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That allows quantum computers to make many calculations in one pass, while digital ones have to perform each calculation separately. By speeding up computation, quantum computers could potentially solve big, complex problems in fields like chemistry and materials science that are out of reach today.

When Google researchers made their supremacy claim in 2019, they said their quantum computer performed a calculation in 3 minutes 20 seconds that would take about 10,000 years on a state-of-the-art conventional supercomputer.

The IBM researchers in the new study performed a different task, one that interests physicists. They used a quantum processor with 127 qubits to simulate the behavior of 127 atom-scale bar magnets — tiny enough to be governed by the spooky rules of quantum mechanics — in a magnetic field. That is a simple system known as the Ising model, which is often used to study magnetism.

This problem is too complex for a precise answer to be calculated even on the largest, fastest supercomputers.

On the quantum computer, the calculation took less than a thousandth of a second to complete. Each quantum calculation was unreliable — fluctuations of quantum noise inevitably intrude and induce errors — but each calculation was quick, so it could be performed repeatedly.

Indeed, for many of the calculations, additional noise was deliberately added, making the answers even more unreliable. But by varying the amount of noise, the researchers could tease out the specific characteristics of the noise and its effects at each step of the calculation.“We can amplify the noise very precisely, and then we can rerun that same circuit,” said Abhinav Kandala, the manager of quantum capabilities and demonstrations at IBM Quantum and an author of the Nature paper. “And once we have results of these different noise levels, we can extrapolate back to what the result would have been in the absence of noise.”In essence, the researchers were able to subtract the effects of noise from the unreliable quantum calculations, a process they call error mitigation.

Altogether, the computer performed the calculation 600,000 times, converging on an answer for the overall magnetization produced by the 127 bar magnets.

Although an Ising model with 127 bar magnets is too big, with far too many possible configurations, to fit in a conventional computer, classical algorithms can produce approximate answers, a technique similar to how compression in JPEG images throws away less crucial data to reduce the size of the file while preserving most of the image’s details

Certain configurations of the Ising model can be solved exactly, and both the classical and quantum algorithms agreed on the simpler examples. For more complex but solvable instances, the quantum and classical algorithms produced different answers, and it was the quantum one that was correct.

Thus, for other cases where the quantum and classical calculations diverged and no exact solutions are known, “there is reason to believe that the quantum result is more accurate,”

Mr. Anand is currently trying to add a version of error mitigation for the classical algorithm, and it is possible that could match or surpass the performance of the quantum calculations.

In the long run, quantum scientists expect that a different approach, error correction, will be able to detect and correct calculation mistakes, and that will open the door for quantum computers to speed ahead for many uses.

Error correction is already used in conventional computers and data transmission to fix garbles. But for quantum computers, error correction is likely years away, requiring better processors able to process many more qubits

“This is one of the simplest natural science problems that exists,” Dr. Gambetta said. “So it’s a good one to start with. But now the question is, how do you generalize it and go to more interesting natural science problems?”

Those might include figuring out the properties of exotic materials, accelerating drug discovery and modeling fusion reactions.

“In Norway, people very much disapprove of inequalities that are due to bad luck,”

“People in the U.S. are more willing to accept inequality, even if it reflects pure good luck for some and pure bad luck for others.”

The purpose of setting up the experiment this way, Tungodden told me, was to find out spectators’ views about different sources of inequality. In the first setting, inequality was a result of luck: The workers both did the task well, but one just got lucky and received a bonus. In the second, inequality was a result of merit: One worker did the task better. And the third was to assess whether people were willing to eradicate inequality created by luck if doing so had costs: The bonus was lower if the spectators chose to redistribute it more fairly.

In the experiment, Americans were more willing to accept inequality if it’s a result of luck than Norwegians were. When both workers did the task well, but only one got the bonus (the first setting), half of Americans said they wanted to redistribute the bonus equally. By contrast, 78 percent of Norwegians did. “It’s an enormous difference in exactly the same situation in a willingness to accept brute luck,” Tungodden said. “Americans hold this view of, whatever comes to you, good for you.”

When inequality was a result of merit, on the other hand, people in both countries were willing to accept it. Just 15 percent of people in the U.S. and 36 percent of people in Norway redistributed the bonus in the second situation.

Together, this helps explain why Norway has a more robust welfare state than the U.S. does, Tungodden said. Norwegians believe that when someone is, by bad luck, born into a poor family, or is, by bad luck, thrust into poverty, that person should have help from others. U.S. residents are more split on this idea

This could be because Americans admire wealth and would be hesitant to implement policies that would hurt people who, by luck, are wealthy.

There were some differences in which demographics in each country were willing to redistribute the bonuses.

white Americans tend to be more withholding when it comes to welfare if they believe the money is going to black Americans. It would be illuminating for another, similar study to be performed that looks at whether white people perceive luck as more or less fair if the beneficiary (or loser, as the case may be) is black.

Perhaps somewhat surprisingly, both Americans and Norwegians seemed willing to weather some costs of wealth redistribution. In the third setting, when spectators were told that the inequality was the result of luck, but that redistributing the bonus would have a significant cost, about equal numbers of Americans and Norwegians decided to redistribute

it shows that people in both countries are more concerned about whether inequalities are fair than about whether there are costs to redistribution.

Debates about the costs of a welfare state and redistribution in America, then, may be besides the point. Costs don’t seem to be Americans’ big hang-up with redistribution. Rather, their opposition seems to go to an underlying acceptance of fate and the fortunes it brings.

invoked an old metaphor to explain why he isn’t convinced by the analysis: He compared it to establishing a theory of how weather works by pointing a video camera out the window for 7 hours.

Indeed, among neuroscientists, the new “comprehensive atlas” of the cerebral cortex is almost as controversial as a historical atlas of the Middle East. That’s because every word has a constellation of meanings and associations — and it’s hard for scientists to agree about how best to study them in the lab.

For this study, neuroscientist Jack Gallant and his team at the University of California, Berkeley played more than two hours’ worth of stories from the Moth Radio Hour for seven grad students and postdocs while measuring their cerebral blood flow using functional magnetic resonance imaging. Then, they linked the activity in some 50,000 pea-sized regions of the cortex to the “meaning” of the words being heard at that moment.

How, you might ask, did they establish the meaning of words? The neuroscientists pulled all the nouns and verbs from the podcasts. With a computer program, they then looked across millions of pages of text to see how often the words from the podcasts are used near 985 common words taken from Wikipedia’s List of 1,000 Basic Words. “Wolf,” for instance, would presumably be used more often in proximity to “dog” than to, say, “eggplant.” Using that data, the program assigned numbers that approximated the meaning of each individual word from the podcasts — and, with some fancy number crunching, they figured out what areas of the brain were activated when their research subjects heard words with certain meanings.

Everyone agrees that the research is innovative in its method. After all, linking up the meanings of thousands of words to the second-by-second brain activity in thousands of tiny brain regions is no mean feat. “That’s way more data than any human being can possibly think about,” said Gallant.

What they can’t agree on is what it means. “In this study, our goal was not to ask a specific question. Our goal was to map everything so that we can ask questions after that,” said Gallant. “One of the most frequent questions we get is, ‘What does it mean?’ If I gave you a globe, you wouldn’t ask what it means, you’d start using it for stuff. You can look for the smallest ocean or how long it will take to get to San Francisco.”

This “data-driven approach” still involves assumptions about how to break up language into different categories of meaning

“Of course it’s a very simplified version of how meaning is captured in our minds, but it seems to be a pretty good proxy,” she said.

hordes of unanswered questions: “We can map where your brain represents the meaning of a narrative text that is associated with family, but we don’t know why the brain is responding to family at that location. Is it the word ‘father’ itself? Is it your memories of your own father? Is it your own thinking about being a parent yourself?” He hopes that it’s just those types of questions that researchers will ask, using his brain map as a guide.

the lesson in Virginia, as the Washington Post reporter Paul Farhi wrote at the time, was that nothing exceeds the value of shoe-leather reporting, given that politics is an essentially human endeavor and therefore can defy prediction and reason.

Yet when Mr. Trump showed up on the scene, it was as if that had never happened.

It was another thing to declare, as The Huffington Post did, that coverage of his campaign could be relegated to the entertainment section (and to add a disclaimer to articles about him) and still another to give Mr. Trump a “2 percent” chance at the nomination despite strong polls in his favor, as FiveThirtyEight did six months before the first votes were cast.

Predictions that far out can be viewed as being all in good fun. But in Mr. Trump’s case, they also arguably sapped the journalistic will to scour his record as aggressively as those of his supposedly more serious rivals. In other words, predictions can have consequences.

The problems weren’t at all only due to the reliance on data. Don’t forget those moments that were supposed to have augured Mr. Trump’s collapse: the certainty that once the race narrowed to two or three candidates, Mr. Trump would be through, and what at one point became the likelihood of a contested convention.

That’s all the more reason in the coming months to be as sharply focused on the data we don’t have as we are on the data we do have (and maybe watching out for making any big predictions about the fall based on the polling of today). But a good place to start would be to get a good night’s sleep, and then talk to some voters.

“We think we’re all unique, and we think every novel is individual, and it is. So when they reduce us all to a bunch of data about words, I guess you have to laugh.

A 1999 study found that when social and economic conditions were bad, movie actresses with “mature facial features” — small eyes, thin cheeks, large chins — were popular, but when conditions were good, the public liked actresses with childlike features.

In the new study, researchers also analyzed 650,000 German books and found the same misery correlation.

Still, the practice of applying data-sorting algorithms to art can only go so far. For one thing, the lists of emotion words, created by other researchers and used for years, include some surprising choices: words like “smug” and “wallow” were among 224 words on the “joy” list; potentially neutral adjectives like “dark” and “low” were among 115 words on the “sadness” list.

First, members of a group lavish one another with praise

This creates a set of common behavior patterns.

Second, there are nonetheless enforcers within the group who build their personal power and reputation by policing the group and condemning those who break the group code

Third, people are extremely anxious that their group might be condemned or denigrated. They demand instant respect and recognition for their group

Campus controversies get so hot so fast because even a minor slight to a group is perceived as a basic identity threat.

In a guilt culture you know you are good or bad by what your conscience feels. In a shame culture you know you are good or bad by what your community says about you, by whether it honors or excludes you. In a guilt culture people sometimes feel they do bad things; in a shame culture social exclusion makes people feel they are bad.

this shame culture is different from the traditional shame cultures, the ones in Asia, for example. In traditional shame cultures the opposite of shame was honor or “face” — being known as a dignified and upstanding citizen

In the new shame culture, the opposite of shame is celebrity — to be attention-grabbing and aggressively unique on some media platform.

On the positive side, this new shame culture might rebind the social and communal fabric. It might reverse, a bit, the individualistic, atomizing thrust of the past 50 years.

On the other hand, everybody is perpetually insecure in a moral system based on inclusion and exclusion. There are no permanent standards, just the shifting judgment of the crowd. It is a culture of oversensitivity, overreaction and frequent moral panics, during which everybody feels compelled to go along.

26 Comments If we’re going to avoid a constant state of anxiety, people’s identities have to be based on standards of justice and virtue that are deeper and more permanent than the shifting fancy of the crowd

In an era of omnipresent social media, it’s probably doubly important to discover and name your own personal True North, vision of an ultimate good, which is worth defending even at the cost of unpopularity and exclusion.

The guilt culture could be harsh, but at least you could hate the sin and still love the sinner. The modern shame culture allegedly values inclusion and tolerance, but it can be strangely unmerciful to those who disagree and to those who don’t fit in.

What is it about a new year? How does our psychology influence how we think about that and making fresh starts? We do what social psychologists call temporal accounting -- that is, we have a ledger in our head of how we are spending our time. What we’re trying to do, in some cases, is relegate our previous selves to the past: This year we’re going to do a lot better.

breaks are much more important than we realize.

Many hard-core workplaces think of breaks as a deviation from performance, when in fact the science of breaks tells us they’re a part of performance.

Research shows us that social breaks are better than solo breaks -- taking a break with somebody else is more restorative than doing it on your own. A break that involves movement is better than a stationary one. And then there's the restorative power in nature. Simply going outside outside rather than being inside, simply being able to look out a window during a break is better. And there's the importance of being fully detached,

Every day I write down two breaks that I’m going to take. I make a 'break list,' and I try to treat them with the same reverence with which I’d treat scheduled meetings. We would never skip a meeting.

One of the issues you explore is when it pays to go first — whether you’re up for a competitive pitch or trying to get a job. When is it good to go first

Here’s where you should go first: If you’re not the default choice

If you are the default choice, you’re better off not going first. What happens is that early in a process, people are more likely to be open-minded, to challenge assumptions. But over time, they wear out, and they’re more likely to go with the default choice.

Also, if you’re operating in an uncertain environment -- and this is actually really important -- where the criteria for selections are not fully fully sharp, you’re better off going at the end. In the beginning, the judges are still trying to figure out what they want.

In fact, what researchers have found is that at the beginning, project teams pretty much do nothing. They bicker, they dicker. Yet astonishingly, many project teams she followed ended up really getting started in earnest at the exact midpoint. If you give a team 34 days, they’ll get started in earnest on day 17. This is actually a big shift in the way organizational scholars thought about how teams work.

There are two key things a leader can do at a midpoint. One is to identify it to make it salient: Say "ok guys, it’s day 17 of this 35 day project. We better get going."

The second comes from research on basketball. It shows that when teams are ahead at the midpoint, they get complacent. When they’re way behind at the midpoint, they get demoralized. But when they’re a little behind, it can be galvanizing. So what leaders can do is suggest hey, we’re a little bit behind.

When you're giving feedback to employees, should you give good news or bad news first?

If you ask people what they prefer, four out of five prefer getting the bad news first. The reason has to do with endings. Given the choice, human beings prefer endings that elevate. We prefer endings that go up, that have a rising sequence rather than a declining sequence.

“Since older people are also more likely to experience severe disease symptoms and, sadly, die, our findings make clear how important it is to implement policies to protect the elderly during the pandemic,

The large new study out of Denmark did not examine the role of variants in reinfection, given the time frame of the research. So it does not offer any clues about whether variants make it more likely for someone to come down with COVID-19 more than once.

The Centers for Disease Control and Prevention recommends that people who have had COVID-19 should get vaccinated once it’s available to them, in large part because there is a slim chance they could become infected again if they come into contact with the virus.

The attorney representing 10 of the families who lost relatives in the Sandy Hook massacre told me that he welcomed YouTube's Wednesday action, but said it was "too late to undo the harm" that has been caused to his clients from conspiracy theories circulating on the platform over the past several years. "Sandy Hook happened now nearly seven years ago, and so during that entire time the clients were subject to hostile postings on YouTube that disseminated this false narrative and caused undue harassment, threats, and fallacies as they were trying to heal," said the attorney, Josh Koskoff. "At the same time, better late than never."

Moving forward, it will be interesting to see if other social media company adopts guidelines similar to the ones YouTube announced on Wednesday regarding content that denies well-documented violent events like Sandy Hook. "All social media platforms who have not taken this step, should look in the mirror and decide whether they want to continue to facilitate harassment and hate in this day and age where that has serious consequences," Koskoff told me. And Pozner echoed that, saying that he hoped "Twitter and other hosting platforms will follow suit in implementing and enforcing more socially responsible policies."

“When inequality increases, people with high incomes don’t benefit much from their gains – many rich people are focused on those who have even more than they do, and they never feel they have enough,”

“But people who earn little really suffer from falling further behind – they feel excluded and frustrated by not being able to keep up even with people who receive average incomes.”

examined survey data of life satisfaction levels, where people rate their life satisfaction on a scale of one to 10, and linked it to Gini coefficient numbers – a measure of inequality – from 1981 to 2020.

In 1981, as the UK was gripped by a recession, life satisfaction stood at 7.7. But during the economic boom of the 1980s, inequality grew, and the research shows that the happiness figure dropped to 7.4 by 1999.

However, as measures to reduce inequality began to take effect, happiness slowly returned so that by 2018, life satisfaction stood at 7.8.

Any country that moved from the lowest quarter of countries in terms of inequality to the highest quarter saw a decrease in life satisfaction of about 0.4 on the 10-point scale, he found.

India’s life satisfaction declined from 6.7 in 1990 to 5.8 in 2006 as inequality rose. By 2012 it was still lower than in 1990, despite the country’s prolonged economic boom.

The US and Australia also both saw pronounced falls in life satisfaction, but those countries where inequality had fallen were generally happier, such as Poland, Peru, Mexico and Ukraine, before the Russian invasion.

“In some of the previous research, you see people saying ‘inequality isn’t that big a deal, so all efforts to address inequality are misguided because inequality is beneficial’.

“I think that’s misguided – inequality is generally damaging to people’s life satisfaction so we should pay attention to efforts to mitigate it,

that joy also feels misguided, misplaced, or simply out of time—from an era that definitively ended. The aughties era of universal social-media onboarding that includes Twitter was defined by Millennial optimism and its whoop-whoop soundtrack.

Threads represents a memory of a time that has probably passed but of which we cannot yet let go.

With a few threads posted, and the most eager followees following or followed, the dopamine high cleared, revealing reality: The age of social media is over, and it cannot be recovered.

Zuckerberg has merely copied and pasted a social network, and we are back where we started, only with all the baggage and psychological scarring of previous connectivity experiences.

Big tech companies now dictate where attention, and therefore money, power, and influence, reside. You don’t have to like that fact to admit that it’s the case: Is Threads a thing? Should we be on it? MrBeast has 1 million Thread followers already.

Who, if anyone, is this for? Did anyone ask for this? Why are these hot people with excellent skin, blue check marks, and 750,000 followers so excited?

Who, if

The cascade of new followers, the collective rush of establishing new communication norms on the fly with friends and total strangers—all of that is fleeting. And the true sickos know what happens next: the trolls, the spam, the ads, the Conversations About Politics. Even if those things never materialize, the nagging feeling is still there

It’s not exactly like rebuilding your home on the coastline after it was destroyed by a hurricane, but the vibe is similar: rebirth and hope, but also regret and dread. If only it had all just fallen into the sea.

It’s better to spend time building a dedicated viewer base that will support you for you.

But the headline-grabbing differences between the findings of these Nobel laureates are less significant than the profound agreement in their scientific approach to economic questions, which is characterized by formulating and testing precise hypotheses

I’m troubled by the sense among skeptics that disagreements about the answers to certain questions suggest that economics is a confused discipline, a fake science whose findings cannot be a useful basis for making policy decisions.

It is true that the answers to many “big picture” macroeconomic questions — like the causes of recessions or the determinants of growth — remain elusive.

As is the case with epidemiologists, the fundamental challenge faced by economists — and a root cause of many disagreements in the field — is our limited ability to run experiments

economists have recently begun to overcome these challenges by developing tools that approximate scientific experiments to obtain compelling answer

Other economic studies have taken advantage of the constraints inherent in a particular policy to obtain scientific evidence

Even when such experiments are unfeasible, there are ways to use “big data” to help answer policy questions

In the early days of his campaign, Mr. Biden’s team envisioned setting up its own digital media empire. It posted videos to his official YouTube channel, conducted virtual forums and even set up a podcast hosted by Mr. Biden, “Here’s the Deal.”

those efforts were marred by technical glitches and lukewarm receptions, and they never came close to rivaling the reach of Mr. Trump’s social media machine.

So the campaign pivoted to a different strategy, which involved expanding Mr. Biden’s reach by working with social media influencers and “validators,

Perhaps the campaign’s most unlikely validator was Fox News. Headlines from the outlet that reflected well on Mr. Biden were relatively rare, but the campaign’s tests showed that they were more persuasive to on-the-fence voters than headlines from other outlets

“When people saw a Fox News headline endorsing Joe Biden, it made them stop scrolling and think.”

2. Tune Out Twitter, and Focus on ‘Facebook Moms’

“The whole Biden campaign ethos was ‘Twitter isn’t real life,’” Mr. Flaherty said. “There are risks of running a campaign that is too hyper-aware of your own ideological corner.”

As it focused on Facebook, the Biden campaign paid extra attention to “Facebook moms” — women who spend a lot of time sharing cute and uplifting content

“Our goal was really to meet people where they were,”

3. Build a Facebook Brain Trust

the “Rebel Alliance,” a jokey nod to Mr. Parscale’s “Death Star,” and it eventually grew to include the proprietors of pages like Occupy Democrats, Call to Activism, The Other 98 Percent and Being Liberal.

On the messaging app Signal, the page owners formed a group text that became a kind of rapid-response brain trust for the campaign.

“I had the freedom to go for the jugular,” said Rafael Rivero, a co-founder of Occupy Democrats and Ridin’ With Biden, another big pro-Biden Facebook page.

“It was sort of a big, distributed message test,” Mr. Flaherty said of the Rebel Alliance. “If it was popping through Occupy or any of our other partners, we knew there was heat there.”

These left-wing pages gave the campaign a bigger Facebook audience than it could have reached on its own. But they also allowed Mr. Biden to keep most of his messaging positive, while still tapping into the anger and outrage many Democratic voters felt.

4. Promote ‘Small-Batch Creators,’ Not Just Slick Commercials

the Biden campaign found that traditional political ads — professionally produced, slick-looking 30-second spots — were far less effective than impromptu, behind-the-scenes footage and ads that featured regular voters talking directly into their smartphones or webcams about why they were voting for Mr. Biden.

“The things that were realer, more grainy and cheaper to produce were more credible.”

In addition to hiring traditional Democratic ad firms, the campaign also teamed up with what it called “small-batch creators” — lesser-known producers and digital creators, some of whom had little experience making political ads

5. Fight Misinformation, but Pick Your Battles

The campaign formed an in-house effort to combat these rumors, known as the “Malarkey Factory.” But it picked its battles carefully, using data from voter testing to guide its responses.

“The Hunter Biden conversation was many times larger than the Hillary Clinton email conversation, but it really didn’t stick, because people think Joe Biden’s a good guy,”

the campaign’s focus on empathy had informed how it treated misinformation: not as a cynical Trump ploy that was swallowed by credulous dupes, but as something that required listening to voters to understand their concerns and worries before fighting back

Ultimately, he said, the campaign’s entire digital strategy — the Malarkey Factory, the TikTok creators and Facebook moms, the Fortnite signs and small-batch creators — was about trying to reach a kinder, gentler version of the internet that it still believed existed.

“We made a decision early that we were going to be authentically Joe Biden online, even when people were saying that was a trap.”

It’s a slippery number, however. Measurements using different techniques have produced different results, and the numbers show no sign of converging even as researchers refine their observations

the theorists are intrigued. They hope the Hubble Constant confusion is the harbinger of a potential major discovery — some "new physics."

“Any time there’s a discrepancy, some kind of anomaly, we all get very excited,”

“Where’s it all going to go? How’s it all going to end? That’s a big question,”

One idea floating around is that there could have been something called Early Dark Energy that skewed the appearance of the background radiation

“New physics might be that there’s some form of energy that acted in the earliest moments of the evolution of the universe. You’d get an injection of energy that’d then have to disappear,”

Leavitt, a then-obscure employee of the Harvard College Observatory, discovered that the intrinsically brighter stars have longer periods. This insight — Leavitt’s law — allows astronomers to know the Cepheid’s absolute luminosity, then gauge the distance to the star based on how bright or faint it appears.

just to be clear: The Hubble Constant in question is the rate of expansion in our “local” universe, not the rate of expansion when the background radiation was first emitted billions of years ago. Over time, the Hubble Constant isn’t constant.)

At the dawn of the 21st century, this Standard Model seemed to pass every observational test. And any disparities in the measurement of the Hubble Constant would surely be ironed out with further observations, scientists assumed. They had even nailed down the age of the universe precisely: 13.8 billion years.

“We felt really good,”

He added, jokingly, “We should have stopped taking data.”

“We are wired to use our intuition to understand things around us,” Riess said. “Most of the universe is made out of stuff that’s completely different than us. This adherence to intuition is often wildly unsuccessful in the universe.”

Smart technology will extend inside residents' homes, according to Ingels, whose firm also designed the 2 World Trade Center in New York, and Google's headquarters in both London and Silicon Valley.

"In an age when technology, social media and online retail is replacing and eliminating our natural meeting places, the Woven City will explore ways to stimulate human interaction in the urban space," he said. "After all, human connectivity is the kind of connectivity that triggers wellbeing and happiness, productivity and innovation."

he blends the best of modern statistical analysis with research on cognition biases pioneered by Princeton psychologist and Nobel laureate in economics  Daniel Kahneman and the late Stanford psychologist Amos Tversky. 

Silver’s background in sports and poker turns out to be invaluable. Successful analysts in gambling and sports are different from fans and partisans—far more aware that “sure things” are likely to be illusions,

The second step is starting to understand why it is that big data, super computers, and mathematical sophistication haven’t made us better at separating signals (information with true predictive value) from noise (misleading information). 

One of the biggest problems we have in separating signal from noise is that when we look too hard for certainty that isn’t there, we often end up attracted to noise, either because it is more prominent or because it confirms what we would like to believe.

In discipline after discipline, Silver shows in his book that when you look at even the best single forecast, the average of all independent forecasts is 15 to 20 percent more accurate. 

Silver has taken the next major step: constantly incorporating both state polls and national polls into Bayesian models that also incorporate economic data.

Silver explains why we will be misled if we only consider significance tests—i.e., statements that the margin of error for the results is, for example, plus or minus four points, meaning there is one chance in 20 that the percentages reported are off by more than four. Calculations like these assume the only source of error is sampling error—the irreducible error—while ignoring errors attributable to house effects, like the proportion of cell-phone users, one of the complex set of assumptions every pollster must make about who will actually vote. In other words, such an approach ignores context in order to avoid having to justify and defend judgments. 

More F.S. Oliver: Nothing in politics is sadder than: the man of sterling character whose genius is so antipathetic to the particular emergency in which he finds himself as to stupefy his thoughts and paralyze his actions. He drifts to disaster, grappling blindfolded which are beyond his comprehension, failing without really fighting.

Bad choices over the past decade by Republican political leaders opened the way to Donald Trump, yes.  For a decade, Republican voters have signaled they wanted to protect Medicare, cut immigration, fight fewer wars, and nominate no more Bushes. Their party leaders interpreted those signals as demands to cut Medicare, increase immigration, put boots on the ground in Syria, and nominate another Bush.

Their task ahead, in the Biblical phrase, is to pluck the brands from the fire—rescue as much of their party as can be rescued—while simultaneously minimizing the damage to party and country by the nominee their rank-and-file has imposed on them. They need to maneuver so that Trump’s defeat is as solitary as possible, and so that he cannot shift the blame for the failure he has earned onto the heads of others

Trump’s taught Republican politicians that they’ve neglected the interests and values of their core supporters. He’s demonstrated that much of their party ideology is obsolete, and that their language no longer moves their voters. He’s proven that their party is less culturally conservative than they believed, less hostile to social insurance than they imagined, and more worried about the economic and social costs of mass migration than they realized. Those are valuable lessons that need to be absorbed and pondered.

He’s also demonstrated that he himself is a dangerous person

To save themselves and their country, Republican politicians will have to rediscover the politician’s arts of deftness, flexibility, and self-preservation—while stealthily hastening Trump toward the defeat that almost certainly awaits him in November.

That’s a big job and a hard job, all the harder because they cannot acknowledge what they are doing. They will seem to help Trump win, while actually working to ensure he fail

What Walter Lippman said of presidents is really true of all politicians: They are not “working through noble institutions to dear ends … but trying to grind out a few crude results from a decadent political machine.”

The harms they stop are more important than the good they cannot achieve. What they’re called upon to do is to practice statesmanship without fine phrases; to protect the republic without receiving any credit for it

go this route if you believe privacy is dead, but find social networking too good to miss out on.

While we should be attuned to constraints and their consequences, there are at least four problems with conceptualizing the social media user's dilemma as a version of "if you can't stand the heat, get out of the kitchen".

The efficacy of abandoning social media can be questioned when others are free to share information about you on a platform long after you've left.

Second, while abandoning a single social technology might seem easy, this "love it or leave it" strategy -- which demands extreme caution and foresight from users and punishes them for their naivete -- isn't sustainable without great cost in the aggregate. If we look past the consequences of opting out of a specific service (like Facebook), we find a disconcerting and more far-reaching possibility: behavior that justifies a never-ending strategy of abandoning every social technology that threatens privacy -- a can being kicked down the road in perpetuity without us resolving the hard question of whether a satisfying balance between protection and publicity can be found online

if your current social network has no obligation to respect the obscurity of your information, what justifies believing other companies will continue to be trustworthy over time?

Sticking with the opt-out procedure turns digital life into a paranoid game of whack-a-mole where the goal is to stay ahead of the crushing mallet. Unfortunately, this path of perilously transferring risk from one medium to another is the direction we're headed if social media users can't make reasonable decisions based on the current context of obscurity, but instead are asked to assume all online social interaction can or will eventually lose its obscurity protection.

The fourth problem with the "leave if you're unhappy" ethos is that it is overly individualistic. If a critical mass participates in the "Opt-Out Revolution," what would happen to the struggling, the lonely, the curious, the caring, and the collaborative if the social web went dark?

Our point is that there is a middle ground between reclusion and widespread publicity, and the reduction of user options to quitting or coping, which are both problematic, need not be inevitable, especially when we can continue exploring ways to alleviate the user burden of retreat and the societal cost of a dark social web.

it is easy to presume that "even if you unfriend everybody on Facebook, and you never join Twitter, and you don't have a LinkedIn profile or an About.me page or much else in the way of online presence, you're still going to end up being mapped and charted and slotted in to your rightful place in the global social network that is life." But so long it remains possible to create obscurity through privacy enhancing technology, effective regulation, contextually appropriate privacy settings, circumspect behavior, and a clear understanding of how our data can be accessed and processed, that fatalism isn't justified.