structures?

New forms of public discourse came into being through newspapers, pamphlets, broadsides, and books.

First Amendment to the United States Constitution stands as a monument to the ideolo_g~~ print. It says: "Congress shall make no law respecting the establishment of religion, or prohibiting the free exercise thereof; or abridging freedom of speech or of the press; or of the right of the people peaceably to assemble, and to petition the government for a redress of grievances." In these forty-five words we may find the fundamental values of the literate, reasoning_giind as fostered by the print revolution: a belief in privacy, individuality, intellectual freedom, open criticism, and ~.' adio .

telegraphy created the idea of context-free . 1 informatig_n::= that fs'~the idea that the value of information need ;;~t be ti~ to any function it might serve in social and political

decision-making and action. The telegraph made information into a commodity, a "thing" that could be bought and sold irrespective of its uses or meaning. 2

a new definition qf information came into being. Here was information that rejected the necessit ·of interco~nectedness, proceeded without conte~rgued for instancy against historic continuity, and offere · ascination· in place of corn !exit and cohe ence.

the fourth stage of the information revolution occurred, broadcasting. And then the fifth, computer technology. Each of these brought with it new forms of information, unpre~edented amounts of it, and increased speeds

photography was invented at approximately the same time a~phy, and initiated the Ehi:rd stage of the information revolution. Daniel Boorstin has called it "the graphic revolution," bec~use the photograph and other ico~ogr~phs br~ on a massive intrusion of ima es into the symbolic environment:

~ the beginning of the seventeenth century, an entirely new information environment had been created by_12rint

It is an improbable world. It is a world in which the idea of human progress, as Bacon ex~sed it, has been g~ by the idea of technological progress.

echnopoly is a state of cttlture., It is also a st~te of mind. It consists in the deification of technology, which means that the culture seeks its authorization in te0,~logy, finds · .atisf~tions in technolo , and takes its orders from technolog-¥,

Th_e relationship between information and the mechanisms ( for its control is fairly simple ~ec · ·ology increases the available supply of information. As the supply is increased, \ control mechanisms are strained. Additional control mech\ anisms ~re needed to cope with new information. When addi1 tional control mechanisms are themselves technical, they in tum I further increase the supply of information. When the supply of information is no longer controllable, a general breakdown in psychic tranquillity and social purpose occurs. Without defenses, people have no way of finding meaning in their experiences, lose their capacity to remember, and have difficulty imagining reasonable futures.

any decline in the force of i~~~ti'?n_s makes people vulnerable to information chaos. 1 To say that life is destabilized by weakened institutions is merely to say that information loses its use and therefore becomes a source of confu;~n rather than coherence.

T echnop_oly, then, is to say it is what h~pens to society when the defe~ainst informati;~ glut have broken down.

the school as a mechanism for information control. What its standards are can usually be found in, a curriculum or, with even more clarity, in a course catalogue. A college catalogue lists courses, subjects, and fields of study that, taken together, amount to a certified statement of what a serious student ought to think about.

In the West, the family as an institution for the management of nonbiological information began with the ascendance of print. As books on every conceivable subject become available, parent_~ were forced int°._the roles of guard-· ians'... protectors, nurturers, and arbiters of taste and rectitude. \ Their function was to define what it means to be a child by \ excluding from the family's domain information that would 1. undermine its purpose.

all_ theories are oversimplifications, or at least lead to oversimplification. The rule of law is an oversimplification. A curriculum is an oversimplification. So is a family's conception of a child. T~~t is the funt!ion _o._Ltheories-_ to o~~~~ip:lp}}_fy, and thus to assist believers in_ organiziDg, weighting, _ _an~_ excluding information. Therein lies the power of theories.

The political party is another.

The most imposing institutions for the control of information are religio!1 ~nd the st~J:f, .. They do their work in a somewhat more abstract way than do courts, schools, families, or political parties. The_y m?n~g~__Ji;1formation throug~ creation of mytJ:is and stories that express theories about funq1m1entaf question_s_:_ __ 10:_hy are we here, where have we come from, and where are we headed?

any educational institution, if it is to function well in the mana~~nt of information, must have a theory about its purpose and meaning-'. .!n'!::!Sl. have the means to give clear expression to its_ theory, and must do so, to a large extent, by excluding information.

Those who reject the Bible's theory and who believe, let us say, in the theory of Science are also protected from unwanted information. Their theory, for example, instructs them to disregard information about astrology, dianetics, and creationism, which they usually label as medieval superstition or subjective opinion.

thought-world that functions not only without a transcendent; narrative to provide moral underpinnings but also without strong social institutions to control the flood of information produced by technology.

In the r case of the United States, the great eighteenth-century revolution was not indifferent to commodity capitalism but was nonetheless infused with profound moral content. The U~!ed States was not merely an experiment in a new form of governance; it wai1nefu1fillmenl-oFGocf s plan. True, Adams, Jeffe;son, and Painere1ected-fne supernatural elements in the Bible,· but they never doubted that their experiment had the imprimatur of \ Providence. People were to be free but for a eurp_9se. Their [ God~giv_e~ig[ifs im li~_? obli ations and responsibilities, not L onfytoGod but to other nations, to which the new republic would be a guide and a showcase of what is possible-w~en reason and spirituality commingle.

American Technopoly must rel,y, to an obsessive extent, on technica( ~ethods to control the flow of information. Three such means merit speci attention.

Francis Fukuyama is wrong. There is another ideological conflict to be fought-between "liberal democracy" as conceived in the eighteenth century, with all its transcendent moral underpinnings, and T echnopoly, a twentieth-century

in at- ~ tempting to make the most rational use of information, bureaucracy ignores all information and ideas that do not contribute to efficiency

in principle a bureaucracy is simply a coordinated series of techniques for reducing the amount of information that requires processing.

The transformation of bureaucracy from a set of techniques·> designecfto serve social ~tutions to an auton-;;mous metainstitution that largely serves itself came as a result of several developments in the mid-andlate-nineteenth century: rapid ../ industrial growth, improvements in transportation and commu- ·✓ nication, the extension of government into ever-larger realms of V public and business affairs, the increasing centralization of gov- v ernmental structures.

Along the way, it ceased to be merely a servant of social institutions an

became ~ their master. Bureaucracy now not only solves problems but creates them. More important, it defines what our problems are---and they arec!.lways, in the bureaucra!!c view, problems of l . , efficiency.

Th_~-role of t!;_e ~xpert is to concentrate o_l}_one_ .H~ld of knowledge, sift through all that is available, eliminate that -.--:-: __ __:~---------which has no bearing on a problem, and use what is left !Q. !!§Sist in solving a probl~.

Institutions ca~~aked~cisions on the basis of scores and. sfatistics, and. there certainly may be occasions where there is no reasonable alternative. But unless such decisions are made with profound skepticism-that is, acknowledged as being made for administrative convenience-they are delusionary.

The god they serve does not speak \ of righteousness or goodness or mercy or grace. Their god speaks of efficiency, precision, objectivity. And that is why such concepts as sin and evil disappear in Technopoly. They come from a moral universe that is irrelevant to the theology of expertise. And so the priests of Technopoly call sin "social deviance," which is a statistical concept, and they call evil "psychopathology," which is a medical concept. Sin and evil disappear because they cannot be measured and objectified, and therefore cannot be dealt with by experts.