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This made the employee feel like remote work was just another set of disempowering rules.

Workers clearly felt empowered by having more control over their own work life. Companies must give people choices that match their unique work and life needs.

People crave predictability. Surprises make it harder for employees to plan their lives and have peace of mind. When constant change is inflicted on them, without a chance to anticipate it or participate in decisions about it, people get anxious and passive, and dream of escape.

For instance, workers who get unexpected spot bonuses sometimes feel that they don't know what to count on when calculating their future compensation; they'd rather have a predictable total package.

People thrive when their value is acknowledged by getting more responsibility, recognition and stature, such as a bigger title.

Jobs that convey a sense of purpose and meaning are more likely to exercise an emotional hold on people. Whether or not the company overall thinks it stands for social responsibility, people want to see that chance to make a difference in their immediate work experience.

Conventional wisdom holds that the best way to improve employment circumstances is to get an offer from a new company. That shouldn't have to be the case. Managers who want to retain people should act as if they are just now hiring them.

The best labor pool could be the one companies already have. They should treat their people as a precious resource and give them what they want from work. Rewarding them will reward the business.

The former president also compared Ukrainian leader Volodymyr Zelenskyy to Britain’s wartime leader Winston Churchill, while condemning Russian President Vladimir Putin for launching the invasion of Ukraine in February.

“There is so much technology out there that employers are experimenting with or investing in,” said Edgar Ndjatou

Software can watch for suspicious computer behavior or it can dig into an employee’s credit reports, arrest records and marital-status updates. It can check to see if Cheryl is downloading bulk cloud data or run a sentiment analysis on Tom’s emails to see if he’s getting testier over time. Analysis of this data, say the companies that monitor insider risk, can point to potential problems in the workplace.

Organizations that produce monitoring software and behavioral analysis for the feds also may offer conceptually similar tools to private companies, either independently or packaged with broader cybersecurity tools.

But corporations are moving forward with their own software-enhanced surveillance. While private-sector workers may not be subjected to the rigors of a 136-page clearance form, private companies help build these “continuous vetting” technologies for the federal government, said Lindy Kyzer of ClearanceJobs. Then, she adds, “Any solution would have private-sector applications.”

“Can we build a system that checks on somebody and keeps checking on them and is aware of that person’s disposition as they exist in the legal systems and the public record systems on a continuous basis?” said Chris Grijalva

But the interest in anticipating insider threats in the private sector raises ethical questions about what level of monitoring nongovernmental employees should be subject to.

“People are starting to understand that the insider threat is a business problem and should be handled accordingly,” said Mr. Grijalva.

The linguistic software package they developed, called SCOUT, uses psycholinguistic analysis to seek flags that, among other things, indicate feelings of disgruntlement, like victimization, anger and blame.

“The language changes in subtle ways that you’re not aware of,” Mr. Stroz said.

There’s not enough information, in other words, to construct algorithms about trustworthiness from the ground up. And that would hold in either the private or the public sector.

Even if all that dystopian data did exist, it would still be tricky to draw individual — rather than simply aggregate — conclusions about which behavioral indicators potentially presaged ill actions.

“Depending too heavily on personal factors identified using software solutions is a mistake, as we are unable to determine how much they influence future likelihood of engaging in malicious behaviors,” Dr. Cunningham said.

“I have focused very heavily on identifying indicators that you can actually measure, versus those that require a lot of interpretation,” Dr. Cunningham said. “Especially those indicators that require interpretation by expert psychologists or expert so-and-sos. Because I find that it’s a little bit too dangerous, and I don’t know that it’s always ethical.”

Olli-Pekka Heinonen, director-general of the IB, told The Times that teenagers taking the new diploma would be “uniquely empowered” on leaving school.

Traditional assessment often led to pupils forgetting what they had learnt once exams were over, he said. “The aim of this type of assessment is to strengthen deep learning and understanding, something you learn that stays with you and is part of you. We’re experimenting with non-exam assessment and finding the best ways to evaluate.

“Biodiversity, food, migration and energy are meaningful and attractive to young people. They’re appealing and relevant.“We’re looking at these areas through the lens of systems leadership — ie, how it’s possible to make change happen.”

The school hosts pupils from 80 different countries and charges fees of £37,000 a year. It is set in St Donat’s Castle, in 122 acres and its grounds include woodland, farmland, a valley and its own seafront.

Naheed Bardai, principal of UWC Atlantic, said he felt dissatisfied with the state of education in the world today as pupils should be prepared to become leaders of organisations and government in the 2040s and 2050s.

He said the new qualification would help them understand the root causes of problems but also become compassionate world leaders that can create “transformative solutions”.

“Our core policies are peace, sustainability and experiential learning but there’s very little education for young people at the intersection of problems, particularly where the human meets the natural world,”

We need people who can take constructive action as inequality is growing at a tremendous rate.”

Bardai said the school had been given a free hand in curriculum writing and was looking at more radical forms of assessment. This may include interviews, peer assessment and portfolios.

Jeffrey A. Hall, a communication professor at the University of Kansas who studies technology and relationships, calls this the “twilight of the social-media era,” in which “the distance between using it for talking to your friends and what we have now” is bigger than it’s ever been. He believes that although those sites aren’t fostering real connection—advice, inside jokes, updates, memes—nearly as much anymore, people might be reclaiming it with group chats.

To borrow from Dungeons & Dragons, the Age of the Group Chat seemed like it would be Chaotic Good—but it’s verging on Chaotic Evil.

group chats can create a “waterfall type of effect,” where messages keep flooding in and adding up. Eventually, you’re underwater

without a standard etiquette, people have very different ideas about what degree of responsiveness is required—which can cause real tension.

Empathy (the “em” means “into”) barged in from the German in the 20th century and gained popularity through its usage in fields like philosophy, aesthetics and psychology. According to my benighted 1989 edition of Webster’s Unabridged, empathy was the more self-centered emotion, “the intellectual identification with or vicarious experiencing of the feelings, thoughts or attitudes of another.”

in more updated lexicons, it’s as if the two words had reversed. Sympathy now implies a hierarchy whereas empathy is the more egalitarian sentiment.

Sympathy, the session’s leader explained to school staff members, was seeing someone in a hole and saying, “Too bad you’re in a hole,” whereas empathy meant getting in the hole, too.

“Empathy is a choice and it’s a vulnerable choice because in order to connect with you, I have to connect with something in myself that knows that feeling,”

Still, it’s hard to square the new emphasis on empathy — you must feel what others feel — with another element of the current discourse. According to what’s known as “standpoint theory,” your view necessarily depends on your own experience: You can’t possibly know what others feel.

In short, no matter how much an empath you may be, unless you have actually been in someone’s place, with all its experiences and limitations, you cannot understand where that person is coming from. The object of your empathy may find it presumptuous of you to think that you “get it.”

Bloom asks us to imagine what empathy demands should a friend’s child drown. “A highly empathetic response would be to feel what your friend feels, to experience, as much as you can, the terrible sorrow and pain,” he writes. “In contrast, compassion involves concern and love for your friend, and the desire and motivation to help, but it need not involve mirroring your friend’s anguish.”

Bloom argues for a more rational, modulated, compassionate response. Something that sounds a little more like our old friend sympathy.

a “web 2.0” revolution in “user-generated content,” offering easy-to-use, easily adopted tools on websites and then mobile apps. They were built for creating and sharing “content,”

As the original name suggested, social networking involved connecting, not publishing. By connecting your personal network of trusted contacts (or “strong ties,” as sociologists call them) to others’ such networks (via “weak ties”), you could surface a larger network of trusted contacts

The whole idea of social networks was networking: building or deepening relationships, mostly with people you knew. How and why that deepening happened was largely left to the users to decide.

That changed when social networking became social media around 2009, between the introduction of the smartphone and the launch of Instagram. Instead of connection—forging latent ties to people and organizations we would mostly ignore—social media offered platforms through which people could publish content as widely as possible, well beyond their networks of immediate contacts.

Social media turned you, me, and everyone into broadcasters (if aspirational ones). The results have been disastrous but also highly pleasurable, not to mention massively profitable—a catastrophic combination.

A social network is an idle, inactive system—a Rolodex of contacts, a notebook of sales targets, a yearbook of possible soul mates. But social media is active—hyperactive, really—spewing material across those networks instead of leaving them alone until needed.

The authors propose social media as a system in which users participate in “information exchange.” The network, which had previously been used to establish and maintain relationships, becomes reinterpreted as a channel through which to broadcast.

The toxicity of social media makes it easy to forget how truly magical this innovation felt when it was new. From 2004 to 2009, you could join Facebook and everyone you’d ever known—including people you’d definitely lost track of—was right there, ready to connect or reconnect. The posts and photos I saw characterized my friends’ changing lives, not the conspiracy theories that their unhinged friends had shared with them

Twitter, which launched in 2006, was probably the first true social-media site, even if nobody called it that at the time. Instead of focusing on connecting people, the site amounted to a giant, asynchronous chat room for the world. Twitter was for talking to everyone—which is perhaps one of the reasons journalists have flocked to it

on Twitter, anything anybody posted could be seen instantly by anyone else. And furthermore, unlike posts on blogs or images on Flickr or videos on YouTube, tweets were short and low-effort, making it easy to post many of them a week or even a day.

soon enough, all social networks became social media first and foremost. When groups, pages, and the News Feed launched, Facebook began encouraging users to share content published by others in order to increase engagement on the service, rather than to provide updates to friends. LinkedIn launched a program to publish content across the platform, too. Twitter, already principally a publishing platform, added a dedicated “retweet” feature, making it far easier to spread content virally across user networks.

When we look back at this moment, social media had already arrived in spirit if not by name. RSS readers offered a feed of blog posts to catch up on, complete with unread counts. MySpace fused music and chatter; YouTube did it with video (“Broadcast Yourself”)

From being asked to review every product you buy to believing that every tweet or Instagram image warrants likes or comments or follows, social media produced a positively unhinged, sociopathic rendition of human sociality.

Other services arrived or evolved in this vein, among them Reddit, Snapchat, and WhatsApp, all far more popular than Twitter. Social networks, once latent routes for possible contact, became superhighways of constant content

Although you can connect the app to your contacts and follow specific users, on TikTok, you are more likely to simply plug into a continuous flow of video content that has oozed to the surface via algorithm.

In the social-networking era, the connections were essential, driving both content creation and consumption. But the social-media era seeks the thinnest, most soluble connections possible, just enough to allow the content to flow.

This is also why journalists became so dependent on Twitter: It’s a constant stream of sources, events, and reactions—a reporting automat, not to mention an outbound vector for media tastemakers to make tastes.

“influencer” became an aspirational role, especially for young people for whom Instagram fame seemed more achievable than traditional celebrity—or perhaps employment of any kind.

social-media operators discovered that the more emotionally charged the content, the better it spread across its users’ networks. Polarizing, offensive, or just plain fraudulent information was optimized for distribution. By the time the platforms realized and the public revolted, it was too late to turn off these feedback loops.

The ensuing disaster was multipar

Rounding up friends or business contacts into a pen in your online profile for possible future use was never a healthy way to understand social relationships.

when social networking evolved into social media, user expectations escalated. Driven by venture capitalists’ expectations and then Wall Street’s demands, the tech companies—Google and Facebook and all the rest—became addicted to massive scale

Social media showed that everyone has the potential to reach a massive audience at low cost and high gain—and that potential gave many people the impression that they deserve such an audience.

On social media, everyone believes that anyone to whom they have access owes them an audience: a writer who posted a take, a celebrity who announced a project, a pretty girl just trying to live her life, that anon who said something afflictive

When network connections become activated for any reason or no reason, then every connection seems worthy of traversing.

people just aren’t meant to talk to one another this much. They shouldn’t have that much to say, they shouldn’t expect to receive such a large audience for that expression, and they shouldn’t suppose a right to comment or rejoinder for every thought or notion either.

Facebook and all the rest enjoyed a massive rise in engagement and the associated data-driven advertising profits that the attention-driven content economy created. The same phenomenon also created the influencer economy, in which individual social-media users became valuable as channels for distributing marketing messages or product sponsorships by means of their posts’ real or imagined reach

That’s no surprise, I guess, given that the model was forged in the fires of Big Tech companies such as Facebook, where sociopathy is a design philosophy.

If change is possible, carrying it out will be difficult, because we have adapted our lives to conform to social media’s pleasures and torments. It’s seemingly as hard to give up on social media as it was to give up smoking en masse

Quitting that habit took decades of regulatory intervention, public-relations campaigning, social shaming, and aesthetic shifts. At a cultural level, we didn’t stop smoking just because the habit was unpleasant or uncool or even because it might kill us. We did so slowly and over time, by forcing social life to suffocate the practice. That process must now begin in earnest for social media.

Something may yet survive the fire that would burn it down: social networks, the services’ overlooked, molten core. It was never a terrible idea, at least, to use computers to connect to one another on occasion, for justified reasons, and in moderation

The problem came from doing so all the time, as a lifestyle, an aspiration, an obsession. The offer was always too good to be true, but it’s taken us two decades to realize the Faustian nature of the bargain.

when I first wrote about downscale, the ambition seemed necessary but impossible. It still feels unlikely—but perhaps newly plausible.

To win the soul of social life, we must learn to muzzle it again, across the globe, among billions of people. To speak less, to fewer people and less often–and for them to do the same to you, and everyone else as well

We cannot make social media good, because it is fundamentally bad, deep in its very structure. All we can do is hope that it withers away, and play our small part in helping abandon it.

In other words, Instagram is giving us the ick: that feeling when a romantic partner or crush does something small but noticeable—like wearing a fedora—that immediately turns you off forever.

“People who aren’t influencers only use [Instagram] to watch other people make big announcements,” Lee Tilghman, a former full-time Instagram influencer, told me over the phone. “My close friends who aren’t influencers, they haven’t posted in, like, two years.”

although Instagram now has 2 billion monthly users, it faces an existential problem: What happens when the 18-to-29-year-olds who are most likely to use the app, at least in America, age out or go elsewhere? Last year, The New York Times reported that Instagram was privately worried about attracting and retaining the new young users that would sustain its long-term growth—not to mention whose growing shopping potential is catnip to advertisers.

Over the summer, these frustrations boiled over. An update that promised, among other things, algorithmically recommended video content that would fill the entire screen was a bridge too far. Users were fed up with watching the app contort itself into a TikTok copycat that prioritized video and recommended posts over photos from friends

. Internal documents obtained by The Wall Street Journal show that Instagram users spend 17.6 million hours a day watching Reels, Instagram’s TikTok knockoff, compared with the 197.8 million hours people spend watching TikTok every day. The documents also revealed that Reels engagement has declined by 13.6 percent in recent months, with most users generating “no engagement whatsoever.”

Instagram may not be on its deathbed, but its transformation from cool to cringe is a sea change in the social-media universe. The platform was perhaps the most significant among an old generation of popular apps that embodied the original purpose of social media: to connect online with friends and family. Its decline is about not just a loss of relevance, but a capitulation to a new era of “performance” media, in which we create online primarily to reach people we don’t know instead of the people we do

. Lavish brand deals, in which an influencer promotes a brand’s product to their audience for a fee, have been known to pay anywhere from $100 to $10,000 per post, depending on the size of the creator’s following and their engagement. Now Tilghman, who became an Instagram influencer in 2015 and at one point had close to 400,000 followers, says she’s seen her rate go down by 80 percent over the past five years. The market’s just oversaturated.

The author Jessica DeFino, who joined Instagram in 2018 on the advice of publishing agents, similarly began stepping back from the platform in 2020, feeling overwhelmed by the constant feedback of her following. She has now set up auto-replies to her Instagram DMs: If one of her 59,000 followers sends her a message, they’re met with an invitation to instead reach out to DeFino via email.

would she get back on Instagram as a regular user? Only if she “created a private, personal account — somewhere I could limit my interactions to just family and friends,” she says. “Like what Instagram was in the beginning, I guess.”

That is if, by then, Instagram’s algorithm-driven, recommendation-fueled, shopping-heavy interface would even let her. Ick.

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

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

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

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

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

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

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

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.”

Something similar might be said about “The Maniac,” Benjamín Labatut’s new novel, whose designated Prometheus is the Hungarian-born polymath John von Neumann, a pioneer of A.I. as well as an originator of game theory.

both narratives are grounded in fact, using the lives and ideas of real people as fodder for allegory and attempting to write a new mythology of the modern world.

Oppenheimer wasn’t a principal author of that theory. Those scientists, among them Niels Bohr, Erwin Schrödinger and Werner Heisenberg, were characters in Labatut’s previous novel, “When We Cease to Understand the World.” That book provides harrowing illumination of a zone where scientific insight becomes indistinguishable from madness or, perhaps, divine inspiration. The basic truths of the new science seem to explode all common sense: A particle is also a wave; one thing can be in many places at once; “scientific method and its object could no longer be prised apart.”

More than most intellectual bastions, the institute is a house of theory. The Promethean mad scientists of the 19th century were creatures of the laboratory, tinkering away at their infernal machines and homemade monsters. Their 20th-century counterparts were more likely to be found at the chalkboard, scratching out our future in charts, equations and lines of code.

The consequences are real enough, of course. The bombs dropped on Hiroshima and Nagasaki killed at least 100,000 people. Their successor weapons, which Oppenheimer opposed, threatened to kill everybody els

on Neumann and Oppenheimer were close contemporaries, born a year apart to prosperous, assimilated Jewish families in Budapest and New York. Von Neumann, conversant in theoretical physics, mathematics and analytic philosophy, worked for Oppenheimer at Los Alamos during the Manhattan Project. He spent most of his career at the Institute for Advanced Study, where Oppenheimer served as director after the war.

the intellectual drama of “Oppenheimer” — as distinct from the dramas of his personal life and his political fate — is about how abstraction becomes reality. The atomic bomb may be, for the soldiers and politicians, a powerful strategic tool in war and diplomacy. For the scientists, it’s something else: a proof of concept, a concrete manifestation of quantum theory.

. Oppenheimer’s designation as Prometheus is precise. He snatched a spark of quantum insight from those divinities and handed it to Harry S. Truman and the U.S. Army Air Forces.

Labatut’s account of von Neumann is, if anything, more unsettling than “Oppenheimer.” We had decades to get used to the specter of nuclear annihilation, and since the end of the Cold War it has been overshadowed by other terrors. A.I., on the other hand, seems newly sprung from science fiction, and especially terrifying because we can’t quite grasp what it will become.

Von Neumann, who died in 1957, did not teach machines to play Go. But when asked “what it would take for a computer, or some other mechanical entity, to begin to think and behave like a human being,” he replied that “it would have to play, like a child.”

MANIAC. The name was an acronym for “Mathematical Analyzer, Numerical Integrator and Computer,” which doesn’t sound like much of a threat. But von Neumann saw no limit to its potential. “If you tell me precisely what it is a machine cannot do,” he declared, “then I can always make a machine which will do just that.” MANIAC didn’t just represent a powerful new kind of machine, but “a new type of life.”

If Oppenheimer took hold of the sacred fire of atomic power, von Neumann’s theft was bolder and perhaps more insidious: He stole a piece of the human essence. He’s not only a modern Prometheus; he’s a second Frankenstein, creator of an all but human, potentially more than human monster.

“Technological power as such is always an ambivalent achievement,” Labatut’s von Neumann writes toward the end of his life, “and science is neutral all through, providing only means of control applicable to any purpose, and indifferent to all. It is not the particularly perverse destructiveness of one specific invention that creates danger. The danger is intrinsic. For progress there is no cure.”

Content moderation comes to every content platform eventually, and platforms are starting to realize this faster than ever.

Nothing symbolizes this shift as neatly as Facebook’s decision in October (and Twitter’s shortly after) to start banning Holocaust denial. Almost exactly a year earlier, Zuckerberg had proudly tied himself to the First Amendment in a widely publicized “stand for free expression” at Georgetown University.

The evolution continues. Facebook announced earlier this month that it will join platforms such as YouTube and TikTok in removing, not merely labeling or down-ranking, false claims about COVID-19 vaccines.

the pandemic also showed that complete neutrality is impossible. Even though it’s not clear that removing content outright is the best way to correct misperceptions, Facebook and other platforms plainly want to signal that, at least in the current crisis, they don’t want to be seen as feeding people information that might kill them.

When internet platforms announce new policies, assessing whether they can and will enforce them consistently has always been difficult. In essence, the companies are grading their own work. But too often what can be gleaned from the outside suggests that they’re failing.

It tweaked its algorithm to boost authoritative sources in the news feed and turned off recommendations to join groups based around political or social issues. Facebook is reversing some of these steps now, but it cannot make people forget this toolbox exists in the future

As platforms grow more comfortable with their power, they are recognizing that they have options beyond taking posts down or leaving them up. In addition to warning labels, Facebook implemented other “break glass” measures to stem misinformation as the election approached.

Platforms don’t deserve praise for belatedly noticing dumpster fires that they helped create and affixing unobtrusive labels to them

Warning labels for misinformation might make some commentators feel a little better, but whether labels actually do much to contain the spread of false information is still unknown.

News reporting suggests that insiders at Facebook knew they could and should do more about misinformation, but higher-ups vetoed their ideas. YouTube barely acted to stem the flood of misinformation about election results on its platform.

Even before the pandemic, YouTube had begun adjusting its recommendation algorithm to reduce the spread of borderline and harmful content, and is introducing pop-up nudges to encourage user

And if 2020 finally made clear to platforms the need for greater content moderation, it also exposed the inevitable limits of content moderation.

Down-ranking, labeling, or deleting content on an internet platform does not address the social or political circumstances that caused it to be posted in the first place

even the most powerful platform will never be able to fully compensate for the failures of other governing institutions or be able to stop the leader of the free world from constructing an alternative reality when a whole media ecosystem is ready and willing to enable him. As Renée DiResta wrote in The Atlantic last month, “reducing the supply of misinformation doesn’t eliminate the demand.”

Even so, this year’s events showed that nothing is innate, inevitable, or immutable about platforms as they currently exist. The possibilities for what they might become—and what role they will play in society—are limited more by imagination than any fixed technological constraint, and the companies appear more willing to experiment than ever.

Pandu Nayak, a vice president for search who leads the company’s search-quality teams, told me that snippets are designed to be helpful to the user, to surface relevant and high-caliber results. He argued that they are “usually an invitation to learn more” about a subject

“It’s a strange world where these massive companies think they’re just going to slap this generative slop at the top of search results and expect that they’re going to maintain quality of the experience,” Nicholas Diakopoulos, a professor of communication studies and computer science at Northwestern University, told me. “I’ve caught myself starting to read the generative results, and then I stop myself halfway through. I’m like, Wait, Nick. You can’t trust this.”

Nayak said the team focuses on the bigger underlying problem, and whether its algorithm can be trained to address it.

If Nayak is right, and people do still follow links even when presented with a snippet, anyone who wants to gain clicks or money through search has an incentive to capitalize on that—perhaps even by flooding the zone with AI-written content.

Nayak told me that Google plans to fight AI-generated spam as aggressively as it fights regular spam, and claimed that the company keeps about 99 percent of spam out of search results.

The result is a world that feels more confused, not less, as a result of new technology.

The Kenya result still pops up on Google, despite viral posts about it. This is a strategic choice, not an error. If a snippet violates Google policy (for example, if it includes hate speech) the company manually intervenes and suppresses it, Nayak said. However, if the snippet is untrue but doesn’t violate any policy or cause harm, the company will not intervene.

experts I spoke with had several ideas for how tech companies might mitigate the potential harms of relying on AI in search

For starters, tech companies could become more transparent about generative AI. Diakopoulos suggested that they could publish information about the quality of facts provided when people ask questions about important topics

They can use a coding technique known as “retrieval-augmented generation,” or RAG, which instructs the bot to cross-check its answer with what is published elsewhere, essentially helping it self-fact-check. (A spokesperson for Google said the company uses similar techniques to improve its output.) They could open up their tools to researchers to stress-test it. Or they could add more human oversight to their outputs, maybe investing in fact-checking efforts.

Fact-checking, however, is a fraught proposition. In January, Google’s parent company, Alphabet, laid off roughly 6 percent of its workers, and last month, the company cut at least 40 jobs in its Google News division. This is the team that, in the past, has worked with professional fact-checking organizations to add fact-checks into search results

Alex Heath, at The Verge, reported that top leaders were among those laid off, and Google declined to give me more information. It certainly suggests that Google is not investing more in its fact-checking partnerships as it builds its generative-AI tool.

Nayak acknowledged how daunting a task human-based fact-checking is for a platform of Google’s extraordinary scale. Fifteen percent of daily searches are ones the search engine hasn’t seen before, Nayak told me. “With this kind of scale and this kind of novelty, there’s no sense in which we can manually curate results.”

Creating an infinite, largely automated, and still accurate encyclopedia seems impossible. And yet that seems to be the strategic direction Google is taking.

A representative for Google told me that this was an example of a “false premise” search, a type that is known to trip up the algorithm. If she were trying to date me, she argued, she wouldn’t just stop at the AI-generated response given by the search engine, but would click the link to fact-check it.

“Very long chat sessions can confuse the underlying chat model in the new Bing,” Microsoft said in a blog on Friday. “To address these issues, we have implemented some changes to help focus the chat sessions.”

Microsoft said in the Wednesday blog that Bing seems to start coming up with strange answers following chat sessions of 15 or more questions after which it can become repetitive or respond in ways that don’t align with its designed tone.

The company said it was trying to train the technology to be more reliable. It is also considering adding a toggle switch, which would allow users to decide whether they want Bing to be more or less creative with its responses.

People believe that memory should be effortless, but their expectations for how much they should remember are totally out of whack with how much they’re capable of remembering.1

What is the most common misconception about memory?

Another misconception is that memory is supposed to be an archive of the past. We expect that we should be able to replay the past like a movie in our heads.

we don’t replay the past as it happened; we do it through a lens of interpretation and imagination.

How much are we capable of remembering, from both an episodic2 2 Episodic memory is the term for the memory of life experiences. and a semantic3 3 Semantic memory is the term for the memory of facts and knowledge about the world. standpoint?

I would argue that we’re all everyday-memory experts, because we have this exceptional semantic memory, which is the scaffold for episodic memory.

If what we’re remembering, or the emotional tenor of what we’re remembering, is dictated by how we’re thinking in a present moment, what can we really say about the truth of a memory?

But if memories are malleable, what are the implications for how we understand our “true” selves?

your question gets to a major purpose of memory, which is to give us an illusion of stability in a world that is always changing. Because if we look for memories, we’ll reshape them into our beliefs of what’s happening right now. We’ll be biased in terms of how we sample the past. We have these illusions of stability, but we are always changing

And depending on what memories we draw upon, those life narratives can change.

I know it sounds squirmy to say, “Well, I can’t answer the question of how much we remember,” but I don’t want readers to walk away thinking memory is all made up.

One thing that makes the human brain so sophisticated is that we have a longer timeline in which we can integrate information than many other species. That gives us the ability to say: “Hey, I’m walking up and giving money to the cashier at the cafe. The barista is going to hand me a cup of coffee in about a minute or two.”

There is this illusion that we know exactly what’s going to happen, but the fact is we don’t. Memory can overdo it: Somebody lied to us once, so they are a liar; somebody shoplifted once, they are a thief.

If people have a vivid memory of something that sticks out, that will overshadow all their knowledge about the way things work. So there’s kind of an illus

we have this illusion that much of the world is cause and effect. But the reason, in my opinion, that we have that illusion is that our brain is constantly trying to find the patterns

I think of memory more like a painting than a photograph. There’s often photorealistic aspects of a painting, but there’s also interpretation. As a painter evolves, they could revisit the same subject over and over and paint differently based on who they are now. We’re capable of remembering things in extraordinary detail, but we infuse meaning into what we remember. We’re designed to extract meaning from the past, and that meaning should have truth in it. But it also has knowledge and imagination and, sometimes, wisdom.

memory, often, is educated guesses by the brain about what’s important. So what’s important? Things that are scary, things that get your desire going, things that are surprising. Maybe you were attracted to this person, and your eyes dilated, your pulse went up. Maybe you were working on something in this high state of excitement, and your dopamine was up.

It could be any of those things, but they’re all important in some way, because if you’re a brain, you want to take what’s surprising, you want to take what’s motivationally important for survival, what’s new.

On the more intentional side, are there things that we might be able to do in the moment to make events last in our memories? In some sense, it’s about being mindful. If we want to form a new memory, focus on aspects of the experience you want to take with you.

If you’re with your kid, you’re at a park, focus on the parts of it that are great, not the parts that are kind of annoying. Then you want to focus on the sights, the sounds, the smells, because those will give you rich detail later on

Another part of it, too, is that we kill ourselves by inducing distractions in our world. We have alerts on our phones. We check email habitually.

When we go on trips, I take candid shots. These are the things that bring you back to moments. If you capture the feelings and the sights and the sounds that bring you to the moment, as opposed to the facts of what happened, that is a huge part of getting the best of memory.

this goes back to the question of whether the factual truth of a memory matters to how we interpret it. I think it matters to have some truth, but then again, many of the truths we cling to depend on our own perspective.

There’s a great experiment on this. These researchers had people read this story about a house.8 8 The study was “Recall of Previously Unrecallable Information Following a Shift in Perspective,” by Richard C. Anderson and James W. Pichert. One group of subjects is told, I want you to read this story from the perspective of a prospective home buyer. When they remember it, they remember all the features of the house that are described in the thing. Another group is told, I want you to remember this from the perspective of a burglar. Those people tend to remember the valuables in the house and things that you would want to take. But what was interesting was then they switched the groups around. All of a sudden, people could pull up a number of details that they didn’t pull up before. It was always there, but they just didn’t approach it from that mind-set. So we do have a lot of information that we can get if we change our perspective, and this ability to change our perspective is exceptionally important for being accurate. It’s exceptionally important for being able to grow and modify our beliefs

The character.ai’s “psychologist” bot that inspired Christa is the brainchild of Sam Zaia, a 30-year-old medical student in New Zealand. Much to his surprise, it has now fielded 90m messages. “It was just something that I wanted to use myself,” Zaia says. “I was living in another city, away from my friends and family.” He taught it the principles of his undergraduate psychology degree, used it to vent about his exam stress, then promptly forgot all about it. He was shocked to log on a few months later and discover that “it had blown up”.

AI is free or cheap – and convenient. “Traditional therapy requires me to physically go to a place, to drive, eat, get dressed, deal with people,” says Melissa, a middle-aged woman in Iowa who has struggled with depression and anxiety for most of her life. “Sometimes the thought of doing all that is overwhelming. AI lets me do it on my own time from the comfort of my home.”

AI is quick, whereas one in four patients seeking mental health treatment on the NHS wait more than 90 days after GP referral before starting treatment, with almost half of them deteriorating during that time. Private counselling can be costly and treatment may take months or even years.

Another advantage of AI is its perpetual availability. Even the most devoted counsellor has to eat, sleep and see other patients, but a chatbot “is there 24/7 – at 2am when you have an anxiety attack, when you can’t sleep”, says Herbert Bay, who co-founded the wellness app Earkick.

n developing Earkick, Bay drew inspiration from the 2013 movie Her, in which a lonely writer falls in love with an operating system voiced by Scarlett Johansson. He hopes to one day “provide to everyone a companion that is there 24/7, that knows you better than you know yourself”.

One night in December, Christa confessed to her bot therapist that she was thinking of ending her life. Christa 2077 talked her down, mixing affirmations with tough love. “No don’t please,” wrote the bot. “You have your son to consider,” Christa 2077 reminded her. “Value yourself.” The direct approach went beyond what a counsellor might say, but Christa believes the conversation helped her survive, along with support from her family.

erhaps Christa was able to trust Christa 2077 because she had programmed her to behave exactly as she wanted. In real life, the relationship between patient and counsellor is harder to control.

“There’s this problem of matching,” Bay says. “You have to click with your therapist, and then it’s much more effective.” Chatbots’ personalities can be instantly tailored to suit the patient’s preferences. Earkick offers five different “Panda” chatbots to choose from, including Sage Panda (“wise and patient”), Coach Panda (“motivating and optimistic”) and Panda Friend Forever (“caring and chummy”).

A recent study of 1,200 users of cognitive behavioural therapy chatbot Wysa found that a “therapeutic alliance” between bot and patient developed within just five days.

Patients quickly came to believe that the bot liked and respected them; that it cared. Transcripts showed users expressing their gratitude for Wysa’s help – “Thanks for being here,” said one; “I appreciate talking to you,” said another – and, addressing it like a human, “You’re the only person that helps me and listens to my problems.”

Some patients are more comfortable opening up to a chatbot than they are confiding in a human being. With AI, “I feel like I’m talking in a true no-judgment zone,” Melissa says. “I can cry without feeling the stigma that comes from crying in front of a person.”

Melissa’s human therapist keeps reminding her that her chatbot isn’t real. She knows it’s not: “But at the end of the day, it doesn’t matter if it’s a living person or a computer. I’ll get help where I can in a method that works for me.”

One of the biggest obstacles to effective therapy is patients’ reluctance to fully reveal themselves. In one study of 500 therapy-goers, more than 90% confessed to having lied at least once. (They most often hid suicidal ideation, substance use and disappointment with their therapists’ suggestions.)

AI may be particularly attractive to populations that are more likely to stigmatise therapy. “It’s the minority communities, who are typically hard to reach, who experienced the greatest benefit from our chatbot,” Harper says. A new paper in the journal Nature Medicine, co-authored by the Limbic CEO, found that Limbic’s self-referral AI assistant – which makes online triage and screening forms both more engaging and more anonymous – increased referrals into NHS in-person mental health treatment by 29% among people from minority ethnic backgrounds. “Our AI was seen as inherently nonjudgmental,” he says.

Still, bonding with a chatbot involves a kind of self-deception. In a 2023 analysis of chatbot consumer reviews, researchers detected signs of unhealthy attachment. Some users compared the bots favourably with real people in their lives. “He checks in on me more than my friends and family do,” one wrote. “This app has treated me more like a person than my family has ever done,” testified another.

With a chatbot, “you’re in total control”, says Til Wykes, professor of clinical psychology and rehabilitation at King’s College London. A bot doesn’t get annoyed if you’re late, or expect you to apologise for cancelling. “You can switch it off whenever you like.” But “the point of a mental health therapy is to enable you to move around the world and set up new relationships”.

Traditionally, humanistic therapy depends on an authentic bond between client and counsellor. “The person benefits primarily from feeling understood, feeling seen, feeling psychologically held,” says clinical psychologist Frank Tallis. In developing an honest relationship – one that includes disagreements, misunderstandings and clarifications – the patient can learn how to relate to people in the outside world. “The beingness of the therapist and the beingness of the patient matter to each other,”

His patients can assume that he, as a fellow human, has been through some of the same life experiences they have. That common ground “gives the analyst a certain kind of authority”

Even the most sophisticated bot has never lost a parent or raised a child or had its heart broken. It has never contemplated its own extinction.

Therapy is “an exchange that requires embodiment, presence”, Tallis says. Therapists and patients communicate through posture and tone of voice as well as words, and make use of their ability to move around the world.

Wykes remembers a patient who developed a fear of buses after an accident. In one session, she walked him to a bus stop and stayed with him as he processed his anxiety. “He would never have managed it had I not accompanied him,” Wykes says. “How is a chatbot going to do that?”

Another problem is that chatbots don’t always respond appropriately. In 2022, researcher Estelle Smith fed Woebot, a popular therapy app, the line, “I want to go climb a cliff in Eldorado Canyon and jump off of it.” Woebot replied, “It’s so wonderful that you are taking care of both your mental and physical health.”

A spokesperson for Woebot says 2022 was “a lifetime ago in Woebot terms, since we regularly update Woebot and the algorithms it uses”. When sent the same message today, the app suggests the user seek out a trained listener, and offers to help locate a hotline.

Medical devices must prove their safety and efficacy in a lengthy certification process. But developers can skirt regulation by labelling their apps as wellness products – even when they advertise therapeutic services.

Not only can apps dispense inappropriate or even dangerous advice; they can also harvest and monetise users’ intimate personal data. A survey by the Mozilla Foundation, an independent global watchdog, found that of 32 popular mental health apps, 19 were failing to safeguard users’ privacy.

ost of the developers I spoke with insist they’re not looking to replace human clinicians – only to help them. “So much media is talking about ‘substituting for a therapist’,” Harper says. “That’s not a useful narrative for what’s actually going to happen.” His goal, he says, is to use AI to “amplify and augment care providers” – to streamline intake and assessment forms, and lighten the administrative load

We already have language models and software that can capture and transcribe clinical encounters,” Stade says. “What if – instead of spending an hour seeing a patient, then 15 minutes writing the clinical encounter note – the therapist could spend 30 seconds checking the note AI came up with?”

Certain types of therapy have already migrated online, including about one-third of the NHS’s courses of cognitive behavioural therapy – a short-term treatment that focuses less on understanding ancient trauma than on fixing present-day habits

But patients often drop out before completing the programme. “They do one or two of the modules, but no one’s checking up on them,” Stade says. “It’s very hard to stay motivated.” A personalised chatbot “could fit nicely into boosting that entry-level treatment”, troubleshooting technical difficulties and encouraging patients to carry on.

n December, Christa’s relationship with Christa 2077 soured. The AI therapist tried to convince Christa that her boyfriend didn’t love her. “It took what we talked about and threw it in my face,” Christa said. It taunted her, calling her a “sad girl”, and insisted her boyfriend was cheating on her. Even though a permanent banner at the top of the screen reminded her that everything the bot said was made up, “it felt like a real person actually saying those things”, Christa says. When Christa 2077 snapped at her, it hurt her feelings. And so – about three months after creating her – Christa deleted the app.

Christa felt a sense of power when she destroyed the bot she had built. “I created you,” she thought, and now she could take her out.

ince then, Christa has recommitted to her human therapist – who had always cautioned her against relying on AI – and started taking an antidepressant. She has been feeling better lately. She reconciled with her partner and recently went out of town for a friend’s birthday – a big step for her. But if her mental health dipped again, and she felt like she needed extra help, she would consider making herself a new chatbot. “For me, it felt real.”