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Bush wanted to remake the world. President Trump, by contrast, just wants to make it up as he goes along

Through all their debates over who is to blame for imperiling truth (whether Trump, postmodernism, social media or Fox News), as well as the consequences (invariably dire) and the solutions (usually vague), a few conclusions materialize, should you choose to believe them.

There is a pattern and logic behind the dishonesty of Trump and his surrogates; however, it’s less multidimensional chess than the simple subordination of reality to political and personal ambition

Trump’s untruth sells best precisely when feelings and instincts overpower facts, when America becomes a safe space for fabrication.

Rand Corp. scholars Jennifer Kavanagh and Michael D. Rich point to the Gilded Age, the Roaring Twenties and the rise of television in the mid-20th century as recent periods of what they call “Truth Decay” — marked by growing disagreement over facts and interpretation of data; a blurring of lines between opinion, fact and personal experience; and diminishing trust in once-respected sources of information.

In eras of truth decay, “competing narratives emerge, tribalism within the U.S. electorate increases, and political paralysis and dysfunction grow,”

intelligent-design proponents and later climate deniers drew from postmodernism to undermine public perceptions of evolution and climate change. “Even if right-wing politicians and other science deniers were not reading Derrida and Foucault, the germ of the idea made its way to them: science does not have a monopoly on the truth,

To interpret our era’s debasement of language, Kakutani reflects perceptively on the World War II-era works of Victor Klemperer, who showed how the Nazis used “words as ‘tiny doses of arsenic’ to poison and subvert the German culture,” and of Stefan Zweig, whose memoir “The World of Yesterday” highlights how ordinary Germans failed to grasp the sudden erosion of their freedoms.

Kakutani calls out lefty academics who for decades preached postmodernism and social constructivism, which argued that truth is not universal but a reflection of relative power, structural forces and personal vantage points.

postmodernists rejected Enlightenment ideals as “vestiges of old patriarchal and imperialist thinking,” Kakutani writes, paving the way for today’s violence against fact in politics and science.

“dumbed-down corollaries” of postmodernist thought have been hijacked by Trump’s defenders, who use them to explain away his lies, inconsistencies and broken promises.

Once you add the silos of social media as well as deeply polarized politics and deteriorating civic education, it becomes “nearly impossible to have the types of meaningful policy debates that form the foundation of democracy.”

McIntyre quotes at length from mea culpas by postmodernist and social constructivist writers agonizing over what their theories have wrought, shocked that conservatives would use them for nefarious purposes

pro-Trump troll and conspiracy theorist Mike Cernovich , who helped popularize the “Pizzagate” lie, has forthrightly cited his unlikely influences. “Look, I read postmodernist theory in college,” Cernovich told the New Yorker in 2016. “If everything is a narrative, then we need alternatives to the dominant narrative. I don’t seem like a guy who reads [Jacques] Lacan, do I?

When truth becomes malleable and contestable regardless of evidence, a mere tussle of manufactured narratives, it becomes less about conveying facts than about picking sides, particularly in politics.

In “On Truth,” Cambridge University philosopher Simon Blackburn writes that truth is attainable, if at all, “only at the vanishing end points of enquiry,” adding that, “instead of ‘facts first’ we may do better if we think of ‘enquiry first,’ with the notion of fact modestly waiting to be invited to the feast afterward.

He is concerned, but not overwhelmingly so, about the survival of truth under Trump. “Outside the fevered world of politics, truth has a secure enough foothold,” Blackburn writes. “Perjury is still a serious crime, and we still hope that our pilots and surgeons know their way about.

Kavanaugh and Rich offer similar consolation: “Facts and data have become more important in most other fields, with political and civil discourse being striking exceptions. Thus, it is hard to argue that the world is truly ‘post-fact.’ ”

McIntyre argues persuasively that our methods of ascertaining truth — not just the facts themselves — are under attack, too, and that this assault is especially dangerous.

Ideologues don’t just disregard facts they disagree with, he explains, but willingly embrace any information, however dubious, that fits their agenda. “This is not the abandonment of facts, but a corruption of the process by which facts are credibly gathered and reliably used to shape one’s beliefs about reality. Indeed, the rejection of this undermines the idea that some things are true irrespective of how we feel about them.”

“It is hardly a depressing new phenomenon that people’s beliefs are capable of being moved by their hopes, grievances and fears,” Blackburn writes. “In order to move people, objective facts must become personal beliefs.” But it can’t work — or shouldn’t work — in reverse.

More than fearing a post-truth world, Blackburn is concerned by a “post-shame environment,” in which politicians easily brush off their open disregard for truth.

it is human nature to rationalize away the dissonance. “Why get upset by his lies, when all politicians lie?” Kakutani asks, distilling the mind-set. “Why get upset by his venality, when the law of the jungle rules?”

So any opposition is deemed a witch hunt, or fake news, rigged or just so unfair. Trump is not killing the truth. But he is vandalizing it, constantly and indiscriminately, diminishing its prestige and appeal, coaxing us to look away from it.

the collateral damage includes the American experiment.

“One of the most important ways to fight back against post-truth is to fight it within ourselves,” he writes, whatever our particular politics may be. “It is easy to identify a truth that someone else does not want to see. But how many of us are prepared to do this with our own beliefs? To doubt something that we want to believe, even though a little piece of us whispers that we do not have all the facts?”

Reich simply points out that this utopian fiction is in danger of collapse because it is not true and because genetic research is increasingly proving it untrue.

“You will sometimes hear that any biological differences among populations are likely to be small, because humans have diverged too recently from common ancestors for substantial differences to have arisen under the pressure of natural selection. This is not true. The ancestors of East Asians, Europeans, West Africans and Australians were, until recently, almost completely isolated from one another for 40,000 years or longer, which is more than sufficient time for the forces of evolution to work.” Which means to say that the differences could be (and actually are) substantial.

If you don’t establish a reasonable forum for debate on this, Reich argues, if you don’t establish the principle is that we do not have to be afraid of any of this, it will be monopolized by truly unreasonable and indeed dangerous racists. And those racists will have the added prestige for their followers of revealing forbidden knowledge.

so there are two arguments against the suppression of this truth and the stigmatization of its defenders: that it’s intellectually dishonest and politically counterproductive.

Klein seems to back a truly extreme position: that only the environment affects IQ scores, and genes play no part in group differences in human intelligence. To this end, he cites the “Flynn effect,” which does indeed show that IQ levels have increased over the years, and are environmentally malleable up to a point. In other words, culture, politics, and economics do matter.

But Klein does not address the crucial point that even with increases in IQ across all races over time, the racial gap is still frustratingly persistent, that, past a certain level, IQ measurements have actually begun to fall in many developed nations, and that Flynn himself acknowledges that the effect does not account for other genetic influences on intelligence.

In an email exchange with me, in which I sought clarification, Klein stopped short of denying genetic influences altogether, but argued that, given rising levels of IQ, and given how brutal the history of racism against African-Americans has been, we should nonetheless assume “right now” that genes are irrelevant.

My own brilliant conclusion: Group differences in IQ are indeed explicable through both environmental and genetic factors and we don’t yet know quite what the balance is.

We are, in this worldview, alone on the planet, born as blank slates, to be written on solely by culture. All differences between men and women are a function of this social effect; as are all differences between the races. If, in the aggregate, any differences in outcome between groups emerge, it is entirely because of oppression, patriarchy, white supremacy, etc. And it is a matter of great urgency that we use whatever power we have to combat these inequalities.

Liberalism has never promised equality of outcomes, merely equality of rights. It’s a procedural political philosophy rooted in means, not a substantive one justified by achieving certain ends.

A more nuanced understanding of race, genetics, and environment would temper this polarization, and allow for more unifying, practical efforts to improve equality of opportunity, while never guaranteeing or expecting equality of outcomes.

In some ways, this is just a replay of the broader liberal-conservative argument. Leftists tend to believe that all inequality is created; liberals tend to believe we can constantly improve the world in every generation, forever perfecting our societies.

Rightists believe that human nature is utterly unchanging; conservatives tend to see the world as less plastic than liberals, and attempts to remake it wholesale dangerous and often counterproductive.

I think the genius of the West lies in having all these strands in our politics competing with one another.

Where I do draw the line is the attempt to smear legitimate conservative ideas and serious scientific arguments as the equivalent of peddling white supremacy and bigotry. And Klein actively contributes to that stigmatization and demonization. He calls the science of this “race science” as if it were some kind of illicit and illegitimate activity, rather than simply “science.”

He goes on to equate the work of these scientists with the “most ancient justification for bigotry and racial inequality.” He even uses racism to dismiss Murray and Harris: they are, after all, “two white men.

He still refuses to believe that Murray’s views on this are perfectly within the academic mainstream in studies of intelligence, as they were in 1994.

Klein cannot seem to hold the following two thoughts in his brain at the same time: that past racism and sexism are foul, disgusting, and have wrought enormous damage and pain and that unavoidable natural differences between races and genders can still exist.

, it matters that we establish a liberalism that is immune to such genetic revelations, that can strive for equality of opportunity, and can affirm the moral and civic equality of every human being on the planet.

We may even embrace racial discrimination, as in affirmative action, that fuels deeper divides. All of which, it seems to me, is happening — and actively hampering racial progress, as the left defines the most multiracial and multicultural society in human history as simply “white supremacy” unchanged since slavery; and as the right viscerally responds by embracing increasingly racist white identity politics.

liberalism is integral to our future as a free society — and it should not falsely be made contingent on something that can be empirically disproven. It must allow for the truth of genetics to be embraced, while drawing the firmest of lines against any moral or political abuse of it

We have dozens of new pronouns in colleges (for all those genders that have suddenly sprung into existence), and biological males competing in all-female high-school athletic teams (guess who wins at track).

Worse, we have constant admonitions against those who actually conform, as most human beings always have, to the general gender rule.

We have gone from rightly defending the minority to wrongly problematizing the majority. It should surprise no one that, at some point, the majority will find all of this, as Josh Barro recently explained, “annoying.”

I say this as someone happily in the minority — and who believes strongly in the right to subvert or adapt traditional gender roles.

But you can’t subvert something that you simultaneously argue doesn’t exist.

the core contradiction of ideological transgenderism. By severing the link between sex and gender completely, it abolishes the core natural framework without which the transgender experience makes no sense at all.

It’s also a subtle, if unintentional, attack on homosexuality. Most homosexuals are strongly attached to their own gender and attracted to traditional, natural expressions of it. That’s what makes us gay, for heaven’s sake. And that’s one reason the entire notion of a common “LGBT” identity is so misleading. How can a single identity comprise both the abolition of gender and at the same time its celebration?

Exceptions, in other words, need a rule to exist. Abolish gender’s roots in biology and sex — and you abolish gay people and transgender people as well.

I’m not in favor of boycotting Israel when we don’t boycott, say, Saudi Arabia. But seriously: making it illegal?

Transgender people exist and should be treated with absolutely the same human respect, decency, and civil equality as anyone else. But they don’t disprove traditional notions of gender as such — which have existed in all times, places, and cultures in human history and prehistory, and are rooted deeply in evolutionary biology and reproductive strategy.

Intersex people exist and, in my view, should not be genitally altered or “fixed” without their adult consent. But they do not somehow negate the overwhelming majority who have no such gender or sexual ambiguity.

the entire society does not need to be overhauled in order to make gay or trans experience central to it. Inclusion, yes. Revolution, no.

The added problem with this war on nature is the backlash it inevitably incurs. There’s a reason so many working-class men find it hard to vote for Democrats any more. And there’s a reason why a majority of white women last year voted for a man who boasted of sexual assault if the alternative was a triumph for contemporary left-feminism.

You can’t assault the core identity of most people’s lives and then expect them to vote for you. As a Trump supporter in Colorado just told a reporter from The New Yorker: “I’ve never been this emotionally invested in a political leader in my life. The more they hate him, the more I want him to succeed. Because what they hate about him is what they hate about me.”

One of the features you most associate with creeping authoritarianism is the criminalization of certain political positions. Is anything more anathema to a liberal democracy? If Trump were to suggest it, can you imagine the reaction?

And yet it’s apparently fine with a hefty plurality of the Senate and House. I’m referring to the remarkable bill introduced into the Congress earlier this year — with 237 sponsors and co-sponsors in the House and 43 in the Senate — which the ACLU and the Intercept have just brought to light. It’s a remarkably bipartisan effort, backed by Chuck Schumer and Ted Cruz, among many solid Trump-resisting Democrats and hard-line Republicans.

it would actually impose civil and criminal penalties on American citizens for backing or joining any international boycott of Israel because of its settlement activities. There are even penalties for simply inquiring about such a boycott. And they’re not messing around. The minimum civil penalty would be $250,000 and the maximum criminal penalty $1 million and 20 years in prison. Up to 20 years in prison for opposing the policies of a foreign government and doing something about it!

Yes, there’s a range of gender expression among those of the same sex. But it’s still tethered among most to the forces of chromosomes and hormones that make us irreducibly male and female. Nature can be interpreted; it can even be played with; but it cannot be abolished. After all, how can you be “queer” if there is no such thing as “normal”?

Every now and again, you just have to sit back and admire the extraordinary skills of the Greater Israel lobby. You’ve never heard of this bill, and I hadn’t either. But that is partly the point. AIPAC doesn’t want the attention — writers who notice this attempted assault on a free society will be tarred as anti-Semites (go ahead, it wouldn’t be the first time) and politicians who resist it will see their careers suddenly stalled.

pointing out this special interest’s distortion of democracy is not the equivalent of bigotry. It’s simply a defense of our democratic way of life.

The more screen time, the more revenue.

The goal of Facebook Inc., Alphabet Inc.’s Google, Snap Inc. and their peers is to create or host captivating experiences that keep users glued to their screens, whether for Instagram, YouTube, Snapchat or Facebook

Snapchat users 25 and younger, for example, were spending 40 minutes a day on the app, Chief Executive Evan Spiegel said in August. Alphabet boasted to investors recently that YouTube’s 1.5 billion users were spending an average 60 minutes a day on mobile.

Facebook’s stock slid 4.5% to close at $179 Friday after CEO Mark Zuckerberg announced plans Thursday to overhaul the Facebook news feed in a way that could reduce the time users spend.

Tech companies are working to instill viewing habits earlier than ever. The number of users of YouTube Kids is soaring. Facebook recently launched Messenger Kids, a messaging app for children as young as 6.

Ms. Ho’s 16-year-old son, Brian is an Eagle Scout and chorister, who at times finds it hard to break away from online videogames, even at 3 a.m. The teen recently told his mother he thinks he is addicted. Ms. Ho’s daughter, Samantha, 14, also is glued to her device, in conversations with friends.

“You think you’re buying a piece of technology,” Ms. Shepardson said. “Now it’s like oxygen to her.”

Psychologists say social media creates anxiety among children when they are away from their phones—what they call “fear of missing out,” whether on social plans, conversations or damaging gossip teens worry could be about themselves.

About half the teens in a survey of 620 families in 2016 said they felt addicted to their smartphones. Nearly 80% said they checked the phones more than hourly and felt the need to respond instantly to messages

Children set up Instagram accounts under pseudonyms that friends but not parents recognize. Some teens keep several of these so-called Finsta accounts without their parents knowing.

An app called Secret Calculator looks and works like an iPhone calculator but doubles as a private vault to hide files, photos and videos.

Mr. Zuckerberg told investors late last year that Facebook planned to boost video offerings, noting that live video generates 10 times as many user interactions. Netflix Inc. chief executive Reed Hastings, said in April about the addictiveness of its shows that the company was “competing with sleep on the margins.”

Keeping children away from disturbing content, though, is easier than keeping them off their phones.

About 16% of the nation’s high-school students were bullied online in 2015, according to the U.S. Centers for Disease Control and Prevention. Children who are cyberbullied are three times more likely to contemplate suicide

Smartphones “bring the outside in,” said Ms. Ahn, whose husband works for a major tech company. “We want the family to be the center of gravity.”

The problem is that we confuse a shallow familiarity with general concepts for real, in-depth knowledge.

our knowledge is also highly selective: we conveniently remember facts that support our beliefs and forget others

Psychological studies show that people fail to notice the logical fallacies in an argument if the conclusion supports their viewpoint

“motivated reasoning”

A high standard of education doesn’t necessarily protect us from these flaws

That false sense of expertise can, in turn, lead them to feel that they have the licence to be more closed-minded in their political views – an attitude known as “earned dogmatism”.

“People confuse their current level of understanding with their peak knowledge,”

Graduates, for instance, often overestimate their understanding of their degree subject:

recent psychological research also offers evidence-based ways towards achieving more fruitful discussions.

a simple but powerful way of deflating someone’s argument is to ask for more detail. “You need to get the ‘other side’ focusing on how something would play itself out, in a step by step fashion”

By revealing the shallowness of their existing knowledge, this prompts a more moderate and humble attitude.

You need to ask how something works to get the effect

If you are trying to debunk a particular falsehood – like a conspiracy theory or fake news – you should make sure that your explanation offers a convincing, coherent narrative that fills all the gaps left in the other person’s understanding

The persuasive power of well-constructed narratives means that it’s often useful to discuss the sources of misinformation, so that the person can understand why they were being misled in the first place

Each of our beliefs is deeply rooted in a much broader and more complex political ideology. Climate crisis denial, for instance, is now inextricably linked to beliefs in free trade, capitalism and the dangers of environmental regulation.

Attacking one issue may therefore threaten to unravel someone’s whole worldview – a feeling that triggers emotionally charged motivated reasoning. It is for this reason that highly educated Republicans in the US deny the overwhelming evidence.

disentangle the issue at hand from their broader beliefs, or to explain how the facts can still be accommodated into their worldview.

“All people have multiple identities,” says Prof Jay Van Bavel at New York University, who studies the neuroscience of the “partisan brain”. “These identities can become active at any given time, depending on the circumstances.”

you might have more success by appealing to another part of the person’s identity entirely.

when people are asked to first reflect on their other, nonpolitical values, they tend to become more objective in discussion on highly partisan issues, as they stop viewing facts through their ideological lens.

Another simple strategy to encourage a more detached and rational mindset is to ask your conversation partner to imagine the argument from the viewpoint of someone from another country

The aim is to help them recognise that they can change their mind on certain issues while staying true to other important elements of their personality.

this strategy increases “psychological distance” from the issue at hand and cools emotionally charged reasoning so that you can see things more objectively.

If you are considering policies with potentially long-term consequences, you could ask them to imagine viewing the situation through the eyes of someone in the future

people are generally much more rational in their arguments, and more willing to own up to the limits of their knowledge and understanding, if they are treated with respect and compassion.

Aggression, by contrast, leads them to feel that their identity is threatened, which in turn can make them closed-minded

Assuming that the purpose of your argument is to change minds, rather than to signal your own superiority, you are much more likely to achieve your aims by arguing gently and kindly rather than belligerently, and affirming your respect for the person, even if you are telling them some hard truths

As a bonus, you will also come across better to onlookers. “There’s a lot of work showing that third-party observers always attribute high levels of competence when the person is conducting themselves with more civility,”

That’s the latest among several recent studies by economists working independently, all arriving at similar findings: A few “superstar firms” have grown to dominate their industries, crowding out competitors and controlling markets to a degree not seen in many decades.

Let’s look beyond such obvious winner-take-all examples as Apple or Alphabet, the parent of Google.

Consider real-estate services. In 1997, according to Profs. Grullon, Larkin and Michaely, that sector had 42 publicly traded companies; the four largest generated 49% of the group’s total revenue. By 2014, only 20 public firms were left, and the top four— CBRE Group, Jones Lang LaSalle, Realogy Holdings and Wyndham Worldwide—commanded 78% of the group’s combined revenue.

Or look at supermarkets. In 1997, there were 36 publicly traded companies in that industry, with the top four accounting for more than half of total sales. By 2014, only 11 were left. The top four—Kroger, Supervalu, Whole Foods Market and Roundy’s (since acquired by Kroger)—held 89% of the pie.

The U.S. had more than 7,000 public companies 20 years ago, the professors say; nowadays, it’s fewer than 4,000.

The winners are also grabbing most of the profits

At the end of 1996, the 25 companies in the S&P 500 with the highest net profit margins—income as a percentage of revenue—earned a median of just under 21 cents on every dollar of sales. Last year, the top 25 such companies earned a median of 39 cents on the dollar.

Two decades ago, the median net margin among all S&P 500 members was 6.7%. By the end of 2016, that had increased to 9.7%.

So while companies as a whole became more profitable over the past 20 years, the winners have become vastly more profitable, nearly doubling the gains they got on each dollar of sales.

Why might it be easier now for winners to take all? Prof. Michaely suggests two theories. Declining enforcement of antitrust rules has led to bigger mergers, less competition and higher profits.

The other is technology. “If you want to compete with Google or Amazon,” he says, “you’ll have to invest not just billions, but tens of billions of dollars.”

Still, history offers a warning. Many times in the past, winners have taken all but seldom for long.

This failing in the West’s economies is also a failing of economics

many people have long felt the desire to do something with their lives besides consuming goods and having leisure. They desire to participate in a community in which they can interact and develop.

Our prevailing political economy is blind to the very concept of inclusion; it does not map out any remedy for the deficiency

injustice of another sort. Workers in decent jobs view the economy as unjust if they or their children have virtually no chance of climbing to a higher rung in the socioeconomic ladder

“Money is like blood. You need it to live but it isn’t the point of life.”4

justice is not everything that people need from their economy. They need an economy that is good as well as just. And for some decades, the Western economies have fallen short of any conception of a “good economy”—an economy offering a “good life,” or a life of “richness,” as some humanists call it

The good life as it is popularly conceived typically involves acquiring mastery in one’s work, thus gaining for oneself better terms—or means to rewards, whether material, like wealth, or nonmaterial—an experience we may call “prospering.”

As humanists and philosophers have conceived it, the good life involves using one’s imagination, exercising one’s creativity, taking fascinating journeys into the unknown, and acting on the world—an experience I call “flourishing.”

prospering and flourishing became prevalent in the nineteenth century when, in Europe and America, economies emerged with the dynamism to generate their own innovation.

What is the mechanism of the slowdown in productivity

prospering

In nineteenth-century Britain and America, and later Germany and France, a culture of exploration, experimentation, and ultimately innovation grew out of the individualism of the Renaissance, the vitalism of the Baroque era, and the expressionism of the Romantic period.

What made innovating so powerful in these economies was that it was not limited to elites. It permeated society from the less advantaged parts of the population on up.

High-enough wages, low-enough unemployment, and wide-enough access to engaging work are necessary for a “good-enough” economy—though far from sufficient. The material possibilities of the economy must be adequate for the nonmaterial possibilities to be widespread—the satisfactions of prospering and of flourishing through adventurous, creative, and even imaginative work.

today’s standard economics. This economics, despite its sophistication in some respects, makes no room for economies in which people are imagining new products and using their creativity to build them. What is most fundamentally “wrong with economics” is that it takes such an economy to be the norm—to be “as good as it gets.”

ince around 1970, or earlier in some cases, most of the continental Western European economies have come to resemble more completely the mechanical model of standard economics. Most companies are highly efficient. Households, apart from the very low-paid or unemployed, have gone on saving

In most of Western Europe, economic dynamism is now at lows not seen, I would judge, since the advent of dynamism in the nineteenth century. Imagining and creating new products has almost disappeared from the continent

The bleak levels of both unemployment and job satisfaction in Europe are testimony to its dreary economies.

a recent survey of household attitudes found that, in “happiness,” the median scores in Spain (54), France (51), Italy (48), and Greece (37) are all below those in the upper half of the nations labeled “emerging”—Mexico (79), Venezuela (74), Brazil (73), Argentina (66), Vietnam (64), Colombia (64), China (59), Indonesia (58), Chile (58), and Malaysia (56)

The US economy is not much better. Two economists, Stanley Fischer and Assar Lindbeck, wrote of a “Great Productivity Slowdown,” which they saw as beginning in the late 1960s.11 The slowdown in the growth of capital and labor combined—what is called “total factor productivity”—is star

though the injustices in the West’s economies are egregious, they ought not to be seen as a major cause of the productivity slowdowns and globalization. (For one thing, a slowdown of productivity started in the US in the mid-1960s and the sharp loss of manufacturing jobs to poorer countries occurred much later—from the late 1970s to the early 1990s.) Deeper causes must be at work.

The plausible explanation of the syndrome in America—the productivity slowdown and the decline of job satisfaction, among other things—is a critical loss of indigenous innovation in the established industries like traditional manufacturing and services that was not nearly offset by the innovation that flowered in a few new industries

hat then caused this narrowing of innovation? No single explanation is persuasive. Yet two classes of explanations have the ring of truth. One points to suppression of innovation by vested interests

some professions, such as those in education and medicine, have instituted regulation and licensing to curb experimentation and change, thus dampening innovation

established corporations—their owners and stakeholders—and entire industries, using their lobbyists, have obtained regulations and patents that make it harder for new firms to gain entry into the market and to compete with incumbents.

The second explanation points to a new repression of potential innovators by families and schools. As the corporatist values of control, solidarity, and protection are invoked to prohibit innovation, traditional values of conservatism and materialism are often invoked to inhibit a young person from undertaking an innovation.

ow might Western nations gain—or regain—widespread prospering and flourishing? Taking concrete actions will not help much without fresh thinking: people must first grasp that standard economics is not a guide to flourishing—it is a tool only for efficiency.

Widespread flourishing in a nation requires an economy energized by its own homegrown innovation from the grassroots on up. For such innovation a nation must possess the dynamism to imagine and create the new—economic freedoms are not sufficient. And dynamism needs to be nourished with strong human values.

a reform of education stands out. The problem here is not a perceived mismatch between skills taught and skills in demand

The problem is that young people are not taught to see the economy as a place where participants may imagine new things, where entrepreneurs may want to build them and investors may venture to back some of them. It is essential to educate young people to this image of the economy.

It will also be essential that high schools and colleges expose students to the human values expressed in the masterpieces of Western literature, so that young people will want to seek economies offering imaginative and creative careers. Education systems must put students in touch with the humanities in order to fuel the human desire to conceive the new and perchance to achieve innovations

This reorientation of general education will have to be supported by a similar reorientation of economic education.

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 matters for social animals like us, whose safety and very survival ultimately depend on our ability to coexist. Views that have more to do with competing tribal biases than objective interpretations of the evidence create destructive and violent conflict. Denial of scientifically established ‘truth’ cause all sorts of serious direct harms. Consider a few examples; • The widespread faith-based rejection of evolution feeds intense polarization. • Continued fear of vaccines is allowing nearly eradicated diseases to return. • Those who deny the evidence of the safety of genetically modified food are also denying the immense potential benefits of that technology to millions. • Denying the powerful evidence for climate change puts us all in serious jeopardy should that evidence prove to be true.

To address these harms, we need to understand why we often have trouble agreeing on what is true (what some have labeled science denialism). Social science has taught us that human cognition is innately, and inescapably, a process of interpreting the hard data about our world – its sights and sound and smells and facts and ideas - through subjective affective filters that help us turn those facts into the judgments and choices and behaviors that help us survive. The brain’s imperative, after all, is not to reason. It’s job is survival, and subjective cognitive biases and instincts have developed to help us make sense of information in the pursuit of safety, not so that we might come to know ‘THE universal absolute truth

This subjective cognition is built-in, subconscious, beyond free will, and unavoidably leads to different interpretations of the same facts.

But here is a truth with which I hope we can all agree. Our subjective system of cognition can be dangerous.

It can produce perceptions that conflict with the evidence, what I call The Perception Gap, which can in turn produce profound harm

We need to recognize the greater threat that our subjective system of cognition can pose, and in the name of our own safety and the welfare of the society on which we depend, do our very best to rise above it or, when we can’t, account for this very real danger in the policies we adopt.

"Everyone engages in motivated reasoning, everyone screens out unwelcome evidence, no one is a fully rational actor. Sure. But when it comes to something with such enormous consequences to human welfare

I think it's fair to say we have an obligation to confront our own ideological priors. We have an obligation to challenge ourselves, to push ourselves, to be suspicious of conclusions that are too convenient, to be sure that we're getting it right.

they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it.

What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests.

“Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.”

alls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer.

The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions.

Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.”

While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve.

“Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since

Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know,

In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?

But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money.

Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research

which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.”

these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said.

in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate.

Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3The bill has been passed by the House but still awaits a vote in the Senate. is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration.

It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’

ost scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement.

objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,”

The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them.

Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it

While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,”

These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence.

For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations

the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated?

But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

virtually no speaker of English gets confused when he or she hears the word “mean.” That’s because the different senses of the word occur in such different contexts as to allow listeners to infer its meaning nearly automatically.

To understand why ambiguity makes a language more efficient rather than less so, think about the competing desires of the speaker and the listener. The speaker is interested in conveying as much as possible with the fewest possible words, while the listener is aiming to get a complete and specific understanding of what the speaker is trying to say.

it is “cognitively cheaper” to have the listener infer certain things from the context than to have the speaker spend time on longer and more complicated utterances. The result is a system that skews toward ambiguity, reusing the “easiest” words. Once context is considered, it’s clear that “ambiguity is actually something you would want in the communication system,” Piantadosi says.

“You would expect that since languages are constantly changing, they would evolve to get rid of ambiguity,” Wasow says. “But if you look at natural languages, they are massively ambiguous: Words have multiple meanings, there are multiple ways to parse strings of words. … This paper presents a really rigorous argument as to why that kind of ambiguity is actually functional for communicative purposes, rather than dysfunctional.”

“Ambiguity is only good for us [as humans] because we have these really sophisticated cognitive mechanisms for disambiguating,” he says. “It’s really difficult to work out the details of what those are, or even some sort of approximation that you could get a computer to use.”

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”:

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.

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.

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.

the faceless communication social media creates, the linked distances between people, both provokes and mitigates the inherent capacity for monstrosity.

The Gyges effect, the well-noted disinhibition created by communications over the distances of the Internet, in which all speech and image are muted and at arm’s reach, produces an inevitable reaction — the desire for impact at any cost, the desire to reach through the screen, to make somebody feel something, anything. A simple comment can so easily be ignored. Rape threat? Not so much. Or, as Mr. Nunn so succinctly put it on Twitter: “If you can’t threaten to rape a celebrity, what is the point in having them?”

The challenge of our moment is that the face has been at the root of justice and ethics for 2,000 years.

The precondition of any trial, of any attempt to reconcile competing claims, is that the victim and the accused look each other in the face.

For the great French-Jewish philosopher Emmanuel Levinas, the encounter with another’s face was the origin of identity — the reality of the other preceding the formation of the self. The face is the substance, not just the reflection, of the infinity of another person. And from the infinity of the face comes the sense of inevitable obligation, the possibility of discourse, the origin of the ethical impulse.

“Through imitation and mimicry, we are able to feel what other people feel. By being able to feel what other people feel, we are also able to respond compassionately to other people’s emotional states.” The face is the key to the sense of intersubjectivity, linking mimicry and empathy through mirror neurons — the brain mechanism that creates imitation even in nonhuman primates.

it’s also no mere technical error on the part of Twitter; faceless rage is inherent to its technology.

Without a face, the self can form only with the rejection of all otherness, with a generalized, all-purpose contempt — a contempt that is so vacuous because it is so vague, and so ferocious because it is so vacuous. A world stripped of faces is a world stripped, not merely of ethics, but of the biological and cultural foundations of ethics.

The spirit of facelessness is coming to define the 21st. Facelessness is not a trend; it is a social phase we are entering that we have not yet figured out how to navigate.

the flight back to the face takes on new urgency. Google recently reported that on Android alone, which has more than a billion active users, people take 93 million selfies a day

Emojis are an explicit attempt to replicate the emotional context that facial expression provides. Intriguingly, emojis express emotion, often negative emotions, but you cannot troll with them.

But all these attempts to provide a digital face run counter to the main current of our era’s essential facelessness. The volume of digital threats appears to be too large for police forces to adequately deal with.

The more established wisdom about trolls, at this point, is to disengage. Obviously, in many cases, actual crimes are being committed, crimes that demand confrontation, by victims and by law enforcement officials, but in everyday digital life engaging with the trolls “is like trying to drown a vampire with your own blood,”

There is a third way, distinct from confrontation or avoidance: compassion

we need a new art of conversation for the new conversations we are having — and the first rule of that art must be to remember that we are talking to human beings: “Never say anything online that you wouldn’t say to somebody’s face.” But also: “Don’t listen to what people wouldn’t say to your face.”

The neurological research demonstrates that empathy, far from being an artificial construct of civilization, is integral to our biology.

Yet the judgement was not respected. A United Nations report published six years later found that Shell had not followed its own procedures regarding the maintenance of oilfield infrastructure. Today, Shell is still gas flaring in the Niger Delta.

The word “ecocide” is an umbrella term for all forms of environmental destruction from deforestation to greenhouse gas emissions.

Although there are questions about whether the ICC as an institution has the teeth to prosecute any crimes, Bassey and other activists believe the law will act as a powerful deterrent against future forms of environmental destruction. “We will not get different outcomes in cases of exploitation and marginalization unless we reimagine the laws that govern us,” Bassey says.

In December 2020, lawyers from around the world gathered to begin drafting a legal definition of ecocide.

The term ecocide first rose to the public consciousness in 1972, when Olof Palme, the premier of Sweden, used the term at a United Nations environmental conference in Stockholm to describe the environmental damage caused by the Vietnam War. At the conference, an ecocide convention was proposed but never came to pass.

“My recollection is that there was just no political support for it,” says Philippe Sands, who was involved in drafting the preamble of the Rome Statute in 1998 (and who would go on to co-chair the expert panel formed in 2020 to draft a legal definition of ecocide). Environmental destruction, Sands says, was not on the public’s consciousness.

Environmental advocates believe an ecocide law at the ICC would be groundbreaking. While some countries have national laws on environmental harm, there is no international criminal law that explicitly imposes penalties on individuals responsible for environmental destruction. If adopted, experts say there are three main areas where an ecocide law would make a difference.

The first is the symbolic impact of having the ICC elevate environmental destruction to the same level as genocidal crimes

The second area where this law could make a difference is by setting a legal precedent, creating a bandwagon effect where international law could prompt changes in national criminal laws, as countries look to signal their environmental commitment to others.

The third way an ecocide law could be useful is by prosecuting environmental crimes that fall outside of national jurisdictions.

Economic literacy contributes to a second class of knowledge.

For some economic decisions, such as buying a home or investing in the stock market, it is possible to hire professional or technical help when making a choice, but in most cases it is neither economical nor practical for an individual to hire a skilled professional every time an economic decision needs to be made.

There are three essential ingredients for effective economic education in the schools.

The development of economic literacy must begin in the schools. Even young children are capable of learning basic economic concepts that help them understand their economic world. In the secondary years, that initial foundation can be expanded to include instruction in a broader set of economic ideas and concepts

Some may think that economics is too difficult a subject to be taught to children and youth, and that such instruction should wait until college

Waiting until students are in college to teach economics is simply a matter of "too little and too late." The majority of students end their formal education with secondary school, and even those students who continue their learning at a college or university may not take an economics course.

Economic literacy improves the competence of each individual for making personal and social decisions about the multitude of economic issues that will be encountered over a lifetime.

First, teachers must be knowledgeable about the subject and be able to help students learn how to use basic economic concepts to analyze personal and social issues. Second, good curriculum guides and instructional materials are needed that present economic content at an appropriate level for the student to understand. Third, economics must have a central place in the school curriculum—similar to math, science, history and language arts—so that substantial classroom time is devoted to economics instruction

Over the past 40 years there has been a significant improvement in each area.

A study of high school transcripts shows that only about 44 percent of high school students take a separate course in economics. This course is usually offered in the 12th grade as an elective and lasts for only a semester.

Given this situation—that fewer than half of high school graduates take a course in economics—it should not be surprising that study after study show that there is widespread economic illiteracy among youth and the American public.

Some 87 percent of high school seniors rated their knowledge and understanding of economic and economic issues as only fair or poor.

Knowing what determines prices in a market economy and accepting the outcomes are two different things. If demand or supply conditions change, prices in a competitive market will rise and fall. Having a basic understanding of how markets work does not always mean that people will like price changes, especially if prices rise, but it should increase the probability of accepting the market outcome

The development of basic economic literacy is an important goal for a democratic society that relies heavily on informed citizenry and personal economic decision-making.

To achieve that goal will require that significant gaps in the economic education of youth be closed by giving economics a more central place in the school curriculum. More economics coursework at the precollege level sets a foundation for economic literacy, but it is only the beginning.

Over multiple years, family income fluctuates, and so the distribution of multiyear income is moderately more equal than the distribution of single-year income.

n one sense, the growth of inequality in the last part of the twentieth century comes as a surprise. In the 1950s, the bottom part of the income distribution contained large concentrations of two kinds of families: farm families whose in-kind income was not counted in Census data, and elderly families, many of whom were ineligible for the new Social Security program

Over subsequent decades, farm families declined as a proportion of the population while increased Social Security benefits and an expanding private pension system lifted elderly incomes. Both trends favored greater income equality but were outweighed by four main factors.

Family structure. Over time, the two-parent, one-earner family was increasingly replaced by low-income single-parent families and higher-income two-parent, two-earner families

Trade and technology increasingly shifted demand away from less-educated and less-skilled workers toward workers with higher education or particular skills. The result was a growing earnings gap between more- and less-educated/skilled workers.

With improved communications and transportation, people increasingly functioned in national, rather than local, markets. In these broader markets, persons with unique talents could command particularly high salaries.

In 2002, immigrants who had entered the country since 1980 constituted nearly 11 percent of the labor force (see immigration). A relatively high proportion of these immigrants had low levels of education and increased the number of workers competing for low-paid work.

A second offset to estimated inequality is economic mobility. Because most family incomes increase as people’s careers develop, long-run incomes are more equal than standard single-year statistics suggest

Is inequality of wages and incomes bad? The question seems ludicrous. Of course inequality is bad, isn’t it? Actually, no. What matters crucially is how the inequality came about.

Inequality of wages and incomes is clearly bad if it results from government privileges. Many people would find such an outcome unjust, but even more important to many economists is that such inequality sets up perverse incentives.

But inequality in wages and incomes in relatively free economies serves two important social functions.