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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The complaint — filed last month with the Securities and Exchange Commission and the Department of Justice, as well as the FTC — says thousands of employees still had wide-ranging and poorly tracked internal access to core company software, a situation that for years had led to embarrassing hacks, including the commandeering of accounts held by such high-profile users as Elon Musk and former presidents Barack Obama and Donald Trump.

the whistleblower document alleges the company prioritized user growth over reducing spam, though unwanted content made the user experience worse. Executives stood to win individual bonuses of as much as $10 million tied to increases in daily users, the complaint asserts, and nothing explicitly for cutting spam.

Chief executive Parag Agrawal was “lying” when he tweeted in May that the company was “strongly incentivized to detect and remove as much spam as we possibly can,” the complaint alleges.

Zatko described his decision to go public as an extension of his previous work exposing flaws in specific pieces of software and broader systemic failings in cybersecurity. He was hired at Twitter by former CEO Jack Dorsey in late 2020 after a major hack of the company’s systems.

“I felt ethically bound. This is not a light step to take,” said Zatko, who was fired by Agrawal in January. He declined to discuss what happened at Twitter, except to stand by the formal complaint. Under SEC whistleblower rules, he is entitled to legal protection against retaliation, as well as potential monetary rewards.

“Security and privacy have long been top companywide priorities at Twitter,” said Twitter spokeswoman Rebecca Hahn. She said that Zatko’s allegations appeared to be “riddled with inaccuracies” and that Zatko “now appears to be opportunistically seeking to inflict harm on Twitter, its customers, and its shareholders.” Hahn said that Twitter fired Zatko after 15 months “for poor performance and leadership.” Attorneys for Zatko confirmed he was fired but denied it was for performance or leadership.

A person familiar with Zatko’s tenure said the company investigated Zatko’s security claims during his time there and concluded they were sensationalistic and without merit. Four people familiar with Twitter’s efforts to fight spam said the company deploys extensive manual and automated tools to both measure the extent of spam across the service and reduce it.

Overall, Zatko wrote in a February analysis for the company attached as an exhibit to the SEC complaint, “Twitter is grossly negligent in several areas of information security. If these problems are not corrected, regulators, media and users of the platform will be shocked when they inevitably learn about Twitter’s severe lack of security basics.”

Zatko’s complaint says strong security should have been much more important to Twitter, which holds vast amounts of sensitive personal data about users. Twitter has the email addresses and phone numbers of many public figures, as well as dissidents who communicate over the service at great personal risk.

This month, an ex-Twitter employee was convicted of using his position at the company to spy on Saudi dissidents and government critics, passing their information to a close aide of Crown Prince Mohammed bin Salman in exchange for cash and gifts.

Zatko’s complaint says he believed the Indian government had forced Twitter to put one of its agents on the payroll, with access to user data at a time of intense protests in the country. The complaint said supporting information for that claim has gone to the National Security Division of the Justice Department and the Senate Select Committee on Intelligence. Another person familiar with the matter agreed that the employee was probably an agent.

“Take a tech platform that collects massive amounts of user data, combine it with what appears to be an incredibly weak security infrastructure and infuse it with foreign state actors with an agenda, and you’ve got a recipe for disaster,” Charles E. Grassley (R-Iowa), the top Republican on the Senate Judiciary Committee,

Many government leaders and other trusted voices use Twitter to spread important messages quickly, so a hijacked account could drive panic or violence. In 2013, a captured Associated Press handle falsely tweeted about explosions at the White House, sending the Dow Jones industrial average briefly plunging more than 140 points.

After a teenager managed to hijack the verified accounts of Obama, then-candidate Joe Biden, Musk and others in 2020, Twitter’s chief executive at the time, Jack Dorsey, asked Zatko to join him, saying that he could help the world by fixing Twitter’s security and improving the public conversation, Zatko asserts in the complaint.

In 1998, Zatko had testified to Congress that the internet was so fragile that he and others could take it down with a half-hour of concentrated effort. He later served as the head of cyber grants at the Defense Advanced Research Projects Agency, the Pentagon innovation unit that had backed the internet’s invention.

But at Twitter Zatko encountered problems more widespread than he realized and leadership that didn’t act on his concerns, according to the complaint.

Twitter’s difficulties with weak security stretches back more than a decade before Zatko’s arrival at the company in November 2020. In a pair of 2009 incidents, hackers gained administrative control of the social network, allowing them to reset passwords and access user data. In the first, beginning around January of that year, hackers sent tweets from the accounts of high-profile users, including Fox News and Obama.

Several months later, a hacker was able to guess an employee’s administrative password after gaining access to similar passwords in their personal email account. That hacker was able to reset at least one user’s password and obtain private information about any Twitter user.

Twitter continued to suffer high-profile hacks and security violations, including in 2017, when a contract worker briefly took over Trump’s account, and in the 2020 hack, in which a Florida teen tricked Twitter employees and won access to verified accounts. Twitter then said it put additional safeguards in place.

This year, the Justice Department accused Twitter of asking users for their phone numbers in the name of increased security, then using the numbers for marketing. Twitter agreed to pay a $150 million fine for allegedly breaking the 2011 order, which barred the company from making misrepresentations about the security of personal data.

After Zatko joined the company, he found it had made little progress since the 2011 settlement, the complaint says. The complaint alleges that he was able to reduce the backlog of safety cases, including harassment and threats, from 1 million to 200,000, add staff and push to measure results.

But Zatko saw major gaps in what the company was doing to satisfy its obligations to the FTC, according to the complaint. In Zatko’s interpretation, according to the complaint, the 2011 order required Twitter to implement a Software Development Life Cycle program, a standard process for making sure new code is free of dangerous bugs. The complaint alleges that other employees had been telling the board and the FTC that they were making progress in rolling out that program to Twitter’s systems. But Zatko alleges that he discovered that it had been sent to only a tenth of the company’s projects, and even then treated as optional.

“If all of that is true, I don’t think there’s any doubt that there are order violations,” Vladeck, who is now a Georgetown Law professor, said in an interview. “It is possible that the kinds of problems that Twitter faced eleven years ago are still running through the company.”

The complaint also alleges that Zatko warned the board early in his tenure that overlapping outages in the company’s data centers could leave it unable to correctly restart its servers. That could have left the service down for months, or even have caused all of its data to be lost. That came close to happening in 2021, when an “impending catastrophic” crisis threatened the platform’s survival before engineers were able to save the day, the complaint says, without providing further details.

One current and one former employee recalled that incident, when failures at two Twitter data centers drove concerns that the service could have collapsed for an extended period. “I wondered if the company would exist in a few days,” one of them said.

The current and former employees also agreed with the complaint’s assertion that past reports to various privacy regulators were “misleading at best.”

For example, they said the company implied that it had destroyed all data on users who asked, but the material had spread so widely inside Twitter’s networks, it was impossible to know for sure

As the head of security, Zatko says he also was in charge of a division that investigated users’ complaints about accounts, which meant that he oversaw the removal of some bots, according to the complaint. Spam bots — computer programs that tweet automatically — have long vexed Twitter. Unlike its social media counterparts, Twitter allows users to program bots to be used on its service: For example, the Twitter account @big_ben_clock is programmed to tweet “Bong Bong Bong” every hour in time with Big Ben in London. Twitter also allows people to create accounts without using their real identities, making it harder for the company to distinguish between authentic, duplicate and automated accounts.

In the complaint, Zatko alleges he could not get a straight answer when he sought what he viewed as an important data point: the prevalence of spam and bots across all of Twitter, not just among monetizable users.

Zatko cites a “sensitive source” who said Twitter was afraid to determine that number because it “would harm the image and valuation of the company.” He says the company’s tools for detecting spam are far less robust than implied in various statements.

“Agrawal’s Tweets and Twitter’s previous blog posts misleadingly imply that Twitter employs proactive, sophisticated systems to measure and block spam bots,” the complaint says. “The reality: mostly outdated, unmonitored, simple scripts plus overworked, inefficient, understaffed, and reactive human teams.”

The four people familiar with Twitter’s spam and bot efforts said the engineering and integrity teams run software that samples thousands of tweets per day, and 100 accounts are sampled manually.

Some employees charged with executing the fight agreed that they had been short of staff. One said top executives showed “apathy” toward the issue.

Zatko’s complaint likewise depicts leadership dysfunction, starting with the CEO. Dorsey was largely absent during the pandemic, which made it hard for Zatko to get rulings on who should be in charge of what in areas of overlap and easier for rival executives to avoid collaborating, three current and former employees said.

For example, Zatko would encounter disinformation as part of his mandate to handle complaints, according to the complaint. To that end, he commissioned an outside report that found one of the disinformation teams had unfilled positions, yawning language deficiencies, and a lack of technical tools or the engineers to craft them. The authors said Twitter had no effective means of dealing with consistent spreaders of falsehoods.

Dorsey made little effort to integrate Zatko at the company, according to the three employees as well as two others familiar with the process who spoke on the condition of anonymity to describe sensitive dynamics. In 12 months, Zatko could manage only six one-on-one calls, all less than 30 minutes, with his direct boss Dorsey, who also served as CEO of payments company Square, now known as Block, according to the complaint. Zatko allegedly did almost all of the talking, and Dorsey said perhaps 50 words in the entire year to him. “A couple dozen text messages” rounded out their electronic communication, the complaint alleges.

Faced with such inertia, Zatko asserts that he was unable to solve some of the most serious issues, according to the complaint.

Some 30 percent of company laptops blocked automatic software updates carrying security fixes, and thousands of laptops had complete copies of Twitter’s source code, making them a rich target for hackers, it alleges.

A successful hacker takeover of one of those machines would have been able to sabotage the product with relative ease, because the engineers pushed out changes without being forced to test them first in a simulated environment, current and former employees said.

“It’s near-incredible that for something of that scale there would not be a development test environment separate from production and there would not be a more controlled source-code management process,” said Tony Sager, former chief operating officer at the cyberdefense wing of the National Security Agency, the Information Assurance divisio

Sager is currently senior vice president at the nonprofit Center for Internet Security, where he leads a consensus effort to establish best security practices.

Zatko stopped the material from being presented at the Dec. 9, 2021 meeting, the complaint said. But over his continued objections, Agrawal let it go to the board’s smaller Risk Committee a week later.

“A best practice is that you should only be authorized to see and access what you need to do your job, and nothing else,” said former U.S. chief information security officer Gregory Touhill. “If half the company has access to and can make configuration changes to the production environment, that exposes the company and its customers to significant risk.”

The complaint says Dorsey never encouraged anyone to mislead the board about the shortcomings, but that others deliberately left out bad news.

The complaint says that about half of Twitter’s roughly 7,000 full-time employees had wide access to the company’s internal software and that access was not closely monitored, giving them the ability to tap into sensitive data and alter how the service worked. Three current and former employees agreed that these were issues.

An unnamed executive had prepared a presentation for the new CEO’s first full board meeting, according to the complaint. Zatko’s complaint calls the presentation deeply misleading.

The presentation showed that 92 percent of employee computers had security software installed — without mentioning that those installations determined that a third of the machines were insecure, according to the complaint.

Another graphic implied a downward trend in the number of people with overly broad access, based on the small subset of people who had access to the highest administrative powers, known internally as “God mode.” That number was in the hundreds. But the number of people with broad access to core systems, which Zatko had called out as a big problem after joining, had actually grown slightly and remained in the thousands.

The presentation included only a subset of serious intrusions or other security incidents, from a total Zatko estimated as one per week, and it said that the uncontrolled internal access to core systems was responsible for just 7 percent of incidents, when Zatko calculated the real proportion as 60 percent.

When Dorsey left in November 2021, a difficult situation worsened under Agrawal, who had been responsible for security decisions as chief technology officer before Zatko’s hiring, the complaint says.

Agrawal didn’t respond to requests for comment. In an email to employees after publication of this article, obtained by The Post, he said that privacy and security continues to be a top priority for the company, and he added that the narrative is “riddled with inconsistences” and “presented without important context.”

On Jan. 4, Zatko reported internally that the Risk Committee meeting might have been fraudulent, which triggered an Audit Committee investigation.

Agarwal fired him two weeks later. But Zatko complied with the company’s request to spell out his concerns in writing, even without access to his work email and documents, according to the complaint.

Since Zatko’s departure, Twitter has plunged further into chaos with Musk’s takeover, which the two parties agreed to in May. The stock price has fallen, many employees have quit, and Agrawal has dismissed executives and frozen big projects.

Zatko said he hoped that by bringing new scrutiny and accountability, he could improve the company from the outside.

“I still believe that this is a tremendous platform, and there is huge value and huge risk, and I hope that looking back at this, the world will be a better place, in part because of this.”

It was hard to get there, because I had to learn over and over again that extreme conviction requires extraordinary evidence, and the evidence we have is usually far from extraordinary.

Just as we solved many of the mysteries that befuddled our ancestors, our descendants will solve many of the mysteries that befuddle us. Our ignorance is profound, forgivable and temporary. There are only two true errors: One is believing that we have no errors left to make, and the other is believing that those errors are permanent and irreversible.

It’s hard to maintain this attitude when you realize just how much we have left to figure out. And we often have to cultivate this attitude for ourselves, because our educators and experts often fail to give it to us.

Experts, for their part, are perfectly comfortable issuing blanket recommendations with scant evidence and then shaming people for not following them.

Our teachers and officials may think the public simply can’t handle uncertainty, and maybe that’s why they project so much confidence, even when the science is faulty. But the best way to cultivate informed citizens is to give them the evidence that we have, not the evidence we wish we had.

Over the past four years, more than 1,600 cybercrime cases on TikTok have been reported to authorities, said Kuber Kadayat, a Nepal police spokesman. He said most of the complaints were related to sharing nude photos or financial extortion.

Last week, the government said it would require social-media companies running platforms used in Nepal to set up liaison offices in the country.

India banned TikTok—citing threats to national security—along with dozens of other Chinese apps in 2020 after a clash between Indian and Chinese troops on the countries’ disputed border.

Nepal isn’t the first to cite concerns about the content shared on the app. Pakistan has banned the app multiple times after authorities received complaints of indecent content, later lifting the bans after receiving promises from TikTok to better control the content. In August, Senegal blocked access to the app citing hateful and subversive content being shared on it.

“When you show people deepfakes and generative AI, a lot of times they come out of the experiment saying, ‘I just don’t trust anything anymore,’” says David Rand, a professor at MIT Sloan who studies the creation, spread and impact of misinformation.

This problem, which has grown more acute in the age of generative AI, is known as the “liar’s dividend,

The combination of easily-generated fake content and the suspicion that anything might be fake allows people to choose what they want to believe, adds DiResta, leading to what she calls “bespoke realities.”

Examples of misleading content created by generative AI are not hard to come by, especially on social media

The signs that an image is AI-generated are easy to miss for a user simply scrolling past, who has an instant to decide whether to like or boost a post on social media. And as generative AI continues to improve, it’s likely that such signs will be harder to spot in the future.

“What our work suggests is that most regular people do not want to share false things—the problem is they are not paying attention,”

in the course of a lawsuit over the death of a man using Tesla’s “full self-driving” system, Elon Musk’s lawyers responded to video evidence of Musk making claims about this software by suggesting that the proliferation of “deepfakes” of Musk was grounds to dismiss such evidence. They advanced that argument even though the clip of Musk was verifiably real

are now using its existence as a pretext to dismiss accurate information

People’s attention is already limited, and the way social media works—encouraging us to gorge on content, while quickly deciding whether or not to share it—leaves us precious little capacity to determine whether or not something is true

If the crisis of authenticity were limited to social media, we might be able to take solace in communication with those closest to us. But even those interactions are now potentially rife with AI-generated fakes.

what sounds like a call from a grandchild requesting bail money may be scammers who have scraped recordings of the grandchild’s voice from social media to dupe a grandparent into sending money.

companies like Alphabet, the parent company of Google, are trying to spin the altering of personal images as a good thing. 

With its latest Pixel phone, the company unveiled a suite of new and upgraded tools that can automatically replace a person’s face in one image with their face from another, or quickly remove someone from a photo entirely.

Joseph Stalin, who was fond of erasing people he didn’t like from official photos, would have loved this technology.

In Google’s defense, it is adding a record of whether an image was altered to data attached to it. But such metadata is only accessible in the original photo and some copies, and is easy enough to strip out.

The rapid adoption of many different AI tools means that we are now forced to question everything that we are exposed to in any medium, from our immediate communities to the geopolitical, said Hany Farid, a professor at the University of California, Berkeley who

To put our current moment in historical context, he notes that the PC revolution made it easy to store and replicate information, the internet made it easy to publish it, the mobile revolution made it easier than ever to access and spread, and the rise of AI has made creating misinformation a cinch. And each revolution arrived faster than the one before it.

Not everyone agrees that arming the public with easy access to AI will exacerbate our current difficulties with misinformation. The primary argument of such experts is that there is already vastly more misinformation on the internet than a person can consume, so throwing more into the mix won’t make things worse.

it’s not exactly reassuring, especially given that trust in institutions is already at one of the lowest points in the past 70 years, according to the nonpartisan Pew Research Center, and polarization—a measure of how much we distrust one another—is at a high point.

“What happens when we have eroded trust in media, government, and experts?” says Farid. “If you don’t trust me and I don’t trust you, how do we respond to pandemics, or climate change, or have fair and open elections? This is how authoritarianism arises—when you erode trust in institutions.”

The aim of an argument should not be proving who is right, but conveying that you care about the issues,

Show the person with whom you are speaking that you care about what he or she says.

The goal should be to state your views and to hear theirs. It should not be: “I am not leaving until you admit that you are wrong, or here is what I believe, and I am not budging from this,”

And when you listen, go all in

“Don’t half-listen while figuring out what you’re going to say next,”

Don’t ‘drop the anchor’

Some people start an argument by staking their position and refusing to budge, an impulse that Dr. Cuddy called “dropping the anchor.”Instead, try to understand the other person’s point of view; it does not mean you have to agree with him or her, or that you are abandoning deeply felt objections to, for example, racism or sexism, she said.

Mind your body languageYour body language can send messages that are more compelling than the words coming out of your mouth.Try to avoid gestures that are patronizing or defensive, like crossing your arms or clenching your jaw.

Maintain eye contact in a way that is not a stare-down.Lean forward slightly to show you are interested.And no eye-rolling,

Don’t argue to winDr. Gutting says it helps to use neutral or charitable language when acknowledging opposing viewpoints, especially during arguments over politics. It lays the groundwork for a more effective argument on points of genuine weakness.

Don’t think of an argument as an opportunity to convince the other person of your view; think of it as a way to test and improve your opinions, and to gain a better understanding of the other side.

“People do give up views because of rational arguments against them,” Dr. Gutting said in the interview. “But this is almost always a long process, not the outcome of a single decisive encounter.”

Know the factsA good argument is supported by evidence, but that is just a starting point. Sometimes, especially with political back-and-forths, one side will look only at evidence supporting its own position, conveniently leaving out the full picture,

Speak and listen fearlessly

“So for me, the condition for a conversation has to be that you are unafraid to speak courageously, and you are unafraid to tell your partner exactly what it is that you think about the world.”But a two-way argument also requires fearless listening, “even if it is me talking to a white supremacist who is trying to tell me that I am inferior,” he added. “One of the conditions for the possibility of a fruitful argument is to allow for some kind of opening up in myself to hear.”

“What you need to be able to do is to speak the same language,” he said. “They believe in God, and you would say: ‘You and I believe the same thing. How is it that this God who loves you can’t possibly love me?’ Is it possible that we can agree to disagree on some issues?”

Following what it described as Meta’s unsatisfactory response to its complaints, Match began canceling Meta advertising for some of its apps, such as Tinder, in October. It has since halted all Reels advertising and stopped promoting its major brands on any of Meta’s platforms. “We have no desire to pay Meta to market our brands to predators or place our ads anywhere near this content,” said Match spokeswoman Justine Sacco.

The Journal set up the test accounts after observing that the thousands of followers of such young people’s accounts often include large numbers of adult men, and that many of the accounts who followed those children also had demonstrated interest in sex content related to both children and adults

The Journal also tested what the algorithm would recommend after its accounts followed some of those users as well, which produced more-disturbing content interspersed with ads.

The Canadian Centre for Child Protection, a child-protection group, separately ran similar tests on its own, with similar results.

Meta said the Journal’s tests produced a manufactured experience that doesn’t represent what billions of users see. The company declined to comment on why the algorithms compiled streams of separate videos showing children, sex and advertisements, but a spokesman said that in October it introduced new brand safety tools that give advertisers greater control over where their ads appear, and that Instagram either removes or reduces the prominence of four million videos suspected of violating its standards each month. 

The Journal reported in June that algorithms run by Meta, which owns both Facebook and Instagram, connect large communities of users interested in pedophilic content. The Meta spokesman said a task force set up after the Journal’s article has expanded its automated systems for detecting users who behave suspiciously, taking down tens of thousands of such accounts each month. The company also is participating in a new industry coalition to share signs of potential child exploitation.

“Our systems are effective at reducing harmful content, and we’ve invested billions in safety, security and brand suitability solutions,” said Samantha Stetson, a Meta vice president who handles relations with the advertising industry. She said the prevalence of inappropriate content on Instagram is low, and that the company invests heavily in reducing it.

Even before the 2020 launch of Reels, Meta employees understood that the product posed safety concerns, according to former employees.

Robbie McKay, a spokesman for Bumble, said it “would never intentionally advertise adjacent to inappropriate content,” and that the company is suspending its ads across Meta’s platforms.

Meta created Reels to compete with TikTok, the video-sharing platform owned by Beijing-based ByteDance. Both products feed users a nonstop succession of videos posted by others, and make money by inserting ads among them. Both companies’ algorithms show to a user videos the platforms calculate are most likely to keep that user engaged, based on his or her past viewing behavior

The Journal reporters set up the Instagram test accounts as adults on newly purchased devices and followed the gymnasts, cheerleaders and other young influencers. The tests showed that following only the young girls triggered Instagram to begin serving videos from accounts promoting adult sex content alongside ads for major consumer brands, such as one for Walmart that ran after a video of a woman exposing her crotch. 

When the test accounts then followed some users who followed those same young people’s accounts, they yielded even more disturbing recommendations. The platform served a mix of adult pornography and child-sexualizing material, such as a video of a clothed girl caressing her torso and another of a child pantomiming a sex act.

Experts on algorithmic recommendation systems said the Journal’s tests showed that while gymnastics might appear to be an innocuous topic, Meta’s behavioral tracking has discerned that some Instagram users following preteen girls will want to engage with videos sexualizing children, and then directs such content toward them.

Instagram’s system served jarring doses of salacious content to those test accounts, including risqué footage of children as well as overtly sexual adult videos—and ads for some of the biggest U.S. brands.

Preventing the system from pushing noxious content to users interested in it, they said, requires significant changes to the recommendation algorithms that also drive engagement for normal users. Company documents reviewed by the Journal show that the company’s safety staffers are broadly barred from making changes to the platform that might reduce daily active users by any measurable amount.

The test accounts showed that advertisements were regularly added to the problematic Reels streams. Ads encouraging users to visit Disneyland for the holidays ran next to a video of an adult acting out having sex with her father, and another of a young woman in lingerie with fake blood dripping from her mouth. An ad for Hims ran shortly after a video depicting an apparently anguished woman in a sexual situation along with a link to what was described as “the full video.”

Current and former Meta employees said in interviews that the tendency of Instagram algorithms to aggregate child sexualization content from across its platform was known internally to be a problem. Once Instagram pigeonholes a user as interested in any particular subject matter, they said, its recommendation systems are trained to push more related content to them.

Part of the problem is that automated enforcement systems have a harder time parsing video content than text or still images. Another difficulty arises from how Reels works: Rather than showing content shared by users’ friends, the way other parts of Instagram and Facebook often do, Reels promotes videos from sources they don’t follow

In an analysis conducted shortly before the introduction of Reels, Meta’s safety staff flagged the risk that the product would chain together videos of children and inappropriate content, according to two former staffers. Vaishnavi J, Meta’s former head of youth policy, described the safety review’s recommendation as: “Either we ramp up our content detection capabilities, or we don’t recommend any minor content,” meaning any videos of children.

At the time, TikTok was growing rapidly, drawing the attention of Instagram’s young users and the advertisers targeting them. Meta didn’t adopt either of the safety analysis’s recommendations at that time, according to J.

Stetson, Meta’s liaison with digital-ad buyers, disputed that Meta had neglected child safety concerns ahead of the product’s launch. “We tested Reels for nearly a year before releasing it widely, with a robust set of safety controls and measures,” she said. 

After initially struggling to maximize the revenue potential of its Reels product, Meta has improved how its algorithms recommend content and personalize video streams for users

Among the ads that appeared regularly in the Journal’s test accounts were those for “dating” apps and livestreaming platforms featuring adult nudity, massage parlors offering “happy endings” and artificial-intelligence chatbots built for cybersex. Meta’s rules are supposed to prohibit such ads.

The Journal informed Meta in August about the results of its testing. In the months since then, tests by both the Journal and the Canadian Centre for Child Protection show that the platform continued to serve up a series of videos featuring young children, adult content and apparent promotions for child sex material hosted elsewhere. 

As of mid-November, the center said Instagram is continuing to steadily recommend what the nonprofit described as “adults and children doing sexual posing.”

Meta hasn’t offered a timetable for resolving the problem or explained how in the future it would restrict the promotion of inappropriate content featuring children. 

The Journal’s test accounts found that the problem even affected Meta-related brands. Ads for the company’s WhatsApp encrypted chat service and Meta’s Ray-Ban Stories glasses appeared next to adult pornography. An ad for Lean In Girls, the young women’s empowerment nonprofit run by former Meta Chief Operating Officer Sheryl Sandberg, ran directly before a promotion for an adult sex-content creator who often appears in schoolgirl attire. Sandberg declined to comment. 

Through its own tests, the Canadian Centre for Child Protection concluded that Instagram was regularly serving videos and pictures of clothed children who also appear in the National Center for Missing and Exploited Children’s digital database of images and videos confirmed to be child abuse sexual material. The group said child abusers often use the images of the girls to advertise illegal content for sale in dark-web forums.

The nature of the content—sexualizing children without generally showing nudity—reflects the way that social media has changed online child sexual abuse, said Lianna McDonald, executive director for the Canadian center. The group has raised concerns about the ability of Meta’s algorithms to essentially recruit new members of online communities devoted to child sexual abuse, where links to illicit content in more private forums proliferate.

“Time and time again, we’ve seen recommendation algorithms drive users to discover and then spiral inside of these online child exploitation communities,” McDonald said, calling it disturbing that ads from major companies were subsidizing that process.

Behavioral economics is at the center of the so-called replication crisis, a euphemism for the uncomfortable fact that the results of a significant percentage of social science experiments can’t be reproduced in subsequent trials

this key result was not replicated in similar experiments, undermining confidence in a whole area of study. It’s obvious that we do associate old age and slower walking, and we probably do slow down sometimes when thinking about older people. It’s just not clear that that’s a law of the mind.

And these attempts to “correct” human behavior are based on tenuous science. The replication crisis doesn’t have a simple solution

Journals have instituted reforms like having scientists preregister their hypotheses to avoid the possibility of results being manipulated during the research. But that doesn’t change how many uncertain results are already out there, with a knock-on effect that ripples through huge segments of quantitative social scienc

The Johns Hopkins science historian Ruth Leys, author of a forthcoming book on priming research, points out that cognitive science is especially prone to building future studies off disputed results. Despite the replication crisis, these fields are a “train on wheels, the track is laid and almost nothing stops them,” Dr. Leys said.

These cases result from lax standards around data collection, which will hopefully be corrected. But they also result from strong financial incentives: the possibility of salaries, book deals and speaking and consulting fees that range into the millions. Researchers can get those prizes only if they can show “significant” findings.

It is no coincidence that behavioral economics, from Dr. Kahneman to today, tends to be pro-business. Science should be not just reproducible, but also free of obvious ideology.

Technology and modern data science have only further entrenched behavioral economics. Its findings have greatly influenced algorithm design.

The collection of personal data about our movements, purchases and preferences inform interventions in our behavior from the grocery store to who is arrested by the police.

Setting people up for safety and success and providing good default options isn’t bad in itself, but there are more sinister uses as well. After all, not everyone who wants to exploit your cognitive biases has your best interests at heart.

Despite all its flaws, behavioral economics continues to drive public policy, market research and the design of digital interfaces.

One might think that a kind of moratorium on applying such dubious science would be in order — except that enacting one would be practically impossible. These ideas are so embedded in our institutions and everyday life that a full-scale audit of the behavioral sciences would require bringing much of our society to a standstill.

There is no peer review for algorithms that determine entry to a stadium or access to credit. To perform even the most banal, everyday actions, you have to put implicit trust in unverified scientific results.

We can’t afford to defer questions about human nature, and the social and political policies that come from them, to commercialized “research” that is scientifically questionable and driven by ideology. Behavioral economics claims that humans aren’t rational.

That’s a philosophical claim, not a scientific one, and it should be fought out in a rigorous marketplace of ideas. Instead of unearthing real, valuable knowledge of human nature, behavioral economics gives us “one weird trick” to lose weight or quit smoking.

Humans may not be perfectly rational, but we can do better than the predictably irrational consequences that behavioral economics has left us with today.

it lacks practical application. If humans found something on another planet that seemed to be alive, how much time would we have to sit around and wait for it to evolve?

The only life we know is life on Earth. Some scientists call this the n=1 problem, where n is the number of examples from which we can generalize.

Cronin studies the origin of life, also a major interest of Walker’s, and it turned out that, when expressed in math, their ideas were essentially the same. They had both zeroed in on complexity as a hallmark of life. Cronin is devising a way to systematize and measure complexity, which he calls Assembly Theory.

What we really want is more than a definition of life. We want to know what life, fundamentally, is. For that kind of understanding, scientists turn to theories. A theory is a scientific fundamental. It not only answers questions, but frames them, opening new lines of inquiry. It explains our observations and yields predictions for future experiments to test.

Consider the difference between defining gravity as “the force that makes an apple fall to the ground” and explaining it, as Newton did, as the universal attraction between all particles in the universe, proportional to the product of their masses and so on. A definition tells us what we already know; a theory changes how we understand things.

the potential rewards of unlocking a theory of life have captivated a clutch of researchers from a diverse set of disciplines. “There are certain things in life that seem very hard to explain,” Sara Imari Walker, a physicist at Arizona State University who has been at the vanguard of this work, told me. “If you scratch under the surface, I think there is some structure that suggests formalization and mathematical laws.”

Walker doesn’t think about life as a biologist—or an astrobiologist—does. When she talks about signs of life, she doesn’t talk about carbon, or water, or RNA, or phosphine. She reaches for different examples: a cup, a cellphone, a chair. These objects are not alive, of course, but they’re clearly products of life. In Walker’s view, this is because of their complexity. Life brings complexity into the universe, she says, in its own being and in its products, because it has memory: in DNA, in repeating molecular reactions, in the instructions for making a chair.

He measures the complexity of an object—say, a molecule—by calculating the number of steps necessary to put the object’s smallest building blocks together in that certain way. His lab has found, for example, when testing a wide range of molecules, that those with an “assembly number” above 15 were exclusively the products of life. Life makes some simpler molecules, too, but only life seems to make molecules that are so complex.

I reach for the theory of gravity as a familiar parallel. Someone might ask, “Okay, so in terms of gravity, where are we in terms of our understanding of life? Like, Newton?” Further back, further back, I say. Walker compares us to pre-Copernican astronomers, reliant on epicycles, little orbits within orbits, to make sense of the motion we observe in the sky. Cleland has put it in terms of chemistry, in which case we’re alchemists, not even true chemists yet

Walker’s whole notion is that it’s not only theoretically possible but genuinely achievable to identify something smaller—much smaller—that still nonetheless simply must be the result of life. The model would, in a sense, function like biosignatures as an indication of life that could be searched for. But it would drastically improve and expand the targets.

Walker would use the theory to predict what life on a given planet might look like. It would require knowing a lot about the planet—information we might have about Venus, but not yet about a distant exoplanet—but, crucially, would not depend at all on how life on Earth works, what life on Earth might do with those materials.

Without the ability to divorce the search for alien life from the example of life we know, Walker thinks, a search is almost pointless. “Any small fluctuations in simple chemistry can actually drive you down really radically different evolutionary pathways,” she told me. “I can’t imagine [life] inventing the same biochemistry on two worlds.”

Walker’s approach is grounded in the work of, among others, the philosopher of science Carol Cleland, who wrote The Quest for a Universal Theory of Life.

she warns that any theory of life, just like a definition, cannot be constrained by the one example of life we currently know. “It’s a mistake to start theorizing on the basis of a single example, even if you’re trying hard not to be Earth-centric. Because you’re going to be Earth-centric,” Cleland told me. In other words, until we find other examples of life, we won’t have enough data from which to devise a theory. Abstracting away from Earthliness isn’t a way to be agnostic, Cleland argues. It’s a way to be too abstract.

Cleland calls for a more flexible search guided by what she calls “tentative criteria.” Such a search would have a sense of what we’re looking for, but also be open to anomalies that challenge our preconceptions, detections that aren’t life as we expected but aren’t familiar not-life either—neither a flower nor a rock

it speaks to the hope that exploration and discovery might truly expand our understanding of the cosmos and our own world.

The astrobiologist Kimberley Warren-Rhodes studies life on Earth that lives at the borders of known habitability, such as in Chile’s Atacama Desert. The point of her experiments is to better understand how life might persist—and how it might be found—on Mars. “Biology follows some rules,” she told me. The more of those rules you observe, the better sense you have of where to look on other worlds.

In this light, the most immediate concern in our search for extraterrestrial life might be less that we only know about life on Earth, and more that we don’t even know that much about life on Earth in the first place. “I would say we understand about 5 percent,” Warren-Rhodes estimates of our cumulative knowledge. N=1 is a problem, and we might be at more like n=.05.

who knows how strange life on another world might be? What if life as we know it is the wrong life to be looking for?

We understand so little, and we think we’re ready to find other life?

Rather, our conversations are mediated through institutions like journals and newspapers and social-media platforms. They rely on a dense network of norms and rules, like truthfulness and fact-checking. They depend on the expertise of professionals, like peer reviewers and editors. The entire system rests on a foundation of values: a shared understanding that there are right and wrong ways to make knowledge.

Those values and rules and institutions do for knowledge what the U.S. Constitution does for politics: They create a governing structure, forcing social contestation onto peaceful and productive pathways.

I call them, collectively, the Constitution of Knowledge. If we want to defend that system from its many persistent attackers, we need to understand it—and its very special notion of reality.

What reality really is

The question “What is reality?” may seem either too metaphysical to answer meaningfully or too obvious to need answering

The whole problem is that humans have no direct access to an objective world independent of our minds and senses, and subjective certainty is no guarantee of truth. Faced with those problems and others, philosophers and practitioners think of reality as a set of propositions (or claims, or statements) that have been validated in some way, and that have thereby been shown to be at least conditionally true—true, that is, unless debunked

Some propositions reflect reality as we perceive it in everyday life (“The sky is blue”). Others, like the equations on a quantum physicist’s blackboard, are incomprehensible to intuition. Many fall somewhere in between.

a phrase I used a few sentences ago, “validated in some way,” hides a cheat. In epistemology, the whole question is, validated in what way? If we care about knowledge, freedom, and peace, then we need to stake a strong claim: Anyone can believe anything, but liberal science—open-ended, depersonalized checking by an error-seeking social network—is the only legitimate validator of knowledge, at least in the reality-based community.

That is a very bold, very broad, very tough claim, and it goes down very badly with lots of people and communities who feel ignored or oppressed by the Constitution of Knowledge: creationists, Christian Scientists, homeopaths, astrologists, flat-earthers, anti-vaxxers, birthers, 9/11 truthers, postmodern professors, political partisans, QAnon followers, and adherents of any number of other belief systems and religions.

But, like the U.S. Constitution’s claim to exclusivity in governing (“unconstitutional” means “illegal,” period), the Constitution of Knowledge’s claim to exclusivity is its sine qua non.

Rules for reality

The specific proposition does not matter. What does matter is that the only way to validate it is to submit it to the reality-based community. Otherwise, you could win dominance for your proposition by, say, brute force, threatening and jailing and torturing and killing those who see things differently—a standard method down through history

Say you believe something (X) to be true, and you believe that its acceptance as true by others is important or at least warranted

Or you and your like-minded friends could go off and talk only to each other, in which case you would have founded a cult—which is lawful but socially divisive and epistemically worthless.

Or you could engage in a social-media campaign to shame and intimidate those who disagree with you—a very common method these days, but one that stifles debate and throttles knowledge (and harms a lot of people).

What the reality-based community does is something else again. Its distinctive qualities derive from two core rules: 

what counts is the way the rule directs us to behave: You must assume your own and everyone else’s fallibility and you must hunt for your own and others’ errors, even if you are confident you are right. Otherwise, you are not reality-based.

The fallibilist rule: No one gets the final say. You may claim that a statement is established as knowledge only if it can be debunked, in principle, and only insofar as it withstands attempts to debunk it.

The empirical rule: No one has personal authority. You may claim that a statement has been established as knowledge only insofar as the method used to check it gives the same result regardless of the identity of the checker, and regardless of the source of the statement

Who you are does not count; the rules apply to everybody and persons are interchangeable. If your method is valid only for you or your affinity group or people who believe as you do, then you are not reality-based.

Whatever you do to check a proposition must be something that anyone can do, at least in principle, and get the same result. Also, no one proposing a hypothesis gets a free pass simply because of who she is or what group she belongs to.

Both rules have very profound social implications. “No final say” insists that to be knowledge, a statement must be checked; and it also says that knowledge is always provisional, standing only as long as it withstands checking.

“No personal authority” adds a crucial second step by defining what properly counts as checking. The point, as the great American philosopher Charles Sanders Peirce emphasized more than a century ago, is not that I look or you look but that we look; and then we compare, contest, and justify our views. Critically, then, the empirical rule is a social principle that forces us into the same conversation—a requirement that all of us, however different our viewpoints, agree to discuss what is in principle only one reality.

By extension, the empirical rule also dictates what does not count as checking: claims to authority by dint of a personally or tribally privileged perspective.

In principle, persons and groups are interchangeable. If I claim access to divine revelation, or if I claim the support of miracles that only believers can witness, or if I claim that my class or race or historically dominant status or historically oppressed status allows me to know and say things that others cannot, then I am breaking the empirical rule by exempting my views from contestability by others.

Though seemingly simple, the two rules define a style of social learning that prohibits a lot of the rhetorical moves we see every day.

Claiming that a conversation is too dangerous or blasphemous or oppressive or traumatizing to tolerate will almost always break the fallibilist rule.

Claims which begin “as a Jew,” or “as a queer,” or for that matter “as minister of information” or “as Pope” or “as head of the Supreme Soviet,” can be valid if they provide useful information about context or credentials; but if they claim to settle an argument by appealing to personal or tribal authority, rather than earned authority, they violate the empirical rule. 

“No personal authority” says nothing against trying to understand where people are coming from. If we are debating same-sex marriage, I may mention my experience as a gay person, and my experience may (I hope) be relevant.

But statements about personal standing and interest inform the conversation; they do not control it, dominate it, or end it. The rule acknowledges, and to an extent accepts, that people’s social positions and histories matter; but it asks its adherents not to burrow into their social identities, and not to play them as rhetorical trump cards, but to bring them to the larger project of knowledge-building and thereby transcend them.

the fallibilist and empirical rules are the common basis of science, journalism, law, and all the other branches of today’s reality-based community. For that reason, both rules also attract hostility, defiance, interference, and open warfare from those who would rather manipulate truth than advance it.

Above all, the manual emphasized efficiency. Managers were told to answer DMs in less than five minutes, since users were coming to OnlyFans for immediate gratification and would go elsewhere if ignored. It encouraged the creation of keyboard shortcuts, so that managers could deploy an arsenal of rote sexual phrases with a few keystrokes, steering conversations toward the hard sell. It also outlined a series of strategies to boost engagement on the pages, including a gambit in which models would offer to rate a picture of a subscriber’s penis for a fee.

“Every page needs to have an established back story to make the person seem more believable,” it stated. OnlyFans works because people pay for a connection that feels deeper than porn. The document encouraged Ekko’s employees, called page managers, to identify “big spenders” who would part ways with more than $200 in short order, and cultivate a deep rapport by asking about their life and what they do for a living.

This can be extremely time-consuming: In an interview with this magazine last year, an OnlyFans creator said she spends six hours a day just sexting with subscribers. But these relationships are important to cultivate. In a blog post on its website, OnlyFans encourages creators to cater to their “superfans,” who pay for custom content and will “give more if they feel they’re getting something special.”

But all of them take advantage of the same raw materials: the endless reproducibility of digital images; the widespread global availability of cheap English-speaking labor; and the world’s unquenchable desire for companionship.

The key to this business model is the ready availability of cheap English-speaking labor around the globe. Job postings for OnlyFans chatters are widespread on freelance sites like Upwork, many offering as little as $3 an hour. Agency heads told me they’ve hired workers from Eastern Europe, Africa and all across Southeast Asia. “At the end of the day, it is a geo-arbitrage business,”

This phenomenon is part of a broader boom in homespun online businesses that connect cheap developing-world labor with American consumers, allowing the proprietor to step back and reap the profits

During his stint as a chatter, Andre has become intimately familiar with the quirks and desires of the subscribers. Over time, he’s learned something of a sex-work cliché: More than sexual gratification, he said, many of the guys just want someone to talk to

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Pew Research Center survey asked people different questions but found similar doubts about AI. Just 15 percent of respondents said they were more excited than concerned about the increasing use of AI in daily life.

“It’s fantastic that there is public skepticism about AI. There absolutely should be,” said Meredith Broussard, an artificial intelligence researcher and professor at New York University.

Broussard said there can be no way to design artificial intelligence software to make inherently human decisions, like grading students’ tests or determining the course of medical treatment.

Most Americans essentially agree with Broussard that AI has a place in our lives, but not for everything.

Most people said it was a bad idea to use AI for military drones that try to distinguish between enemies and civilians or trucks making local deliveries without human drivers. Most respondents said it was a good idea for machines to perform risky jobs such as coal mining.

Roman Yampolskiy, an AI specialist at the University of Louisville engineering school, told me he’s concerned about how quickly technologists are building computers that are designed to “think” like the human brain and apply knowledge not just in one narrow area, like recommending Netflix movies, but for complex tasks that have tended to require human intelligence.

“We have an arms race between multiple untested technologies. That is my concern,” Yampolskiy said. (If you want to feel terrified, I recommend Yampolskiy’s research paper on the inability to control advanced AI.)

The term “AI” is a catch-all for everything from relatively uncontroversial technology, such as autocomplete in your web search queries, to the contentious software that promises to predict crime before it happens. Our fears about the latter might be overwhelming our beliefs about the benefits from more mundane AI.

In the days following the disappearance of the columnist Jamal Khashoggi, Arabic-language social media erupted in support for Crown Prince Mohammed bin Salman, who was widely rumored to have ordered his murder. On a single day in October, the phrase “we all have trust in Mohammed bin Salman” featured in 250,000 tweets. “We have to stand by our leader” was posted more than 60,000 times, along with 100,000 messages imploring Saudis to “Unfollow enemies of the nation.” In all likelihood, the majority of these messages were generated by chatbots.

around a fifth of all tweets discussing the 2016 presidential election are believed to have been the work of chatbots.

a third of all traffic on Twitter before the 2016 referendum on Britain’s membership in the European Union was said to come from chatbots, principally in support of the Leave side.

It’s irrelevant that current bots are not “smart” like we are, or that they have not achieved the consciousness and creativity hoped for by A.I. purists. What matters is their impact

In the past, despite our differences, we could at least take for granted that all participants in the political process were human beings. This no longer true

Increasingly we share the online debate chamber with nonhuman entities that are rapidly growing more advanced

a bot developed by the British firm Babylon reportedly achieved a score of 81 percent in the clinical examination for admission to the Royal College of General Practitioners. The average score for human doctors? 72 percent.

If chatbots are approaching the stage where they can answer diagnostic questions as well or better than human doctors, then it’s possible they might eventually reach or surpass our levels of political sophistication

chatbots could seriously endanger our democracy, and not just when they go haywire.

They’ll likely have faces and voices, names and personalities — all engineered for maximum persuasion. So-called “deep fake” videos can already convincingly synthesize the speech and appearance of real politicians.

The most obvious risk is that we are crowded out of our own deliberative processes by systems that are too fast and too ubiquitous for us to keep up with.

A related risk is that wealthy people will be able to afford the best chatbots.

in a world where, increasingly, the only feasible way of engaging in debate with chatbots is through the deployment of other chatbots also possessed of the same speed and facility, the worry is that in the long run we’ll become effectively excluded from our own party.

the wholesale automation of deliberation would be an unfortunate development in democratic history.

A blunt approach — call it disqualification — would be an all-out prohibition of bots on forums where important political speech takes place, and punishment for the humans responsible

The Bot Disclosure and Accountability Bil

would amend the Federal Election Campaign Act of 1971 to prohibit candidates and political parties from using any bots intended to impersonate or replicate human activity for public communication. It would also stop PACs, corporations and labor organizations from using bots to disseminate messages advocating candidates, which would be considered “electioneering communications.”

A subtler method would involve mandatory identification: requiring all chatbots to be publicly registered and to state at all times the fact that they are chatbots, and the identity of their human owners and controllers.

We should also be exploring more imaginative forms of regulation. Why not introduce a rule, coded into platforms themselves, that bots may make only up to a specific number of online contributions per day, or a specific number of responses to a particular human?

We need not treat the speech of chatbots with the same reverence that we treat human speech. Moreover, bots are too fast and tricky to be subject to ordinary rules of debate

the methods we use to regulate bots must be more robust than those we apply to people. There can be no half-measures when democracy is at stake.

The volatility of chatbots has made it impossible to predict their impact. In one second, the systems impress by fielding a complex request for a five-day itinerary, making Google’s search engine look archaic. A moment later, they disturb by taking conversations in dark directions and launching verbal assaults.

The result is an industry gripped with the question: What do we do now?

The A.I. systems could disrupt $100 billion in cloud spending, $500 billion in digital advertising and $5.4 trillion in e-commerce sales,

As Microsoft figures out a chatbot business model, it is forging ahead with plans to sell the technology to others. It charges $10 a month for a cloud service, built in conjunction with the OpenAI lab, that provides developers with coding suggestions, among other things.

Smaller companies like Box need help building chatbot tools, so they are turning to the giants that process, store and manage information across the web. Those companies — Google, Microsoft and Amazon — are in a race to provide businesses with the software and substantial computing power behind their A.I. chatbots.

“The cloud computing providers have gone all in on A.I. over the last few months,

“They are realizing that in a few years, most of the spending will be on A.I., so it is important for them to make big bets.”

Yusuf Mehdi, the head of Bing, said the company was wrestling with how the new version would make money. Advertising will be a major driver, he said, but the company expects fewer ads than traditional search allows.

Google, perhaps more than any other company, has reason to both love and hate the chatbots. It has declared a “code red” because their abilities could be a blow to its $162 billion business showing ads on searches.

“The discourse on A.I. is rather narrow and focused on text and the chat experience,” Mr. Taylor said. “Our vision for search is about understanding information and all its forms: language, images, video, navigating the real world.”

Sridhar Ramaswamy, who led Google’s advertising division from 2013 to 2018, said Microsoft and Google recognized that their current search business might not survive. “The wall of ads and sea of blue links is a thing of the past,” said Mr. Ramaswamy, who now runs Neeva, a subscription-based search engine.

As that underlying tech, known as generative A.I., becomes more widely available, it could fuel new ideas in e-commerce. Late last year, Manish Chandra, the chief executive of Poshmark, a popular online secondhand store, found himself daydreaming during a long flight from India about chatbots building profiles of people’s tastes, then recommending and buying clothes or electronics. He imagined grocers instantly fulfilling orders for a recipe.

“It becomes your mini-Amazon,” said Mr. Chandra, who has made integrating generative A.I. into Poshmark one of the company’s top priorities over the next three years. “That layer is going to be very powerful and disruptive and start almost a new layer of retail.”

In early December, users of Stack Overflow, a popular social network for computer programmers, began posting substandard coding advice written by ChatGPT. Moderators quickly banned A.I.-generated text

t people could post this questionable content far faster than they could write posts on their own, said Dennis Soemers, a moderator for the site. “Content generated by ChatGPT looks trustworthy and professional, but often isn’t,”

When websites thrived during the pandemic as traffic from Google surged, Nilay Patel, editor in chief of The Verge, a tech news site, warned publishers that the search giant would one day turn off the spigot. He had seen Facebook stop linking out to websites and foresaw Google following suit in a bid to boost its own business.

He predicted that visitors from Google would drop from a third of websites’ traffic to nothing. He called that day “Google zero.”

Because chatbots replace website search links with footnotes to answers, he said, many publishers are now asking if his prophecy is coming true.

, strategists and engineers at the digital advertising company CafeMedia have met twice a week to contemplate a future where A.I. chatbots replace search engines and squeeze web traffic.

The group recently discussed what websites should do if chatbots lift information but send fewer visitors. One possible solution would be to encourage CafeMedia’s network of 4,200 websites to insert code that limited A.I. companies from taking content, a practice currently allowed because it contributes to search rankings.

Courts are expected to be the ultimate arbiter of content ownership. Last month, Getty Images sued Stability AI, the start-up behind the art generator tool Stable Diffusion, accusing it of unlawfully copying millions of images. The Wall Street Journal has said using its articles to train an A.I. system requires a license.

In the meantime, A.I. companies continue collecting information across the web under the “fair use” doctrine, which permits limited use of material without permission.

“My first and biggest wish is that we had known early that Covid-19 was airborne,”

, “Once you’ve realized that, it informs an entirely different strategy for protection.” Masking, ventilation and air cleaning become key, as well as avoiding high-risk encounters with strangers, he says.

Instead of washing our produce and wearing hand-sewn cloth masks, we could have made sure to avoid superspreader events and worn more-effective N95 masks or their equivalent. “We could have made more of an effort to develop and distribute N95s to everyone,” says Dr. Volckens. “We could have had an Operation Warp Speed for masks.”

We didn’t realize how important clear, straight talk would be to maintaining public trust. If we had, we could have explained the biological nature of a virus and warned that Covid-19 would change in unpredictable ways.  

We didn’t know how difficult it would be to get the basic data needed to make good public-health and medical decisions. If we’d had the data, we could have more effectively allocated scarce resources

In the face of a pandemic, he says, the public needs an early basic and blunt lesson in virology

and mutates, and since we’ve never seen this particular virus before, we will need to take unprecedented actions and we will make mistakes, he says.

Since the public wasn’t prepared, “people weren’t able to pivot when the knowledge changed,”

By the time the vaccines became available, public trust had been eroded by myriad contradictory messages—about the usefulness of masks, the ways in which the virus could be spread, and whether the virus would have an end date.

, the absence of a single, trusted source of clear information meant that many people gave up on trying to stay current or dismissed the different points of advice as partisan and untrustworthy.

“The science is really important, but if you don’t get the trust and communication right, it can only take you so far,”

people didn’t know whether it was OK to visit elderly relatives or go to a dinner party.

Doctors didn’t know what medicines worked. Governors and mayors didn’t have the information they needed to know whether to require masks. School officials lacked the information needed to know whether it was safe to open schools.

Had we known that even a mild case of Covid-19 could result in long Covid and other serious chronic health problems, we might have calculated our own personal risk differently and taken more care.

just months before the outbreak of the pandemic, the Council of State and Territorial Epidemiologists released a white paper detailing the urgent need to modernize the nation’s public-health system still reliant on manual data collection methods—paper records, phone calls, spreadsheets and faxes.

While the U.K. and Israel were collecting and disseminating Covid case data promptly, in the U.S. the CDC couldn’t. It didn’t have a centralized health-data collection system like those countries did, but rather relied on voluntary reporting by underfunded state and local public-health systems and hospitals.

doctors and scientists say they had to depend on information from Israel, the U.K. and South Africa to understand the nature of new variants and the effectiveness of treatments and vaccines. They relied heavily on private data collection efforts such as a dashboard at Johns Hopkins University’s Coronavirus Resource Center that tallied cases, deaths and vaccine rates globally.

For much of the pandemic, doctors, epidemiologists, and state and local governments had no way to find out in real time how many people were contracting Covid-19, getting hospitalized and dying

To solve the data problem, Dr. Ranney says, we need to build a public-health system that can collect and disseminate data and acts like an electrical grid. The power company sees a storm coming and lines up repair crews.

If we’d known how damaging lockdowns would be to mental health, physical health and the economy, we could have taken a more strategic approach to closing businesses and keeping people at home.

t many doctors say they were crucial at the start of the pandemic to give doctors and hospitals a chance to figure out how to accommodate and treat the avalanche of very sick patients.

The measures reduced deaths, according to many studies—but at a steep cost.

The lockdowns didn’t have to be so harmful, some scientists say. They could have been more carefully tailored to protect the most vulnerable, such as those in nursing homes and retirement communities, and to minimize widespread disruption.

Lockdowns could, during Covid-19 surges, close places such as bars and restaurants where the virus is most likely to spread, while allowing other businesses to stay open with safety precautions like masking and ventilation in place.  

The key isn’t to have the lockdowns last a long time, but that they are deployed earlier,

If England’s March 23, 2020, lockdown had begun one week earlier, the measure would have nearly halved the estimated 48,600 deaths in the first wave of England’s pandemic

If the lockdown had begun a week later, deaths in the same period would have more than doubled

It is possible to avoid lockdowns altogether. Taiwan, South Korea and Hong Kong—all countries experienced at handling disease outbreaks such as SARS in 2003 and MERS—avoided lockdowns by widespread masking, tracking the spread of the virus through testing and contact tracing and quarantining infected individuals.

With good data, Dr. Ranney says, she could have better managed staffing and taken steps to alleviate the strain on doctors and nurses by arranging child care for them.

Early in the pandemic, public-health officials were clear: The people at increased risk for severe Covid-19 illness were older, immunocompromised, had chronic kidney disease, Type 2 diabetes or serious heart conditions

t had the unfortunate effect of giving a false sense of security to people who weren’t in those high-risk categories. Once case rates dropped, vaccines became available and fear of the virus wore off, many people let their guard down, ditching masks, spending time in crowded indoor places.

it has become clear that even people with mild cases of Covid-19 can develop long-term serious and debilitating diseases. Long Covid, whose symptoms include months of persistent fatigue, shortness of breath, muscle aches and brain fog, hasn’t been the virus’s only nasty surprise

In February 2022, a study found that, for at least a year, people who had Covid-19 had a substantially increased risk of heart disease—even people who were younger and had not been hospitalized

respiratory conditions.

Some scientists now suspect that Covid-19 might be capable of affecting nearly every organ system in the body. It may play a role in the activation of dormant viruses and latent autoimmune conditions people didn’t know they had

 A blood test, he says, would tell people if they are at higher risk of long Covid and whether they should have antivirals on hand to take right away should they contract Covid-19.

If the risks of long Covid had been known, would people have reacted differently, especially given the confusion over masks and lockdowns and variants? Perhaps. At the least, many people might not have assumed they were out of the woods just because they didn’t have any of the risk factors.

Making friends can be hard—but there may be more opportunities than we think. Doing these interviews has taught me that connection can come from anywhere, at any time, if both parties are open to it.

“You have to look for friendship in places you would never expect it.”

Paying attention goes a long way when forging these unexpected friendships—noticing when you click with someone, being open to chance encounters.

as much as we may feel like our social networks are set and settled, it’s never too late to meet someone who will be important to you for the rest of your life. I spoke with more than one group who was surprised and grateful to have found one another in middle age, a period when work and family responsibilities tend to peak and keeping up with friends is not always easy.

I’m inspired by the people I’ve spoken with who imagined something different for themselves: the friends who bought a house together, who went to therapy together, who have raised their children together, who committed to an “arranged friendship,” whose friendship has fueled their fight for justice.

they won’t grow without intention. This is the hardest part of friendship. It takes energy and thought, and our mental and physical resources are often spread thin. In other words, friendships take work. But I have never liked framing our friendships as labor. Showing up for our friends takes effort, yes, but it shouldn’t be drudgery. It should be a joy.

One thing that seems to make keeping up with friends easier is ritual. I personally find that the effort of coordinating hangs (or even phone calls) is the biggest barrier to seeing my friends. It’s much easier when something is baked into my schedule, and all I have to do is show up.

Some have organized a book club, a monthly hike, or a regular dinner party. Others have committed to a group chat that runs all day every day, or a Dungeons & Dragons campaign that’s lasted for 30 years. In addition to keeping groups close, these traditions can fuel a friendship and give it a shared culture.

Imagination

Society has a place for friendships, and it’s on the sidelines. They’re supposed to play a supporting role to work, family, and romance. It takes imagination not to default to this norm, and to design your life so that friendship plays the role you really want it to.

Attention only gets you so far without action. When opportunity arises, you have to put yourself out there, and that requires courage, vulnerability, and a willingness to let things be awkward.

The man who gave his friend a kidney and the woman who gave birth to her best friend’s quadruplets remind me that there are friends who choose to love each other radically every day. Their love does not stand on the sidelines.

The beauty and the challenge of friendship is its diversity. A friendship can be whatever you want it to. Each one is a canvas whose only limit is our imagination.

Grace

All of the forces I’ve mentioned so far—accumulation, attention, intention, ritual, and imagination—are ideals. They’re impossible to fully live up to. Life often gets in the way.

I do love the concept of grace, of a gift so profound that it could never be earned or deserved. And so when I cite grace here as the final and most important force in friendships, I mean it in two ways. One is the forgiveness that we offer each other when we fall short. The other is the space that creates for connections—and reconnections—that feel nothing short of miraculous.

Many of the people I spoke with—who, in many cases, love each other so much that they nominated themselves to be interviewed about their friendship—told me that they don’t see each other that often, or that they don’t talk as much as they would like. I’ve come to believe that friendship doesn’t always have to be about presence; it can also be about love that can weather absence.

Sometimes, people have assumed that I must be a really great friend, given how much time I’ve spent thinking about this. And I’m not. I try to be, but I tend to retreat too much into myself and my romantic relationship and don’t prioritize my friends as much as I’d like to.

But absence doesn’t have to last forever. “The Friendship Files” includes many stories of second chances and rekindlings.

Accumulation

Attention

Intention

Ritual