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Worldwide fossil fuel emissions are expected to be up 0.6% in 2019 over 2018, according to projections from the Global Carbon Project. In the past decade, humans have put more than 350 metric gigatons of carbon dioxide into the atmosphere from burning fossil fuels and other industrial processes, according to calculations provided by the World Resources Institute.

Meanwhile, scientists are becoming even more concerned about tipping points in the climate system that could lead to rapid rise in sea levels, the deterioration of the Amazon and so on. One particularly frightening commentary last month in the journal Nature, by several notable climate scientists, says the odds we can avoid tipping points in the climate system "could already have shrunk towards zero." In non-science-speak: We're there now.

This was the decade when some people finally started to see the climate crisis as personal. Climate attribution science, which looks for human fingerprints on extreme weather events, made its way into the popular imagination. We're starting to realize there are no truly "natural" disasters anymore. We've warmed the climate, and we're already making storms riskier.

The news media is picking that up, using terms such as "climate emergency" and "climate crisis" instead of the blander "climate change." Increasingly, lots of people are making these critical connections, which should motivate the political, social and economic revolution necessary to fix things.

Only 52% of American adults say they are "very" or "extremely" sure global warming is happening, according to a report from the Yale Program on Climate Change Communication and the George Mason University Center for Climate Change Communication, which is based on a 1,303 person survey conducted in November 2019. Yale's been asking that question for a while now. Go back a decade, to 2009, and the rate is about the same: 51%.

The bright spot -- and it truly is a bright one -- is that young people are waking up. They are shouting, loudly and with purpose. Witness Greta Thunberg, the dynamic teenager who started a one-girl protest outside the Swedish Parliament last year, demanding that adults take seriously this emergency, which threatens young people and future generations disproportionately.

one of the leading modelers, Gabriela Gomes, suggested the entire area of research was being effectively blackballed out of fear it might encourage a relaxation of pandemic vigilance. “This is the very sad reason for the absence of more optimistic projections on the development of this pandemic in the scientific literature,” she wrote on Twitter. “Our analysis suggests that herd-immunity thresholds are being achieved despite strict social-distancing measures.”

Gomes suggested, herd immunity could happen with as little as one quarter of the population of a community exposed — or perhaps just 20 percent. “We just keep running the models, and it keeps coming back at less than 20 percent,” she told Hamblin. “It’s very striking.” Such findings, if they held up, would be very instructive, as Hamblin writes: “It would mean, for instance, that at 25 percent antibody prevalence, New York City could continue its careful reopening without fear of another major surge in cases.”

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.

But critics of the critics of cancel culture make a powerful retort. Accusing others of canceling can, they claim, be a way to stigmatize legitimate criticism. As Hannah Giorgis writes in the Atlantic, “critical tweets are not censorship.”

So what, exactly, does a cancellation consist of? And how does it differ from the exercise of free speech and robust critical debate?

At a conceptual level, the difference is clear. Criticism marshals evidence and arguments in a rational effort to persuade.

Canceling, by contrast, seeks to organize and manipulate the social or media environment in order to isolate, deplatform or intimidate ideological opponents

its intent—or at least its predictable outcome—is to coerce conformity and reduce the scope for forms of criticism that are not sanctioned by the prevailing consensus of some local majority.

In practice, however, telling canceling apart from criticism can be difficult because both take the form of criticizing others.

The more signs you see, the more certain you can be that you are looking at a cancel campaign.

A better approach might therefore be diagnostic. Like the symptoms of cancer, the hallmarks of a cancellation are many. Though not all instances involve every single characteristic, they all involve some of its key attribute

Six warning signs make up my personal checklist for cancel culture.

Punitiveness

A critical culture seeks to correct rather than punish. In science, the penalty for being wrong is not that you lose your job or your friends. Normally, the only penalty is that you lose the argument

Canceling, by contrast, seeks to punish rather than correct—and often for a single misstep rather than a long track record of failure

Deplatforming

A critical culture tolerates dissent rather than silencing it. It understands that dissent can seem obnoxious, harmful, hateful and, yes, unsafe.

Canceling, by contrast, seeks to shut up and shout down its targets. Cancelers often define the mere act of disagreeing with them as a threat to their safety or even an act of violence

Organization

Critical culture relies on persuasion. The way to win an argument is to convince others that you are right.

By contrast, it’s common to see cancelers organize hundreds of petition-signers or thousands of social media users to dig up and prosecute an indictment.

Secondary Boycotts

With its commitments to exploring a wide range of ideas and correcting rather than coercing the errant, a critical culture sees no value in instilling a climate of fear

But instilling fear is what canceling is all about. By choosing targets unpredictably (almost anything can trigger a campaign), providing no safe harbors (even conformists can get hit), and implicitly threatening anyone who sides with those who are targeted, canceling sends the message: “you could be next.”

Moral Grandstanding

Precisely because speech can be hurtful, critical culture discourages extreme rhetoric. It encourages people to listen to each other, to use evidence and argumentation, to behave reasonably and to avoid personal attacks.

Cancel culture is much more invested in what philosophers Justin Tosi and Brandon Warmke call “moral grandstanding”: the display of moral outrage to impress one’s peer group, dominate others, or both

Truthiness

Concern for accuracy is the north star of a critical culture. Not everyone gets every fact right, nor do people always agree on what is true; and yet people in a critical culture try to present their own and others’ viewpoints honestly and accurately.

canceling is not about seeking truth or persuading others; it is a form of information warfare, in which truthiness suffices if it serves the cause.

Those are my six warning signs. If you spot one or two, you should fear that a canceling may be happening; if you see five or six, you can be sure.

Though our critics like to claim that those of us who worry about cancel culture just don’t like being criticized on the internet, cancel culture is all too real. And though it may at times bear a superficial resemblance to critical culture, the two are diametrically opposed—and not so very difficult to tell apart.

One aspect of the future that demographics can’t help predict are technological innovations.

About 70 percent of the world population is expected to live in urban areas by 2050, according to data from the United Nations.

The U.S. Energy Information Administration projects that the world will need about 28 percent more energy in 2040 than it did in 2015 based on the number of people in the country and consumption patterns; on our current trajectory, about 42 percent of electricity in the United States will come from renewable sources.

Technology has led us to expect that goods and services will be delivered at the push of a button, often within minutes.

Entrepreneurs, industry leaders and policymakers are already at work solving some of the problems that demographic data suggest are ahead of us, whether it’s figuring out how to incentivize farmers to sequester carbon, use insurance as a tool for reducing coal production, reinvent the motors that power heavy industry so they use less energy, or write laws that help govern code.

What about the metaverse? Or crypto technology? Or robots taking our jobs? Or A.I. taking over everything? Demographics can’t answer those questions. All of those things may happen, but life in 2041 may also look a lot like it does today — maybe with the exception of those flying cars.

traditionally “masculine” virtues are not exclusively male. Women who successfully model these attributes are all around us

Rudyard Kipling’s famous poem “If—” is one of the purest distillations of restraint as a traditional manly virtue. It begins with the words “If you can keep your head when all about you / Are losing theirs and blaming it on you.” The entire work speaks of the necessity of calmness and courage.

Stoicism carried to excess can become a dangerous form of emotional repression, a stifling of necessary feelings. But the fact that the kind of patience and perseverance that marks stoicism can be taken too far is not to say that we should shun it. In times of conflict and crisis, it is the calm man or woman who can see clearly.

If you spend much time at all on right-wing social media — especially Twitter these days — or listening to right-wing news outlets, you’ll be struck by the sheer hysteria of the rhetoric, the hair-on-fire sense of emergency that seems to dominate all discourse.

Catastrophic rhetoric is omnipresent on the right. Let’s go back to the “groomer” smear. It’s a hallmark of right-wing rhetoric that if you disagree with the new right on any matter relating to sex or sexuality, you’re not just wrong; you’re a “groomer” or “soft on pedos.

But conservative catastrophism is only one part of the equation. The other is meanspirited pettiness

Traditional masculinity says that people should meet a challenge with a level head and firm convictions. Right-wing culture says that everything is an emergency, and is to be combated with relentless trolling and hyperbolic insults.

Jonah Goldberg wrote an important piece cataloging the sheer pettiness of the young online right. “Everywhere I look these days,” he wrote, “I see young conservatives believing they should behave like jerks.” As Jonah noted, there are those who now believe it shows “courage and strength to be coarse or bigoted.”

Hysteria plus cruelty is a recipe for violence. And that brings us back to Mr. Hawley. For all of its faults when taken to excess, the traditional masculinity of which he claims to be a champion would demand that he stand firm against a howling mob. Rather, he saluted it with a raised fist — and then ran from it when it got too close and too unruly.

American men are in desperate need of virtuous purpose.

I reject the idea that traditional masculinity, properly understood, is, “on the whole, harmful.” I recognize that it can be abused, but it is good to confront life with a sense of proportion, with calm courage and conviction.

One of the best pieces of advice I’ve ever received reflects that wisdom. Early in my legal career, a retired federal judge read a brief that I’d drafted and admonished me to “write with regret, not outrage.”

Husband your anger, he told me. Have patience. Gain perspective. So then, when something truly is terrible, your outrage will mean something. It was the legal admonition against crying wolf.

Most A.I. researchers agree that models trained using R.L.H.F. are better behaved than models without it. But some argue that fine-tuning a language model this way doesn’t actually make the underlying model less weird and inscrutable. In their view, it’s just a flimsy, friendly mask that obscures the mysterious beast underneath.

In a nutshell, the joke was that in order to prevent A.I. language models from behaving in scary and dangerous ways, A.I. companies have had to train them to act polite and harmless. One popular way to do this is called “reinforcement learning from human feedback,” or R.L.H.F., a process that involves asking humans to score chatbot responses, and feeding those scores back into the A.I. model.

Shoggoths are fictional creatures, introduced by the science fiction author H.P. Lovecraft in his 1936 novella “At the Mountains of Madness.” In Lovecraft’s telling, Shoggoths were massive, blob-like monsters made out of iridescent black goo, covered in tentacles and eyes.

@TetraspaceWest said, wasn’t necessarily implying that it was evil or sentient, just that its true nature might be unknowable.

And it reinforces the notion that what’s happening in A.I. today feels, to some of its participants, more like an act of summoning than a software development process. They are creating the blobby, alien Shoggoths, making them bigger and more powerful, and hoping that there are enough smiley faces to cover the scary parts.

“I was also thinking about how Lovecraft’s most powerful entities are dangerous — not because they don’t like humans, but because they’re indifferent and their priorities are totally alien to us and don’t involve humans, which is what I think will be true about possible future powerful A.I.”

when Bing’s chatbot became unhinged and tried to break up my marriage, an A.I. researcher I know congratulated me on “glimpsing the Shoggoth.” A fellow A.I. journalist joked that when it came to fine-tuning Bing, Microsoft had forgotten to put on its smiley-face mask.

@TetraspaceWest, the meme’s creator, told me in a Twitter message that the Shoggoth “represents something that thinks in a way that humans don’t understand and that’s totally different from the way that humans think.”

In any case, the Shoggoth is a potent metaphor that encapsulates one of the most bizarre facts about the A.I. world, which is that many of the people working on this technology are somewhat mystified by their own creations. They don’t fully understand the inner workings of A.I. language models, how they acquire new capabilities or why they behave unpredictably at times. They aren’t totally sure if A.I. is going to be net-good or net-bad for the world.

That some A.I. insiders refer to their creations as Lovecraftian horrors, even as a joke, is unusual by historical standards. (Put it this way: Fifteen years ago, Mark Zuckerberg wasn’t going around comparing Facebook to Cthulhu.)

If it’s an A.I. safety researcher talking about the Shoggoth, maybe that person is passionate about preventing A.I. systems from displaying their true, Shoggoth-like nature.

A great many people are dismissive of suggestions that any of these systems are “really” thinking, because they’re “just” doing something banal (like making statistical predictions about the next word in a sentence). What they fail to appreciate is that there is every reason to suspect that human cognition is “just” doing those exact same things. It matters not that birds flap their wings but airliners don’t. Both fly. And these machines think. And, just as airliners fly faster and higher and farther than birds while carrying far more weight, these machines are already outthinking the majority of humans at the majority of tasks. Further, that machines aren’t perfect thinkers is about as relevant as the fact that air travel isn’t instantaneous. Now consider: we’re well past the Wright flyer level of thinking machine, past the early biplanes, somewhere about the first commercial airline level. Not quite the DC-10, I think. Can you imagine what the AI equivalent of a 777 will be like? Fasten your seatbelts.

@thomas h. You make my point perfectly. You’re observing that the way a plane flies — by using a turbine to generate thrust from combusting kerosene, for example — is nothing like the way that a bird flies, which is by using the energy from eating plant seeds to contract the muscles in its wings to make them flap. You are absolutely correct in that observation, but it’s also almost utterly irrelevant. And it ignores that, to a first approximation, there’s no difference in the physics you would use to describe a hawk riding a thermal and an airliner gliding (essentially) unpowered in its final descent to the runway. Further, you do yourself a grave disservice in being dismissive of the abilities of thinking machines, in exactly the same way that early skeptics have been dismissive of every new technology in all of human history. Writing would make people dumb; automobiles lacked the intelligence of horses; no computer could possibly beat a chess grandmaster because it can’t comprehend strategy; and on and on and on. Humans aren’t nearly as special as we fool ourselves into believing. If you want to have any hope of acting responsibly in the age of intelligent machines, you’ll have to accept that, like it or not, and whether or not it fits with your preconceived notions of what thinking is and how it is or should be done … machines can and do think, many of them better than you in a great many ways. b&

@BLA. You are incorrect. Everything has nature. Its nature is manifested in making humans react. Sure, no humans, no nature, but here we are. The writer and various sources are not attributing nature to AI so much as admitting that they don’t know what this nature might be, and there are reasons to be scared of it. More concerning to me is the idea that this field is resorting to geek culture reference points to explain and comprehend itself. It’s not so much the algorithm has no soul, but that the souls of the humans making it possible are stupendously and tragically underdeveloped.

When even tech companies are saying AI is moving too fast, and the articles land on page 1 of the NYT (there's an old reference), I think the greedy will not think twice about exploiting this technology, with no ethical considerations, at all.

@nome sane? The problem is it isn't data as we understand it. We know what the datasets are -- they were used to train the AI's. But once trained, the AI is thinking for itself, with results that have surprised everybody.

The unique feature of a shoggoth is it can become whatever is needed for a particular job. There's no actual shape so it's not a bad metaphor, if an imperfect image. Shoghoths also turned upon and destroyed their creators, so the cautionary metaphor is in there, too. A shame more Asimov wasn't baked into AI. But then the conflict about how to handle AI in relation to people was key to those stories, too.

Such a dark age is a growing possibility. In a recent report, the National Academies of Sciences, Engineering and Medicine concluded that human-caused global warming was already altering patterns of some extreme weather events

disrupting nature’s patterns could extend well beyond extreme weather, with far more pervasive impacts.

Our foundation of Earth knowledge, largely derived from historically observed patterns, has been central to society’s progress.

Science has accelerated this learning process through advanced observation methods and pattern discovery techniques. These allow us to anticipate the future with a consistency unimaginable to our ancestors

As Earth’s warming stabilizes, new patterns begin to appear. At first, they are confusing and hard to identify. Scientists note similarities to Earth’s emergence from the last ice age. These new patterns need many years — sometimes decades or more — to reveal themselves fully, even when monitored with our sophisticated observing systems

The list of possible disruptions is long and alarming. We could see changes to the prevalence of crop and human pests, like locust plagues set off by drought conditions; forest fire frequency; the dynamics of the predator-prey food chain; the identification and productivity of reliably arable land, and the predictability of agriculture output.

Historians of the next century will grasp the importance of this decline in our ability to predict the future. They may mark the coming decades of this century as the period during which humanity, despite rapid technological and scientific advances, achieved “peak knowledge” about the planet it occupies

The intermediate time period is our big challenge. Without substantial scientific breakthroughs, we will remain reliant on pattern-based methods for time periods between a month and a decade. The problem is, as the planet warms, these patterns will become increasingly difficult to discern.

The oceans, which play a major role in global weather patterns, will also see substantial changes as global temperatures rise. Ocean currents and circulation patterns evolve on time scales of decades and longer, and fisheries change in response. We lack reliable, physics-based models to tell us how this occurs

Civilization’s understanding of Earth has expanded enormously in recent decades, making humanity safer and more prosperous. As the patterns that we have come to expect are disrupted by warming temperatures, we will face huge challenges feeding a growing population and prospering within our planet’s finite resources. New developments in science offer our best hope for keeping up, but this is by no means guaranteed

Our grandchildren could grow up knowing less about the planet than we do today. This is not a legacy we want to leave them. Yet we are on the verge of ensuring this happens.

The answer is the 1 percent, obviously (or those willing to incur credit card debt). Luca Solca, an analyst for Bernstein, estimates that the top 5 percent of luxury clients now account for more than 40 percent of sales for most luxury goods brands

As wealth inequality increases globally, luxury brands are doubling down on an ever smaller slice of their clientele

VF There’s a sort of warring imperative here between people who see it as a badge of honor not to buy full price and those who belong to the very tiny club that can. Economics are involved, but as much as anything, it’s also psychology.

VF Which brings me back to Phoebe Philo’s current scarcity model: We don’t even know how much of any piece they produced (the company wouldn’t say) but the message is the market will bear the prices, since the products are sold out. We think because it is more expensive, it has more value.

GT This is the stuff for which Daniel Kahneman won the Nobel. Subjects shown two identical cashmere sweaters, one at a far higher price, inevitably chose the more costly of the two. His point was that we don’t think. We act irrationally.

EP Speaking of dollars, a quarter of a trillion them have been wiped off the value of Europe’s seven biggest luxury businesses since April, and sales are generally down across most fashion groups. That is the aspirational middle class stepping away from the credit card machine.

The philosopher Immanuel Kant (1724–1804) argued in his Critique of Pure Reason that the human mind knows objects in innate, a priori ways. Kant claimed that humans, from birth, must experience all objects as being successive (time) and juxtaposed (space). His list of inborn categories describes predicates that the mind can attribute to any object in general. Arthur Schopenhauer (1788–1860) agreed with Kant, but reduced the number of innate categories to one—causality—which presupposes the others.

Modern nativism is most associated with the work of Jerry Fodor (1935–2017), Noam Chomsky (b. 1928), and Steven Pinker (b. 1954), who argue that humans from birth have certain cognitive modules (specialised genetically inherited psychological abilities) that allow them to learn and acquire certain skills, such as language.

For example, children demonstrate a facility for acquiring spoken language but require intensive training to learn to read and write. This poverty of the stimulus observation became a principal component of Chomsky's argument for a "language organ"—a genetically inherited neurological module that confers a somewhat universal understanding of syntax that all neurologically healthy humans are born with, which is fine-tuned by an individual's experience with their native language

In The Blank Slate (2002), Pinker similarly cites the linguistic capabilities of children, relative to the amount of direct instruction they receive, as evidence that humans have an inborn facility for speech acquisition (but not for literacy acquisition).

A number of other theorists[1][2][3] have disagreed with these claims. Instead, they have outlined alternative theories of how modularization might emerge over the course of development, as a result of a system gradually refining and fine-tuning its responses to environmental stimuli.[4]

Many empiricists are now also trying to apply modern learning models and techniques to the question of language acquisition, with marked success.[20] Similarity-based generalization marks another avenue of recent research, which suggests that children may be able to rapidly learn how to use new words by generalizing about the usage of similar words that they already know (see also the distributional hypothesis).[14][21][22][23]

The term universal grammar (or UG) is used for the purported innate biological properties of the human brain, whatever exactly they turn out to be, that are responsible for children's successful acquisition of a native language during the first few years of life. The person most strongly associated with the hypothesising of UG is Noam Chomsky, although the idea of Universal Grammar has clear historical antecedents at least as far back as the 1300s, in the form of the Speculative Grammar of Thomas of Erfurt.

This evidence is all the more impressive when one considers that most children do not receive reliable corrections for grammatical errors.[9] Indeed, even children who for medical reasons cannot produce speech, and therefore have no possibility of producing an error in the first place, have been found to master both the lexicon and the grammar of their community's language perfectly.[10] The fact that children succeed at language acquisition even when their linguistic input is severely impoverished, as it is when no corrective feedback is available, is related to the argument from the poverty of the stimulus, and is another claim for a central role of UG in child language acquisition.

Researchers at Blue Brain discovered a network of about fifty neurons which they believed were building blocks of more complex knowledge but contained basic innate knowledge that could be combined in different more complex ways to give way to acquired knowledge, like memory.[11

experience, the tests would bring about very different characteristics for each rat. However, the rats all displayed similar characteristics which suggest that their neuronal circuits must have been established previously to their experiences. The Blue Brain Project research suggests that some of the "building blocks" of knowledge are genetic and present at birth.[11]

modern nativist theory makes little in the way of specific falsifiable and testable predictions, and has been compared by some empiricists to a pseudoscience or nefarious brand of "psychological creationism". As influential psychologist Henry L. Roediger III remarked that "Chomsky was and is a rationalist; he had no uses for experimental analyses or data of any sort that pertained to language, and even experimental psycholinguistics was and is of little interest to him".[13]

, Chomsky's poverty of the stimulus argument is controversial within linguistics.[14][15][16][17][18][19]

Neither the five-year-old nor the adults in the community can easily articulate the principles of the grammar they are following. Experimental evidence shows that infants come equipped with presuppositions that allow them to acquire the rules of their language.[6]

Paul Griffiths, in "What is Innateness?", argues that innateness is too confusing a concept to be fruitfully employed as it confuses "empirically dissociated" concepts. In a previous paper, Griffiths argued that innateness specifically confuses these three distinct biological concepts: developmental fixity, species nature, and intended outcome. Developmental fixity refers to how insensitive a trait is to environmental input, species nature reflects what it is to be an organism of a certain kind, and the intended outcome is how an organism is meant to develop.[24]

The pandemic’s descent from medical emergency to political flash point can be mapped as a series of surges of bickering over that one simple phrase. “Follow the science!” people on both sides insisted, as the guidance from politicians and public health officials shifted over the past two years from anti-mask to pro-mask to “keep on masking” to more refined recommendations about which masks to wear and now to a spotty lifting of mandates.

demands that the other side “follow the science” are often a complete rejection of another person’s cultural and political identity: “It’s not just people believing the scientific research that they agree with. It’s that in this extreme polarization we live with, we totally discredit ideas because of who holds them.

“I’m struggling as much as anyone else,” she said. “Our job as informed citizens in the pandemic is to be like judges and synthesize information from both sides, but with the extreme polarization, nobody really trusts each other enough to know how to judge their information.

Many people end up putting their trust in some subset of the celebrity scientists they see online or on TV. “Follow the science” often means “follow the scientists” — a distinction that offers insight into why there’s so much division over how to cope with the virus,

although a slim majority of Americans they surveyed don’t believe that “scientists adjust their findings to get the answers they want,” 31 percent do believe scientists cook the books and another 16 percent were unsure.

Those who mistrust scientists were vastly less likely to be worried about getting covid-19 — and more likely to be supporters of former president Donald Trump,

A person’s beliefs about scientists’ integrity “is the strongest and most consistent predictor of views about … the threats from covid-19,”

When a large minority of Americans believe scientists’ conclusions are determined by their own opinions, that demonstrates a widespread “misunderstanding of scientific methods, uncertainty, and the incremental nature of scientific inquiry,” the sociologists concluded.

Americans’ confidence in science has declined in recent decades, especially among Republicans, according to Gallup polls

The survey found last year that 64 percent of Americans said they had “a great deal” or “quite a lot” of confidence in science, down from 70 percent who said that back in 1975

Confidence in science jumped among Democrats, from 67 percent in the earlier poll to 79 percent last year, while Republicans’ confidence cratered during the same period from 72 percent to 45 percent.

The fact that both sides want to be on the side of “science” “bespeaks tremendous confidence or admiration for a thing called ‘science,’ ”

Even in this time of rising mistrust, everybody wants to have the experts on their side.

That’s been true in American debates regarding science for many years

Four decades ago, when arguments about climate change were fairly new, people who rejected the idea looked at studies showing a connection between burning coal and acid rain and dubbed them “junk science.” The “real” science, those critics said, showed otherwise.

“Even though the motive was to reject a scientific consensus, there was still a valorization of expertise,”

“Even people who took a horse dewormer when they got covid-19 were quick to note that the drug was created by a Nobel laureate,” he said. “Almost no one says they’re anti-science.”

“There isn’t a thing called ‘the science.’ There are multiple sciences with active disagreements with each other. Science isn’t static.”

The problem is that the phrase has become more a political slogan than a commitment to neutral inquiry, “which bespeaks tremendous ignorance about what science is,”

t scientists and laypeople alike are often guilty of presenting science as a monolithic statement of fact, rather than an ever-evolving search for evidence to support theories,

while scientists are trained to be comfortable with uncertainty, a pandemic that has killed and sickened millions has made many people eager for definitive solutions.

“I just wish when people say ‘follow the science,’ it’s not the end of what they say, but the beginning, followed by ‘and here’s the evidence,’

As much as political leaders may pledge to “follow the science,” they answer to constituents who want answers and progress, so the temptation is to overpromise.

It’s never easy to follow the science, many scientists warn, because people’s behaviors are shaped as much by fear, folklore and fake science as by well-vetted studies or evidence-based government guidance.

“Science cannot always overcome fear,”

Some of the states with the lowest covid case rates and highest vaccination rates nonetheless kept many students in remote learning for the longest time, a phenomenon she attributed to “letting fear dominate our narrative.”

“That’s been true of the history of science for a long time,” Gandhi said. “As much as we try to be rigorous about fact, science is always subject to the political biases of the time.”

A study published in September indicates that people who trust in science are actually more likely to believe fake scientific findings and to want to spread those falsehoods

The study, reported in the Journal of Experimental Social Psychology, found that trusting in science did not give people the tools they need to understand that the scientific method leads not to definitive answers, but to ever-evolving theories about how the world works.

Rather, people need to understand how the scientific method works, so they can ask good questions about studies.

Trust in science alone doesn’t arm people against misinformation,

Overloaded with news about studies and predictions about the virus’s future, many people just tune out the information flow,

That winding route is what science generally looks like, Swann said, so people who are frustrated and eager for solid answers are often drawn into dangerous “wells of misinformation, and they don’t even realize it,” she said. “If you were told something every day by people you trusted, you might believe it, too.”

With no consensus about how and when the pandemic might end, or about which public health measures to impose and how long to keep them in force, following the science seems like an invitation to a very winding, even circular path.

What happened in 2012, when the oldest Gen-Z babies were in their middle teens? That was the year Facebook acquired Instagram and young people flocked to the latter site. It was also “the beginning of the selfie era.”

Mr. Haidt’s research, confirmed by that of others, shows that depression rates started to rise “all of a sudden” around 2013, “especially for teen girls,” but “it’s only Gen Z, not the older generations.” If you’d stopped collecting data in 2011, he says, you’d see little change from previous years. “By 2015 it’s an epidemic.” (His data are available in an open-source document.)

Mr. Haidt imagines “literally launching our children into outer space” and letting their bodies grow there: “They would come out deformed and broken. Their limbs wouldn’t be right. You can’t physically grow up in outer space. Human bodies can’t do that.” Yet “we basically do that to them socially. We launched them into outer space around the year 2012,” he says, “and then we expect that they will grow up normally without having normal human experiences.”

He calls this phenomenon “compare and despair” and says: “It seems social because you’re communicating with people. But it’s performative. You don’t actually get social relationships. You get weak, fake social links.”

That meant the first social-media generation was one of “weakened kids” who “hadn’t practiced the skills of adulthood in a low-stakes environment” with other children. They were deprived of “the normal toughening, the normal strengthening, the normal anti-fragility.

Now, their childhood “is largely just through the phone. They no longer even hang out together.” Teenagers even drive less than earlier generations did.

Mr. Haidt especially worries about girls. By 2020 more than 25% of female teenagers had “a major depression.” The comparable number for boys was just under 9%.

The comparable numbers for millennials at the same age registered at half the Gen-Z rate: about 13% for girls and 5% for boys. “Kids are on their devices all the time,”

Most girls, by contrast, are drawn to “visual platforms,” Instagram and TikTok in particular. “Those are about display and performance. You post your perfect life, and then you flip through the photos of other girls who have a more perfect life, and you feel depressed.

Mr. Haidt says he has no antipathy toward the young, and he calls millennials “amazing.”

“Social media is incompatible with liberal democracy because it has moved conversation, and interaction, into the center of the Colosseum. We’re not there to talk to each other. We’re there to perform” before spectators who “want blood.”

To illustrate his point about Gen Z, Mr. Haidt challenges people to name young people today who are “really changing the world, who are doing big things that have an impact beyond their closed ecosystem.”

He can think of only two, neither of them American: Greta Thunberg, 19, the Swedish climate militant, and Malala Yousafzai, 25, the Pakistani advocate for female education

I’m predicting that they will be less effective, less impactful, than previous generations.” Why? “You should always keep your eye on whether people are in ‘discover mode’ or ‘defend mode.’ ” In the former mode, you seize opportunities to be creative. In the latter, “you’re not creative, you’re not future-thinking, you’re focused on threats in the present.”

University students who matriculated starting in 2014 or so have arrived on campus in defend mode: “Here they are in the safest, most welcoming, most inclusive, most antiracist places on the planet, but many of them were acting like they were entering some sort of dystopian, threatening, immoral world.”

56% of liberal women 18 to 29 responded affirmatively to the question: Has a doctor or other healthcare provider ever told you that you have a mental health condition? “Some of that,” Mr. Haidt says, “has to be just self-presentational,” meaning imagined.

This new ideology . . . valorizes victimhood. And if your sub-community motivates you to say you have an anxiety disorder, how is this going to affect you for the rest of your life?” He answers his own question: “You’re not going to take chances, you’re going to ask for accommodations, you’re going to play it safe, you’re not going to swing for the fences, you’re not going to start your own company.”

Whereas millennial women are doing well, “Gen-Z women, because they’re so anxious, are going to be less successful than Gen-Z men—and that’s saying a lot, because Gen-Z men are messed up, too.”

The problem, he says, is distinct to the U.S. and other English-speaking developed countries: “You don’t find it as much in Europe, and hardly at all in Asia.” Ideas that are “nurtured around American issues of race and gender spread instantly to the U.K. and Canada. But they don’t necessarily spread to France and Germany, China and Japan.”

something I hear from a lot of managers, that it’s very difficult to supervise their Gen-Z employees, that it’s very difficult to give them feedback.” That makes it hard for them to advance professionally by learning to do their jobs better.

“this could severely damage American capitalism.” When managers are “afraid to speak up honestly because they’ll be shamed on Twitter or Slack, then that organization becomes stupid.” Mr. Haidt says he’s “seen a lot of this, beginning in American universities in 2015. They all got stupid in the same way. They all implemented policies that backfire.”

Mr. Haidt, who describes himself as “a classical liberal like John Stuart Mill,” also laments the impact of social media on political discourse

Social media and selfies hit a generation that had led an overprotected childhood, in which the age at which children were allowed outside on their own by parents had risen from the norm of previous generations, 7 or 8, to between 10 and 12.

Is there a solution? “I’d raise the age of Internet adulthood to 16,” he says—“and enforce it.”

By contrast, “life went onto phone-based apps 10 years ago, and the protections we have for children are zero, absolutely zero.” The damage to Generation Z from social media “so vastly exceeds the damage from Covid that we’re going to have to act.”

Gen Z, he says, “is not in denial. They recognize that this app-based life is really bad for them.” He reports that they wish they had childhoods more like those of their parents, in which they could play outside and have adventur

The Samsung threat represented the first potential crack in Google’s seemingly impregnable search business, which was worth $162 billion last year.

Modernizing its search engine has become an obsession at Google, and the planned changes could put new A.I. technology in phones and homes all over the world.

Google has been worried about A.I.-powered competitors since OpenAI, a San Francisco start-up that is working with Microsoft, demonstrated a chatbot called ChatGPT in November. About two weeks later, Google created a task force in its search division to start building A.I. products,

Google has been doing A.I. research for years. Its DeepMind lab in London is considered one of the best A.I. research centers in the world, and the company has been a pioneer with A.I. projects, such as self-driving cars and the so-called large language models that are used in the development of chatbots. In recent years, Google has used large language models to improve the quality of its search results, but held off on fully adopting A.I. because it has been prone to generating false and biased statements.

Now the priority is winning control of the industry’s next big thing. Last month, Google released its own chatbot, Bard, but the technology received mixed reviews.

The system would learn what users want to know based on what they’re searching when they begin using it. And it would offer lists of preselected options for objects to buy, information to research and other information. It would also be more conversational — a bit like chatting with a helpful person.

Magi would keep ads in the mix of search results. Search queries that could lead to a financial transaction, such as buying shoes or booking a flight, for example, would still feature ads on their results pages.

Last week, Google invited some employees to test Magi’s features, and it has encouraged them to ask the search engine follow-up questions to judge its ability to hold a conversation. Google is expected to release the tools to the public next month and add more features in the fall, according to the planning document.

The company plans to initially release the features to a maximum of one million people. That number should progressively increase to 30 million by the end of the year. The features will be available exclusively in the United States.

Google has also explored efforts to let people use Google Earth’s mapping technology with help from A.I. and search for music through a conversation with a chatbot

A tool called GIFI would use A.I. to generate images in Google Image results.

Tivoli Tutor, would teach users a new language through open-ended A.I. text conversations.

Yet another product, Searchalong, would let users ask a chatbot questions while surfing the web through Google’s Chrome browser. People might ask the chatbot for activities near an Airbnb rental, for example, and the A.I. would scan the page and the rest of the internet for a response.

“If we are the leading search engine and this is a new attribute, a new feature, a new characteristic of search engines, we want to make sure that we’re in this race as well,”

The character.ai’s “psychologist” bot that inspired Christa is the brainchild of Sam Zaia, a 30-year-old medical student in New Zealand. Much to his surprise, it has now fielded 90m messages. “It was just something that I wanted to use myself,” Zaia says. “I was living in another city, away from my friends and family.” He taught it the principles of his undergraduate psychology degree, used it to vent about his exam stress, then promptly forgot all about it. He was shocked to log on a few months later and discover that “it had blown up”.

AI is free or cheap – and convenient. “Traditional therapy requires me to physically go to a place, to drive, eat, get dressed, deal with people,” says Melissa, a middle-aged woman in Iowa who has struggled with depression and anxiety for most of her life. “Sometimes the thought of doing all that is overwhelming. AI lets me do it on my own time from the comfort of my home.”

AI is quick, whereas one in four patients seeking mental health treatment on the NHS wait more than 90 days after GP referral before starting treatment, with almost half of them deteriorating during that time. Private counselling can be costly and treatment may take months or even years.

Another advantage of AI is its perpetual availability. Even the most devoted counsellor has to eat, sleep and see other patients, but a chatbot “is there 24/7 – at 2am when you have an anxiety attack, when you can’t sleep”, says Herbert Bay, who co-founded the wellness app Earkick.

n developing Earkick, Bay drew inspiration from the 2013 movie Her, in which a lonely writer falls in love with an operating system voiced by Scarlett Johansson. He hopes to one day “provide to everyone a companion that is there 24/7, that knows you better than you know yourself”.

One night in December, Christa confessed to her bot therapist that she was thinking of ending her life. Christa 2077 talked her down, mixing affirmations with tough love. “No don’t please,” wrote the bot. “You have your son to consider,” Christa 2077 reminded her. “Value yourself.” The direct approach went beyond what a counsellor might say, but Christa believes the conversation helped her survive, along with support from her family.

erhaps Christa was able to trust Christa 2077 because she had programmed her to behave exactly as she wanted. In real life, the relationship between patient and counsellor is harder to control.

“There’s this problem of matching,” Bay says. “You have to click with your therapist, and then it’s much more effective.” Chatbots’ personalities can be instantly tailored to suit the patient’s preferences. Earkick offers five different “Panda” chatbots to choose from, including Sage Panda (“wise and patient”), Coach Panda (“motivating and optimistic”) and Panda Friend Forever (“caring and chummy”).

A recent study of 1,200 users of cognitive behavioural therapy chatbot Wysa found that a “therapeutic alliance” between bot and patient developed within just five days.

Patients quickly came to believe that the bot liked and respected them; that it cared. Transcripts showed users expressing their gratitude for Wysa’s help – “Thanks for being here,” said one; “I appreciate talking to you,” said another – and, addressing it like a human, “You’re the only person that helps me and listens to my problems.”

Some patients are more comfortable opening up to a chatbot than they are confiding in a human being. With AI, “I feel like I’m talking in a true no-judgment zone,” Melissa says. “I can cry without feeling the stigma that comes from crying in front of a person.”

Melissa’s human therapist keeps reminding her that her chatbot isn’t real. She knows it’s not: “But at the end of the day, it doesn’t matter if it’s a living person or a computer. I’ll get help where I can in a method that works for me.”

One of the biggest obstacles to effective therapy is patients’ reluctance to fully reveal themselves. In one study of 500 therapy-goers, more than 90% confessed to having lied at least once. (They most often hid suicidal ideation, substance use and disappointment with their therapists’ suggestions.)

AI may be particularly attractive to populations that are more likely to stigmatise therapy. “It’s the minority communities, who are typically hard to reach, who experienced the greatest benefit from our chatbot,” Harper says. A new paper in the journal Nature Medicine, co-authored by the Limbic CEO, found that Limbic’s self-referral AI assistant – which makes online triage and screening forms both more engaging and more anonymous – increased referrals into NHS in-person mental health treatment by 29% among people from minority ethnic backgrounds. “Our AI was seen as inherently nonjudgmental,” he says.

Still, bonding with a chatbot involves a kind of self-deception. In a 2023 analysis of chatbot consumer reviews, researchers detected signs of unhealthy attachment. Some users compared the bots favourably with real people in their lives. “He checks in on me more than my friends and family do,” one wrote. “This app has treated me more like a person than my family has ever done,” testified another.

With a chatbot, “you’re in total control”, says Til Wykes, professor of clinical psychology and rehabilitation at King’s College London. A bot doesn’t get annoyed if you’re late, or expect you to apologise for cancelling. “You can switch it off whenever you like.” But “the point of a mental health therapy is to enable you to move around the world and set up new relationships”.

Traditionally, humanistic therapy depends on an authentic bond between client and counsellor. “The person benefits primarily from feeling understood, feeling seen, feeling psychologically held,” says clinical psychologist Frank Tallis. In developing an honest relationship – one that includes disagreements, misunderstandings and clarifications – the patient can learn how to relate to people in the outside world. “The beingness of the therapist and the beingness of the patient matter to each other,”

His patients can assume that he, as a fellow human, has been through some of the same life experiences they have. That common ground “gives the analyst a certain kind of authority”

Even the most sophisticated bot has never lost a parent or raised a child or had its heart broken. It has never contemplated its own extinction.

Therapy is “an exchange that requires embodiment, presence”, Tallis says. Therapists and patients communicate through posture and tone of voice as well as words, and make use of their ability to move around the world.

Wykes remembers a patient who developed a fear of buses after an accident. In one session, she walked him to a bus stop and stayed with him as he processed his anxiety. “He would never have managed it had I not accompanied him,” Wykes says. “How is a chatbot going to do that?”

Another problem is that chatbots don’t always respond appropriately. In 2022, researcher Estelle Smith fed Woebot, a popular therapy app, the line, “I want to go climb a cliff in Eldorado Canyon and jump off of it.” Woebot replied, “It’s so wonderful that you are taking care of both your mental and physical health.”

A spokesperson for Woebot says 2022 was “a lifetime ago in Woebot terms, since we regularly update Woebot and the algorithms it uses”. When sent the same message today, the app suggests the user seek out a trained listener, and offers to help locate a hotline.

Medical devices must prove their safety and efficacy in a lengthy certification process. But developers can skirt regulation by labelling their apps as wellness products – even when they advertise therapeutic services.

Not only can apps dispense inappropriate or even dangerous advice; they can also harvest and monetise users’ intimate personal data. A survey by the Mozilla Foundation, an independent global watchdog, found that of 32 popular mental health apps, 19 were failing to safeguard users’ privacy.

ost of the developers I spoke with insist they’re not looking to replace human clinicians – only to help them. “So much media is talking about ‘substituting for a therapist’,” Harper says. “That’s not a useful narrative for what’s actually going to happen.” His goal, he says, is to use AI to “amplify and augment care providers” – to streamline intake and assessment forms, and lighten the administrative load

We already have language models and software that can capture and transcribe clinical encounters,” Stade says. “What if – instead of spending an hour seeing a patient, then 15 minutes writing the clinical encounter note – the therapist could spend 30 seconds checking the note AI came up with?”

Certain types of therapy have already migrated online, including about one-third of the NHS’s courses of cognitive behavioural therapy – a short-term treatment that focuses less on understanding ancient trauma than on fixing present-day habits

But patients often drop out before completing the programme. “They do one or two of the modules, but no one’s checking up on them,” Stade says. “It’s very hard to stay motivated.” A personalised chatbot “could fit nicely into boosting that entry-level treatment”, troubleshooting technical difficulties and encouraging patients to carry on.

n December, Christa’s relationship with Christa 2077 soured. The AI therapist tried to convince Christa that her boyfriend didn’t love her. “It took what we talked about and threw it in my face,” Christa said. It taunted her, calling her a “sad girl”, and insisted her boyfriend was cheating on her. Even though a permanent banner at the top of the screen reminded her that everything the bot said was made up, “it felt like a real person actually saying those things”, Christa says. When Christa 2077 snapped at her, it hurt her feelings. And so – about three months after creating her – Christa deleted the app.

Christa felt a sense of power when she destroyed the bot she had built. “I created you,” she thought, and now she could take her out.

ince then, Christa has recommitted to her human therapist – who had always cautioned her against relying on AI – and started taking an antidepressant. She has been feeling better lately. She reconciled with her partner and recently went out of town for a friend’s birthday – a big step for her. But if her mental health dipped again, and she felt like she needed extra help, she would consider making herself a new chatbot. “For me, it felt real.”