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SEIR models start to fall apart when you think about the underlying causes of the data. You need models that can allow for all possible states, and assess which ones matter for shaping the pandemic’s trajectory over time.

These techniques have enjoyed enormous success ever since they moved out of physics. They’ve been running your iPhone and nuclear power stations for a long time. In my field, neurobiology, we call the approach dynamic causal modelling (DCM). We can’t see brain states directly, but we can infer them given brain imaging data

Epidemiologists currently tackle the inference problem by number-crunching on a huge scale, making use of high-performance computers. Imagine you want to simulate an outbreak in Scotland. Using conventional approaches, this would take you a day or longer with today’s computing resources. And that’s just to simulate one model or hypothesis – one set of parameters and one set of starting conditions.

Using DCM, you can do the same thing in a minute. That allows you to score different hypotheses quickly and easily, and so to home in sooner on the best one.

This is like dark matter in the universe: we can’t see it, but we know it must be there to account for what we can see. Knowing it exists is useful for our preparations for any second wave, because it suggests that targeted testing of those at high risk of exposure to Covid-19 might be a better approach than non-selective testing of the whole population.

Our response as individuals – and as a society – becomes part of the epidemiological process, part of one big self-organising, self-monitoring system. That means it is possible to predict not only numbers of cases and deaths in the future, but also societal and institutional responses – and to attach precise dates to those predictions.

How well have your predictions been borne out in this first wave of infections?For London, we predicted that hospital admissions would peak on 5 April, deaths would peak five days later, and critical care unit occupancy would not exceed capacity – meaning the Nightingale hospitals would not be required. We also predicted that improvements would be seen in the capital by 8 May that might allow social distancing measures to be relaxed – which they were in the prime minister’s announcement on 10 May. To date our predictions have been accurate to within a day or two, so there is a predictive validity to our models that the conventional ones lack.

What do your models say about the risk of a second wave?The models support the idea that what happens in the next few weeks is not going to have a great impact in terms of triggering a rebound – because the population is protected to some extent by immunity acquired during the first wave. The real worry is that a second wave could erupt some months down the line when that immunity wears off.

the important message is that we have a window of opportunity now, to get test-and-trace protocols in place ahead of that putative second wave. If these are implemented coherently, we could potentially defer that wave beyond a time horizon where treatments or a vaccine become available, in a way that we weren’t able to before the first one.

We’ve been comparing the UK and Germany to try to explain the comparatively low fatality rates in Germany. The answers are sometimes counterintuitive. For example, it looks as if the low German fatality rate is not due to their superior testing capacity, but rather to the fact that the average German is less likely to get infected and die than the average Brit. Why? There are various possible explanations, but one that looks increasingly likely is that Germany has more immunological “dark matter” – people who are impervious to infection, perhaps because they are geographically isolated or have some kind of natural resistance

Any other advantages?Yes. With conventional SEIR models, interventions and surveillance are something you add to the model – tweaks or perturbations – so that you can see their effect on morbidity and mortality. But with a generative model these things are built into the model itself, along with everything else that matters.

Are generative models the future of disease modelling?That’s a question for the epidemiologists – they’re the experts. But I would be very surprised if at least some part of the epidemiological community didn’t become more committed to this approach in future, given the impact that Feynman’s ideas have had in so many other disciplines.

No test is perfectly accurate; all generate false positives and false negatives. How many varies by the test — the new Abbott Labs test, for example, has a false negative rate of about 3 percent and a false positive rate of about 1.5 percent.

We’d also require public understanding that test results are a risk-assessment tool rather than a definitive answer. And shifting the public’s thinking might be harder than shifting Trump.

Doing that would also require fundamentally changing our thinking.

For mass testing to work, people will need to understand that even an event where all attendees just tested negative isn’t necessarily covid-free, because some false negatives might have slipped through

Giving hundreds of millions of citizens this crash course in elementary statistics would be very difficult. Teaching people how to think about a positive result would be even harder — especially if mass testing does its job of reducing caseloads. Because as case numbers fall, false positives will become a bigger and bigger problem.

Say we’re testing 200 people, 10 of whom have covid-19. Given its rate of false negatives, the Abbott test would probably catch all 10. But with false positives, it could also tell one or two people who don’t have covid-19 that they’re infected. That’s not ideal — as good citizens, they’d have to go home and quarantine. But a more sensitive follow-up test could substantially mitigate this problem, shortening such quarantines to a day or so. It would be worth it to get those 10 true positives out of circulation.

Doing this, we might eventually reduce the share of the population that’s infected to, say, 0.5 percent from 5 percent. Unfortunately, the false positive rate won’t budge, so now for every one true positive uncovered, roughly three false positives would still be generated.

That’s inherently costly: Every false positive means skipping your flight, rehearsal or birthday party. But it would be catastrophic if people didn’t understand that a positive covid-19 test is a guideline, not a guarantee

People who think that they’ve had covid-19, when they haven’t, are apt to go out and engage in risky behavior, maybe a lot of it. And if mass testing ever becomes common, there could be a lot of those people.

So mass testing isn’t just a matter of getting a test that is cheap enough and plentiful enough; the administration and the public must be educated to use this bounty wisely. That’s a hard messaging problem. Given the alternative, though, it’s the kind of problem we’d really like to have.

An outbreak isn’t a double pendulum; it’s much more convoluted. Myriad chains of events, operating in overlapping networks, conspire to chart its course.

It’s the double pendulum, and as a physical object, it’s very simple: A pendulum (a string and a weight) is attached to the bottom of another. Its movement is explained by the laws of motion written by Isaac Newton hundreds of years ago.

But slight changes in the initial condition of the pendulum — say it starts its swing from a little higher up, or if the weight of the pendulum balls is a little heavier, or one of the pendulum arms is a bit longer than the other — lead to wildly different outcomes that are very hard to predict.

The double pendulum is chaotic because the motion of the first pendulum influences the motion of the second, which then influences the entire apparatus. There isn’t a simple scale or ratio to describe how the inputs relate to the outputs. A one-gram change to the weight of a pendulum ball can result in a very different swing pattern than a two-gram change.

It teaches us to understand the mechanics of a system — the science of how it works — without being able to precisely predict its future. It helps us visualize how something that seems like it should be linear and predictable just isn’t.

That’s why, when pressed, epidemiologists have to say they don’t know what’s going to happen.

Climate scientists clearly tell us adding CO2 to the air will increase global temperatures. Yet they argue about when the worst effects of climate change will be felt and how bad it will be

Still, they know the mechanics of outbreaks. The chaos “doesn’t necessarily mean we know nothing,” Kissler says. They understand the conditions that make an outbreak worse and the conditions that make it better.

There is a tough tension of the current moment that we all need to work through: The future is clouded in chaos, but we know the mechanics of this system

Here are the mechanics. Scientists know that if we let up on social distancing, without an alternative plan in place, the virus can infect more people. They know this virus is likely to persist for at least a few years without a vaccine. They know it’s very contagious. That it’s very deadly. They also know that its pandemic potential is hardly spent, and that most of the population of the United States and the world is still vulnerable to it.

Will residents keep up with mask-wearing and social distancing, even when their leaders relax regulations? Plus, there are scientific questions about the virus still not understood: Will it diminish transmission in a seasonal pattern? Do children contribute greatly to its spread? How long does immunity last after an infection? Why do some people breathe out more of the virus than others? The answers to these questions will influence the future, and we do not know the answers.

Scientists are still unraveling what makes the difference between a sprawling outbreak in one city and a more manageable one in another. Some of it is the result of policy, some is the result of demographics, some is about structural inequality and racism, and some comes down to individual behavior. Some of it is just luck. That’s chaos for you.

“I don’t see uncertainty as a lack of knowledge,” says Philipp Lorenz-Spreen, a physicist who studies the chaos of a different sort of viral dynamics. “I think it’s a fundamental part of how our world works. It’s not our fault we do not know where this all will go.”

Newton clearly told us what happens when an object drops from the sky. But follow his laws, and find that the path of a double pendulum is very, very difficult to predict.

There’s a simple mechanism that is helping me understand the many possible futures we face with the Covid-19 pandemic.

Epidemiologists are clearly telling us what happens when you bring masses of people together during a pandemic. But they can’t tell us the exact shape this outbreak will take.

The new study provides “unassailable” evidence that the central nervous system can control the peripheral immune system, Tracey says. “It’s an incredibly important contribution to the fields of neuroscience and immunology.”

Just as researchers have traced sensory and motor processing to specific brain regions, Tracey suspects that a similar neurological “map” of immunologic information also exists. This new study, he says, is the first direct evidence of that map. “It’s going to be really exciting to see what comes next,” he adds.

a reminder to stay informed and vigilant against groupthink.

A common refrain in battles about Covid-19 and vaccination, politics and conspiracy theories, parenting, drugs, food, stock trading and media, it signals not just a rejection of authority but often trust in another kind.

“Do your own research” is an idea central to Joe Rogan’s interview podcast, the most listened to program on Spotify, where external claims of expertise are synonymous with admissions of malice. In its current usage, DYOR is often an appeal to join in, rendered in the language of opting out.

“There’s this idea that the goal of science is consensus,” Professor Carrion said. “The model they brought to it was that we didn’t need consensus.” She noted that the women she surveyed often used singular rather than plural pronouns. “It was ‘she needs to do her own research,” Professor Carrion said, rather than we need to do ours. Unlike some critical health movements in the past, this was an individualist endeavor.

One of the enticing aspects of cryptocurrencies, which pose an alternative to traditional financial institutions, is that expertise is available to anyone who wants to claim it.

In crypto, the uses of DYOR are various and contradictory, earnest and ironic sometimes within the same discussion. Breathless investment pitches for new coins are punctuated with “NFA/DYOR” (not financial advice), or admonitions not to invest more than you can afford to lose, which many people are obviously ignoring; stories about getting rich are prefaced with DYOR; requests for advice about which coins to hold are answered with DYOR. It is the siren song of crypto investing.

In that way — the momentum of a group — crypto investing isn’t altogether distinct from how people have invested in the stock market for decades. Though here it is tinged with a rebellious, anti-authoritarian streak: We’re outsiders, in this together; we’re doing something sort of ridiculous, but also sort of cool.

“Now it seems like DYOR can only do so much,” the user wrote. Eventually, the user said, you end up relying on “trust.”

a self-driving car could have avoided choosing between two bad outcomes by making a decision earlier on — the speaker pointed out that, when entering the alley, the car could have determined that the space was narrow and slowed to a speed that would keep everyone safe.

Auditors have to inspect the algorithm without accessing sensitive user data.

Other considerations come into play as well, such as balancing the removal of misinformation with the protection of free speech.

To meet these challenges, Cen and Shah developed an auditing procedure that does not need more than black-box access to the social media algorithm (which respects trade secrets), does not remove content (which avoids issues of censorship), and does not require access to users (which preserves users’ privacy).

which is known to help reduce the spread of misinformation

In labor markets, for example, workers learn their preferences about what kinds of jobs they want, and employers learn their preferences about the qualifications they seek from workers.

But learning can be disrupted by competition

it is indeed possible to get to a stable outcome (workers aren’t incentivized to leave the matching market), with low regret (workers are happy with their long-term outcomes), fairness (happiness is evenly distributed), and high social welfare.

For instance, when Covid-19 cases surged in the pandemic, many cities had to decide what restrictions to adopt, such as mask mandates, business closures, or stay-home orders. They had to act fast and balance public health with community and business needs, public spending, and a host of other considerations.

But of course, no county exists in a vacuum.

These complex interactions matter,

“Accountability, legitimacy, trust — these principles play crucial roles in society and, ultimately, will determine which systems endure with time.” 

In November 2020, the AI group DeepMind announced it had developed a program called AlphaFold that could rapidly predict this information using an algorithm. Since then, it has been crunching through the genetic codes of every organism that has had its genome sequenced, and predicting the structures of the hundreds of millions of proteins they collectively contain.

Last year, DeepMind published the protein structures for 20 species – including nearly all 20,000 proteins expressed by humans – on an open database. Now it has finished the job, and released predicted structures for more than 200m proteins.

“Essentially, you can think of it as covering the entire protein universe. It includes predictive structures for plants, bacteria, animals, and many other organisms, opening up huge new opportunities for AlphaFold to have an impact on important issues, such as sustainability, food insecurity, and neglected diseases,”

In May, researchers led by Prof Matthew Higgins at the University of Oxford announced they had used AlphaFold’s models to help determine the structure of a key malaria parasite protein, and work out where antibodies that could block transmission of the parasite were likely to bind.

“Previously, we’d been using a technique called protein crystallography to work out what this molecule looks like, but because it’s quite dynamic and moves around, we just couldn’t get to grips with it,” Higgins said. “When we took the AlphaFold models and combined them with this experimental evidence, suddenly it all made sense. This insight will now be used to design improved vaccines which induce the most potent transmission-blocking antibodies.”

AlphaFold’s models are also being used by scientists at the University of Portsmouth’s Centre for Enzyme Innovation, to identify enzymes from the natural world that could be tweaked to digest and recycle plastics. “It took us quite a long time to go through this massive database of structures, but opened this whole array of new three-dimensional shapes we’d never seen before that could actually break down plastics,” said Prof John McGeehan, who is leading the work. “There’s a complete paradigm shift. We can really accelerate where we go from here

“AlphaFold protein structure predictions are already being used in a myriad of ways. I expect that this latest update will trigger an avalanche of new and exciting discoveries in the months and years ahead, and this is all thanks to the fact that the data are available openly for all to use.”

start with epistemic bubbles

That omission might be purposeful

But that omission can also be entirely inadvertent. Even if we’re not actively trying to avoid disagreement, our Facebook friends tend to share our views and interests

An ‘echo chamber’ is a social structure from which other relevant voices have been actively discredited. Where an epistemic bubble merely omits contrary views, an echo chamber brings its members to actively distrust outsiders.

an echo chamber is something like a cult. A cult isolates its members by actively alienating them from any outside sources. Those outside are actively labelled as malignant and untrustworthy.

In epistemic bubbles, other voices are not heard; in echo chambers, other voices are actively undermined.

The way to break an echo chamber is not to wave “the facts” in the faces of its members. It is to attack the echo chamber at its root and repair that broken trust.

Looking to others for corroboration is a basic method for checking whether one has reasoned well or badly

They have been in the limelight lately, most famously in Eli Pariser’s The Filter Bubble (2011) and Cass Sunstein’s #Republic: Divided Democracy in the Age of Social Media (2017).

The general gist: we get much of our news from Facebook feeds and similar sorts of social media. Our Facebook feed consists mostly of our friends and colleagues, the majority of whom share our own political and cultural views

various algorithms behind the scenes, such as those inside Google search, invisibly personalise our searches, making it more likely that we’ll see only what we want to see. These processes all impose filters on information.

Such filters aren’t necessarily bad. The world is overstuffed with information, and one can’t sort through it all by oneself: filters need to be outsourced.

That’s why we all depend on extended social networks to deliver us knowledge

any such informational network needs the right sort of broadness and variety to work

Each individual person in my network might be superbly reliable about her particular informational patch but, as an aggregate structure, my network lacks what Sanford Goldberg in his book Relying on Others (2010) calls ‘coverage-reliability’. It doesn’t deliver to me a sufficiently broad and representative coverage of all the relevant information.

Epistemic bubbles also threaten us with a second danger: excessive self-confidence.

An ‘epistemic bubble’ is an informational network from which relevant voices have been excluded by omission

Suppose that I believe that the Paleo diet is the greatest diet of all time. I assemble a Facebook group called ‘Great Health Facts!’ and fill it only with people who already believe that Paleo is the best diet. The fact that everybody in that group agrees with me about Paleo shouldn’t increase my confidence level one bit. They’re not mere copies – they actually might have reached their conclusions independently – but their agreement can be entirely explained by my method of selection.

Luckily, though, epistemic bubbles are easily shattered. We can pop an epistemic bubble simply by exposing its members to the information and arguments that they’ve missed.

echo chambers are a far more pernicious and robust phenomenon.

amieson and Cappella’s book is the first empirical study into how echo chambers function

echo chambers work by systematically alienating their members from all outside epistemic sources.

Their research centres on Rush Limbaugh, a wildly successful conservative firebrand in the United States, along with Fox News and related media

His constant attacks on the ‘mainstream media’ are attempts to discredit all other sources of knowledge. He systematically undermines the integrity of anybody who expresses any kind of contrary view.

outsiders are not simply mistaken – they are malicious, manipulative and actively working to destroy Limbaugh and his followers. The resulting worldview is one of deeply opposed force, an all-or-nothing war between good and evil

The result is a rather striking parallel to the techniques of emotional isolation typically practised in cult indoctrination

cult indoctrination involves new cult members being brought to distrust all non-cult members. This provides a social buffer against any attempts to extract the indoctrinated person from the cult.

The echo chamber doesn’t need any bad connectivity to function. Limbaugh’s followers have full access to outside sources of information

As Elijah Millgram argues in The Great Endarkenment (2015), modern knowledge depends on trusting long chains of experts. And no single person is in the position to check up on the reliability of every member of that chain

Their worldview can survive exposure to those outside voices because their belief system has prepared them for such intellectual onslaught.

exposure to contrary views could actually reinforce their views. Limbaugh might offer his followers a conspiracy theory: anybody who criticises him is doing it at the behest of a secret cabal of evil elites, which has already seized control of the mainstream media.

Perversely, exposure to outsiders with contrary views can thus increase echo-chamber members’ confidence in their insider sources, and hence their attachment to their worldview.

‘evidential pre-emption’. What’s happening is a kind of intellectual judo, in which the power and enthusiasm of contrary voices are turned against those contrary voices through a carefully rigged internal structure of belief.

One might be tempted to think that the solution is just more intellectual autonomy. Echo chambers arise because we trust others too much, so the solution is to start thinking for ourselves.

that kind of radical intellectual autonomy is a pipe dream. If the philosophical study of knowledge has taught us anything in the past half-century, it is that we are irredeemably dependent on each other in almost every domain of knowledge

Limbaugh’s followers regularly read – but do not accept – mainstream and liberal news sources. They are isolated, not by selective exposure, but by changes in who they accept as authorities, experts and trusted sources.

we depend on a vastly complicated social structure of trust. We must trust each other, but, as the philosopher Annette Baier says, that trust makes us vulnerable. Echo chambers operate as a kind of social parasite on that vulnerability, taking advantage of our epistemic condition and social dependency.

I am quite confident that there are plenty of echo chambers on the political Left. More importantly, nothing about echo chambers restricts them to the arena of politics

The world of anti-vaccination is clearly an echo chamber, and it is one that crosses political lines. I’ve also encountered echo chambers on topics as broad as diet (Paleo!), exercise technique (CrossFit!), breastfeeding, some academic intellectual traditions, and many, many more

Here’s a basic check: does a community’s belief system actively undermine the trustworthiness of any outsiders who don’t subscribe to its central dogmas? Then it’s probably an echo chamber.

much of the recent analysis has lumped epistemic bubbles together with echo chambers into a single, unified phenomenon. But it is absolutely crucial to distinguish between the two.

Epistemic bubbles are rather ramshackle; they go up easily, and they collapse easily

Echo chambers are far more pernicious and far more robust. They can start to seem almost like living things. Their belief systems provide structural integrity, resilience and active responses to outside attacks

the two phenomena can also exist independently. And of the events we’re most worried about, it’s the echo-chamber effects that are really causing most of the trouble.

new data does, in fact, seem to show that people on Facebook actually do see posts from the other side, or that people often visit websites with opposite political affiliation.

their basis for evaluation – their background beliefs about whom to trust – are radically different. They are not irrational, but systematically misinformed about where to place their trust.

Many people have claimed that we have entered an era of ‘post-truth’.

Not only do some political figures seem to speak with a blatant disregard for the facts, but their supporters seem utterly unswayed by evidence. It seems, to some, that truth no longer matters.

This is an explanation in terms of total irrationality. To accept it, you must believe that a great number of people have lost all interest in evidence or investigation, and have fallen away from the ways of reason.

echo chambers offers a less damning and far more modest explanation. The apparent ‘post-truth’ attitude can be explained as the result of the manipulations of trust wrought by echo chambers.

We don’t have to attribute a complete disinterest in facts, evidence or reason to explain the post-truth attitude. We simply have to attribute to certain communities a vastly divergent set of trusted authorities.

An echo chamber doesn’t destroy their members’ interest in the truth; it merely manipulates whom they trust and changes whom they accept as trustworthy sources and institutions.

in many ways, echo-chamber members are following reasonable and rational procedures of enquiry. They’re engaging in critical reasoning. They’re questioning, they’re evaluating sources for themselves, they’re assessing different pathways to information. They are critically examining those who claim expertise and trustworthiness, using what they already know about the world

none of this weighs against the existence of echo chambers. We should not dismiss the threat of echo chambers based only on evidence about connectivity and exposure.

Notice how different what’s going on here is from, say, Orwellian doublespeak, a deliberately ambiguous, euphemism-filled language designed to hide the intent of the speaker.

echo chambers don’t trade in vague, ambiguous pseudo-speech. We should expect that echo chambers would deliver crisp, clear, unambiguous claims about who is trustworthy and who is not

clearly articulated conspiracy theories, and crisply worded accusations of an outside world rife with untrustworthiness and corruption.

Once an echo chamber starts to grip a person, its mechanisms will reinforce themselves.

In an epistemically healthy life, the variety of our informational sources will put an upper limit to how much we’re willing to trust any single person. Everybody’s fallible; a healthy informational network tends to discover people’s mistakes and point them out. This puts an upper ceiling on how much you can trust even your most beloved leader

nside an echo chamber, that upper ceiling disappears.

Being caught in an echo chamber is not always the result of laziness or bad faith. Imagine, for instance, that somebody has been raised and educated entirely inside an echo chamber

when the child finally comes into contact with the larger world – say, as a teenager – the echo chamber’s worldview is firmly in place. That teenager will distrust all sources outside her echo chamber, and she will have gotten there by following normal procedures for trust and learning.

It certainly seems like our teenager is behaving reasonably. She could be going about her intellectual life in perfectly good faith. She might be intellectually voracious, seeking out new sources, investigating them, and evaluating them using what she already knows.

The worry is that she’s intellectually trapped. Her earnest attempts at intellectual investigation are led astray by her upbringing and the social structure in which she is embedded.

Echo chambers might function like addiction, under certain accounts. It might be irrational to become addicted, but all it takes is a momentary lapse – once you’re addicted, your internal landscape is sufficiently rearranged such that it’s rational to continue with your addiction

Similarly, all it takes to enter an echo chamber is a momentary lapse of intellectual vigilance. Once you’re in, the echo chamber’s belief systems function as a trap, making future acts of intellectual vigilance only reinforce the echo chamber’s worldview.

There is at least one possible escape route, however. Notice that the logic of the echo chamber depends on the order in which we encounter the evidence. An echo chamber can bring our teenager to discredit outside beliefs precisely because she encountered the echo chamber’s claims first. Imagine a counterpart to our teenager who was raised outside of the echo chamber and exposed to a wide range of beliefs. Our free-range counterpart would, when she encounters that same echo chamber, likely see its many flaws

Those caught in an echo chamber are giving far too much weight to the evidence they encounter first, just because it’s first. Rationally, they should reconsider their beliefs without that arbitrary preference. But how does one enforce such informational a-historicity?

The escape route is a modified version of René Descartes’s infamous method.

Meditations on First Philosophy (1641). He had come to realise that many of the beliefs he had acquired in his early life were false. But early beliefs lead to all sorts of other beliefs, and any early falsehoods he’d accepted had surely infected the rest of his belief system.

The only solution, thought Descartes, was to throw all his beliefs away and start over again from scratch.

He could start over, trusting nothing and no one except those things that he could be entirely certain of, and stamping out those sneaky falsehoods once and for all. Let’s call this the Cartesian epistemic reboot.

Notice how close Descartes’s problem is to our hapless teenager’s, and how useful the solution might be. Our teenager, like Descartes, has problematic beliefs acquired in early childhood. These beliefs have infected outwards, infesting that teenager’s whole belief system. Our teenager, too, needs to throw everything away, and start over again.

Let’s call the modernised version of Descartes’s methodology the social-epistemic reboot.

when she starts from scratch, we won’t demand that she trust only what she’s absolutely certain of, nor will we demand that she go it alone

For the social reboot, she can proceed, after throwing everything away, in an utterly mundane way – trusting her senses, trusting others. But she must begin afresh socially – she must reconsider all possible sources of information with a presumptively equanimous eye. She must take the posture of a cognitive newborn, open and equally trusting to all outside sources

we’re not asking people to change their basic methods for learning about the world. They are permitted to trust, and trust freely. But after the social reboot, that trust will not be narrowly confined and deeply conditioned by the particular people they happened to be raised by.

Such a profound deep-cleanse of one’s whole belief system seems to be what’s actually required to escape. Look at the many stories of people leaving cults and echo chambers

Take, for example, the story of Derek Black in Florida – raised by a neo-Nazi father, and groomed from childhood to be a neo-Nazi leader. Black left the movement by, basically, performing a social reboot. He completely abandoned everything he’d believed in, and spent years building a new belief system from scratch. He immersed himself broadly and open-mindedly in everything he’d missed – pop culture, Arabic literature, the mainstream media, rap – all with an overall attitude of generosity and trust.

It was the project of years and a major act of self-reconstruction, but those extraordinary lengths might just be what’s actually required to undo the effects of an echo-chambered upbringing.

we need to attack the root, the systems of discredit themselves, and restore trust in some outside voices.

Stories of actual escapes from echo chambers often turn on particular encounters – moments when the echo-chambered individual starts to trust somebody on the outside.

Black’s is case in point. By high school, he was already something of a star on neo-Nazi media, with his own radio talk-show. He went on to college, openly neo-Nazi, and was shunned by almost every other student in his community college. But then Matthew Stevenson, a Jewish fellow undergraduate, started inviting Black to Stevenson’s Shabbat dinners. In Black’s telling, Stevenson was unfailingly kind, open and generous, and slowly earned Black’s trust. This was the seed, says Black, that led to a massive intellectual upheaval – a slow-dawning realisation of the depths to which he had been misled

Similarly, accounts of people leaving echo-chambered homophobia rarely involve them encountering some institutionally reported fact. Rather, they tend to revolve around personal encounters – a child, a family member, a close friend coming out.

hese encounters matter because a personal connection comes with a substantial store of trust.

We don’t simply trust people as educated experts in a field – we rely on their goodwill. And this is why trust, rather than mere reliability, is the key concept

goodwill is a general feature of a person’s character. If I demonstrate goodwill in action, then you have some reason to think that I also have goodwill in matters of thought and knowledge.

f one can demonstrate goodwill to an echo-chambered member – as Stevenson did with Black – then perhaps one can start to pierce that echo chamber.

the path I’m describing is a winding, narrow and fragile one. There is no guarantee that such trust can be established, and no clear path to its being established systematically.

what we’ve found here isn’t an escape route at all. It depends on the intervention of another. This path is not even one an echo-chamber member can trigger on her own; it is only a whisper-thin hope for rescue from the outside.

the need for regulation to maintain the reliability of essential aspects of the economy like electricity supply and the monetary system.

Which is why I’m calling the modern American right antisocial — because its members reject any policy that relies on social cooperation, and they want us to return instead to Hobbes’s dystopian state of nature

why Republicans have become fanatics about cryptocurrency, to the extent that one Senate candidate has defined his position as being “pro-God, pro-family, pro-Bitcoin.” The answer, I’d argue, is that Bitcoin plays into a fantasy of self-sufficient individualism, of protecting your family with your personal AR-15, treating your Covid with an anti-parasite drug or urine and managing your financial affairs with privately created money, untainted by institutions like governments or banks.

In the end, none of this will work. Government exists for a reason. But the right’s constant attacks on essential government functions will take a toll, making all of our lives nastier, more brutish and shorter.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

“Science cannot always overcome fear,”

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

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

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

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

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

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

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

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

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

In the summer of 2020, “public-health experts” decided that racism is a public-health crisis comparable to the coronavirus pandemic. It was therefore, they claimed, within their purview to express public support for the Black Lives Matter protests following the murder of George Floyd and to argue that the benefits of such protests outweighed the increased risk of spreading the disease. Those supposed experts actually knew nothing about the likely effects of the protests. They made no concrete predictions about whether they would in any way ameliorate racism in America, just as Nature can make no concrete predictions about whether its political endorsements will actually help a preferred candidate without jeopardizing its other important goals. The political action was expressive, not evidence-based...

as is often the case, a debate which appears to be about the neutrality of institutions is not really about neutrality at all... Rather, it is about whether there is any room left for soberly weighing our goals and values and thinking in a measured way about the consequences of our actions rather than simply reacting to situations in an impulsive and expressive manner, broadcasting our views to the world so that people know where we stand.

Our goals and values might not be “neutral” at all, but they might still be best served by procedures, institutions, and even individuals that follow neutral principles.