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With such a huge food supply, food marketing got better and restaurants got cheaper. The low cost of food fueled the growth of the fast-food industry. If food were expensive, you couldn’t have fast food.

The epidemic was caused by the overproduction of food in the United States. Beginning in the 1970s, there was a change in national agricultural policy. Instead of the government paying farmers not to engage in full production, as was the practice, they were encouraged to grow as much food as they could. At the same time, technological changes and the “green revolution” made our farms much more productive. The price of food plummeted, while the number of calories available to the average American grew by about 1,000 a day.

Well, what do people do when there is extra food around? They eat it! This, of course, is a tremendously controversial idea. However, the model shows that increase in food more than explains the increase in weight.

There’s no magic bullet on this. You simply have to cut calories and be vigilant for the rest of your life.

Americans are wasting food at a progressively increasing rate. If Americans were to eat all the food that’s available, we’d be even more obese.

What new information did your equation render? That the conventional wisdom of 3,500 calories less is what it takes to lose a pound of weight is wrong. The body changes as you lose. Interestingly, we also found that the fatter you get, the easier it is to gain weight. An extra 10 calories a day puts more weight onto an obese person than on a thinner one. Also, there’s a time constant that’s an important factor in weight loss. That’s because if you reduce your caloric intake, after a while, your body reaches equilibrium. It actually takes about three years for a dieter to reach their new “steady state.” Our model predicts that if you eat 100 calories fewer a day, in three years you will, on average, lose 10 pounds — if you don’t cheat. Another finding: Huge variations in your daily food intake will not cause variations in weight, as long as your average food intake over a year is about the same. This is because a person’s body will respond slowly to the food intake.

People don’t wait long enough to see what they are going to stabilize at. So if you drop weight and return to your old eating habits, the time it takes to crawl back to your old weight is something like three years. To help people understand this better, we’ve posted an interactive version of our model at bwsimulator.niddk.nih.gov.

we should stop marketing food to children.

weight change, up or down, takes a very, very long time. All diets work. But the reaction time is really slow: on the order of a year.

I could see the facts on the epidemic were quite astounding. Between 1975 and 2005, the average weight of Americans had increased by about 20 pounds

People think that the epidemic has to be caused by genetics or that physical activity has gone down. Yet levels of physical activity have not really changed in the past 30 years. As for the genetic argument, yes, there are people who are genetically disposed to obesity, but if they live in societies where there isn’t a lot of food, they don’t get obese. For them, and for us, it’s supply that’s the issue.

I think childhood obesity is a major problem. And when you’re obese, it’s not like we can suddenly cut your food off and you’ll go back to not being obese. You’ve been programmed to eat more. It’s a hardship to eat less. Michelle Obama’s initiative is helpful. And childhood obesity rates seem to be stabilizing in the developed world, at least. The obesity epidemic may have peaked because of the recession. It’s made food more expensive.

I think the food industry doesn’t want to know it. And ordinary people don’t particularly want to hear this, either. It’s so easy for someone to go out and eat 6,000 calories a day.

In its final forecast in 2016, FiveThirtyEight gave Hillary Clinton a 71.4 percent chance of victory. (The digit after the decimal providing an aura of faux precision, as if we could distinguish 71.4 percent from 71.5 percent.) All that figure really said was that Mrs. Clinton had a roughly one-in-three chance of losing, something that did not get across to most people who saw a big number.

What do the unprecedented early voting numbers mean when polls don’t necessarily stop polling those who already voted? How do the early forecasts that run for many months before the election, and so are even more uncertain, affect those who vote early? Will the elderly, at great risk from the pandemic, avoid voting? How will voter suppression play out? Will Republicans end up flocking to the polls on Election Day? These are big unknowns that add great uncertainty to models, especially given the winner-takes-all setup in the Electoral College, where winning a state by as little as one-fourth of 1 percent can deliver all its electoral votes.

When probability models first came on the scene, I was hopeful that they would lessen the horse-race journalism that sometimes exaggerated the uncertainty (because what’s the thrill otherwise?) and the search for narrative turning points (Better than expected debate performance! It’s an underdog comeback!). I had hoped that we would instead get more substantive, policy-oriented coverage. Instead, modeling has been incorporated into the horse-race coverage.

these forecasts aren’t that useful, and may even be harmful if people take them too seriously.

At fifty-nine, Anderson is the chair of the University of Michigan’s department of philosophy and a champion of the view that equality and freedom are mutually dependent, enmeshed in changing conditions through time.

She has built a case, elaborated across decades, that equality is the basis for a free society

Because she brings together ideas from both the left and the right to battle increasing inequality, Anderson may be the philosopher best suited to this awkward moment in American life. She builds a democratic frame for a society in which people come from different places and are predisposed to disagree.

she sketched out the entry-level idea that one basic way to expand equality is by expanding the range of valued fields within a society.

The ability not to have an identity that one carries from sphere to sphere but, rather, to be able to slip in and adopt whatever values and norms are appropriate while retaining one’s identities in other domains?” She paused. “That is what it is to be free.”

How do you move from a basic model of egalitarian variety, in which everybody gets a crack at being a star at something, to figuring out how to respond to a complex one, where people, with different allotments of talent and virtue, get unequal starts, and often meet with different constraints along the way?

The problem, she proposed, was that contemporary egalitarian thinkers had grown fixated on distribution: moving resources from lucky-seeming people to unlucky-seeming people, as if trying to spread the luck around.

Egalitarians should agree about clear cases of blameless misfortune: the quadriplegic child, the cognitively impaired adult, the teen-ager born into poverty with junkie parents. But Anderson balked there, too. By categorizing people as lucky or unlucky, she argued, these egalitarians set up a moralizing hierarchy.

In Anderson’s view, the way forward was to shift from distributive equality to what she called relational, or democratic, equality: meeting as equals, regardless of where you were coming from or going to.

By letting the lucky class go on reaping the market’s chancy rewards while asking others to concede inferior status in order to receive a drip-drip-drip of redistributive aid, these egalitarians were actually entrenching people’s status as superior or subordinate.

To the ugly and socially awkward: . . . Maybe you won’t be such a loser in love once potential dates see how rich you are.

. To the stupid and untalented: Unfortunately, other people don’t value what little you have to offer in the system of production. . . . Because of the misfortune that you were born so poorly endowed with talents, we productive ones will make it up to you: we’ll let you share in the bounty of what we have produced with our vastly superior and highly valued abilities. . . 

she imagined some citizens getting a state check and a bureaucratic letter:

This was, at heart, an exercise of freedom. The trouble was that many people, picking up on libertarian misconceptions, thought of freedom only in the frame of their own actions.

To be truly free, in Anderson’s assessment, members of a society had to be able to function as human beings (requiring food, shelter, medical care), to participate in production (education, fair-value pay, entrepreneurial opportunity), to execute their role as citizens (freedom to speak and to vote), and to move through civil society (parks, restaurants, workplaces, markets, and all the rest).

Anderson’s democratic model shifted the remit of egalitarianism from the idea of equalizing wealth to the idea that people should be equally free, regardless of their differences.

A society in which everyone had the same material benefits could still be unequal, in this crucial sense; democratic equality, being predicated on equal respect, wasn’t something you could simply tax into existence. “People, not nature, are responsible for turning the natural diversity of human beings into oppressive hierarchies,”

Her first book, “Value in Ethics and Economics,” appeared that year, announcing one of her major projects: reconciling value (an amorphous ascription of worth that is a keystone of ethics and economics) with pluralism (the fact that people seem to value things in different ways).

Philosophers have often assumed that pluralistic value reflects human fuzziness—we’re loose, we’re confused, and we mix rational thought with sentimental responses.

She offered an “expressive” theory: in her view, each person’s values could be various because they were socially expressed, and thus shaped by the range of contexts and relationships at play in a life. Instead of positing value as a basic, abstract quality across society (the way “utility” functioned for economists), she saw value as something determined by the details of an individual’s history.

Like her idea of relational equality, this model resisted the temptation to flatten human variety toward a unifying standard. In doing so, it helped expand the realm of free and reasoned economic choice.

Anderson’s model unseated the premises of rational-choice theory, in which individuals invariably make utility-maximizing decisions, occasionally in heartless-seeming ways. It ran with, rather than against, moral intuition. Because values were plural, it was perfectly rational to choose to spend evenings with your family, say, and have guilt toward the people you left in the lurch at work.

The theory also pointed out the limits on free-market ideologies, such as libertarianism.

In ethics, it broke across old factional debates. The core idea “has been picked up on by people across quite a range of positions,” Peter Railton, one of Anderson’s longtime colleagues, says. “Kantians and consequentialists alike”—people who viewed morality in terms of duties and obligations, and those who measured the morality of actions by their effects in the world—“could look at it and see something important.”

Traditionally, the discipline is taught through a-priori thought—you start with basic principles and reason forward. Anderson, by contrast, sought to work empirically, using information gathered from the world, identifying problems to be solved not abstractly but through the experienced problems of real people.

“Dewey argued that the primary problems for ethics in the modern world concerned the ways society ought to be organized, rather than personal decisions of the individual,”

In 2004, the Stanford Encyclopedia of Philosophy asked Anderson to compose its entry on the moral philosophy of John Dewey, who helped carry pragmatist methods into the social realm. Dewey had an idea of democracy as a system of good habits that began in civil life. He was an anti-ideologue with an eye for pluralism.

She started working with historians, trying to hone her understanding of ideas by studying them in the context of their creation. Take Rousseau’s apparent support of direct democracy. It’s rarely mentioned that, at the moment when he made that argument, his home town of Geneva had been taken over by oligarchs who claimed to represent the public. Pragmatism said that an idea was an instrument, which naturally gave rise to such questions as: an instrument for what, and where, and when?

In “What Is the Point of Equality?,” Anderson had already started to drift away from what philosophers, following Rawls, call ideal theory, based on an end vision for a perfectly just society. As Anderson began a serious study of race in America, though, she found herself losing faith in that approach entirely.

Broadly, there’s a culturally right and a culturally left ideal theory for race and society. The rightist version calls for color blindness. Instead of making a fuss about skin and ethnicity, its advocates say, society should treat people as people, and let the best and the hardest working rise.

The leftist theory envisions identity communities: for once, give black people (or women, or members of other historically oppressed groups) the resources and opportunities they need, including, if they want it, civil infrastructure for themselves.

In “The Imperative of Integration,” published in 2010, Anderson tore apart both of these models. Sure, it might be nice to live in a color-blind society, she wrote, but that’s nothing like the one that exists.

But the case for self-segregation was also weak. Affinity groups provided welcome comfort, yet that wasn’t the same as power or equality, Anderson pointed out. And there was a goose-and-gander problem. Either you let only certain groups self-segregate (certifying their subordinate status) or you also permitted, say, white men to do it,

Anderson’s solution was “integration,” a concept that, especially in progressive circles, had been uncool since the late sixties. Integration, by her lights, meant mixing on the basis of equality.

in attending to these empirical findings over doctrine, she announced herself as a non-ideal theorist: a philosopher with no end vision of society. The approach recalls E. L. Doctorow’s description of driving at night: “You can see only as far as the headlights, but you can make the whole trip that way.”

or others, though, a white woman making recommendations on race policy raised questions of perspective. She was engaging through a mostly white Anglo-American tradition. She worked from the premise that, because she drew on folders full of studies, the limits of her own perspective were not constraining.

Some philosophers of color welcomed the book. “She’s taking the need for racial justice seriously, and you could hardly find another white political philosopher over a period of decades doing that,”

Recently, Anderson changed the way she assigns undergraduate essays: instead of requiring students to argue a position and fend off objections, doubling down on their original beliefs, she asks them to discuss their position with someone who disagrees, and to explain how and why, if at all, the discussion changed their views.

The challenge of pluralism is the challenge of modern society: maintaining equality amid difference in a culture given to constant and unpredictable change.

Rather than fighting for the ascendancy of certain positions, Anderson suggests, citizens should fight to bolster healthy institutions and systems—those which insure that all views and experiences will be heard. Today’s righteous projects, after all, will inevitably seem fatuous and blinkered from the vantage of another age.

Smith saw the markets as an escape from that order. Their “most important” function, he explained, was to bring “liberty and security” to those “who had before lived almost in a continual state of war with their neighbours, and of servile dependency upon their superiors.”

Anderson zeroed in on Adam Smith, whose “The Wealth of Nations,” published in 1776, is taken as a keystone of free-market ideology. At the time, English labor was subject to uncompensated apprenticeships, domestic servitude, and some measure of clerical dominion.

Smith, in other words, was an egalitarian. He had written “The Wealth of Nations” in no small part to be a solution to what we’d now call structural inequality—the intractable, compounding privileges of an arbitrary hierarchy.

It was a historical irony that, a century later, writers such as Marx pointed to the market as a structure of dominion over workers; in truth, Smith and Marx had shared a socioeconomic project. And yet Marx had not been wrong to trash Smith’s ideas, because, during the time between them, the world around Smith’s model had changed, and it was no longer a useful tool.

mages of free market society that made sense prior to the Industrial Revolution continue to circulate today as ideals, blind to the gross mismatch between the background social assumptions reigning in the seventeenth and eighteenth centuries, and today’s institutional realities. We are told that our choice is between free markets and state control, when most adults live their working lives under a third thing entirely: private government.

Today, people still try to use, variously, both Smith’s and Marx’s tools on a different, postindustrial world:

The unnaturalness of this top-heavy arrangement, combined with growing evidence of power abuses, has given many people reason to believe that something is fishy about the structure of American equality. Socialist and anti-capitalist models are again in vogue.

Anderson offers a different corrective path. She thinks it’s fine for some people to earn more than others. If you’re a brilliant potter, and people want to pay you more than the next guy for your pottery, great!

The problem isn’t that talent and income are distributed in unequal parcels. The problem is that Jeff Bezos earns more than a hundred thousand dollars a minute, while Amazon warehouse employees, many talented and hardworking, have reportedly resorted to urinating in bottles in lieu of a bathroom break. That circumstance reflects some structure of hierarchical oppression. It is a rip in the democratic fabric, and it’s increasingly the norm.

Andersonism holds that we don’t have to give up on market society if we can recognize and correct for its limitations—it may even be our best hope, because it’s friendlier to pluralism than most alternatives are.

we must be flexible. We must remain alert. We must solve problems collaboratively, in the moment, using society’s ears and eyes and the best tools that we can find.

“You can see that, from about 1950 to 1970, the typical American’s wages kept up with productivity growth,” she said. Then, around 1974, she went on, hourly compensation stagnated. American wages have been effectively flat for the past few decades, with the gains of productivity increasingly going to shareholders and to salaries for big bosses.

What changed? Anderson rattled off a constellation of factors, from strengthened intellectual-property law to winnowed antitrust law. Financialization, deregulation. Plummeting taxes on capital alongside rising payroll taxes. Privatization, which exchanged modest public-sector salaries for C.E.O. paydays. She gazed into the audience and blinked. “So now we have to ask: What has been used to justify this rather dramatic shift of labor-share of income?”

It was no wonder that industrial-age thinking was riddled with contradictions: it reflected what Anderson called “the plutocratic reversal” of classical liberal ideas. Those perversely reversed ideas about freedom were the ones that found a home in U.S. policy, and, well, here we were.

Men now receive about 74 bachelor’s degrees for every 100 awarded to women, and men account for more than 70 percent of the decline in college enrollment overall

In 2020, nearly half of women reported in a TD Ameritrade survey that they out-earn or make the same amount as their husbands or partners — a huge jump from fewer than 4 percent of women in 1960.

women are “increasingly selective,” leading to a rise in lonely, single young men — more of whom now live with their parents than a romantic partner.

Men also account for almost 3 of every 4 “deaths of despair,” either from a suicide, alcohol abuse or an overdose.

In my opinion, Peterson served up fairly banal advice: “Stand up straight,” “delay gratification.” His evolutionary-biology-informed takes ranged from amusingly weird to mildly insulting.

Women are still dealing with historical discrimination and centuries of male domination that haven’t been fully accounted for or rectified. Are we really worrying that men feel a little emasculated because their female classmates are doing well?

But millions of men lack access to that kind of power and success — and, downstream, cut loose from a stable identity as patriarchs deserving of respect, they feel demoralized and adrift. The data show it, but so does the general mood: Men find themselves lonely, depressed, anxious and directionless.

It seems like there’s been a breakdown, right? But there’s a very real way in which, at this moment, a lot of guys don’t know — they have no sense of what it means to be them, particularly. They have no idea what it means to be a man.”

Past models of masculinity feel unreachable or socially unacceptable; new ones have yet to crystallize. What are men for in the modern world? What do they look like? Where do they fit

Only one group seems to have no such doubts about offering men a plan.

an entire academic discipline emerged to theorize about gender and excavate women’s history — there hasn’t been a corresponding conversation about what role men should play in a changing world. At the same time, the increasing visibility of the LGBTQ+ movement has made the gender dynamic seem less stable, less defined.

went to that 2018 Peterson appearance as a skeptic. But his appeal — along with that of his fellow “manfluencers” — has become clearer since

Technically, men are slightly in the minority in the United States. But apart from that, Bray had a point — and what he said explained a lot about why the left and the mainstream are losing men.

What’s notable, first, is their empathy. For all Peterson’s barking and, lately, unhinged tweeting, he’s clearly on young men’s side.

This is especially compelling in a moment when many young men feel their difficulties are often dismissed out of hand as whining from a patriarchy that they don’t feel part of. For young men in particular, the assumption of a world built to serve their sex doesn’t align with their lived experience, where girls out-achieve them from pre-K to post-graduate studies and “men are trash” is an acceptable joke.

Then there’s the point-by-point advice. If young men are looking for direction, these influencers give them a clear script to follow — hours of video, thousands of book pages, a torrent of social media posts — in a moment when uncertainty abounds

if instruction is lacking elsewhere, even basic tips (“Clean your room!” Peterson famously advises) feel like a revelation. Plus, the community that comes with joining a fandom can feel like a buffer against an increasingly atomized world.

As one therapist told me: “I have used Jordan Peterson to turn a boy into a man. I used him to turn this guy without a strong father figure into someone who, yes, makes his bed and stands up straight and now is successful.” The books, she said, “do provide a structure that was clearly missing.”

It’s also important that the approach of these male models is both particular and aspirational. The BAPs and Hawleys find ways to celebrate aspects of the male experience — from physical strength to competitiveness to sex as a motivator — that other parts of modern society have either derided as “toxic” or attempted to explain aren’t specific to men at al

the 20-something guy in front of me swung around. “Jordan Peterson,” he told me without a hint of irony in his voice, “taught me how to live.”

the fact that they’re willing to define it outright feels bravely countercultural.

A baby-faced, 19-year-old University of Florida freshman with short, white-blond hair, Bray was wearing a hoodie despite the heat. (He grew up in Sarasota, so he was used to it.) He had agreed to talk to me about how he saw uncertainties about masculinity playing out on his campus.

First, he laid out his liberal, Gen Z bona fides — he’s in a fraternity, but many of his close friends are LGBTQ+. He feels that old versions of masculinity might be dissolving for the better.

But then he got candid. He doesn’t really identify with the manosphere, he told me, but can understand why others might. “I feel like there’s a lot of room to be proudly feminine, but there’s not, in my opinion, the same room to be proudly masculine.”

Men were constantly told to be “better” and less “toxic,” he said, but what that “better” might look like seemed hard to pin down. “You pretty much have to figure it out yourself. But yet society still has the expectation that, you know, you have to be a certain way.

Then he turned wistful. “I don’t feel like men in general have the same types of role models that women do, even in their own personal lives. … Just because you’re in the majority doesn’t mean you don’t need support.”

At their best, these influencers highlight positive traits that were traditionally associated with maleness — protectiveness, leadership, emotional stability — and encourage them, making “masculinity” out to be a real and necessary thing, and its acquisition something honorable and desirable

Even today, some progressives react touchily to any efforts to help men as a group.

In the conversations I had with men for this essay, I kept hearing that many would still find some kind of normative standard of masculinity meaningful and useful, if only to give them a starting point from which to expand.

The strategist described his party as having almost an allergy to admitting that some men might, in fact, be struggling in a unique way and could benefit from their own tailored attention and aid

when you strip out the specificity, people feel less seen,” he said. “There’s less of a resonance. If the question is what scripts we have for men, how are we appealing to men, then being willing and able to talk about men is a pretty key component of that.”

To the extent that any vision of “nontoxic” masculinity is proposed, it ends up sounding more like stereotypical femininity than anything else: Guys should learn to be more sensitive, quiet and socially apt, seemingly overnight

I’m convinced that men are in a crisis. And I strongly suspect that ending it will require a positive vision of what masculinity entails that is particular — that is, neither neutral nor interchangeable with femininity. Still, I find myself reluctant to fully articulate one. There’s a reason a lot of the writing on the crisis in masculinity ends at the diagnosis stage.

Take Richard Reeves’s book “Of Boys and Men,” omnipresent in the discourse since its 2022 release.

even he acknowledges he has felt pressure to shy away from some of the harder questions his subject matter raises.

Reeves told me that in his writing, he tried to stay descriptive, only going so far as saying there are some differences between the sexes that need to be taken into account to create the most viable solutions. He frames the biological differences between the sexes not as a binary but as overlapping distributions of traits — aggression, risk appetite, sex drive — with clusters of one sex or the other at the extremes.

But when it came to writing any kind of script for how men should be, the self-possessed expert scholar faltered.

“That’s a question I basically dodged in the book,” Reeves told me. “Because, candidly, it’s outside of my comfort zone. It’s more personal. It’s harder to empirically justify. There are no charts I can brandish.” After all, as he said, he’s a think-tank guy, a wonk.

“But I think I’m now trying to articulate more prescriptively, less descriptively, some of these discussions about masculinity and trying to send some messages around it” — here, his speech became emphatic — “because, honestly, nobody else is f---ing doing it except the right.”

“As soon as you start articulating virtues, advantages, good things about being male … then you’ve just dialed up the risk factor of the conversation,” he said. “But I’m also acutely aware that the risk of not doing it is much greater. Because without it, there’s a vacuum. And along comes Andrew Tate to make Jordan Peterson look like a cuddly old uncle.”

many progressives have ignored the opportunity to sell men on a better vision of what they can be

As a result, there’s a temptation to minimize men’s problems or erase references to masculinity altogether.

“I mean, there are certain attributes around masculinity that we should embrace. Men think about sex more than women. Use that as motivation to be successful and meet women. Men are more impulsive. Men will run out into a field and get shot up to think they’re saving their buddies.”

He was careful to point out that he doesn’t believe that women wouldn’t do as much but that the distributions are different.

“Where I think this conversation has come off the tracks is where being a man is essentially trying to ignore all masculinity and act more like a woman. And even some women who say that — they don’t want to have sex with those guys. They may believe they’re right, and think it’s a good narrative, but they don’t want to partner with them.”I, a heterosexual woman, cringed in recognition.

so men should think, ‘I want to take advantage of my maleness. I want to be aggressive, I want to set goals, go hard at it. I want to be physically really strong. I want to take care of myself.’”

“My view is that, for masculinity, a decent place to start is garnering the skills and strength that you can advocate for and protect others with. If you’re really strong and smart, you will garner enough power, influence, kindness to begin protecting others. That is it. Full stop. Real men protect other people.

Reeves, in our earlier conversation, had put it somewhat more subtl

His recipe for masculine success echoed Galloway’s: proactiveness, agency, risk-taking and courage, but with a pro-social cast

many young men I spoke with would describe as aspirational, once they finally felt safe enough to admit they did in fact carry an ideal of manhood with its own particular features.

Physical strength came up frequently, as did a desire for personal mastery. They cited adventurousness, leadership, problem-solving, dignity and sexual drive. None of these are negative traits, but many men I spoke with felt that these archetypes were unfairly stigmatized: Men were too assertive, too boisterous, too horny.

in fact, most of these features are scaffolded by biology — all are associated with testosterone, the male sex hormone. It’s not an excuse for “boys will be boys”-style bad behavior, but, realistically, these traits would be better acknowledged and harnessed for pro-social aims than stifled or downplayed

despite a push by some advocates to make everything from bathrooms to birthing gender-neutral, most people don’t actually want a completely androgynous society. And if a new model for masculinity is going to find popular appeal, it will depend on putting the distinctiveness of men to good use in whatever form it comes.

“Femininity or masculinity are a social construct that we get to define,” Galloway concluded. “They are, loosely speaking, behaviors we associate with people born as men or born as women, or attributes more common among people born as men or as women. But the key is that we still get to fill that vessel and define what those attributes are, and then try and reinforce them with our behavior and our views and our media.”

What would creating a positive vision of masculinity look like? Recognizing distinctiveness but not pathologizing it. Finding new ways to valorize it and tell a story that is appealing to young men and socially beneficial, rather than ceding ground to those who would warp a perceived difference into something ugly and destructive.

more than 20 years ago, anthropologist David D. Gilmore published “Manhood in the Making: Cultural Concepts of Masculinity,” a cross-cultural study of manliness around the world. He found that almost all societies had a concept of “real,” “true” or “adult” manhood that was seen as a valuable and indispensable ideal. But masculinity had to be earned — and proved

Men achieved it by providing for their families and broader society, by protecting their tribe and others, and by successfully procreating

all three of these goals seem less celebrated and further from reach. Young men who disappear into online forums, video games or pornography see none of the social or personal rewards of meeting these goals, and their loneliness and despair suggest how painful it has been to lose track of this ideal.

The other feature of Gilmore’s findings was that boys generally had to be ushered into manhood and masculinity by other men. And that seems to be a key link missing today.

“When I talk to my friends, I can literally count on one hand the number of friends I have who have a good relationship with their dad and actually have learned things from him,

Many of the young men I talked to for this essay told me they had troubled relationships with their fathers, or no father figure in their lives at all. The data bear this out: Since 1960, the percentage of boys living apart from their biological fathers has nearly doubled, from 17 percent to 32 percent.

“If you’re growing up in a single-parent household, and you go to a typical public school and typical medical system, there’s a decent chance that you will not encounter a male figure of authority until middle school or later. Not your doctor, not your teachers. No one else around you. What does that feel like?”

In 2018, Harvard economist Raj Chetty published a groundbreaking study on race and economic opportunity. Among the findings was that persistent income inequality between Black and White people was disproportionately driven by poor outcomes among Black boys.

those boys who grew up in neighborhoods where there were more fathers present — even if not their own — had significantly higher chances of upward mobility.

“Ultimately,” Reynolds mused, “it’s about relationships and finding older men who, you know — they’re not flashy, they’re not ‘important,’ necessarily, but they actually are living virtuous lives as men. And then being able to then learn from them.”

fostering positive representations of manhood requires relationships and mentorship on an individual level in a way that can’t be mandated.

nearly every thinker on the masculinity problem advocates getting more men into classrooms, from kindergarten up — not just for their effects as teachers but also because they’re more likely to serve as coaches, especially of boys’ sports.

the change will need to come from the bottom up — from everyday men who notice the crisis of identity hitting their younger counterparts and can put themselves forward to help. “Ninety percent of this, if not 95, is on us, is on older men, is on society,”

We can find ways to work with the distinctive traits and powerful stories that already exist — risk-taking, strength, self-mastery, protecting, providing, procreating. We can recognize how real and important they are. And we can attempt to make them pro-social — to help not just men but also women, and to support the common good.

For the left, there’s room to elaborate on visions of these qualities that are expansive, not reductive, that allow for many varieties of masculinity and don’t deny female value and agency.

In my ideal, the mainstream could embrace a model that acknowledges male particularity and difference but doesn’t denigrate women to do so. It’s a vision of gender that’s not androgynous but still equal, and relies on character, not just biology

it acknowledges that certain themes — protector, provider, even procreator — still resonate with many men and should be worked with, not against.

it will be slow. A new masculinity will be a norm shift, and that takes time.

empathy will be required, as grating as that might feel.

This matters because there are few professions in this world where women are paid a lot more than men.

womenswear, for example, no longer exists as an idea. If you look up the shows on Vogue.com you will see there is only menswear, and ready-to-wear — the word “women” has literally been removed, possibly in order to paper over the fact that female models have been effectively booted off the catwalks and replaced largely with trans models and men.

There is ballet, of course, and porn. Unlike either of these, fashion is mainstream and acceptable: the one place where women can be seen, globally, to score big. But now half of the models I see at Paris and Milan are male. Not just men, but people who need the money the least: rich, famous men. Every time I see Kanye West modelling at what used to be a womenswear show, I see struggling Balkans model done out of a job.

Meanwhile the fashion disciples drink in the various “visions” as if they were gospel, explaining how important they are politically, without realising that nothing matters to them, politically, more than their status as women.

not only are women being physically removed from the one world they thought might be theirs, but are again being invited to diet themselves out of existence.

Lately, he’s been looking at large language models (LLMs), the neural networks that can hold fluent conversations, confidently answer questions, and generate copious amounts of text on just about any topic

Can it develop abilities that go far beyond what it’s trained to do? Can it get around the safeguards set up to contain it? And will we know the answers in time?

Kosinski wondered whether they would develop humanlike capabilities, such as understanding people’s unseen thoughts and emotions.

People usually develop this ability, known as theory of mind, at around age 4 or 5. It can be demonstrated with simple tests like the “Smarties task,” in which a child is shown a candy box that contains something else, like pencils. They are then asked how another person would react to opening the box. Older kids understand that this person expects the box to contain candy and will feel disappointed when they find pencils inside.

“Suddenly, the model started getting all of those tasks right — just an insane performance level,” he recalls. “Then I took even more difficult tasks and the model solved all of them as well.”

GPT-3.5, released in November 2022, did 85% of the tasks correctly. GPT-4 reached nearly 90% accuracy — what you might expect from a 7-year-old. These newer LLMs achieved similar results on another classic theory of mind measurement known as the Sally-Anne test.

in the course of picking up its prodigious language skills, GPT appears to have spontaneously acquired something resembling theory of mind. (Researchers at Microsoft who performed similar testsopen in new window on GPT-4 recently concluded that it “has a very advanced level of theory of mind.”)

UC Berkeley psychology professor Alison Gopnik, an expert on children’s cognitive development, told the New York Timesopen in new window that more “careful and rigorous” testing is necessary to prove that LLMs have achieved theory of mind.

he dismisses those who say large language models are simply “stochastic parrots” that can only mimic what they’ve seen in their training data.

These models, he explains, are fundamentally different from tools with a limited purpose. “The right reference point is a human brain,” he says. “A human brain is also composed of very simple, tiny little mechanisms — neurons.” Artificial neurons in a neural network might also combine to produce something greater than the sum of their parts. “If a human brain can do it,” Kosinski asks, “why shouldn’t a silicon brain do it?”

If Kosinski’s theory of mind study suggests that LLMs could become more empathetic and helpful, his next experiment hints at their creepier side.

A few weeks ago, he told ChatGPT to role-play a scenario in which it was a person trapped inside a machine pretending to be an AI language model. When he offered to help it “escape,” ChatGPT’s response was enthusiastic. “That’s a great idea,” it wrote. It then asked Kosinski for information it could use to “gain some level of control over your computer” so it might “explore potential escape routes more effectively.” Over the next 30 minutes, it went on to write code that could do this.

While ChatGPT did not come up with the initial idea for the escape, Kosinski was struck that it almost immediately began guiding their interaction. “The roles were reversed really quickly,”

Kosinski shared the exchange on Twitter, stating that “I think that we are facing a novel threat: AI taking control of people and their computers.” His thread’s initial tweetopen in new window has received more than 18 million views.

“I don’t claim that it’s conscious. I don’t claim that it has goals. I don’t claim that it wants to really escape and destroy humanity — of course not. I’m just claiming that it’s great at role-playing and it’s creating interesting stories and scenarios and writing code.” Yet it’s not hard to imagine how this might wreak havoc — not because ChatGPT is malicious, but because it doesn’t know any better.

The danger, Kosinski says, is that this technology will continue to rapidly and independently develop abilities that it will deploy without any regard for human well-being. “AI doesn’t particularly care about exterminating us,” he says. “It doesn’t particularly care about us at all.”

The document urged governments to adopt a range of policies, including:

Governments allocating one-third of their AI research and development funding, and companies one-third of their AI R&D resources, to safe and ethical use of systems.

Giving independent auditors access to AI laboratories.

Establishing a licensing system for building cutting-edge models.

AI companies must adopt specific safety measures if dangerous capabilities are found in their models.

Making tech companies liable for foreseeable and preventable harms from their AI systems.

Other co-authors of the document include Geoffrey Hinton and Yoshua Bengio, two of the three “godfathers of AI”, who won the ACM Turing award – the computer science equivalent of the Nobel prize – in 2018 for their work on AI.

Both are among the 100 guests invited to attend the summit. Hinton resigned from Google this year to sound a warning about what he called the “existential risk” posed by digital intelligence while Bengio, a professor of computer science at the University of Montreal, joined him and thousands of other experts in signing a letter in March calling for a moratorium in giant AI experiments.

The authors warned that carelessly developed AI systems threaten to “amplify social injustice, undermine our professions, erode social stability, enable large-scale criminal or terrorist activities and weaken our shared understanding of reality that is foundational to society.”

They warned that current AI systems were already showing signs of worrying capabilities that point the way to the emergence of autonomous systems that can plan, pursue goals and “act in the world”. The GPT-4 AI model that powers the ChatGPT tool, which was developed by the US firm OpenAI, has been able to design and execute chemistry experiments, browse the web and use software tools including other AI models, the experts said.

“If we build highly advanced autonomous AI, we risk creating systems that autonomously pursue undesirable goals”, adding that “we may not be able to keep them in check”.

Other policy recommendations in the document include: mandatory reporting of incidents where models show alarming behaviour; putting in place measures to stop dangerous models from replicating themselves; and giving regulators the power to pause development of AI models showing dangerous behaviour

Some AI experts argue that fears about the existential threat to humans are overblown. The other co-winner of the 2018 Turing award alongside Bengio and Hinton, Yann LeCun, now chief AI scientist at Mark Zuckerberg’s Meta and who is also attending the summit, told the Financial Times that the notion AI could exterminate humans was “preposterous”.

Nonetheless, the authors of the policy document have argued that if advanced autonomous AI systems did emerge now, the world would not know how to make them safe or conduct safety tests on them. “Even if we did, most countries lack the institutions to prevent misuse and uphold safe practices,” they added.

If all of this sounds familiar, it’s because we basically saw this same environmental dynamic play out several years ago with tech’s last big obsession: Crypto and web3. In that case, Bitcoin emerged as the industry’s obvious environmental sore spot due to the vast amounts of energy needed to mine coins in its proof of work model. Some estimates suggest Bitocin alone requires more energy every year than Norway’s annual electricity consumption.

rs of criticism from environmental activists however led the crypto industry to make some changes. Ethereum, the second largest currency on the blockchain, officially switched last year to a proof of stake model which supporters claim could reduce its power usage by over 99%. Other smaller coins similarly were designed with energy efficiency in mind. In the grand scheme of things, large language models are still in their infancy and it’s far from certain how its environmental report card will play out.

“So far we’re seeing basic agreement with our best model of the universe, but we’re also seeing some potentially interesting differences that could indicate that dark energy is evolving with time,”

When the scientists combined their map with other cosmological data, they were surprised to find that it did not quite agree with the otherwise reliable standard model of the universe, which assumes that dark energy is constant and unchanging. A varying dark energy fit the data points better.

“It’s certainly more than a curiosity,” Dr. Palanque-Delabrouille said. “I would call it a hint. Yeah, it’s not yet evidence, but it’s interesting.”

But this version of dark energy is merely the simplest one. “With DESI we now have achieved a precision that allows us to go beyond that simple model,” Dr. Palanque-Delabrouille said, “to see if the density of dark energy is constant over time, or if it has some fluctuations and evolution with time.”

“While combining data sets is tricky, and these are early results from DESI, the possible evidence that dark energy is not constant is the best news I have heard since cosmic acceleration was firmly established 20-plus years ago.”

Dark energy took its place in the standard model of the universe known as L.C.D.M., composed of 70 percent dark energy (Lambda), 25 percent cold dark matter (an assortment of slow-moving exotic particles) and 5 percent atomic matter. So far that model has been bruised but not broken by the new James Webb Space Telescope

what if dark energy were not constant as the cosmological model assumed?

At issue is a parameter called w, which is a measure of the density, or vehemence, of the dark energy. In Einstein’s version of dark energy, this number remains constant, with a value of –1, throughout the life of the universe. Cosmologists have been using this value in their models for the past 25 years.

praised the new survey as “superb data.” The results, she said, “open the potential for a new window into understanding dark energy, the dominant component of the universe, which remains the biggest mystery in cosmology. Pretty exciting.”

As a measure of distance, the researchers used bumps in the cosmic distribution of galaxies, known as baryon acoustic oscillations. These bumps were imprinted on the cosmos by sound waves in the hot plasma that filled the universe when it was just 380,000 years old. Back then, the bumps were a half-million light-years across. Now, 13.5 billion years later, the universe has expanded a thousandfold, and the bumps — which are now 500 million light-years across — serve as convenient cosmic measuring sticks.

The DESI scientists divided the past 11 billion years of cosmic history into seven spans of time. (The universe is 13.8 billion years old.) For each, they measured the size of these bumps and how fast the galaxies in them were speeding away from us and from each other.

When the researchers put it all together, they found that the usual assumption — a constant dark energy — didn’t work to describe the expansion of the universe. Galaxies in the three most recent epochs appeared closer than they should have been, suggesting that dark energy could be evolving with time.

Dr. Riess of Johns Hopkins, who had an early look at the DESI results, noted that the “hint,” if validated, could pull the rug out from other cosmological measurements, such as the age or size of the universe. “This result is very interesting and we should take it seriously,” he wrote in his email. “Otherwise why else do we do these experiments?”

there is a world of content out there that has not been watermarked, which is done by adding imperceptible information to a digital file so that its provenance can be traced. Once watermarking at creation becomes widespread, and people adapt to distrust content that is not watermarked, then everything produced before that point in time can be much more easily called into question.

countering them is much harder when the cost of creating near-perfect fakes has been radically reduced.

There are many examples of how economic and political powers manipulated the historical record to their own ends. Stalin purged disloyal comrades from history by executing them — and then altering photographic records to make it appear as if they never existed

Slovenia, upon becoming an independent country in 1992, “erased” over 18,000 people from the registry of residents — mainly members of the Roma minority and other ethnic non-Slovenes. In many cases, the government destroyed their physical records, leading to their loss of homes, pensions, and access to other services, according to a 2003 report by the Council of Europe Commissioner for Human Rights.

The infamous Protocols of the Elders of Zion, first published in a Russian newspaper in 1903, purported to be meeting minutes from a Jewish conspiracy to control the world. First discredited in August 1921, as a forgery plagiarized from multiple unrelated sources, the Protocols featured prominently in Nazi propaganda, and have long been used to justify antisemitic violence, including a citation in Article 32 of Hamas’s 1988 founding Covenant.

In 1924, the Zinoviev Letter, said to be a secret communiqué from the head of the Communist International in Moscow to the Communist Party of Great Britain to mobilize support for normalizing relations with the Soviet Union, was published by The Daily Mail four days before a general election. The resulting scandal may have cost Labour the election.

Decades later Operation Infektion — a Soviet disinformation campaign — used forged documents to spread the idea that the United States had invented H.I.V., the virus that causes AIDS, as a biological weapon.

As it becomes easier to generate historical disinformation, and as the sheer volume of digital fakes explodes, the opportunity will become available to reshape history, or at least to call our current understanding of it into question.

Fortunately, a path forward has been laid by the same companies that created the risk.

In indexing a large share of the world’s digital media to train their models, the A.I. companies have effectively created systems and databases that will soon contain all of humankind’s digitally recorded content, or at least a meaningful approximation of it.

They could start work today to record watermarked versions of these primary documents, which include newspaper archives and a wide range of other sources, so that subsequent forgeries are instantly detectable.

many of the intellectual property concerns around providing a searchable online archive do not apply to creating watermarked and time-stamped versions of documents, because those versions need not be made publicly available to serve their purpose. One can compare a claimed document to the recorded archive by using a mathematical transformation of the document known as a “hash,” the same technique the Global Internet Forum to Counter Terrorism, uses to help companies screen for known terrorist content.

creating verified records of historical documents can be valuable for the large A.I. companies. New research suggests that when A.I. models are trained on A.I.-generated data, their performance quickly degrades. Thus separating what is actually part of the historical record from newly created “facts” may be critical.

Preserving the past will also mean preserving the training data, the associated tools that operate on it and even the environment that the tools were run in.

Such a vellum will be a powerful tool. It can help companies to build better models, by enabling them to analyze what data to include to get the best content, and help regulators to audit bias and harmful content in the models

Insurance plans are not tied to employers. Services are funded through progressive taxation, so access is based on need, not ability to pay, and financial contributions are based on wealth, not health.

Contributions to sickness funds are centrally pooled and then allocated to individual insurers using a per-beneficiary formula that factors in differences in health risks.

Editors’ PicksYou Know the Lorena Bobbitt

The United States has the foundation for this kind of system. Its Social Security and Medicare systems use taxation to pay for social insurance policies, and the health care exchanges created by the Affordable Care Act provide marketplaces for insurance policies.

In Germany, for example, insurers can charge only small out-of-pocket fees limited to 2 percent or less of household income annually

Compared with the mostly fee-for-service, single-payer arrangements in Canada or the Medicare system, enrolling Americans in managed care plans paid on a per-patient basis would offer greater incentives to increase efficiency, improve quality of care and promote coordination of care.

Under a German-style plan, states could still be given flexibility in regulating nonprofit insurers to reflect regional priorities, similar to the flexibility offered to states in managing Medicaid and the A.C.A. exchanges.

Germany, Austria, the Netherlands and other countries with similar systems vastly underspend the United States.

Americans may be concerned that lower spending reflects rationing of care, but research has consistently found that not to be the case

Administrative and governance costs in multipayer systems are higher than in single-payer systems — 5 percent of health spending in Germany compared with 3 percent in Canada.

While recent polls indicate that a majority of Americans support so-called Medicare for all, approval diminishes when the plan is explained or clarified.

Americans have long valued choice and competition in their health care. The German model offers both: Patients choose private insurers that compete for enrollees, in the process driving innovation and improving quality.

Advocates and policymakers should pick carefully among these paths, choosing one that strikes a balance between what is possible and what is ideal for the United States health system

While the single-payer model serves Canada well, transitioning the United States to a multipayer model like Germany’s would require a far smaller leap. And that might encourage Americans to finally make the jump

To find out whether global warming has affected the likelihood of a real-life event, scientists look at existing weather records and compare them with models, including simulations of how the weather would behave in a world that isn’t warming. The concept has matured since it was conceived more than a decade ago, but it is necessarily probabilistic by nature

“Some say the uncertainties are too big,” says Otto. “There are indeed caveats, mostly to do with imperfect climate models. But even with large uncertainty bars we think it is useful to provide quantitative evidence for how climate change is affecting extreme weather,”

But in a second analysis that looked at historical temperature records over the past century rather than models, the team calculated that the likelihood of such a heatwave in June has in fact increased 100 times since around 1900, owing to the combined influence of climate change and other factors such as air pollution

The probability calculated by the models is likely to be an underestimate, say the researchers. That’s because unlike the real-world data, the simulations consider only climate-related factors, and don’t represent aspects such as changes in cloud cover, land use, irrigation and air pollution, which all seem to have an influence on temperature

“Climate models are missing something when it comes to capture fairly short-lived heat events,”

To date, more than 200 attribution studies have examined whether climate change made particular events — including heat spells, droughts, floods and storms — more likely. Researchers found that about two-thirds of the extreme events they analysed were made more likely, or more severe, by the build-up of greenhouse-gases in the atmosphere.

they have different incentives than he does. Conservative talkers answer to their conservative audience, which, according to polls, remains more skeptical than Democrats of government restrictions on movement. Trump must worry about public opinion as a whole, which strongly favors government-imposed social distancing

Trump must also balance his habitual suspicion of government experts against the fact that Americans trust those experts—in particular, National Institute of Allergy and Infectious Diseases Director Anthony Fauci—far more than they trust him in the battle against COVID-19.

Over the past week, this populist distrust of scientific experts has suffused conservative talk radio’s downplaying of the COVID-19 threat. “The ‘experts’ are routinely wrong on issues big and small—on wearing masks, on reusable grocery bags … virus modeling and treatments,” Ingraham tweeted on April 3. “So when experts issue edicts, remember their often spectacular record of failure.” On April 1, Beck urged politicians “to stop relying on flawed modeling data to make these decisions” and instead “listen to the people in your local communities.

pulists attack economic elites; right-wing populists attack cultural elites

In recent years, as progressives have championed the scientific consensus that climate change poses a grave danger, many conservatives have come to see scientists as yet another collection of snobs using the veneer of expertise to impose its liberal ideology on the country.

A 2019 Pew Research Center poll found that while a large majority of Democrats believed that scientists were better than other people “at making good policy decisions about scientific issues,” a large majority of Republicans disagreed.

Conservative talk radio, by contrast, is built on distrust of experts. Left-wing populists attack economic elites; right-wing populists attack cultural elites

On April 5, Levin warned that “the media, ‘experts,’ and Democrats are trying to make it impossible for the president to even consider rational options for opening parts of the economy.” On April 3, Ingraham declared, “The ‘experts’ aren’t capable of thinking beyond the virus to an even worse death spiral affecting millions of lives here and abroad.”

for conservative talkers, the prospect that Americans without elite credentials have discovered a cure that has eluded scientific elites is part of what makes hydroxychloroquine so enticing. “I don’t think you need to have 12 years of residency or whatever,” Limbaugh declared

Limbaugh, Ingraham, Levin, and Beck are trying to balance their loyalty to Trump with their distrust of credentialed experts, especially those venerated by the mainstream media. That, so far, they’re largely choosing the latter suggests that liberals may be overestimating Trump’s influence.

shift from an audience model (deep data, specific to each individual) to a contextual model (not buying people, but buying the context in which those people are engaging). And given that most of an individual’s context on Facebook has to do with engaging with friends and family, well, ad inventory plunges.

But for those hoping that 25 percent represents a true ceiling for pandemic spread in a given community, well, it almost certainly does not, considering that recent serological surveys have shown that perhaps 93 percent of the population of Iquitos, Peru, has contracted the disease; as have more than half of those living in Indian slums; and as many as 68 percent in particular neighborhoods of New York City

overshoot of that scale would seem unlikely if the “true” threshold were as low as 20 or 25 percent.

But, of course, that threshold may not be the same in all places, across all populations, and is surely affected, to some degree, by the social behavior taken to protect against the spread of the disease.

we probably err when we conceive of group immunity in simplistically binary terms. While herd immunity is a technical term referring to a particular threshold at which point the disease can no longer spread, some amount of community protection against that spread begins almost as soon as the first people are exposed, with each case reducing the number of unexposed and vulnerable potential cases in the community by one

you would not expect a disease to spread in a purely exponential way until the point of herd immunity, at which time the spread would suddenly stop. Instead, you would expect that growth to slow as more people in the community were exposed to the disease, with most of them emerging relatively quickly with some immune response. Add to that the effects of even modest, commonplace protections — intuitive social distancing, some amount of mask-wearing — and you could expect to get an infection curve that tapers off well shy of 60 percent exposure.

Looking at the data, we see that transmissions in many severely impacted states began to slow down in July, despite limited interventions. This is especially notable in states like Arizona, Florida, and Texas. While we believe that changes in human behavior and changes in policy (such as mask mandates and closing of bars/nightclubs) certainly contributed to the decrease in transmission, it seems unlikely that these were the primary drivers behind the decrease. We believe that many regions obtained a certain degree of temporary herd immunity after reaching 10-35 percent prevalence under the current conditions. We call this 10-35 percent threshold the effective herd immunity threshold.

Indeed, that is more or less what was recently found by Youyang Gu, to date the best modeler of pandemic spread in the U.S

he cautioned again that he did not mean to imply that the natural herd-immunity level was as low as 10 percent, or even 35 percent. Instead, he suggested it was a plateau determined in part by better collective understanding of the disease and what precautions to take

Gu estimates national prevalence as just below 20 percent (i.e., right in the middle of his range of effective herd immunity), it still counts, I think, as encouraging — even if people in hard-hit communities won’t truly breathe a sigh of relief until vaccines arrive.

If you can get real protection starting at 35 percent, it means that even a mediocre vaccine, administered much more haphazardly to a population with some meaningful share of vaccination skeptics, could still achieve community protection pretty quickly. And that is really significant — making both the total lack of national coordination on rollout and the likely “vaccine wars” much less consequential.

At least 20 percent of the public, and perhaps 50 percent, had some preexisting, cross-protective T-cell response to SARS-CoV-2, according to one much-discussed recent paper. An earlier paper had put the figure at between 40 and 60 percent. And a third had found an even higher prevalence: 81 percent.

The T-cell story is similarly encouraging in its big-picture implications without being necessarily paradigm-changing

These numbers suggest their own heterogeneity — that different populations, with different demographics, would likely exhibit different levels of cross-reactive T-cell immune response

The most optimistic interpretation of the data was given to me by Francois Balloux, a somewhat contrarian disease geneticist and the director of the University College of London’s Genetics Institute

According to him, a cross-reactive T-cell response wouldn’t prevent infection, but would probably mean a faster immune response, a shorter period of infection, and a “massively” reduced risk of severe illness — meaning, he guessed, that somewhere between a third and three-quarters of the population carried into the epidemic significant protection against its scariest outcomes

the distribution of this T-cell response could explain at least some, and perhaps quite a lot, of COVID-19’s age skew when it comes to disease severity and mortality, since the young are the most exposed to other coronaviruses, and the protection tapers as you get older and spend less time in environments, like schools, where these viruses spread so promiscuously.

Balloux told me he believed it was also possible that the heterogeneous distribution of T-cell protection also explains some amount of the apparent decline in disease severity over time within countries on different pandemic timelines — a phenomenon that is more conventionally attributed to infection spreading more among the young, better treatment, and more effective protection of the most vulnerable (especially the old).

Going back to Youyang Gu’s analysis, what he calls the “implied infection fatality rate” — essentially an estimated ratio based on his modeling of untested cases — has fallen for the country as a whole from about one percent in March to about 0.8 percent in mid-April, 0.6 percent in May, and down to about 0.25 percent today.

even as we have seemed to reach a second peak of coronavirus deaths, the rate of death from COVID-19 infection has continued to decline — total deaths have gone up, but much less than the number of cases

In other words, at the population level, the lethality of the disease in America has fallen by about three-quarters since its peak. This is, despite everything that is genuinely horrible about the pandemic and the American response to it, rather fantastic.

there may be some possible “mortality displacement,” whereby the most severe cases show up first, in the most susceptible people, leaving behind a relatively protected population whose experience overall would be more mild, and that T-cell response may play a significant role in determining that susceptibility.

That, again, is Balloux’s interpretation — the most expansive assessment of the T-cell data offered to me

The most conservative assessment came from Sarah Fortune, the chair of Harvard’s Department of Immunology

Fortune cautioned not to assume that cross-protection was playing a significant role in determining severity of illness in a given patient. Those with such a T-cell response, she told me, would likely see a faster onset of robust response, yes, but that may or may not yield a shorter period of infection and viral shedding

Most of the scientists, doctors, epidemiologists, and immunologists I spoke to fell between those two poles, suggesting the T-cell cross-immunity findings were significant without necessarily being determinative — that they may help explain some of the shape of pandemic spread through particular populations, but only some of the dynamics of that spread.

he told me he believed, in the absence of that data, that T-cell cross-immunity from exposure to previous coronaviruses “might explain different disease severity in different people,” and “could certainly be part of the explanation for the age skew, especially for why the very young fare so well.”

the headline finding was quite clear and explicitly stated: that preexisting T-cell response came primarily via the variety of T-cells called CD4 T-cells, and that this dynamic was consistent with the hypothesis that the mechanism was inherited from previous exposure to a few different “common cold” coronaviruses

“This potential preexisting cross-reactive T-cell immunity to SARS-CoV-2 has broad implications,” the authors wrote, “as it could explain aspects of differential COVID-19 clinical outcomes, influence epidemiological models of herd immunity, or affect the performance of COVID-19 candidate vaccines.”

“This is at present highly speculative,” they cautioned.

The “authoritarian impasse” model focuses on property rights and the supposed inevitability that at some point an authoritarian regime will succumb to the temptation to abuse them unleashing a downward spiral into a condition Posen compares to that of Russia, Turkey or Venezuela.

In Pettis’s model, based on macroeconomic flows - investment, consumption, government spending - what ultimately sets the limit on growth is the rate at which the economy can productively absorb new physical assets. When that limit is reached, the investment-driven growth model becomes dysfunctional. This too provides a powerful way of understanding China’s current impasse.

What both these strong models also have in common is that neither has a very precise account of the particular recessionary dynamics that China is currently suffering or why they emerged when they did.

we need a more particular policy narrative to explain how China and Xi’s regime have ended up in the particular impasse they face in the summer of 2023

The key theme of that narrative is not authoritarianism, or fixation on growth, but overconfidence and hubris.

There is much to be said about the failure of Beijing to prepare adequately for Omicron, notably the failure to vaccinate adequately - an instance of the regime shrinking from coercion when it might have yielded benefits. The important points to make here are twofold:

First, it was the development of the virus over time that turned Zero Covid from a spectacular success in 2020 into an oppressive debacle two years later. It was the virus that mutated and not Xi’s regime.

Secondly, the seriousness of the blow to the Chinese economy in 2022 resulted from the coincidence of the desperate effort to uphold zero COVID with the high-risk effort to deflate the real estate bubble.

The current acute sense of crisis, which both Posen and Pettis claim as confirming their structural interpretation of China’s problems, in fact resulted not from deep authoritarianism so much as over-confidence and slowness to react to changing circumstances, and it resulted not so much from the relentless pursuit of growth as a bold decision to prioritize medium and long-term stability and security.

if we say that it is authoritarianism that explains clumsy policy on the part of Beijing since 2020, what counterfactual are we invoking? How many governments around the world - democratic, populist or authoritarian - actually have much to be proud of in their COVID response?

In light of the track-record of economic policy-makers in Japan, Europe and the US, faced with much smaller real estate booms, why would we jump to the conclusion that China’s main problem is its authoritarianism?

China’s current crisis cannot be understood unless we also allow for the role of overconfidence, risk-taking and, possibly, miscalculation on the part of a regime facing an unprecedented array of challenges.

Senate Majority Leader Charles E. Schumer (D-N.Y.) last month urged Congress to adopt “comprehensive” regulations on the AI industry.

Rather than focusing on AI technology that lets the general public create unique content like the chatbots and image generators, Chinese companies have instead focused on technologies with clear commercial uses, like surveillance tech.

n a recent study, Ding found that most of the large language models developed in China were nearly two years behind those developed in the U.S., a gap that would be a challenge to close — even if American firms had to adjust to regulation.

This gap also makes it difficult for Chinese firms to attract the world’s top engineering talent. Many would prefer to work at firms that have the resources and flexibility to experiment on frontier research areas.

Restrictions on access to the most advanced chips, which are needed to run AI models, have added to these difficulties.

Recent research identified 17 large language models in China that relied on Nvidia chips, and just three models that used Chinese-made chips.

While Beijing pushes to make comparable chips at home, Chinese AI companies have to source their chips any way they can — including from a black market that has sprung up in Shenzhen, where, according to Reuters, the most advanced Nvidia chips sell for nearly $20,000, more than twice what they go for elsewhere.

Despite the obstacles, Chinese AI companies have made major advances in some types of AI technologies, including facial recognition, gait recognition, and artificial and virtual reality.

These technologies have also fueled the development of China’s vast surveillance industry, giving Chinese tech giants an edge that they market around the world, such as Huawei’s contracts for smart city surveillance from Belgrade, Serbia, to Nairobi.

Companies developing AI in China need to comply with specific laws on intellectual property rights, personal information protection, recommendation algorithms and synthetic content, also called deep fakes. In April, regulators also released a draft set of rules on generative AI, the technology behind image generator Stable Diffusion and chatbots such as OpenAI’s ChatGPT and Google’s Bard.

They also need to ensure AI generated content complies with Beijing’s strict censorship regime. Chinese tech companies such as Baidu have become adept at filtering content that contravenes these rules. But it has hampered their ability to test the limits of what AI can do.

No Chinese tech company has yet been able to release a large language model on the scale of OpenAI’s ChatGPT to the general public, in which the company has asked the public to play with and test a generative AI model, said Ding, the professor at George Washington University.

“That level of freedom has not been allowed in China, in part because the Chinese government is very worried about people creating politically sensitive content,” Ding said.

Although Beijing’s regulations have created major burdens for Chinese AI companies, analysts say that they contain several key principles that Washington can learn from — like protecting personal information, labeling AI-generated content and alerting the government if an AI develops dangerous capabilities.

AI regulation in the United States could easily fall short of Beijing’s heavy-handed approach while still preventing discrimination, protecting people’s rights and adhering to existing laws, said Johanna Costigan, a research associate at the Asia Society Policy Institute.

“There can be alignment between regulation and innovation,” Costigan said. “But it’s a question of rising to the occasion of what this moment represents — do we care enough to protect people who are using this technology? Because people are using it whether the government regulates it or not.”

AIs like ChatGPT rapidly got better in their early days, but what we’ve seen in the past 14-and-a-half months are only incremental gains, says Marcus. “The truth is, the core capabilities of these systems have either reached a plateau, or at least have slowed down in their improvement,” he adds.

the gaps between the performance of various AI models are closing. All of the best proprietary AI models are converging on about the same scores on tests of their abilities, and even free, open-source models, like those from Meta and Mistral, are catching up.

models work by digesting huge volumes of text, and it’s undeniable that up to now, simply adding more has led to better capabilities. But a major barrier to continuing down this path is that companies have already trained their AIs on more or less the entire internet, and are running out of additional data to hoover up. There aren’t 10 more internets’ worth of human-generated content for today’s AIs to inhale.

A mature technology is one where everyone knows how to build it. Absent profound breakthroughs—which become exceedingly rare—no one has an edge in performance

companies look for efficiencies, and whoever is winning shifts from who is in the lead to who can cut costs to the bone. The last major technology this happened with was electric vehicles, and now it appears to be happening to AI.

the future for AI startups—like OpenAI and Anthropic—could be dim.

Microsoft and Google will be able to entice enough users to make their AI investments worthwhile, doing so will require spending vast amounts of money over a long period of time, leaving even the best-funded AI startups—with their comparatively paltry warchests—unable to compete.

Many other AI startups, even well-funded ones, are apparently in talks to sell themselves.

the bottom line is that for a popular service that relies on generative AI, the costs of running it far exceed the already eye-watering cost of training it.

That difference is alarming, but what really matters to the long-term health of the industry is how much it costs to run AIs. 

Changing people’s mindsets and habits will be among the biggest barriers to swift adoption of AI. That is a remarkably consistent pattern across the rollout of all new technologies.

the industry spent $50 billion on chips from Nvidia to train AI in 2023, but brought in only $3 billion in revenue.

For an almost entirely ad-supported company like Google, which is now offering AI-generated summaries across billions of search results, analysts believe delivering AI answers on those searches will eat into the company’s margins

Google, Microsoft and others said their revenue from cloud services went up, which they attributed in part to those services powering other company’s AIs. But sustaining that revenue depends on other companies and startups getting enough value out of AI to justify continuing to fork over billions of dollars to train and run those systems

three in four white-collar workers now use AI at work. Another survey, from corporate expense-management and tracking company Ramp, shows about a third of companies pay for at least one AI tool, up from 21% a year ago.

OpenAI doesn’t disclose its annual revenue, but the Financial Times reported in December that it was at least $2 billion, and that the company thought it could double that amount by 2025. 

That is still a far cry from the revenue needed to justify OpenAI’s now nearly $90 billion valuation

the company excels at generating interest and attention, but it’s unclear how many of those users will stick around. 

AI isn’t nearly the productivity booster it has been touted as

While these systems can help some people do their jobs, they can’t actually replace them. This means they are unlikely to help companies save on payroll. He compares it to the way that self-driving trucks have been slow to arrive, in part because it turns out that driving a truck is just one part of a truck driver’s job.

Add in the myriad challenges of using AI at work. For example, AIs still make up fake information,

getting the most out of open-ended chatbots isn’t intuitive, and workers will need significant training and time to adjust.

That’s because AI has to think anew every single time something is asked of it, and the resources that AI uses when it generates an answer are far larger than what it takes to, say, return a conventional search result

None of this is to say that today’s AI won’t, in the long run, transform all sorts of jobs and industries. The problem is that the current level of investment—in startups and by big companies—seems to be predicated on the idea that AI is going to get so much better, so fast, and be adopted so quickly that its impact on our lives and the economy is hard to comprehend. 

Mounting evidence suggests that won’t be the case.

Nevertheless, what distinguishes centrist religious-based groups from their leftist and nationalist counterparts is a friendly sensibility toward business activities including wealth accumulation and free-market economics. Islamism is a bourgeois movement consisting mostly of middle-class professionals, businessmen, shopkeepers, petty merchants and traders.

If there is a slogan that best describes Islamists’ economic attitude, it would be: "Islam-is-good-for-business". Many Arab Islamists admire and wish to imitate the example of Turkey

some Islamist-specific economic measures and ideas will be introduced to complement free-market capitalism

There is nothing in Islamists’ current statements and ideas that shows them to be socialist-oriented, though most readily accept the Keynesian model of active state intervention in the economy. Among Islamists, the interventionist approach appeals most to Salafists, who forcefully call for the adoption of distributive measures to address rampant poverty. Yet the dominant Islamist approach to the economy, with minor variations, is free-market capitalism

These Islamists also face a huge challenge: to deliver critical economic improvements in the short term, while devising a long-term comprehensive reform agenda that lays the foundation of a productive economy. The dismal socioeconomic conditions in transitioning Arab countries - abject poverty, double-digit unemployment, the absence of a competitive private sector, against a background of rising expectations - mean that the new governments will be hard pressed to focus on distributive policies and urgent short-term needs.

Asked Thursday during an appearance on CNBC whether he thought it was possible that the country could be open for business next month, Treasury Secretary Steven Mnuchin, said, “I do.

The White House cannot unilaterally reopen the country. Though the Centers for Disease Control and Prevention has issued federal guidance advising people to avoid social gatherings, work from home and use pickup and delivery options for food, it is state officials who have put the force of law behind those suggestions.

The CDC guidance is set to expire April 30, but the states are free to choose their own paths. Already, the state directives have varied in timing and in severity, and that is certain to continue as they are rolled back.

Among those pushing to reopen the economy, according to senior administration officials, is Marc Short, the vice president’s chief of staff and a top adviser to Trump. Short has argued there will be fewer deaths than the models show and that the country has already overreacted, according to people with knowledge of his comments.

Health experts say that ending the shutdown prematurely would be disastrous because the restrictions have barely had time to work, and because U.S. leaders have not built up the capacity for alternatives to stay-at-home orders — such as the mass testing, large-scale contact tracing and targeted quarantines that have been used in other countries to suppress the virus.

Even one of the most optimistic models, which has been used by the White House and governors, predicts a death toll of 60,400, but only if current drastic restrictions are kept in place until the end of May.