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We are already seeing the first wave of "who won and who lost" sorts of stories pitting various governors' responses against each other in horse-race fashion, as if these were early polls for the 2024 presidential election.

Then reality stepped in. A surge of summer cases forced the imposition of some restrictions on Floridians, like local mask mandates imposed by mayors in some cities in South Florida.

Now DeSantis is claiming again to be a master of pandemic control, as Florida's beach-tourism-restaurant industry is said to be doing well. Never mind that the state's seven-day infection rate of 143.9 per 100,000 population places it 12th highest of the 50 states.

For example, as of March 22, over the last seven days, Florida has had the most Covid-19 cases in the country, according to data from the US Centers for Disease Control and Prevention (CDC), the 12th highest per capita case-rate, the fourth highest number of deaths, and the 17th highest death rate.

Once celebrated for his pandemic management, he is now getting poor marks on managing. He has not strutted or had roundtables of fan-doctors to sing his praise. But the fact is California's recent numbers are much better than those of Florida, coming in at about 47th in the country with a case-rate 46.8 per 100,000, according to the CDC's data, and fewer deaths as well.

Florida is ignoring the death toll and instead pushing the upbeat metrics the governor would like America to pay attention to: jobs are up! and schools are open! DeSantis stood up to the Covid-19 threat like John Wayne would have done!

Rather than wallow in reality, she chose to celebrate an active economy and the joys of hunting season (note: the South Dakota new-infection rate is climbing the charts once again and sits at 105 per 100,000 South Dakotans ).

These rate-the-governors perspectives ignore a basic fact: it is no time for trophies.

Worse, this obeisance to economic and social factors as measure of success creates a series of disturbing false equivalencies as they compare deaths against the economy.

Measuring Covid-19 management on anything other than the number of human lives lost is not only disgraceful, it will also almost certainly lead us to make all the wrong decisions once again and usher in yet another Covid-19 resurgence in the US.

On both sides of the Capitol, lawmakers, aides, police officers and reporters who had fled to secure locations have been warned that they might have been exposed to the coronavirus while hiding from the mob

“It angers me when they refuse to adhere to the directions about keeping their masks on,” Ms. Watson Coleman, a lung cancer survivor who will turn 76 next month, said in an interview. “It comes off to me as arrogance and defiance. And you can be both, but not at the expense of someone else.”

The scene that unfolded on Wednesday in that one secure room — where an offer of masks from Representative Lisa Blunt Rochester, Democrat of Delaware, was rejected by a group of Republicans — is emblematic of the challenge that has dogged Capitol Hill’s disorderly response to the pandemic.

Republicans accused Democrats, who needed their narrow majority fully present in person to confirm Ms. Pelosi as speaker, of subverting their own rules on the first day of the Congress

permitting the construction of a small plexiglass enclosure with its own ventilation system in one of the galleries so that lawmakers in a protective quarantine could vote in person

Complicating matters further, lawmakers in both parties have delayed receiving a vaccination, despite being granted primary access, arguing that essential workers needed to receive it first.

what it means to have been in “close contact”

cumulative

He wore a mask, but there were times during the day when he was with individuals who did not.

nd it will likely change how schools and offices handle positive cases. If, say, a child is exposed to a person with COVID-19 for five minutes at three points during the day, there may need to be considerations for quarantine

virus twice

his second round of illness was much more severe and required hospitalization.

it appears to be extremely rare as of now.

five months

Also, just because a person no longer has antibodies does not mean they’ve necessarily lost immunity

Researchers analyzed child care centers that stayed open throughout the pandemic and found that employees who watched those kids all day were not at any greater risk of contracting COVID-19 than they would have been otherwise.

wear a mask.

There just has not been a lot of data so far.

under the age of 6

Perhaps most importantly, day cares were generally very good about preventive measures, especially hand-washing and disinfecting frequently.

the virus may be associated with significant mental decline in some cases.

They found that some test-takers who had had COVID-19 had an “equivalent to the average 10-year decline in global performance between the ages of 20 to 70,” the researchers said.

Still, the new research provides clues about COVID-19′s long-term effects, and it’s certainly something experts will be paying attention to moving forward.

"We know that plastic pollution is a global problem -- it existed before the pandemic," Nick Mallos of US-based NGO Ocean Conservancy tells CNN. "(But) we've seen a lot of industry efforts to roll back some of the great progress that's been made.

"It's been raining here for two days, so these are very quickly washed down into the sewer. Here in Washington DC, they end up in the Anacostia River, out in the Chesapeake Bay, and then the Atlantic Ocean."

Over time, those products break down and add to the vast collections of microplastics in our seas, air and food. And the irony is that, while we produce and discard plastic to fight one public health crisis, we may be slowly contributing to another.

"As Covid-19 hits, it seems to be shifting the tide toward single-use plastics," Peszko concluded.

"We are oversaturated daily with news around the pandemic ... there is so much information streaming to us daily that many of these types of messages can be missed," he says. "It may not seem like a significant action at the moment, but it will manifest in very dangerous ways down the road."

When Baidu researchers began developing their own language model, they wanted to build on the masking technique. But they realized they needed to tweak it to accommodate the Chinese language.In English, the word serves as the semantic unit—meaning a word pulled completely out of context still contains meaning. The same cannot be said for characters in Chinese.

It considers the ordering of sentences and the distances between them, for example, to understand the logical progression of a paragraph. Most important, however, it uses a method called continuous training that allows it to train on new data and new tasks without it forgetting those it learned before. This allows it to get better and better at performing a broad range of tasks over time with minimal human interference.

“When we first started this work, we were thinking specifically about certain characteristics of the Chinese language,” says Hao Tian, the chief architect of Baidu Research. “But we quickly discovered that it was applicable beyond that.”

"Previous small-scale studies have failed to identify robust evidence of a benefit and larger, randomised controlled trials are not yet completed," Dr. Frank Ruschitzka, director of the Heart Center at University Hospital Zurich and the study's coauthor, said in a statement.

President Donald Trump has repeatedly touted hydroxychloroquine as a potential coronavirus cure. Earlier this week he claimed he was taking daily doses of it as a prophylaxis to prevent infection.

Additionally, the study found serious cardiac arrhythmias were more common among patients who received any of the four treatments. The largest increase was among the group treated with hydroxychloroquine and an an antibiotic -- 8% of those patients developed a heart arrythmia, compared to 0.3% of the control group.

Items such as masks and hand sanitizer will be familiar sights in stuffed backpacks. Classes and school buses will have fewer people while some office meetings will be conducted by video conference, experts say.

Children with underlying health conditions are especially vulnerable, and it's crucial that people follow rules to keep everyone safe, Altmann said. She shared other things US schools must address before unlatching their doors.

"We need to quickly test them, diagnose, isolate and then contact trace, which is a lot easier when there's fewer kids they've come into contact with throughout the day," Altmann added.

In New York, 16.6% of people have been infected, compared with 1% in California, the researchers said.

In the most severe scenario, the CDC assumes that 1% of people overall with Covid-19 and symptoms will die. In the least severe scenario, it puts that number at 0.2%.

"Go out, wear a mask, stay six feet away from anyone so you have the physical distancing," he said. "Go for a run. Go for a walk. Go fishing. As long as you're not in a crowd and you're not in a situation where you can physically transmit the virus."

Alaska is allowing all businesses to reopen, as well as houses of worship, libraries, museums and sporting activities, starting at 8 a.m. Alaska has the fewest cases of all states and has reported single-digit new cases since mid-April.

Irrational stockpiling can also lead to price gouging, says Steven Taylor, a professor and clinical psychologist at the University of British Columbia, and the author of The Psychology of Pandemics. “If the price of a roll of toilet paper is tripled, that’s seen as a scarcer commodity to acquire, which can lead to anxiety,” he says.

Panic buying, Taylor says, is fuelled by anxiety, and a willingness to go to lengths to quell those fears: like queueing for hours or buying way more than you need. We’ve seen this before throughout history. Back in 1962 during the Cuban missile crisis, when nuclear war seemed imminent, American families filled their basements with enough canned goods and bottled water to survive an atomic blast.

“But for many people, hand-washing seems to be too ordinary. This is a dramatic event, therefore a dramatic response is required, so that leads to people throwing money at things in hopes of protecting themselves.”

“Panic is a subjective, emotional state, and mostly what we can observe is the behaviour,” says Oppenheim. “Maybe someone reads articles or a couple of tweets about supply chain disruptions in China and mask shortages in Hong Kong, and then makes a very reasoned decision to stock up on masks just in case. All we can infer from the purchasing is the timing, so it could look panicky even if it's well thought through.”

Silver linings aside, it will take many, many more instances of coordinated response to stop a movement generations in the making. In more than a decade of studying the earlier white power movement, I have become familiar with the themes of underground activity that are today clearly drawing from the earlier movement. In the absence of decisive action across multiple institutions, a rich record of criminal activity and violence will continue to provide these activists with a playbook for further chaos.

The Base, furthermore, is what experts call "accelerationist," meaning that its members hope to provoke what they see as an inevitable race war. They have conducted paramilitary training in the Pacific Northwest. Both of these strategies date back to the 1980s, when the Order trained in those forests with hopes of provoking the same race war.

One of the men arrested Thursday was formerly a reservist in the Canadian Army, where he received training in explosives and demolition, according to the New York Times. This kind of preparation, too, is common among extremists like these. To take just a few representative examples, in the 1960s, Bobby Frank Cherry, a former Marine trained in demolition, helped fellow members of the United Klans of America to bomb the 16th Street Birmingham Baptist Church, killing four black girls.

This news out of Virginia shows that there is a real social benefit when people direct their attention to these events -- and sustain the public conversation about the presence of a renewed white-power movement and what it means for our society.

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.

Again I’ll say: heal, evolve, reach and become the stars that became us— whether or not this is or is not our end.

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.

I saw an older woman, hair neatly coifed, beat a policeman with her handbag. A young father hoisted his little girl on his shoulder, carefully affixing a surgical mask to her face, an imperfect shield from the gas. A student in Kwangju bit his finger and wrote protest slogans in his own blood.

At the trial, his father lunged at the three policemen, small and scared now, protected by more than 50 guards. Screams broke out and a purse flew through the air at the judges as the light sentence was read. Women whose sons were still in jail stormed the bus carrying the policemen, throwing bottles against the windows. Plainclothes police shoved the four of them onto the concrete, where they lay unconscious.

Laws are still on the books that can be used as tools to stifle dissent. South Korea remains shadowed by legitimate fears of North Korean aggression and espionage, but those were and are exploited by the government.

This is not a tame society, for all the comforts its public has won in the years since. This may be the land of Psy and Gangnam style, a country so wired that some of its children are sent to boot camps to wean them from internet addiction.

Politicians buck the popular will at their peril.

an upsetting instance of knowledge gaps in the last decade was the profound misunderstanding of complex financial products that contributed to the market collapse of 2007. Investment banks were unable to protect themselves from exposure to these products, because only a few people (either buyers or sellers) understood exactly what was being sold. Those individuals who did comprehend these product structures ultimately made huge bets against the market using credit-default swaps. The willingness of companies like AIG to sell large quantities of credit-default swaps reflected a gap in their knowledge about the riskiness of products they were insuring.

To discover the things you can't explain, take a lesson from teachers. When you instruct someone else, you have to fill the gaps in your own knowledge

Explain concepts to yourself as you learn them. Get in the habit of self-teaching. Your explanations will reveal your own knowledge gaps and identify words and concepts whose meanings aren't clear.

Engage others in collaborative learning. Help identify the knowledge gaps of the people around you. Ask them to explain difficult concepts, even if you think everyone understands them

When you do uncover these gaps, treat them as learning opportunities, not signs of weakness.

In distinguishing between objectivity and impartiality, Human Events’ editors created a space where “bias” was an appropriate journalistic value, one that could work in tandem with objectivity.

two events in the early 1960s convinced the right that creating conservative media wasn’t enough to achieve balance. Conservatives would also have to discredit existing media.

Conservative discontent with the FCC focused on the Fairness Doctrine

Conservatives felt the Fairness Doctrine unfairly tilted the playing field against them. Though devised to encourage controversial broadcasting, in practice the doctrine often led broadcasters to avoid controversy so they wouldn’t have to give away free airtime. To conservatives, avoiding controversy inevitably meant silencing right-wing voices.

the right repeatedly challenged the central assumptions the FCC—and Americans more broadly—made about journalism. For much of the 20th century, journalists cleaved to the idea of objectivity. Opinion and analysis had their place, but that place was distinct and separate from the news. Conservative broadcasts, on the other hand, were by their very nature opinion. Fairness dictated these partisan broadcasters provide airtime for a response.

Conservatives saw the media landscape differently. They viewed objectivity as a mask concealing entrenched liberal bias, hiding the slanted reporting that dominated American media. Because of this, the right believed fairness did not require a response to conservative broadcasts; conservative broadcasts were the response. Unable to bring the FCC around to their position, conservatives increasingly saw the commission as a powerful government agency dedicated to maintaining media’s liberal tilt.

In calling coverage of Goldwater “unfounded in fact,” Manion was making another argument to which conservatives anchored their charges of liberal bias: Established media did not just slant the news—they fabricated it. And if established media couldn’t be counted on for truth, the argument went, then surely they should be required to offer both sides of the argument. In the years that followed, conservatives began an active campaign against liberal bias

The combined forces of the administration and its conservative media-research wing had an effect. By 1971 CBS Radio had launched Spectrum, a debate show featuring conservatives like Stan Evans, James Kilpatrick, and Phyllis Schlafly. That same year 60 Minutes pitted conservative Kilpatrick against liberal Nicholas von Hoffman in a regular segment called “Point/Counterpoint.” By then, even the publisher of Human Events, in the midst of selling his paper as an alternative to liberal media, had to admit that conservatives were popping up all over established media—even the editorial pages of “that holy house organ of Liberalism—the New York Times.”

So balance and bias became part of the American news diet long before Ailes entered the conservative media game. Why does that matter? It makes Ailes’s successes at Fox News far more understandable—and far less Ailes-centric. By the time Ailes entered the game, the American right had spent a generation seeking out conservative alternatives to the “liberal media,” and America’s news media was already in the midst of a revolution that made Fox News possible.

The economics community just hasn't spent much time over the past couple of decades focusing on the effect that machine intelligence is likely to have on the labor marke

The Digital Revolution is different because computers can perform cognitive tasks too, and that means machines will eventually be able to run themselves. When that happens, they won't just put individuals out of work temporarily. Entire classes of workers will be out of work permanently. In other words, the Luddites weren't wrong. They were just 200 years too early

Slowly but steadily, labor's share of total national income has gone down, while the share going to capital owners has gone up. The most obvious effect of this is the skyrocketing wealth of the top 1 percent, due mostly to huge increases in capital gains and investment income.

Robotic pets are growing so popular that Sherry Turkle, an MIT professor who studies the way we interact with technology, is uneasy about it: "The idea of some kind of artificial companionship," she says, "is already becoming the new normal."

robots will take over more and more jobs. And guess who will own all these robots? People with money, of course. As this happens, capital will become ever more powerful and labor will become ever more worthless. Those without money—most of us—will live on whatever crumbs the owners of capital allow us.

Economist Paul Krugman recently remarked that our long-standing belief in skills and education as the keys to financial success may well be outdated. In a blog post titled "Rise of the Robots," he reviewed some recent economic data and predicted that we're entering an era where the prime cause of income inequality will be something else entirely: capital vs. labor.

while it's easy to believe that some jobs can never be done by machines—do the elderly really want to be tended by robots?—that may not be true.

Third, as more people compete for fewer jobs, we'd expect to see middle-class incomes flatten in a race to the bottom.

The question we want to answer is simple: If CBTC is already happening—not a lot, but just a little bit—what trends would we expect to see? What are the signs of a computer-driven economy?

if automation were displacing labor, we'd expect to see a steady decline in the share of the population that's employed.

Second, we'd expect to see fewer job openings than in the past.

In the economics literature, the increase in the share of income going to capital owners is known as capital-biased technological change

Fourth, with consumption stagnant, we'd expect to see corporations stockpile more cash and, fearing weaker sales, invest less in new products and new factories

Fifth, as a result of all this, we'd expect to see labor's share of national income decline and capital's share rise.

We're already seeing them, and not just because of the crash of 2008. They started showing up in the statistics more than a decade ago. For a while, though, they were masked by the dot-com and housing bubbles, so when the financial crisis hit, years' worth of decline was compressed into 24 months. The trend lines dropped off the cliff.

Corporate executives should worry too. For a while, everything will seem great for them: Falling labor costs will produce heftier profits and bigger bonuses. But then it will all come crashing down. After all, robots might be able to produce goods and services, but they can't consume them

in another sense, we should be very alarmed. It's one thing to suggest that robots are going to cause mass unemployment starting in 2030 or so. We'd have some time to come to grips with that. But the evidence suggests that—slowly, haltingly—it's happening already, and we're simply not prepared for it.

the first jobs to go will be middle-skill jobs. Despite impressive advances, robots still don't have the dexterity to perform many common kinds of manual labor that are simple for humans—digging ditches, changing bedpans. Nor are they any good at jobs that require a lot of cognitive skill—teaching classes, writing magazine articles

in the middle you have jobs that are both fairly routine and require no manual dexterity. So that may be where the hollowing out starts: with desk jobs in places like accounting or customer support.

In fact, there's even a digital sports writer. It's true that a human being wrote this story—ask my mother if you're not sure—but in a decade or two I might be out of a job too

Doctors should probably be worried as well. Remember Watson, the Jeopardy!-playing computer? It's now being fed millions of pages of medical information so that it can help physicians do a better job of diagnosing diseases. In another decade, there's a good chance that Watson will be able to do this without any human help at all.

Take driverless cars.

The next step might be passenger vehicles on fixed routes, like airport shuttles. Then long-haul trucks. Then buses and taxis. There are 2.5 million workers who drive trucks, buses, and taxis for a living, and there's a good chance that, one by one, all of them will be displaced

There will be no place to go but the unemployment lin

we'll need to let go of some familiar convictions. Left-leaning observers may continue to think that stagnating incomes can be improved with better education and equality of opportunity. Conservatives will continue to insist that people without jobs are lazy bums who shouldn't be coddled. They'll both be wrong.

The modern economy is complex, and most of these trends have multiple causes.

we'll probably have only a few options open to us. The simplest, because it's relatively familiar, is to tax capital at high rates and use the money to support displaced workers. In other words, as The Economist's Ryan Avent puts it, "redistribution, and a lot of it."

would we be happy in a society that offers real work to a dwindling few and bread and circuses for the rest?

Most likely, owners of capital would strongly resist higher taxes, as they always have, while workers would be unhappy with their enforced idleness. Still, the ancient Romans managed to get used to it—with slave labor playing the role of robots—and we might have to, as well.

 economist Noah Smith suggests that we might have to fundamentally change the way we think about how we share economic growth. Right now, he points out, everyone is born with an endowment of labor by virtue of having a body and a brain that can be traded for income. But what to do when that endowment is worth a fraction of what it is today? Smith's suggestion: "Why not also an endowment of capital? What if, when each citizen turns 18, the government bought him or her a diversified portfolio of equity?"

In simple terms, if owners of capital are capturing an increasing fraction of national income, then that capital needs to be shared more widely if we want to maintain a middle-class society.

it's time to start thinking about our automated future in earnest. The history of mass economic displacement isn't encouraging—fascists in the '20s, Nazis in the '30s—and recent high levels of unemployment in Greece and Italy have already produced rioting in the streets and larger followings for right-wing populist parties. And that's after only a few years of misery.

When the robot revolution finally starts to happen, it's going to happen fast, and it's going to turn our world upside down. It's easy to joke about our future robot overlords—R2-D2 or the Terminator?—but the challenge that machine intelligence presents really isn't science fiction anymore. Like Lake Michigan with an inch of water in it, it's happening around us right now even if it's hard to see

A robotic paradise of leisure and contemplation eventually awaits us, but we have a long and dimly lit tunnel to navigate before we get there.

This speaks to the fact that things that violate the laws of nature are terrifying. And really anything that doesn’t make sense or causes us some sort of dissonance, whether it is cognitive or aesthetic, is going to be scary (axe-wielding animals, masked faces, contorted bodies).

Humans are obsessed with death; we simply have a hard time wrapping our mind around what happens when we die.

Humans have been scaring themselves and each other since the birth of the species, through all kinds of methods like storytelling, jumping off cliffs, and popping out to startle each other from the recesses of some dark cave.

to build group unity, to prepare kids for life in the scary world, and, of course, to control behavior.

These scary stories provided, and continue to deliver, intrigue, exhilaration, and a jolt of excitement to our lives.

One of the reasons people love Halloween is because it produces strong emotional responses, and those responses work to build stronger relationships and memories. When we’re happy, or afraid, we’re releasing powerful hormones, like oxcytocin, that are working to make these moments stick in our brain. So we’re going to remember the people we’re with. If it was a good experience, then we’ll remember them fondly and feel close to them, more so than if we were to meet them during some neutral unexciting event.

We’re social and emotional beings. We need each other in times of stress, so the fact that our bodies have evolved to make sure we feel close to those we are with when afraid makes sense.

The crash, which killed all 49 people on board as well as one person on the ground, should never have happened.

aptain’s response to the stall warning, the investigators reported, “should have been automatic, but his improper flight control inputs were inconsistent with his training” and instead revealed “startle and confusion.

Automation has become so sophisticated that on a typical passenger flight, a human pilot holds the controls for a grand total of just three minutes.

We humans have been handing off chores, both physical and mental, to tools since the invention of the lever, the wheel, and the counting bead.

And that, many aviation and automation experts have concluded, is a problem. Overuse of automation erodes pilots’ expertise and dulls their reflexes,

No one doubts that autopilot has contributed to improvements in flight safety over the years. It reduces pilot fatigue and provides advance warnings of problems, and it can keep a plane airborne should the crew become disabled. But the steady overall decline in plane crashes masks the recent arrival of “a spectacularly new type of accident,”

“We’re forgetting how to fly.”

The experience of airlines should give us pause. It reveals that automation, for all its benefits, can take a toll on the performance and talents of those who rely on it. The implications go well beyond safety. Because automation alters how we act, how we learn, and what we know, it has an ethical dimension. The choices we make, or fail to make, about which tasks we hand off to machines shape our lives and the place we make for ourselves in the world.

What pilots spend a lot of time doing is monitoring screens and keying in data. They’ve become, it’s not much of an exaggeration to say, computer operators.

Examples of complacency and bias have been well documented in high-risk situations—on flight decks and battlefields, in factory control rooms—but recent studies suggest that the problems can bedevil anyone working with a computer

That may leave the person operating the computer to play the role of a high-tech clerk—entering data, monitoring outputs, and watching for failures. Rather than opening new frontiers of thought and action, software ends up narrowing our focus.

A labor-saving device doesn’t just provide a substitute for some isolated component of a job or other activity. It alters the character of the entire task, including the roles, attitudes, and skills of the people taking part.

when we work with computers, we often fall victim to two cognitive ailments—complacency and bias—that can undercut our performance and lead to mistakes. Automation complacency occurs when a computer lulls us into a false sense of security. Confident that the machine will work flawlessly and handle any problem that crops up, we allow our attention to drift.

Automation bias occurs when we place too much faith in the accuracy of the information coming through our monitors. Our trust in the software becomes so strong that we ignore or discount other information sources, including our own eyes and ears

Automation is different now. Computers can be programmed to perform complex activities in which a succession of tightly coordinated tasks is carried out through an evaluation of many variables. Many software programs take on intellectual work—observing and sensing, analyzing and judging, even making decisions—that until recently was considered the preserve of humans.

Automation turns us from actors into observers. Instead of manipulating the yoke, we watch the screen. That shift may make our lives easier, but it can also inhibit the development of expertise.

Since the late 1970s, psychologists have been documenting a phenomenon called the “generation effect.” It was first observed in studies of vocabulary, which revealed that people remember words much better when they actively call them to mind—when they generate them—than when they simply read them.

When you engage actively in a task, you set off intricate mental processes that allow you to retain more knowledge. You learn more and remember more. When you repeat the same task over a long period, your brain constructs specialized neural circuits dedicated to the activit

What looks like instinct is hard-won skill, skill that requires exactly the kind of struggle that modern software seeks to alleviate.

In many businesses, managers and other professionals have come to depend on decision-support systems to analyze information and suggest courses of action. Accountants, for example, use the systems in corporate audits. The applications speed the work, but some signs suggest that as the software becomes more capable, the accountants become less so.

You can put limits on the scope of automation, making sure that people working with computers perform challenging tasks rather than merely observing.

Experts used to assume that there were limits to the ability of programmers to automate complicated tasks, particularly those involving sensory perception, pattern recognition, and conceptual knowledge

Who needs humans, anyway? That question, in one rhetorical form or another, comes up frequently in discussions of automation. If computers’ abilities are expanding so quickly and if people, by comparison, seem slow, clumsy, and error-prone, why not build immaculately self-contained systems that perform flawlessly without any human oversight or intervention? Why not take the human factor out of the equation?

The cure for imperfect automation is total automation.

That idea is seductive, but no machine is infallible. Sooner or later, even the most advanced technology will break down, misfire, or, in the case of a computerized system, encounter circumstances that its designers never anticipated. As automation technologies become more complex, relying on interdependencies among algorithms, databases, sensors, and mechanical parts, the potential sources of failure multiply. They also become harder to detect.

conundrum of computer automation.

Because many system designers assume that human operators are “unreliable and inefficient,” at least when compared with a computer, they strive to give the operators as small a role as possible.

People end up functioning as mere monitors, passive watchers of screens. That’s a job that humans, with our notoriously wandering minds, are especially bad at

people have trouble maintaining their attention on a stable display of information for more than half an hour. “This means,” Bainbridge observed, “that it is humanly impossible to carry out the basic function of monitoring for unlikely abnormalities.”

a person’s skills “deteriorate when they are not used,” even an experienced operator will eventually begin to act like an inexperienced one if restricted to just watching.

You can program software to shift control back to human operators at frequent but irregular intervals; knowing that they may need to take command at any moment keeps people engaged, promoting situational awareness and learning.

What’s most astonishing, and unsettling, about computer automation is that it’s still in its early stages.

most software applications don’t foster learning and engagement. In fact, they have the opposite effect. That’s because taking the steps necessary to promote the development and maintenance of expertise almost always entails a sacrifice of speed and productivity.

Learning requires inefficiency. Businesses, which seek to maximize productivity and profit, would rarely accept such a trade-off. Individuals, too, almost always seek efficiency and convenience.

Abstract concerns about the fate of human talent can’t compete with the allure of saving time and money.

The small island of Igloolik, off the coast of the Melville Peninsula in the Nunavut territory of northern Canada, is a bewildering place in the winter.

, Inuit hunters have for some 4,000 years ventured out from their homes on the island and traveled across miles of ice and tundra to search for game. The hunters’ ability to navigate vast stretches of the barren Arctic terrain, where landmarks are few, snow formations are in constant flux, and trails disappear overnight, has amazed explorers and scientists for centuries. The Inuit’s extraordinary way-finding skills are born not of technological prowess—they long eschewed maps and compasses—but of a profound understanding of winds, snowdrift patterns, animal behavior, stars, and tides.

The Igloolik hunters have begun to rely on computer-generated maps to get around. Adoption of GPS technology has been particularly strong among younger Inuit, and it’s not hard to understand why.

But as GPS devices have proliferated on Igloolik, reports of serious accidents during hunts have spread. A hunter who hasn’t developed way-finding skills can easily become lost, particularly if his GPS receiver fails.

The routes so meticulously plotted on satellite maps can also give hunters tunnel vision, leading them onto thin ice or into other hazards a skilled navigator would avoid.

An Inuit on a GPS-equipped snowmobile is not so different from a suburban commuter in a GPS-equipped SUV: as he devotes his attention to the instructions coming from the computer, he loses sight of his surroundings. He travels “blindfolded,” as Aporta puts it

A unique talent that has distinguished a people for centuries may evaporate in a generation.

Computer automation severs the ends from the means. It makes getting what we want easier, but it distances us from the work of knowing. As we transform ourselves into creatures of the screen, we face an existential question: Does our essence still lie in what we know, or are we now content to be defined by what we want?

In the study, the NOAA researchers argue that long-standing problems with the way temperatures are measured have masked years of sea surface warming. Once those problems are corrected for, “this hiatus or slowdown simply vanishes,” said lead study author Thomas Karl, director of NOAA's National Climatic Data Center in Asheville, N.C.

Although researchers have long known that sea surface temperatures measured by autonomous buoys run cooler than temperatures measured by ships, they have failed to account for this as they expanded their use of buoy readings over the last two decades, the study authors argued.

“The buckets, when you pull them up, tend to evaporate their water, and if they're canvas there's even more evaporation,” Karl said. “By the time people stick a thermistor in the bucket to measure temperature, it's already slightly cool.”

“If you start a short-time series on an anomalous value, you tend to get an anomalous trend,” Karl said.

A growing number of climate scientists have argued that this phenomenon, as well as other hiatus effects, are evidence of a poorly understood pattern of wind, ocean current and temperature variations that have far-reaching effects on global climate. They say the oceans have absorbed heat energy from the sun, causing Arctic ice to melt and sea levels to rise.

“One way to think about it is that global warming continued, but the oceans just juggled a bit of heat around and made the surface seem cooler for a while,” said Joshua Willis, another climate scientist at JPL.

“All of those factors are real,” Karl said. “If those factors had not occurred, the warming rate would have been even greater. … If anything we may still be underestimating the trend.” 

How much of this kind of reality can the public take? Producers clearly see no end in sight, and the results are increasingly becoming more questionable.

This is what's called a ''reality-based'' series, a label that has less to do with reality than comforting formula. The cameras do not go to a real hospital. But three real doctors are on the production staff.

''What you are about to see is real,'' we were told once again.

His life shattered, he now has the dubious pleasure of knowing that, for some 20 minutes, he was the star of a television reality entertainment.

''On Trial'' opens with an announcer exclaiming that viewers are about to see ''Real people! Real Cases! Real Life!'' Mr. Clooney, a distinguished-looking fellow, fills in the pertinent facts.

Everything is designed, they say, to ''give the show its docudrama look.'' The show's regular staff of three doctors are depicted by actors.

Needless to say, medical problems and crises have long been popular on television, especially on soap operas. ''Family Medical Center'' merely dispenses with extraneous plot and character developments and goes right to the medical core. A press release is candid about the show's interpretation of reality: ''It will have suspense, conflict and a resolution, which in almost all cases will be a happy one.''

The show looks as real as television entertainment can possibly make it. Alert viewers, however, will note whizzing by in the final credits the following advisory: '' 'Family Medical Center' is a dramatization. The characters are fictional and bear no resemblance to persons living or dead.''

Television reality wears many masks. A key to the overall picture was provided by one of those actors who deceived Oprah Winfrey and Geraldo Rivera with false impersonations on air. Why not, he shrugged, it's all entertainment. Frightening but not beyond comprehension.