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How AGI became the most consequential conspiracy theory of our time (MIT Technology Review)

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technologyreview.com

Original article

Will Douglas Heaven

October 30, 2025

Are you feeling it?

I hear it’s close: two years, five years—maybe next year! And I hear it’s going to change everything: it will cure disease, save the planet, and usher in an age of abundance. It will solve our biggest problems in ways we cannot yet imagine. It will redefine what it means to be human. 

Wait—what if that’s all too good to be true? Because I also hear it will bring on the apocalypse and kill us all … 

Either way, and whatever your timeline, something big is about to happen. 

We could be talking about the Second Coming. Or the day when Heaven’s Gaters imagined they’d be picked up by a UFO and transformed into enlightened aliens. Or the moment when Donald Trump finally decides to deliver the storm that Q promised. But no. We’re of course talking about artificial general intelligence, or AGI—that hypothetical near-future technology that (I hear) will be able to do pretty much whatever a human brain can do.

This story is part of MIT Technology Review’s series “The New Conspiracy Age,” on how the present boom in conspiracy theories is reshaping science and technology.

For many, AGI is more than just a technology. In tech hubs like Silicon Valley, it’s talked about in mystical terms. Ilya Sutskever, cofounder and former chief scientist at OpenAI, is said to have led chants of “Feel the AGI!” at team meetings. And he feels it more than most: In 2024, he left OpenAI, whose stated mission is to ensure that AGI benefits all of humanity, to cofound Safe Superintelligence, a startup dedicated to figuring out how to avoid a so-called rogue AGI (or control it when it comes). Superintelligence is the hot new flavor—AGI but better!—introduced as talk of AGI becomes commonplace.

Sutskever also exemplifies the mixed-up motivations at play among many self-anointed AGI evangelists. He has spent his career building the foundations for a future technology that he now finds terrifying. “It’s going to be monumental, earth-shattering—there will be a before and an after,” he told me a few months before he quit OpenAI. When I asked him why he had redirected his efforts into reining that technology in, he said: “I’m doing it for my own self-interest. It’s obviously important that any superintelligence anyone builds does not go rogue. Obviously.”

He’s far from alone in his grandiose, even apocalyptic, thinking. 

Every age has its believers, people with an unshakeable faith that something huge is about to happen—a before and an after that they are privileged (or doomed) to live through.  

For us, that’s the promised advent of AGI. People are used to hearing that this or that is the next big thing, says Shannon Vallor, who studies the ethics of technology at the University of Edinburgh. “It used to be the computer age and then it was the internet age and now it’s the AI age,” she says. “It’s normal to have something presented to you and be told that this thing is the future. What’s different, of course, is that in contrast to computers and the internet, AGI doesn’t exist.”

And that’s why feeling the AGI is not the same as boosting the next big thing. There’s something weirder going on. Here’s what I think: AGI is a lot like a conspiracy theory, and it may be the most consequential one of our time.

I have been reporting on artificial intelligence for more than a decade, and I’ve watched the idea of AGI bubble up from the backwaters to become the dominant narrative shaping an entire industry. A onetime pipe dream now props up the profit lines of some of the world’s most valuable companies and thus, you could argue, the US stock market. It justifies dizzying down payments on the new power plants and data centers that we’re told are needed to make the dream come true. Fixated on this hypothetical technology, AI firms are selling us hard. 

Just listen to what the heads of some of those companies are telling us. AGI will be as smart as an entire “country of geniuses” (Dario Amodei, CEO of Anthropic); it will kick-start “an era of maximum human flourishing, where we travel to the stars and colonize the galaxy” (Demis Hassabis, CEO of Google DeepMind); it will “massively increase abundance and prosperity,” even encourage people to enjoy life more and have more children (Sam Altman, CEO of OpenAI). That’s some product.

Or not. Don’t forget the flip side, of course. When those people are not shilling for utopia, they’re saving us from hell. In 2023, Amodei, Hassabis, and Altman all put their names to a 22-word statement that read: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” Elon Musk says AI has a 20% chance of annihilating humans. 

“I’ve noticed recently that superintelligence, which I thought was a concept you definitely shouldn’t mention if you want to be taken seriously in public, is being thrown around by tech CEOs who are apparently planning to build it,” says Katja Grace, lead researcher at AI Impacts, an organization that surveys AI researchers about their field. “I think it’s easy to feel like this is fine. They also say it’s going to kill us, but they’re laughing while they say it.”

You have to admit it all sounds a bit tinfoil hat. If you’re building a conspiracy theory, you need a few things in the mix: a scheme that’s flexible enough to sustain belief even when things don’t work out as planned; the promise of a better future that can be realized only if believers uncover hidden truths; and a hope for salvation from the horrors of this world. 

AGI just about checks all those boxes. The more you poke at the idea, the more it starts to look like a conspiracy. It’s not, of course—not exactly. And I’m not drawing this parallel to dismiss the very real, often jaw-dropping results achieved by many people in this field, including (or especially) the AGI believers. 

But by zooming in on things that AGI has in common with genuine conspiracies, I think we can bring the whole concept into better focus and reveal it for what it is: a techno-utopian (or techno-dystopian—pick your pill) fever dream that got its hooks into some pretty deep-seated beliefs that have made it hard to shake.

This isn’t just a provocative thought experiment. It’s important to question what we’re told about AGI because buying into the idea isn’t harmless. Right now, AGI is the most important narrative in tech—and, to some extent, in the global economy. We can’t make sense of what’s going on in AI without understanding where the idea of AGI came from, why it is so compelling, and how it shapes the way we think about technology overall. 

I get it, I get it—calling AGI a conspiracy isn’t a perfect analogy. It will also piss a lot of people off. But come with me down this rabbit hole and let me show you the light. 

How Silicon Valley got AGI-pilled

It had a ring to it

A typical conspiracy theory usually starts out on the fringes. Maybe it’s just a couple of people posting on a message board, gathering “evidence.” Maybe it’s a few people out in the desert with binoculars waiting to spot some bright lights in the sky. But some conspiracy theories get lucky, if you will: They start to percolate more widely; they start to become a bit more acceptable; they start to influence people in power. Maybe it’s the UFOs (ahem, sorry, “unidentified aerial phenomena”) that are now formally and openly discussed in government hearings. Maybe it’s vaccine skepticism (yes, a much more dangerous example) that becomes official policy. And it’s impossible to ignore that artificial general intelligence has followed a pretty similar trajectory to its more overtly conspiratorial brethren. 

Let’s go back to 2007, when AI wasn’t sexy and it wasn’t cool. Companies like Amazon and Netflix (which was still sending out DVDs in the mail) were using machine-learning models, proto-organisms to today’s LLM behemoths, to recommend movies and books to customers. But that was more or less it.

Ben Goertzel had far bigger plans. About a decade earlier, the AI researcher had set up a dot-com startup called Webmind to train what he thought of as a kind of digital baby brain on the early internet. Childless, Webmind soon went bust.

But Goertzel was an influential figure in a fringe community of researchers who had dreamed for years of building humanlike artificial intelligence, an all-purpose computer program that could do many of the things people can do (and do them better). It was a vision that went far beyond the kind of tech that Netflix was experimenting with.

Goertzel wanted to put out a book promoting that vision, and he needed a name that would set it apart from the humdrum AI of the time. A former Webmind employee named Shane Legg suggested Artificial General Intelligence. It had a ring to it.

A few years later, Legg cofounded DeepMind with Demis Hassabis and Mustafa Suleyman. But to most serious researchers at the time, the claim that AI would one day mimic human abilities was a bit of a joke. AGI used to be a dirty word, Sutskever told me. Andrew Ng, founder of Google Brain and former chief scientist at the Chinese tech giant Baidu, told me he thought it was loony.

So what happened? I caught up with Goertzel last month to ask how a fringe idea went from crackpot to commonplace. “I’m sort of a complex chaotic systems guy, so I have a low estimate that I actually know what the nonlinear dynamic in the memosphere really was,” he said. (Translation: It’s complicated.) 

Goertzel reckons a few things took the idea mainstream. The first is the Conference on Artificial General Intelligence, an annual meeting of researchers that he helped set up in 2008, the year after his book was published. The conference was often coordinated with top mainstream academic meetups, such as the Association for the Advancement of Artificial Intelligence conference and the International Joint Conference on Artificial Intelligence. “If I just published a book with that name AGI, it possibly would have just come and gone,” says Goertzel. “But the conference was circling through every year, with more and more students coming.”

Next is Legg, who took the term with him to DeepMind. “I think they were the first mainstream corporate entity to talk about AGI,” says Goertzel. “It wasn’t the main thing they were harping on, but Shane and Demis would talk about it now and then. That was certainly a source of legitimation.”

When I first talked to Legg about AGI five years ago, he said: “Talking about AGI in the early 2000s put you on the lunatic fringe … Even when we started DeepMind in 2010, we got an astonishing amount of eye-rolling at conferences.” But by 2020 the wind had changed. “Some people are uncomfortable with it, but it’s coming in from the cold,” he told me.

The third thing Goertzel points to is the overlap between early AGI evangelists and Big Tech power brokers. In the years between shutting down Webmind and publishing that AGI book, Goertzel did some work with Peter Thiel at Thiel’s hedge fund Clarium Capital. “We talked a bunch,” says Goertzel. He recalls spending a day with Thiel at the Four Seasons in San Francisco. “I was trying to drum AGI into his head,” says Goertzel. “But then he was also hearing from Eliezer how AGI is going to kill everybody.”

Enter the doomers

That’s Eliezer Yudkowsky, another influential figure who has done at least as much as Goertzel, if not more, to push the idea of AGI. But unlike Goertzel, Yudkowsky thinks there’s a very high chance—99.5% is one number he throws out—that the development of AGI will be a catastrophe.  

In 2000, Yudkowsky cofounded a nonprofit research outfit called the Singularity Institute for Artificial Intelligence (later renamed the Machine Intelligence Research Institute), which pretty quickly dedicated itself to preventing doomer scenarios. Thiel was an early benefactor. 

At first, Yudkowsky’s ideas didn’t get much pickup. Recall that back then the idea of an all-powerful AI—let alone a dangerous one—was pure sci-fi. But in 2014, Nick Bostrom, a philosopher at the University of Oxford, published a book called Superintelligence.

“It put the AGI thing out there,” says Goertzel. “I mean, Bill Gates, Elon Musk—lots of tech-industry AI people—read that book, and whether or not they agreed with his doomer perspective, Nick took Eliezer’s concepts and wrapped them up in a very acceptable way.”  

“All of these things gave AGI a stamp of acceptability,” Goertzel adds. “Rather than it being pure crackpot stuff from mavericks howling out in the wilderness.”

Yudkowsky has been banging the same drum for 25 years; many engineers at today’s top AI companies grew up reading and discussing his views online, especially on LessWrong, a popular hub for the tech industry’s fervent community of rationalists and effective altruists.

Today, those views are more popular than ever, capturing the imagination of a younger generation of doomers like David Krueger, a researcher at the University of Montreal who previously served as research director at the UK’s AI Security Institute. “I think we are definitely on track to build superhuman AI systems that will kill everybody,” Krueger tells me. “And I think that’s horrible and we should stop immediately.”

Yudkowsky gets profiled by the likes of the New York Times, which bills him as “Silicon Valley’s version of a doomsday preacher.” His new book, If Anyone Builds It, Everyone Dies, written with Nate Soares, president of the Machine Intelligence Research Institute, lays out wild claims, with little evidence, that unless we pull the plug on development, near-future AGI will lead to global Armageddon. The pair’s position is extreme: They argue that an international ban should be enforced at all costs, up to and including the point of nuclear retaliation. After all, “datacenters can kill more people than nuclear weapons,” Yudkowsky and Soares write.

This stuff is no longer niche. The book is an NYT bestseller and comes with endorsements from national security experts such as Suzanne Spaulding, a former US Department of Homeland Security official, and Fiona Hill, former senior director of the White House National Security Council, who now advises the UK government; celebrity scientists such as Max Tegmark and George Church; and other household names, including Stephen Fry, Mark Ruffalo, and Grimes. Yudkowsky now has a megaphone. 

Still, it is those early quiet words in certain ears that may prove most consequential. Yudkowsky is credited with introducing Thiel to DeepMind’s founders, after which Thiel became one of the first big investors in the company. Having merged with Google, it is now the in-house AI lab for the tech colossus Alphabet. 

Alongside Musk, Thiel was also instrumental in setting up OpenAI in 2015, sinking millions into a startup founded on the singular ambition to build AGI—and make it safe. In 2023, OpenAI CEO Sam Altman posted on X: “eliezer has IMO done more to accelerate AGI than anyone else. certainly he got many of us interested in AGI.” Yudkowsky might one day deserve the Nobel Peace Prize for that, Altman added. But by this point, Thiel had apparently grown wary of the “AI safety people” and the power they were gaining. “You don’t understand how Eliezer has programmed half the people in your company to believe in that stuff,” he is reported to have told Altman at a dinner party in late 2023. “You need to take this more seriously.” Altman “tried not to roll his eyes,” according to Wall Street Journal reporter Keach Hagey.

OpenAI is now the most valuable private company in the world, worth half a trillion dollars. 

And the transformation is complete: Like all the most powerful conspiracies, AGI has slipped into the mainstream and taken hold.    

The great AGI conspiracy 

The term “AGI” may have been popularized less than 20 years ago, but the mythmaking behind it has been there since the start of the computer age—a cosmic microwave background of chutzpah and marketing. 

Alan Turing asked if machines could think only five years after the first electronic computer, ENIAC, was built in 1945. And here’s Turing a little later, in a 1951 radio broadcast: “It seems probable that once the machine thinking method had started, it would not take long to outstrip our feeble powers. There would be no question of the machines dying, and they would be able to converse with each other to sharpen their wits. At some stage therefore we should have to expect the machines to take control.”

Then, in 1955, the computer scientist John McCarthy and his colleagues applied for US government funding to create what they fatefully chose to call “artificial intelligence”—a canny spin, given that computers at the time were the size of a room and as dumb as a thermostat. Even so, as McCarthy wrote in that funding application: “An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”

It’s this myth that’s the root of the AGI conspiracy. A smarter-than-human machine that can do it all is not a technology. It’s a dream, unmoored from reality. Once you see that, other parallels with conspiracy thinking start to leap out.

It’s impossible to debunk a shape-shifting idea like AGI. 

Talking about AGI can sometimes feel like arguing with an enthusiastic Redditor about what drugs (or particles in the sky) are controlling your mind. Each point has a counterpoint that tries to chip away at your own sense of what’s true. Ultimately, it’s a clash of worldviews, not an exchange of evidence-based reason. AGI is like that, too—it’s slippery. 

Part of the issue is that despite all the money, all the talk, nobody knows how to build it. More than that: Most people don’t even agree on what AGI really is—which helps explain how people can get away with telling us it can both save the world and end it. At the core of most definitions you’ll find the idea of a machine that can match humans on a wide range of cognitive tasks. (And remember, superintelligence is AGI’s shiny new upgrade: a machine that can outmatch us.) But even that’s easy to pull apart: What humans are we talking about? What kind of cognitive task? And how wide a range?

“There’s no real definition of it,” says Christopher Symons, chief artificial intelligence scientist at the AI health-care startup Lirio and former head of the computer science and math division at Oak Ridge National Laboratory. “If you say ‘human-level intelligence,’ that could be an infinite number of things—everybody’s level of intelligence is slightly different.” 

And so, says Symons, we’re in this weird race to build … what, exactly? “What are you trying to get it to do?”

In 2023, a team of researchers at Google DeepMind, including Legg, had a go at categorizing various definitions that people had proposed for AGI. Some said that a machine had to be able to learn; some said that it had to be able to make money; some said that it had to have a body and move about in the world (and maybe make coffee).  

Legg told me that when he’d suggested the term to Goertzel for the title of his book, the hand-waviness had been kind of the point. “I didn’t have an especially clear definition. I didn’t really feel it was necessary,” he said at the time. “I was actually thinking of it more as a field of study, rather than an artifact.”

So, I guess we’ll know it when we see it? The problem is that some people think they’ve seen it already.

In 2023, a team of Microsoft researchers put out a paper in which they described their experiences playing around with a prerelease version of OpenAI’s large language model GPT-4. They called it “Sparks of Artificial General Intelligence”—and it polarized the industry. 

It was a moment when a lot of researchers were blown away and trying to come to terms with what they were seeing. “Shit was working better than they had expected it to,” says Goertzel. “The concept of AGI genuinely started to seem more plausible.”

And yet for all of LLMs’ remarkable wordplay, Goertzel doesn’t think that they do in fact contain sparks of AGI. “It’s a little surprising to me that some people with a deep technical understanding of how these tools work under the hood still think that they could become human-level AGI,” he says. “On the other hand, you can’t prove it’s not true.”

And there it is: You can’t prove it’s not true. “The idea that AGI is coming and that it’s right around the corner and that it’s inevitable has licensed a great many departures from reality,” says the University of Edinburgh’s Vallor. “But we really don’t have any evidence for it.”

Conspiracy thinking looms again. Predictions about when AGI will arrive are made with the precision of numerologists counting down to the end of days. With no real stakes in the game, deadlines come and go with a shrug. Excuses are made and timelines are adjusted yet again.

We saw this when OpenAI released the much-hyped GPT-5 this summer. AI stans were disappointed that the new version of the company’s flagship technology wasn’t the step change they expected. But instead of seeing that as evidence that AGI wasn’t attainable—or attainable with an LLM, at least—believers pushed out their predictions for how soon AGI would come. It was coming—just, you know, next time.

Maybe they’re right. Or maybe people will pick whatever evidence they can to defend an idea and overlook evidence that counts against it. Jeremy Cohen, who studies conspiracy thinking in technology circles at McMaster University in Canada, calls this imperfect evidence gathering—a hallmark of conspiracy thinking.

Cohen started his research career in the Arizona desert, studying a community called People Unlimited that believed its members were immortal. The conviction was impervious to contrary evidence. When its members died of natural causes (including two of its founders), the thinking was that they must have deserved it. “The general consensus was that every death was a suicide,” says Cohen. “If you are immortal and you get cancer and you die—well, you must have done something wrong.”

Cohen has since been focused on transhumanism (the idea that technology can help humans push past their natural limitations) and AGI. “I am seeing a lot of parallels. There are forms of magical thinking that I think are a part of the popular imagination around AGI,” he says. “It connects really well to the kinds of religious imaginaries that you see in conspiracy thinking today.”

The believers are in on the AGI secret.  

Maybe some of you think I’m an idiot: You don’t get it at all lol. But that’s kind of my point. There are insiders and outsiders. When I talk to researchers or engineers who are happy to drop AGI into the conversation as a given, it’s like they know something I don’t. But nobody’s ever been able to tell me what that something is. 

The truth is out there, if you know where to look. Conspiracy theories are primarily concerned about revealing a hidden truth, Cohen tells me: “It’s a really fundamental part of conspiracy thinking, and that’s absolutely something that you see in the way people talk about AGI,” he says. 

Last year, a 23-year-old former OpenAI staffer turned investor, Leopold Aschenbrenner, published a much-dissected 165-page manifesto titled “Situational Awareness.” You don’t need to read it to get the idea: You either see the truth of what’s coming or you don’t. And you don’t need cold, hard facts, either—it’s enough to feel it. Those who don’t just haven’t seen the light.  

This idea stalked the periphery of my conversation with Goertzel, too. When I pushed him on why people are skeptical of AGI, for instance, he said: “Before every major technical achievement, from human flight to electrical power, loads of wise pundits would tell you why it was never going to happen. The fact is, most people only believe what they see in front of their faces.” 

That makes AGI sound like an article of faith. I put that to Krueger, who believes AGI’s arrival is maybe five years out. He scoffed: “I think that’s completely backwards.” For him, the article of faith is the idea that it won’t happen—it’s the skeptics who continue to deny the obvious. (Even so, he hedges: No one knows for sure, he says, but there’s no obvious reason that AGI won’t come.) 

Hidden truths bring truth seekers, bent on revealing what they’ve been able to see all along. With AGI, though, it’s not enough to uncover something hidden. Here, revelation requires an unprecedented act of creation. If you believe AGI is achievable, then you believe that those making it are midwives to machines that will match or surpass human intelligence. “The idea of giving birth to machine gods is obviously very flattering to the ego,” says Vallor. “It’s an incredibly seductive thing to think that you yourself are laying the early foundations for that transcendence.” 

It’s yet another overlap with conspiracy thinking. Part of the draw is the desire for a sense of purpose in an otherwise messy world that can feel meaningless—the longing to be a person of consequence. 

Krueger, who is based in Berkeley, says he knows people working on AI who see the technology as our natural successor. “They view it as akin to having children or something,” he says. “Side note: they usually don’t have children.”

AGI will be our one true savior (or it’ll bring the apocalypse). 

Cohen sees parallels between many modern conspiracy theories and the New Age movement, which reached its peak of influence in the 1970s and ’80s. Adherents believed humanity was on the cusp of unlocking an era of spiritual well-being and expanded consciousness that would usher in a more peaceful and prosperous world. In a nutshell, the idea was that by engaging in a set of pseudo-religious practices, including astrology and the careful curation of crystals, humans would transcend their limitations and enter a kind of hippie utopia.

Today’s tech industry is built on compute, not crystals, but its sense of what’s at stake is no less transcendent: “You know, this idea that there is going to be this fundamental shift, there’s going to be this millenarian turn where we end up in a techno-utopian future,” says Cohen. “And the idea that AGI is going to ultimately allow humanity to overcome the problems that face us.”

In many people’s telling, AGI will arrive all at once. Incremental advances in AI will stack up until, one day, AI will be good enough to start making better AI by itself. At which point—FOOM—it will advance so rapidly that AGI will arrive in what’s often called an intelligence explosion, leading to a point of no return known as the Singularity, a goofy term that’s been popular in AGI circles for years. Co-opting a concept from physics, the science fiction author Vernor Vinge first introduced the idea of a technological singularity in the 1980s. Vinge imagined an event horizon on the path of technological progress beyond which humans would be fast outstripped by the exponential self-improvement of the machines they had created. 

Call it the AI Big Bang—which, again, gives us a before and an after, a transcendent moment when humanity as we know it changes forever (for good or bad). “People imagine it as an event,” says Grace from AI Impacts.

For Vallor, this belief system is notable for the way that a faith in technology has replaced a faith in humans. Despite the woo-woo, New Age thinking was at least motivated by the idea that people had what it took to change the world by themselves, if they could only tap into it. With the pursuit of AGI, we’ve left that self-belief behind and bought into the idea that only technology can save us, she says.  

That’s a compelling—even comforting—thought for many people. “We’re in an era where other paths to material improvement of human lives and our societies seem to have been exhausted,” Vallor says. 

Technology once promised a route to a better future: Progress was a ladder that we would climb toward human and social flourishing. “We’ve passed the peak of that,” says Vallor. “I think the one thing that gives many people hope and a return to that kind of optimism about the future is AGI.”

Push this idea to its conclusion and, again, AGI becomes a kind of god—one that can offer relief from earthly suffering, says Vallor.

Kelly Joyce, a sociologist at the University of North Carolina who studies how cultural, political, and economic beliefs shape the way we think about and use technology, sees all these wild predictions about AGI as something more banal: part of a long-term pattern of overpromising from the tech industry. “What’s interesting to me is that we get sucked in every time,” she says. “There is a deep belief that technology is better than human beings.”

Joyce thinks that’s why, when the hype kicks in, people are predisposed to believe it. “It’s a religion,” she says. “We believe in technology. Technology is God. It’s really hard to push back against it. People don’t want to hear it.”

How AGI hijacked an industry

The fantasy of computers that can do almost anything a person can is seductive. But like many pervasive conspiracy theories, it has very real consequences. It has distorted the way we think about the stakes behind the current technology boom (and potential bust). It may have even derailed the industry, sucking resources away from more immediate, more practical application of the technology. More than anything else, it gives us a free pass to be lazy. It fools us into thinking we might be able to avoid the actual hard work needed to solve intractable, world-spanning problems—problems that will require international cooperation and compromise and expensive aid. Why bother with that when we’ll soon have machines to figure it all out for us?

Consider the resources being sunk into this grand project. Just last month, OpenAI and Nvidia announced an up-to-$100 billion partnership that would see the chip giant supply at least 10 gigawatts of ChatGPT’s insatiable demand. That’s higher than nuclear power plant numbers. A bolt of lightning might release that much energy. The flux capacitor inside Dr. Emmett Brown’s DeLorean time machine only required 1.2 gigawatts to send Marty back to the future. And then, only two weeks later, OpenAI announced a second partnership with chipmaker AMD for another six gigawatts of power.

Promoting the Nvidia deal on CNBC, Altman, straight-faced, claimed that without this kind of data center buildout, people would have to choose between a cure for cancer and free education. “No one wants to make that choice,” he said. (Just a few weeks later, he announced that erotic chats would be coming to ChatGPT.)

Add to those costs the loss of investment in more immediate technology that could change lives today and tomorrow and the next day. “To me it’s a huge missed opportunity to put all these resources into solving something nebulous when we already know there’s real problems that we could solve,” says Lirio’s Symons. 

But that’s not how the likes of OpenAI needs to operate. “With people throwing so much money at these companies, they don’t have to do that,” Symons says. “If you’ve got hundreds of billions of dollars, you don’t have to focus on a practical, solvable project.”

Despite his steadfast belief that AGI is coming, Krueger also thinks the industry’s single-minded pursuit of it means that potential solutions to real problems, such as better health care, are being ignored. “People have a long list of complaints about both the concept of AGI and the idea that it should be a goal,” he says. “I think it’s pretty unpopular in the field.”

And there are consequences for the way governments support and regulate technology (or don’t). Tina Law, who studies technology policy at the University of California–Davis, worries that policymakers are getting lobbied about the ways AI will one day kill us all, instead of addressing real concerns about the ways AI could impact people’s lives in immediate and material ways today. Inequality has been sidetracked by existential risk.

“Hype is a lucrative strategy for tech firms,” says Law. A big part of that hype is the idea that what’s happening is inevitable: If we don’t build it, someone else will. “When something is framed as inevitable,” Law says, “people doubt not only whether they should resist but also whether they have the capacity to do so.” Everyone gets locked in. 

The AGI distortion field isn’t limited to tech policy, says Milton Mueller at the Georgia Institute of Technology, who works on technology policy and regulation. The race to AGI gets compared to the race to the atomic bomb, he says. “So whoever gets it first is going to have ultimate power over everybody else. That’s a crazy and dangerous idea that really will distort our approach to foreign policy.” 

There’s a business incentive for companies (and governments) to push the myth of AGI, says Mueller, because they can then claim that they will be the first to get there. But because they’re running a race in which nobody has agreed on the finish line, the myth can be spun as long as it’s useful. Or as long as investors are willing to buy into it. 

It’s not hard to see how this plays out. It’s not utopia or hell—it’s OpenAI and its peers making a whole lot more money.

The great AGI conspiracy, concluded 

And maybe that brings us back to the whole conspiracy thing—and a late-game twist in this tale. So far we’ve ignored one popular feature of conspiracy thinking: that there’s a group of powerful figures pulling the levers behind the scenes and that, by seeking the truth, believers can expose this elite cabal. 

Sure, the people feeling the AGI aren’t publicly accusing any Illuminati or WEF-like force of preventing the AGI future or withholding its secrets. 

But what if there are, in fact, shadowy puppet masters here—and they’re the very people who have pushed the AGI conspiracy hardest all along? The kings of Silicon Valley are throwing everything they can get at building AGI for profit. The myth of AGI serves their interests more than anybody else’s. 

As one senior executive at an AI company said to us recently, AGI always needs to be six months to a year away, because if it’s any further than that, you won’t be able to recruit people from Jane Street, and if it’s closer to already here, then what’s the point? 

Or as Vallor puts it: “If OpenAI says they’re building a machine that’s going to make corporations even more powerful than they are today, that isn’t going to get the kind of public buy-in that they need.” 

Remember: You create a god and you become like one yourself. Krueger says there’s a line of thinking running through Silicon Valley in which building AI is a way to seize huge amounts of power. (It’s one of the premises of Aschenbrenner’s “Situational Awareness,” for example.) “You know, we’re going to have this godlike power and we’re going to have to figure out what to do with it,” says Krueger. “A lot of people think if they get there first, they can basically take over the world.”

“They’re putting so much effort into selling their vision of a future with AGI in it, and they’re having a pretty good amount of success because they have so much power,” he adds.

Goertzel, for one, is almost lamenting how successful the maybe-cabal has been. He’s actually starting to miss life on the fringes. “In my generation, you had to have a lot of vision to want to work on AGI, and you had to be very stubborn,” he says. “Now it’s almost, like, what your grandma tells you to do to get a job instead of being a business major.”

“It’s disorienting that this stuff is so broadly accepted,” he says. “It almost gives me the desire to go work on something else that not so many people are doing.” He’s half joking (I think): “Obviously, putting the finishing touches to AGI is more important than gratifying my preference to be out on the frontier.”

But I’m no clearer on what exactly they’re putting the finishing touches on. What does it mean for technology in general if we fall so hard for the fairy tales? In a lot of ways, I think the whole idea of AGI is built on a warped view of what we should expect technology to do, and even what intelligence is in the first place. Stripped back to its essentials, the argument for AGI rests on the premise that one technology, AI, has gotten very good, very fast, and will continue to get better. But set aside the technical objections—what if it doesn’t continue to get better?—and you’re left with the claim that intelligence is a commodity you can get more of if you have the right data or compute or neural network. And it’s not. 

Intelligence doesn’t come as a quantity you can just ratchet up and up. Smart people may be brilliant in one area and not in others. Some Nobel Prize winners are really bad at playing the piano or caring for their kids. Some very smart people insist that AGI is coming next year. 

It’s hard not to wonder what will get its hooks into us next. 

Before we ended our call, Goertzel told me about an event he’d just been to in San Francisco on AI consciousness and parapsychology: “ESP, precognition, and whatnot.”

“That’s where AGI was 20 years ago,” he said. “Everyone thinks it’s batshit crazy.”

Correction: This story has been updated to better reflect David Krueger’s views.

Half of Fox News Viewers Believe Bill Gates Wants to Use Virus Vaccines to Track You, New Poll Says (Rolling Stone)

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May 22, 2020 5:00PM ET

Misinformation is taking a dangerous hold on Fox News viewers

By Peter Wade

Fox News Viewers Believe Bill Gates Wants Track You Through Vaccines
Two women hold anti-vaccination signs during a protest against Governor Jay Inslee’s stay-at-home order outside the State Capitol in Olympia, Washington on May 9, 2020.
JASON REDMOND/AFP/Getty Images

Misinformation is taking a dangerous hold on Fox News viewers. According to a new poll, half of all Americans who name Fox News as their primary news source believe the debunked conspiracy theory claiming Bill Gates is looking to use a coronavirus vaccine to inject a microchip into people and track the world’s population.

The Yahoo News/YouGov poll, released on Friday, found that 44 percent of Republicans also buy into the unfounded claim, while just 19 percent of Democrats believe the lie about the Microsoft co-founder and philanthropist.

According to Yahoo’s report on the poll, neither Fox News nor President Trump has promoted the false Gates conspiracy. But sowing seeds of distrust of mainstream media and the spread of misinformation is a hallmark of the network and the current president. Last month, Fox primetime host Laura Ingraham shared a tweet where she expressed agreement with a user who wrote about the debunked conspiracy theory.

“Digitally tracking Americans’ every move has been a dream of the globalists for years. This health crisis is the perfect vehicle for them to push this,” Ingraham wrote.

The poll also found that just 15 percent of MSNBC viewers believe the untrue conspiracy theory which, according to the fact-checking publication Snopes, began with the anti-vaccine movement. They chose to target Gates specifically because of his decade-long advocacy for vaccines.

According to an April report in the New York Times that looked into the right-wing targeting of Gates, media analysis company Zignal Labs found that “misinformation about Gates is now the most widespread of all coronavirus falsehoods” that the company has tracked.

This debunked conspiracy theory could be especially menacing if it deters any portion of the population from getting vaccinated, if and when one becomes available, which would then make it much tougher to rid the world of the virus.

In another poll released on Friday by Reuters/Ipsos showed increasing mistrust in the president due to his consistent habit of sharing misinformation. Thirty-six percent of those surveyed said they would be less willing to take a vaccine if it were endorsed by the president.

The picture these polls paint is both sad and obviously dangerous for all of us, especially with the current pandemic. Unfortunately, our country’s lack of trustworthy leadership means that more and more people are susceptible to bad and untrue advice that is rampant on random Reddit forums, Facebook posts and, yes, even TikTok — where conspiracy theories are paired with viral dances.

‘There is no absolute truth’: an infectious disease expert on Covid-19, misinformation and ‘bullshit’ (The Guardian)

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theguardian.com

Carl Bergstrom’s two disparate areas of expertise merged as reports of a mysterious respiratory illness emerged in January

‘Just because the trend that you see is consistent with a story that someone’s selling,inferring causality is dangerous.’
‘Just because the trend that you see is consistent with a story that someone’s selling,inferring causality is dangerous.’ Photograph: Matthew Horwood/Alamy Stock Photo

Julia Carrie Wong, Tue 28 Apr 2020 11.00 BST

Carl Bergstrom is uniquely suited to understanding the current moment. A professor of biology at the University of Washington, he has spent his career studying two seemingly disparate topics: emerging infectious diseases and networked misinformation. They merged into one the moment reports of a mysterious respiratory illness emerged from China in January.

The coronavirus touched off both a pandemic and an “infodemic” of hoaxes, conspiracy theories, honest misunderstandings and politicized scientific debates. Bergstrom has jumped into the fray, helping the public and the press navigate the world of epidemiological models, statistical uncertainty and the topic of his forthcoming book: bullshit.

The following interview has been edited for length and clarity.

You’ve been teaching a course and have co-written a book about the concept of bullshit. Explain what you mean by bullshit?

The formal definition that we use is “language, statistical figures, data, graphics and other forms of presentation that are intended to persuade by impressing and overwhelming a reader or listener with a blatant disregard for truth or logical coherence”.

The idea with bullshit is that it’s trying to appear authoritative and definitive in a way that’s not about communicating accurately and informing a reader, but rather by overwhelming them, persuading them, impressing them. If that’s done without any allegiance to truth, or accuracy, that becomes bullshit.

We’re all used to verbal bullshit. We’re all used to campaign promises and weasel words, and we’re pretty good at seeing through that because we’ve had a lot of practice. But as the world has become increasingly quantified and the currency of arguments has become statistics, facts and figures and models and such, we’re increasingly confronted, even in the popular press, with numerical and statistical arguments. And this area’s really ripe for bullshit, because people don’t feel qualified to question information that’s given to them in quantitative form.

Are there bullshit narratives about the coronavirus that you are concerned about right now?

What’s happened with this pandemic that we’re not accustomed to in the epidemiology community is that it’s been really heavily politicized. Even when scientists are very well-intentioned and not trying to support any side of the narrative, when they do work and release a paper it gets picked up by actors with political agendas.

Whether it’s talking about seroprevalence or estimating the chance that this is even going to come to the United States at all each study gets picked up and placed into this little political box and sort of used as a cudgel to beat the other side with.

So even when the material isn’t being produced as bullshit, it’s being picked up and used in the service of that by overstating its claims, by cherry-picking the information that’s out there and so on. And I think that’s kind of the biggest problem that we’re facing.

One example [of intentional bullshit] might be this insistence for a while on graphing the number of cases on a per-capita basis, so that people could say the US response is so much better than the rest of the world because we have a slower rate of growth per capita. That was basically graphical malfeasance or bullshit. When a wildfire starts spreading, you’re interested in how it’s spreading now, not whether it’s spreading in a 100-acre wood or millions of square miles of national forest.

Is there one big lesson that you think that the media should keep in mind as we communicate science to the public? What mistakes are we making?

I think the media has been adjusting really fast and doing really well. When I’m talking about how to avoid misinformation around this I’m constantly telling people to trust the professional fact-based media. Rather than looking for the latest rumor that’s spreading across Facebook or Twitter so that you can have information up to the hour, recognize that it’s much better to have solidly sourced, well-vetted information from yesterday.

Hyper-partisan media are making a huge mess of this, but that’s on purpose. They’ve got a reason to promote hydroxychloroquine or whatever it is and just run with that. They’re not even trying to be responsible.

But one of the biggest things that people [in the media]could do to improve would be to recognize that scientific studies, especially in a fast-moving situation like this, are provisional. That’s the nature of science. Anything can be corrected. There’s no absolute truth there. Each model, each finding is just adding to a weight of evidence in one direction or another.

A lot of the reporting is focusing on models, and most of us probably don’t have any basic training in how to read them or what kind of credence to put in them. What should we know?

The key thing, and this goes for scientists as well as non-scientists, is that people are not doing a very good job thinking about what the purpose of different models are, how the purposes of different models vary, and then what the scope of their value is. When these models get treated as if they’re oracles, then people both over-rely on them and treat them too seriously – and then turn around and slam them too hard for not being perfect at everything.

Are there mistakes that are made by people in the scientific community when it comes to communicating with the public?

We’re trying to communicate as a scientific community in a new way, where people are posting their data in real time. But we weren’t ready for the degree to which that stuff would be picked up and assigned meaning in this highly politically polarized environment. Work that might be fairly easy for researchers to contextualize in the field can be portrayed as something very, very different in the popular press.

The first Imperial College model in March was predicting 1.1 million to 2.2 million American deaths if the pandemic were not controlled. That’s a really scary, dramatic story, and I still think that it’s not unrealistic. That got promoted by one side of the partisan divide. Then Imperial came back and modeled a completely different scenario, where the disease was actually brought under control and suppressed in the US, and they released a subsequent model that said, ‘If we do this, something like 50,000 deaths will occur.’ That was picked up by the other side and used to try to discredit the Imperial College team entirely by saying, ‘A couple of weeks ago they said a million now they’re saying 50,000; they can’t get anything right.’ And the answer , of course, is that they were modeling two different scenarios.

We’re also not doing enough of deliberately stressing the possible weaknesses of our interpretations. That varies enormously from researcher to researcher and team to team.

It requires a lot of discipline to argue really hard for something but also be scrupulously open about all of the weaknesses in your own argument.

But it’s more important than ever, right? A really good paper will lay out all the most persuasive evidence it can and then in the conclusion section or the discussion section say, ‘OK, here are all the reasons that this could be wrong and here are the weaknesses.’

When you have something that’s so directly policy relevant, and there’s a lot of lives at stake, we’re learning how to find the right balance.

It is a bit of a nightmare to put out data that is truthful, but also be aware that there are bad faith actors at the moment who might pounce on it and use it in a way you didn’t intend.

There’s a spectrum. You have outright bad faith actors – Russian propaganda picking up on things and bots spreading misinformation – and then you have someone like Georgia Governor Brian Kemp who I wouldn’t calla bad faith actor. He’s a misinformed actor.

There’s so much that goes unsaid in science in terms of context and what findings mean that we don’t usually write in papers. If someone does a mathematical forecasting model, you’re usually not going to have a half-page discussion on the limitations of forecasting. We’re used to writing for an audience of 50 people in the world, if we’re lucky, who have backgrounds that are very similar to our own and have a huge set of shared assumptions and shared knowledge. And it works really well when you’re writing on something that only 50 people in the world care about and all of them have comparable training, but it is a real mess when it becomes pressing, and I don’t think any of us have figured out exactly what to do about that because we’re also trying to work quickly and it’s important to get this information out.

One area that has already become contentious and in some ways politicized is the serology surveys, which are supposed to show what percentage of the population has antibodies to the virus. What are some of the big picture contextual caveats and limitations that we should keep in mind as these surveys come out?

The seroprevalence in the US is a political issue, and so the first thing is to recognize that when anyone is reporting on that stuff, there’s a political context to it. It may even be that some of the research is being done with an implicitly political context, depending on who the funders are or what the orientations and biases of some of the researchers.

On the scientific side, I think there’s really two things to think about. The first one is the issue of selection bias. You’re trying to draw a conclusion about one population by sampling from a subset of that population and you want to know how close to random your subset is with respect to the thing you’re trying to measure. The Santa Clara study recruited volunteers off of Facebook. The obvious source of sampling bias there is that people desperately want to get tested. The people that want it are, of course, people that think they’ve had it.

The other big piece is understanding the notion of positive predictive value and the way false positive and false negative error rates influence the estimate. And that depends on the incidence of infection in the population.

If you have a test that has a 3% error rate, and the incidence in the population is below 3%, then most of the positives that you get are going to be false positives. And so you’re not going to get a very tight estimate about how many people have it. This has been a real problem with the Santa Clara study. From my read of the paper, their data is actually consistent with nobody being infected. A New York Citystudy on the other hand showed 21% seropositive, so even if there has a 3% error rate, the majority of those positives have to be true positives.

Now that we’ve all had a crash course in models and serosurveys, what are the other areas of science where it makes sense for the public to start getting educated on the terms of the debate?

One that I think will come along sooner or later is interpreting studies of treatments. We’ve dealt with that a little bit with the hydroxychloroquine business but not in any serious way because the hydroxychloroquine work has been pretty weak and the results have not been so positive.

But there are ongoing tests of a large range of existing drugs. And these studies are actually pretty hard to do. There’s a lot of subtle technical issues: what are you doing for controls? Is there a control arm at all? If not, how do you interpret the data? If there is a control arm, how is it structured? How do you control for the characteristics of the population on whom you’re using the drug or their selection biases in terms of who’s getting the drug?

Unfortunately, given what we’ve already seen with hydroxychloroquine, it’s fairly likely that this will be politicized as well. There’ll be a parallel set of issues that are going to come around with vaccination, but that’s more like a year off.

If you had the ability to arm every person with one tool – a statistical tool or scientific concept – to help them understand and contextualize scientific information as we look to the future of this pandemic, what would it be?

I would like people to understand that there are interactions between the models we make, the science we do and the way that we behave. The models that we make influence the decisions that we take individually and as a society, which then feed back into the models and the models often don’t treat that part explicitly.

Once you put a model out there that then creates changes in behavior that pull you out of the domain that the model was trying to model in the first place. We have to be very attuned to that as we try to use the models for guiding policy.

That’s very interesting, and not what I expected you to say.

What did you expect?

That correlation does not imply causation.

That’s another very good one. Seasonality is a great example there. We’re trying a whole bunch of things at the same time. We’re throwing all kinds of possible solutions at this and lots of things are changing. It’s remarkable to me actually, that so many US states are seeing the epidemic curve decrease. And so there’s a bunch of possibilities there. It could be because people’s behavior is changing. There could be some seasonality there. And there are other possible explanations as well.

But what is really important is that just because the trend that you see is consistent with a story that someone’s selling, there may be many other stories that are also consistent, so inferring causality is dangerous.

The Coronavirus Death Count Will Be a New Battle in the Culture Wars (Gizmodo)

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Ed Cara – 10 de abril de 2020

As parts of the United States settle in for what may be the worst weeks of their local covid-19 outbreaks, a familiar refrain is sure to emerge.

Some people will complain that the death count attributed to the coronavirus is being exaggerated. Others, including researchers, have argued that covid-19 related deaths are actually being undercounted, as people die at home without being tested. Still others will point to the final death count and say that because it’s lower than X (whether that number be flu deaths, car accident deaths, or some other moving goalpost), then that means the efforts and sacrifices made for social distancing weren’t worth it—ignoring, of course, that social distancing was the reason the toll wasn’t much higher. Figuring out how deadly covid-19 truly is will take far more time to untangle than anyone would want, and no one’s likely to be fully satisfied with the answers we get.

As of April 10, there have been around 1.6 million reported cases of covid-19, the disease caused by the novel coronavirus worldwide. There have also been over 96,000 reported deaths, with over 16,000 deaths documented in the U.S. But these numbers are largely acknowledged as a very rough, possibly even misleading estimate of the problem, given the wide gaps in testing capacity across different countries and even within a country.

On the political right, many have taken to fostering conspiracy theories about these deaths. You don’t have to go far on social media to see people accusing doctors and health officials of fudging the numbers higher to make President Trump look bad or to (somehow) profit off the tragedy. Other conservative voices like the disgraced sex pest Bill O’Reilly are less paranoid but similarly dismissive, arguing that many of those who died “were on their last legs anyway.”

It’s true that older people and those with underlying health conditions are at greater risk of serious complications and death from covid-19. But the same can be said for almost every other leading cause of death, whether it’s cancer, heart attack, or diabetes. And just as living is hardly a simple affair, so too is dying. Sometimes you can point to a single factor that kills a person, but often it’s a mix of ailments, with a viral infection like covid-19 being the final shove.

The key point here is that epidemiologists and others who try to estimate how many people die from any given cause per year know the above very well. The flu, for instance, doesn’t usually kill in isolation either—it too disproportionately kills the elderly and otherwise already sick. Yet many of the same people who are now trying to downplay covid-19 deaths also argued that its early death toll wasn’t coming anywhere close to the typical seasonal flu’s annual tally (an argument meant to push back against the idea of doing anything too serious to mitigate the spread of the coronavirus).

That said, we’re much better at estimating how many deaths in the U.S. are flu-related because the influenza virus is a known entity. We have a decent sense of how many people are infected with the flu every year, how many people go to the doctor or are hospitalized, and how many people it helps kill, thanks to a well-established nationwide surveillance system. But that isn’t true for covid-19.

There’s steady evidence indicating that covid-19 cases nearly everywhere in the world are being undercounted. That’s partly because testing remains so haphazard and has inherent limitations. The most common type of covid-19 test right now, for instance, can only confirm an active infection, not whether you had a previous case (newer antibody tests can address that problem but have their own flaws). It’s also because the virus infects a still-unknown percentage of people without making them feel sick at all.

Many more people have had or will catch the coronavirus than any current tracking will ever indicate. These hidden cases are almost certainly less deadly on average than the known cases that wind up in hospitals, so it’s likely that the current documented fatality rate of covid-19 (over 5 percent worldwide) is an overestimate. But that doesn’t mean more people aren’t dying from covid-19 than are being reported.

In areas of China and Italy hit hard by the coronavirus, news reports have suggested a wide gulf between the official number of covid-19-related deaths in a town and what residents are seeing for themselves. In the U.S., there are still regions where testing is limited and people who may have died from covid-19 in their homes are never tested, including New York City. And there’s the simple harsh reality that we’re probably still in the very beginning of this pandemic.

Even if outbreaks start to peter out in the U.S. and elsewhere, there’s the risk that loosening our restrictions on distancing will fuel new ones. And even if the summer heat in the U.S. makes it harder for the virus to spread here, as some experts hope, a second wave in the fall and winter could certainly happen, much as it did for the last pandemic (a strain of flu) in 2009.

All of these variables will affect the final death toll from covid-19, as will how countries continue to respond to the crisis. Ironically, the steps we take to prevent new cases and deaths may be the very thing that makes people doubt they were necessary.

In late March, the White House and U.S. public health officials announced that they projected 100,000 to 200,000 deaths in the country by the pandemic’s end, provided everything was done to slow its spread. On Thursday, Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, said that newer modeling data has suggested the U.S. death toll may end up closer to 60,000, so long as we keep mitigating the outbreak. Almost immediately, some people chose to take it as evidence that mitigation efforts aren’t necessary and that the initial warnings about the virus were overblown—ignoring, again, that the reason for the downward revision in projected deaths is the success of social distancing.

There are still a lot of things we don’t know about the coronavirus, and many of the things we think we know are going to keep changing. But here’s something to remember.

By the end of the 2009 H1N1 flu pandemic, the World Health Organization reported that about 19,000 people were confirmed to have died from the virus. By 2013, several studies estimated that the true death toll was at least 10 times higher and even higher still when you took into account other causes of death indirectly worsened by the flu, like heart attacks. Knowing how deadly covid-19 will be could very well take that long to nail down too.

Another article of interest:

New York City’s covid-19 death toll is likely higher than reported, due to the fact that the…Read more

Entenda por que as teorias da conspiração sobre coronavírus se proliferam tanto (Estadão)

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internacional.estadao.com.br

Max Fischer, New York Times – 8 de abril de 2020

NOVA YORK – O coronavírus deu origem a uma enxurrada de teorias da conspiração, desinformação e propaganda, minando as autoridades de saúde e corroendo a confiança do público de maneiras que podem prolongar a pandemia e até mesmo se estender para além dela.

Alegações de que o novo coronavírus seria uma arma biológica estrangeira, uma invenção partidária ou parte de um projeto de reengenharia social substituíram um vírus sem razão nem propósito por vilões mais familiares e compreensíveis. Cada alegação parece dar a essa tragédia sem sentido algum grau de significado, por mais sombrio que seja.

Rumores de curas secretas – beber alvejante diluído, desligar os aparelhos eletrônicos, comer banana – dão uma esperança de proteção contra uma ameaça da qual nem mesmo os líderes mundiais estão escapando.

A crença de que alguém teve acesso ao conhecimento proibido proporciona uma sensação de certeza e controle em meio a uma crise que virou o mundo de cabeça para baixo. E compartilhar esse “conhecimento” pode dar às pessoas algo difícil de encontrar depois de semanas de isolamento e morte: a sensação de que se está fazendo alguma coisa.

“Aí estão todos os ingredientes que empurram as pessoas para as teorias da conspiração”, disse Karen Douglas, psicóloga social que estuda a crença em conspirações na Universidade de Kent, na Grã-Bretanha.

Rumores e afirmações flagrantemente estapafúrdias são disseminados por pessoas comuns cujas faculdades críticas simplesmente se viram esmagadas sob sentimentos de confusão e desamparo, dizem os psicólogos.

Mas muitas alegações falsas também vêm sendo promovidas por governos que tentam esconder seus fracassos, líderes partidários em busca de benefícios políticos, golpistas em geral e, nos Estados Unidos, por um presidente que insiste em curas não comprovadas e dispara falsidades que procuram eximi-lo de qualquer culpa.

Todas as teorias da conspiração carregam uma mensagem em comum: o único jeito de se proteger é saber as verdades secretas que “eles” não querem que você ouça.

O sentimento de segurança e controle proporcionado por esses rumores pode ser ilusório, mas os danos à confiança do público são bem reais.

As teorias conspiratórias estão levando as pessoas a consumir remédios caseiros que se revelaram letais e a desrespeitar as orientações de distanciamento social. E estão sabotando as ações coletivas, como ficar em casa ou usar máscaras, atitudes necessárias para conter um vírus que já matou mais de 79 mil pessoas.

“Já enfrentamos pandemias antes desta”, disse Graham Brookie, que dirige o Laboratório de Pesquisa Forense Digital do Atlantic Council. “Mas nunca enfrentamos uma pandemia num momento em que as pessoas estivessem tão conectadas e tivessem tanto acesso a informações quanto agora.”

Esse crescente ecossistema de desinformação e desconfiança pública obrigou a Organização Mundial da Saúde (OMS) a ligar o alerta para uma “infodemia”. “Estamos assistindo a uma verdadeira inundação”, disse Brookie. “A ansiedade é viral, e todos estamos nos sentindo mais ansiosos que nunca.”

O fascínio do ‘conhecimento secreto’

“As conspirações atraem as pessoas porque prometem satisfazer certos motivos psicológicos que são importantes para elas”, disse Douglas. Os principais deles: o domínio sobre os fatos, a autonomia sobre o bem-estar e a sensação de controle.

Quando a verdade não atende a essas necessidades, nós humanos temos uma capacidade incrível de inventar histórias que atenderão, mesmo que uma parte de nós saiba que as histórias são falsas. Um estudo recente revelou que as pessoas são significativamente mais propensas a compartilhar informações falsas sobre o coronavírus do que imaginam.

“A magnitude da desinformação que se espalhou com a pandemia da covid-19 está sobrecarregando nossa equipe”, escreveu no Twitter o Snopes, um site de verificação de fatos. “Estamos vendo que milhares de pessoas, na ânsia de encontrar algum conforto, acabam piorando as coisas ao compartilhar informações falsas (e, às vezes, perigosas).”

Vastamente compartilhadas, postagens de Instagram alegaram, falsamente, que o coronavírus fora planejado por Bill Gates em benefício de empresas farmacêuticas. No Alabama, postagens de Facebook afirmaram, falsamente, que poderes obscuros haviam ordenado que doentes fossem secretamente enviados de helicóptero para o Estado. Na América Latina, proliferaram rumores igualmente infundados de que o vírus fora projetado para espalhar o HIV. No Irã, vozes pró-governo retrataram a doença como uma trama ocidental.

Se as alegações parecerem sigilosas, melhor ainda

A crença de que temos acesso a informações secretas pode nos dar a sensação de que temos uma vantagem, de que, de alguma forma, estamos mais seguros. “Quem acredita em teorias da conspiração acha que tem um poder, conferido pelo conhecimento, que as outras pessoas não têm”, disse Douglas.

A mídia italiana repercutiu um vídeo postado por um italiano que morava em Tóquio, no qual ele dizia que o coronavírus era tratável, mas que as autoridades italianas estavam “escondendo a verdade”.

Outros vídeos, muito populares no YouTube, afirmam que toda a pandemia é uma ficção encenada para controlar a população.

As teorias da conspiração também podem fazer as pessoas se sentirem menos sozinhas. Poucas coisas estreitam mais os laços entre “nós” do que combater “eles”, especialmente quando “eles” são estrangeiros e minorias, frequentes bodes expiatórios de boatos sobre o coronavírus e muitas outras coisas no passado.

Mas qualquer conforto que essas teorias proporcionem terá vida curta. Com o tempo, segundo pesquisas, o intercâmbio de conspirações não apenas fracassa em satisfazer nossas necessidades psicológicas, disse Douglas, como também tende a agravar sentimentos de medo e desamparo.

E isso pode nos levar a procurar explicações ainda mais extremas, como viciados em busca de doses cada vez mais fortes.

Governos vêm uma oportunidade na confusão  

Os conspiradores e questionadores agora têm apoio dos governos. Antecipando a repercussão política da crise, líderes governamentais agiram rapidamente para se eximirem da culpa, espalhando suas próprias mentiras.

Uma importante autoridade chinesa disse que o vírus foi introduzido na China por membros do Exército dos Estados Unidos, uma acusação que teve permissão para se disseminar nas mídias sociais rigidamente controladas da China.

Na Venezuela, o presidente Nicolás Maduro sugeriu que o vírus era uma arma biológica americana cujo alvo seria a China. No Irã, as autoridades o chamaram de conspiração para acabar com o processo eleitoral no país. E agências de notícias que apoiam o governo russo, algumas com filiais na Europa ocidental, ventilaram alegações de que os Estados Unidos projetaram o vírus para minar a economia chinesa.

Nas antigas repúblicas soviéticas do Turcomenistão e Tadjiquistão, líderes recomendaram tratamentos falsos e defenderam a ideia de que os cidadãos deveriam continuar trabalhando.

Mas as autoridades tampouco deixaram de espalhar boatos em nações mais democráticas, particularmente naquelas em que a desconfiança em relação à autoridade abriu espaço para a ascensão de fortes movimentos populistas.

Matteo Salvini, líder do partido anti-imigração Liga Norte, na Itália, escreveu no Twitter que a China havia criado um “supervírus de pulmão” a partir de “morcegos e ratos”.

E o presidente do Brasil, Jair Bolsonaro, repetidas vezes propagandeou tratamentos não comprovados e insinuou que o coronavírus seria menos perigoso do que dizem os especialistas. Facebook, Twitter e YouTube tomaram a extraordinária decisão de remover suas postagens.

O presidente Donald Trump também insistiu repetidamente no uso de medicamentos não comprovados, apesar das advertências dos cientistas e de pelo menos uma overdose fatal, a qual vitimou um homem cuja esposa disse que ele havia tomado o remédio por sugestão de Trump.

Trump acusou seus supostos inimigos de tentar “inflamar” a “situação” do coronavírus para prejudicá-lo. Quando começaram a faltar equipamentos de proteção individual nos hospitais de Nova York, ele insinuou que os profissionais de saúde estavam roubando as máscaras. Seus aliados foram ainda mais longe.

O senador Tom Cotton, republicano do Arkansas, e outros sugeriram que o vírus foi produzido por um laboratório de armas chinês. Alguns aliados da mídia alegaram que os inimigos de Trump exageraram o número de mortos.

Uma crise paralela

“Essa supressão de informações é perigosa – muito, muito perigosa”, disse Brookie, referindo-se aos esforços chineses e americanos para minimizar a ameaça do surto.

A supressão de informações alimentou não apenas conspirações específicas, mas também uma sensação mais generalizada de que as fontes e dados oficiais não são confiáveis, bem como a ideia cada vez mais disseminada de que as pessoas devem buscar a verdade por conta própria.

A cacofonia dos epidemiologistas de sofá, que costumam chamar a atenção com afirmações sensacionalistas, muitas vezes encobre a fala de especialistas legítimos, cujas respostas raramente são muito sintéticas ou tranquilizadoras.

Eles prometem curas fáceis, como evitar os aparelhos eletrônicos ou até mesmo comer bananas, e dizem que o transtorno do isolamento social é desnecessário. Alguns chegam a vender tratamentos enganosos que eles próprios inventaram.

“As teorias da conspiração do campo da medicina têm o poder de aumentar a desconfiança nas autoridades médicas, o que pode afetar a disposição das pessoas a se protegerem”, escreveram Daniel Jolley e Pia Lamberty, pesquisadores de psicologia, em um artigo recente.

Demonstrou-se que tais alegações deixam as pessoas menos propensas a tomar vacinas ou antibióticos e mais propensas a procurar aconselhamento médico junto a amigos e familiares, e não profissionais de saúde.

A crença em uma conspiração também tende a aumentar a crença nas outras. As consequências, alertam os especialistas, podem não apenas piorar a pandemia, mas também se estender para além dela. / TRADUÇÃO DE RENATO PRELORENTZOU 

Why Coronavirus Conspiracy Theories Flourish. And Why It Matters (New York Times)

Uncategorized, , , , , , ,

The Interpreter

Unseen villains. Top-secret cures. In their quest for reassurance during the pandemic, many people are worsening more than just their own anxiety.

Volunteers disinfecting a theater in Wuhan, China, last week.
Volunteers disinfecting a theater in Wuhan, China, last week.Credit…Aly Song/Reuters

By Max Fisher

April 8, 2020; Updated 8:55 a.m. ET

The coronavirus has given rise to a flood of conspiracy theories, disinformation and propaganda, eroding public trust and undermining health officials in ways that could elongate and even outlast the pandemic.

Claims that the virus is a foreign bioweapon, a partisan invention or part of a plot to re-engineer the population have replaced a mindless virus with more familiar, comprehensible villains. Each claim seems to give a senseless tragedy some degree of meaning, however dark.

Rumors of secret cures — diluted bleach, turning off your electronics, bananas — promise hope of protection from a threat that not even world leaders can escape.

The belief that one is privy to forbidden knowledge offers feelings of certainty and control amid a crisis that has turned the world upside down. And sharing that “knowledge” may give people something that is hard to come by after weeks of lockdowns and death: a sense of agency.

“It has all the ingredients for leading people to conspiracy theories,” said Karen M. Douglas, a social psychologist who studies belief in conspiracies at the University of Kent in Britain.

Rumors and patently unbelievable claims are spread by everyday people whose critical faculties have simply been overwhelmed, psychologists say, by feelings of confusion and helplessness.

But many false claims are also being promoted by governments looking to hide their failures, partisan actors seeking political benefit, run-of-the-mill scammers and, in the United States, a president who has pushed unproven cures and blame-deflecting falsehoods.

The conspiracy theories all carry a common message: The only protection comes from possessing the secret truths that “they” don’t want you to hear.

The feelings of security and control offered by such rumors may be illusory, but the damage to the public trust is all too real.

It has led people to consume fatal home remedies and flout social distancing guidance. And it is disrupting the sweeping collective actions, like staying at home or wearing masks, needed to contain a virus that has already killed more than 79,000 people.

“We’ve faced pandemics before,” said Graham Brookie, who directs the Atlantic Council’s Digital Forensic Research Lab. “We haven’t faced a pandemic at a time when humans are as connected and have as much access to information as they do now.”

People gathering on a beach in Rio de Janeiro last week. Brazil’s president has implied that the virus is less dangerous than experts say.
People gathering on a beach in Rio de Janeiro last week. Brazil’s president has implied that the virus is less dangerous than experts say.Credit…Antonio Lacerda/EPA, via Shutterstock

This growing ecosystem of misinformation and public distrust has led the World Health Organization to warn of an “infodemic.”

“You see the space being flooded,” Mr. Brookie said, adding, “The anxiety is viral, and we’re all just feeling that at scale.”

“People are drawn to conspiracies because they promise to satisfy certain psychological motives that are important to people,” Dr. Douglas said. Chief among them: command of the facts, autonomy over one’s well-being and a sense of control.

If the truth does not fill those needs, we humans have an incredible capacity to invent stories that will, even when some part of us knows they are false. A recent study found that people are significantly likelier to share false coronavirus information than they are to believe it.

[Analysis: Peaks, testing and lockdowns: How coronavirus vocabulary causes confusion.]

“The magnitude of misinformation spreading in the wake of the Covid-19 pandemic is overwhelming our small team,” Snopes, a fact-checking site, said on Twitter. “We’re seeing scores of people, in a rush to find any comfort, make things worse as they share (sometimes dangerous) misinformation.”

Widely shared, Instagram posts falsely suggested that the coronavirus was planned by Bill Gates on behalf of pharmaceutical companies. In Alabama, Facebook posts falsely claimed that shadowy powers had ordered sick patients to be secretly helicoptered into the state. In Latin America, equally baseless rumors have proliferated that the virus was engineered to spread H.I.V. In Iran, pro-government voices portray the disease as a Western plot.

If the claims are seen as taboo, all the better.

The belief that we have access to secret information may help us feel that we have an advantage, that we are somehow safer. “If you believe in conspiracy theories, then you have power through knowledge that other people don’t have,” Dr. Douglas said.

Amid a swirl of rumors about the cause of Covid-19, some have attacked cellphone towers, like this one in Birmingham, England.
Amid a swirl of rumors about the cause of Covid-19, some have attacked cellphone towers, like this one in Birmingham, England.Credit…Carl Recine/Reuters

Italian media buzzed over a video posted by an Italian man from Tokyo in which he claimed that the coronavirus was treatable but that Italian officials were “hiding the truth.”

Other videos, popular on YouTube, claim that the entire pandemic is a fiction staged to control the population.

Still others say that the disease is real, but its cause isn’t a virus — it’s 5G cellular networks.

One YouTube video pushing this falsehood, and implying that social distancing measures could be ignored, has received 1.9 million views. In Britain, there has been a rash of attacks on cellular towers.

Conspiracy theories may also make people feel less alone. Few things tighten the bonds of “us” like rallying against “them,” especially foreigners and minorities, both frequent scapegoats of coronavirus rumors and much else before now.

But whatever comfort that affords is short-lived.

Over time, research finds, trading in conspiracies not only fails to satisfy our psychological needs, Dr. Douglas said, but also tends to worsen feelings of fear or helplessness.

And that can lead us to seek out still more extreme explanations, like addicts looking for bigger and bigger hits.

The homegrown conspiracists and doubters are finding themselves joined by governments. Anticipating political backlash from the crisis, government leaders have moved quickly to shunt the blame by trafficking in false claims of their own.

A senior Chinese official pushed claims that the virus was introduced to China by members of the United States Army, an accusation that was allowed to flourish on China’s tightly controlled social media.

In Venezuela, President Nicolás Maduro suggested that the virus was an American bioweapon aimed at China. In Iran, officials called it a plot to suppress the vote there. And outlets that back the Russian government, including branches in Western Europe, have promoted claims that the United States engineered the virus to undermine China’s economy.

In the former Soviet republics of Turkmenistan and Tajikistan, leaders praised bogus treatments and argued that citizens should continue working.

But officials have hardly refrained from the rumor mongering in more democratic nations, particularly those where distrust of authority has given rise to strong populist movements.

Matteo Salvini, the leader of Italy’s anti-migrant League Party, wrote on Twitter that China had devised a “lung supervirus” from “bats and rats.”

And President Jair Bolsonaro of Brazil has repeatedly promoted unproven coronavirus treatments, and implied that the virus is less dangerous than experts say. Facebook, Twitter and YouTube all took the extraordinary step of removing the posts.

President Trump has pushed unproven drugs, despite warnings from scientists.
President Trump has pushed unproven drugs, despite warnings from scientists.Credit…Doug Mills/The New York Times

President Trump, too, has repeatedly pushed unproven drugs, despite warnings from scientists and despite at least one fatal overdose of a man whose wife said he had taken a drug at Mr. Trump’s suggestion.

Mr. Trump has accused perceived enemies of seeking to “inflame” the coronavirus “situation” to hurt him. When supplies of personal protective equipment fell short at New York hospitals, he implied that health workers might be stealing masks.

His allies have gone further.

Senator Tom Cotton, Republican of Arkansas, and others have suggested that the virus was produced by a Chinese weapons lab. Some media allies have claimed that the death toll has been inflated by Mr. Trump’s enemies.

“This kind of information suppression is dangerous — really, really dangerous,” Mr. Brookie said, referring to Chinese and American efforts to play down the threat of the outbreak.

It has nourished not just individual conspiracies but a wider sense that official sources and data cannot be trusted, and a growing belief that people must find the truth on their own.

A cacophony arising from armchair epidemiologists who often win attention through sensational claims is at times crowding out legitimate experts whose answers are rarely as tidy or emotionally reassuring.

They promise easy cures, like avoiding telecommunications or even eating bananas. They wave off the burdens of social isolation as unnecessary. Some sell sham treatments of their own.

“Medical conspiracy theories have the power to increase distrust in medical authorities, which can impact people’s willingness to protect themselves,” Daniel Jolley and Pia Lamberty, scholars of psychology, wrote in a recent article.

Such claims have been shown to make people less likely to take vaccines or antibiotics, and more likely to seek medical advice from friends and family instead of from doctors.

Supposed coronavirus remedies at a market in Yogyakarta, Indonesia.
Supposed coronavirus remedies at a market in Yogyakarta, Indonesia.Credit…Ulet Ifansasti for The New York Times

Belief in one conspiracy also tends to increase belief in others. The consequences, experts warn, could not only worsen the pandemic, but outlive it.

Medical conspiracies have been a growing problem for years. So has distrust of authority, a major driver of the world’s slide into fringe populism. Now, as the world enters an economic crisis with little modern precedent, that may deepen.

The wave of coronavirus conspiracies, Dr. Jolley and Dr. Lamberty wrote, “has the potential to be just as dangerous for societies as the outbreak itself.”

Emma Bubola contributed reporting from Rome.

‘Chemtrails’ not real, say atmospheric science experts (Science Daily)

Uncategorized, , ,

Date:
August 12, 2016
Source:
Carnegie Institution for Science
Summary:
Well-understood physical and chemical processes can easily explain the alleged evidence of a secret, large-scale atmospheric spraying program, commonly referred to as ‘chemtrails’ or ‘covert geoengineering.’ A survey of the world’s leading atmospheric scientists categorically rejects the existence of a secret spraying program.

This is a condensation trail, or contrail, left behind an aircraft. Credit: Courtesy of Mick West

Well-understood physical and chemical processes can easily explain the alleged evidence of a secret, large-scale atmospheric spraying program, commonly referred to as “chemtrails” or “covert geoengineering,” concludes a new study from Carnegie Science, University of California Irvine, and the nonprofit organization Near Zero.

Some groups and individuals erroneously believe that the long-lasting condensation trails, or contrails, left behind aircraft are evidence of a secret large-scale spraying program. They call these imagined features “chemtrails.” Adherents of this conspiracy theory sometimes attribute this alleged spraying to the government and sometimes to industry.

The authors of this study, including Carnegie’s Ken Caldeira, conducted a survey of the world’s leading atmospheric scientists, who categorically rejected the existence of a secret spraying program. The team’s findings, published by Environmental Research Letters, are based on a survey of two groups of experts: atmospheric chemists who specialize in condensation trails and geochemists working on atmospheric deposition of dust and pollution.

The survey results show that 76 of the 77 participating scientists said they had not encountered evidence of a secret spraying program, and agree that the alleged evidence cited by the individuals who believe that atmospheric spraying is occurring could be explained through other factors, such as typical airplane contrail formation and poor data sampling.

The research team undertook their study in response to the large number of people who claim to believe in a secret spraying program. In a 2011 international survey, nearly 17 percent of respondents said they believed the existence of a secret large-scale atmospheric spraying program to be true or partly true. And in recent years a number of websites have arisen claiming to show evidence of widespread secret chemical spraying, which they say is linked to negative impacts on human health and the environment.

“We wanted to establish a scientific record on the topic of secret atmospheric spraying programs for the benefit of those in the public who haven’t made up their minds,” said Steven Davis of UC Irvine. “The experts we surveyed resoundingly rejected contrail photographs and test results as evidence of a large-scale atmospheric conspiracy.”

The research team says they do not hope to sway those already convinced that there is a secret spraying program — as these individuals usually only reject counter-evidence as further proof of their theories — but rather to establish a source of objective science that can inform public discourse.

“Despite the persistence of erroneous theories about atmospheric chemical spraying programs, until now there were no peer-reviewed academic studies showing that what some people think are ‘chemtrails’ are just ordinary contrails, which are becoming more abundant as air travel expands. Also, it is possible that climate change is causing contrails to persist for longer periods than they used to.” Caldeira said. “I felt it was important to definitively show what real experts in contrails and aerosols think. We might not convince die-hard believers that their beloved secret spraying program is just a paranoid fantasy, but hopefully their friends will accept the facts.”

Journal Reference:

  1. Christine Shearer, Mick West, Ken Caldeira, Steven J Davis. Quantifying expert consensus against the existence of a secret, large-scale atmospheric spraying program. Environmental Research Letters, 2016; 11 (8): 084011 DOI: 10.1088/1748-9326/11/8/084011