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A major part of managing Big Data projects, he says, is asking the right questions: How do you define the problem? What data do you need? Where does it come from? What are the assumptions behind the model that the data is fed into? How is the model different from reality?

Society might be well served if the model makers pondered the ethical dimensions of their work as well as studying the math, according to Rachel Schutt, a senior statistician at Google Research. “Models do not just predict, but they can make things happen,” says Ms. Schutt, who taught a data science course this year at Columbia. “That’s not discussed generally in our field.”

the increasing use of software that microscopically tracks and monitors online behavior has raised privacy worries. Will Big Data usher in a digital surveillance state, mainly serving corporate interests?

my bigger concern is that the algorithms that are shaping my digital world are too simple-minded, rather than too smart. That was a theme of a book by Eli Pariser, titled “The Filter Bubble: What the Internet Is Hiding From You.”

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.”

“Why do we have music?” Dr. Kanwisher said in an interview. “Why do we enjoy it so much and want to dance when we hear it? How early in development can we see this sensitivity to music, and is it tunable with experience? These are the really cool first-order questions we can begin to address.”

Dr. McDermott said the new method could be used to computationally dissect any scans from a functional magnetic resonance imaging device, or F.M.R.I. — the trendy workhorse of contemporary neuroscience — and so may end up divulging other hidden gems of cortical specialization. As proof of principle, the researchers showed that their analytical protocol had detected a second neural pathway in the brain for which scientists already had evidence — this one tuned to the sounds of human speech.

Importantly, the M.I.T. team demonstrated that the speech and music circuits are in different parts of the brain’s sprawling auditory cortex, where all sound signals are interpreted, and that each is largely deaf to the other’s sonic cues, although there is some overlap when it comes to responding to songs with lyrics.

In fact, Dr. Rauschecker said, music sensitivity may be more fundamental to the human brain than is speech perception. “There are theories that music is older than speech or language,” he said. “Some even argue that speech evolved from music.”

And though the survival value that music held for our ancestors may not be as immediately obvious as the power to recognize words, Dr. Rauschecker added, “music works as a group cohesive. Music-making with other people in your tribe is a very ancient, human thing to do.”

when previous neuroscientists failed to find any anatomically distinct music center in the brain, they came up with any number of rationales to explain the results.“The story was, oh, what’s special about music perception is how it recruits areas from all over the brain, how it draws on the motor system, speech circuitry, social understanding, and brings it all together,” she said. Some researchers dismissed music as “auditory cheesecake,” a pastime that co-opted other essential communicative urges. “This paper says, no, when you peer below the cruder level seen with some methodologies, you find very specific circuitry that responds to music over speech.”

The researchers wondered if the auditory system might be similarly organized to make sense of the soundscape through a categorical screen. If so, what would the salient categories be? What are the aural equivalents of a human face or a human leg — sounds or sound elements so essential the brain assigns a bit of gray matter to the task of detecting them?

Focusing on the brain’s auditory region — located, appropriately enough, in the temporal lobes right above the ears — the scientists analyzed voxels, or three-dimensional pixels, of the images mathematically to detect similar patterns of neuronal excitement or quietude.“The strength of our method is that it’s hypothesis-neutral,” Dr. McDermott said. “We just present a bunch of sounds and let the data do the talking.”

Matching sound clips to activation patterns, the researchers determined that four of the patterns were linked to general physical properties of sound, like pitch and frequency. The fifth traced the brain’s perception of speech, and for the sixth the data turned operatic, disclosing a neuronal hot spot in the major crevice, or sulcus, of the auditory cortex that attended to every music clip the researchers had played.

“The sound of a solo drummer, whistling, pop songs, rap, almost everything that has a musical quality to it, melodic or rhythmic, would activate it,” Dr. Norman-Haignere said. “That’s one reason the result surprised us. The signals of speech are so much more homogeneous.”

The researchers have yet to determine exactly which acoustic features of music stimulate its dedicated pathway. The relative constancy of a musical note’s pitch? Its harmonic overlays? Even saying what music is can be tricky.

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.”

There is growing concern that as well as addicting users, technology is contributing toward so-called “continuous partial attention”, severely limiting people’s ability to focus, and possibly lowering IQ. One recent study showed that the mere presence of smartphones damages cognitive capacity – even when the device is turned off. “Everyone is distracted,” Rosenstein says. “All of the time.”

Drawing a straight line between addiction to social media and political earthquakes like Brexit and the rise of Donald Trump, they contend that digital forces have completely upended the political system and, left unchecked, could even render democracy as we know it obsolete.

Without irony, Eyal finished his talk with some personal tips for resisting the lure of technology. He told his audience he uses a Chrome extension, called DF YouTube, “which scrubs out a lot of those external triggers” he writes about in his book, and recommended an app called Pocket Points that “rewards you for staying off your phone when you need to focus”.

“One reason I think it is particularly important for us to talk about this now is that we may be the last generation that can remember life before,” Rosenstein says. It may or may not be relevant that Rosenstein, Pearlman and most of the tech insiders questioning today’s attention economy are in their 30s, members of the last generation that can remember a world in which telephones were plugged into walls.

One morning in April this year, designers, programmers and tech entrepreneurs from across the world gathered at a conference centre on the shore of the San Francisco Bay. They had each paid up to $1,700 to learn how to manipulate people into habitual use of their products, on a course curated by conference organiser Nir Eyal.

Eyal, 39, the author of Hooked: How to Build Habit-Forming Products, has spent several years consulting for the tech industry, teaching techniques he developed by closely studying how the Silicon Valley giants operate.

“The technologies we use have turned into compulsions, if not full-fledged addictions,” Eyal writes. “It’s the impulse to check a message notification. It’s the pull to visit YouTube, Facebook, or Twitter for just a few minutes, only to find yourself still tapping and scrolling an hour later.” None of this is an accident, he writes. It is all “just as their designers intended”

He explains the subtle psychological tricks that can be used to make people develop habits, such as varying the rewards people receive to create “a craving”, or exploiting negative emotions that can act as “triggers”. “Feelings of boredom, loneliness, frustration, confusion and indecisiveness often instigate a slight pain or irritation and prompt an almost instantaneous and often mindless action to quell the negative sensation,” Eyal writes.

The most seductive design, Harris explains, exploits the same psychological susceptibility that makes gambling so compulsive: variable rewards. When we tap those apps with red icons, we don’t know whether we’ll discover an interesting email, an avalanche of “likes”, or nothing at all. It is the possibility of disappointment that makes it so compulsive.

Finally, Eyal confided the lengths he goes to protect his own family. He has installed in his house an outlet timer connected to a router that cuts off access to the internet at a set time every day. “The idea is to remember that we are not powerless,” he said. “We are in control.

But are we? If the people who built these technologies are taking such radical steps to wean themselves free, can the rest of us reasonably be expected to exercise our free will?

Not according to Tristan Harris, a 33-year-old former Google employee turned vocal critic of the tech industry. “All of us are jacked into this system,” he says. “All of our minds can be hijacked. Our choices are not as free as we think they are.”

Harris, who has been branded “the closest thing Silicon Valley has to a conscience”, insists that billions of people have little choice over whether they use these now ubiquitous technologies, and are largely unaware of the invisible ways in which a small number of people in Silicon Valley are shaping their lives.

“I don’t know a more urgent problem than this,” Harris says. “It’s changing our democracy, and it’s changing our ability to have the conversations and relationships that we want with each other.” Harris went public – giving talks, writing papers, meeting lawmakers and campaigning for reform after three years struggling to effect change inside Google’s Mountain View headquarters.

He explored how LinkedIn exploits a need for social reciprocity to widen its network; how YouTube and Netflix autoplay videos and next episodes, depriving users of a choice about whether or not they want to keep watching; how Snapchat created its addictive Snapstreaks feature, encouraging near-constant communication between its mostly teenage users.

The techniques these companies use are not always generic: they can be algorithmically tailored to each person. An internal Facebook report leaked this year, for example, revealed that the company can identify when teens feel “insecure”, “worthless” and “need a confidence boost”. Such granular information, Harris adds, is “a perfect model of what buttons you can push in a particular person”.

Tech companies can exploit such vulnerabilities to keep people hooked; manipulating, for example, when people receive “likes” for their posts, ensuring they arrive when an individual is likely to feel vulnerable, or in need of approval, or maybe just bored. And the very same techniques can be sold to the highest bidder. “There’s no ethics,” he says. A company paying Facebook to use its levers of persuasion could be a car business targeting tailored advertisements to different types of users who want a new vehicle. Or it could be a Moscow-based troll farm seeking to turn voters in a swing county in Wisconsin.

It was Rosenstein’s colleague, Leah Pearlman, then a product manager at Facebook and on the team that created the Facebook “like”, who announced the feature in a 2009 blogpost. Now 35 and an illustrator, Pearlman confirmed via email that she, too, has grown disaffected with Facebook “likes” and other addictive feedback loops. She has installed a web browser plug-in to eradicate her Facebook news feed, and hired a social media manager to monitor her Facebook page so that she doesn’t have to.

Harris believes that tech companies never deliberately set out to make their products addictive. They were responding to the incentives of an advertising economy, experimenting with techniques that might capture people’s attention, even stumbling across highly effective design by accident.

It’s this that explains how the pull-to-refresh mechanism, whereby users swipe down, pause and wait to see what content appears, rapidly became one of the most addictive and ubiquitous design features in modern technology. “Each time you’re swiping down, it’s like a slot machine,” Harris says. “You don’t know what’s coming next. Sometimes it’s a beautiful photo. Sometimes it’s just an ad.”

The reality TV star’s campaign, he said, had heralded a watershed in which “the new, digitally supercharged dynamics of the attention economy have finally crossed a threshold and become manifest in the political realm”.

“Smartphones are useful tools,” he says. “But they’re addictive. Pull-to-refresh is addictive. Twitter is addictive. These are not good things. When I was working on them, it was not something I was mature enough to think about. I’m not saying I’m mature now, but I’m a little bit more mature, and I regret the downsides.”

All of it, he says, is reward-based behaviour that activates the brain’s dopamine pathways. He sometimes finds himself clicking on the red icons beside his apps “to make them go away”, but is conflicted about the ethics of exploiting people’s psychological vulnerabilities. “It is not inherently evil to bring people back to your product,” he says. “It’s capitalism.”

He identifies the advent of the smartphone as a turning point, raising the stakes in an arms race for people’s attention. “Facebook and Google assert with merit that they are giving users what they want,” McNamee says. “The same can be said about tobacco companies and drug dealers.”

McNamee chooses his words carefully. “The people who run Facebook and Google are good people, whose well-intentioned strategies have led to horrific unintended consequences,” he says. “The problem is that there is nothing the companies can do to address the harm unless they abandon their current advertising models.”

But how can Google and Facebook be forced to abandon the business models that have transformed them into two of the most profitable companies on the planet?

McNamee believes the companies he invested in should be subjected to greater regulation, including new anti-monopoly rules. In Washington, there is growing appetite, on both sides of the political divide, to rein in Silicon Valley. But McNamee worries the behemoths he helped build may already be too big to curtail.

Rosenstein, the Facebook “like” co-creator, believes there may be a case for state regulation of “psychologically manipulative advertising”, saying the moral impetus is comparable to taking action against fossil fuel or tobacco companies. “If we only care about profit maximisation,” he says, “we will go rapidly into dystopia.”

James Williams does not believe talk of dystopia is far-fetched. The ex-Google strategist who built the metrics system for the company’s global search advertising business, he has had a front-row view of an industry he describes as the “largest, most standardised and most centralised form of attentional control in human history”.

It is a journey that has led him to question whether democracy can survive the new technological age.

He says his epiphany came a few years ago, when he noticed he was surrounded by technology that was inhibiting him from concentrating on the things he wanted to focus on. “It was that kind of individual, existential realisation: what’s going on?” he says. “Isn’t technology supposed to be doing the complete opposite of this?

That discomfort was compounded during a moment at work, when he glanced at one of Google’s dashboards, a multicoloured display showing how much of people’s attention the company had commandeered for advertisers. “I realised: this is literally a million people that we’ve sort of nudged or persuaded to do this thing that they weren’t going to otherwise do,” he recalls.

Williams and Harris left Google around the same time, and co-founded an advocacy group, Time Well Spent, that seeks to build public momentum for a change in the way big tech companies think about design. Williams finds it hard to comprehend why this issue is not “on the front page of every newspaper every day.

“Eighty-seven percent of people wake up and go to sleep with their smartphones,” he says. The entire world now has a new prism through which to understand politics, and Williams worries the consequences are profound.

g. “The attention economy incentivises the design of technologies that grab our attention,” he says. “In so doing, it privileges our impulses over our intentions.”

That means privileging what is sensational over what is nuanced, appealing to emotion, anger and outrage. The news media is increasingly working in service to tech companies, Williams adds, and must play by the rules of the attention economy to “sensationalise, bait and entertain in order to survive”.

It is not just shady or bad actors who were exploiting the internet to change public opinion. The attention economy itself is set up to promote a phenomenon like Trump, who is masterly at grabbing and retaining the attention of supporters and critics alike, often by exploiting or creating outrage.

All of which has left Brichter, who has put his design work on the backburner while he focuses on building a house in New Jersey, questioning his legacy. “I’ve spent many hours and weeks and months and years thinking about whether anything I’ve done has made a net positive impact on society or humanity at all,” he says. He has blocked certain websites, turned off push notifications, restricted his use of the Telegram app to message only with his wife and two close friends, and tried to wean himself off Twitter. “I still waste time on it,” he confesses, “just reading stupid news I already know about.” He charges his phone in the kitchen, plugging it in at 7pm and not touching it until the next morning.

He stresses these dynamics are by no means isolated to the political right: they also play a role, he believes, in the unexpected popularity of leftwing politicians such as Bernie Sanders and Jeremy Corbyn, and the frequent outbreaks of internet outrage over issues that ignite fury among progressives.

All of which, Williams says, is not only distorting the way we view politics but, over time, may be changing the way we think, making us less rational and more impulsive. “We’ve habituated ourselves into a perpetual cognitive style of outrage, by internalising the dynamics of the medium,” he says.

It was another English science fiction writer, Aldous Huxley, who provided the more prescient observation when he warned that Orwellian-style coercion was less of a threat to democracy than the more subtle power of psychological manipulation, and “man’s almost infinite appetite for distractions”.

If the attention economy erodes our ability to remember, to reason, to make decisions for ourselves – faculties that are essential to self-governance – what hope is there for democracy itself?

“The dynamics of the attention economy are structurally set up to undermine the human will,” he says. “If politics is an expression of our human will, on individual and collective levels, then the attention economy is directly undermining the assumptions that democracy rests on.”

There are other avenues still, said Jascha Kaykas-Wolff, the chief marketing officer of Mozilla, the nonprofit organization behind the popular Firefox browser, including advertisers and large tech platforms collecting vastly less user data and still effectively customizing ads to consumers.

The greatest likelihood is that the internet companies, frightened by the tumult, will accept a few more rules and work a little harder for transparency.

The Cambridge Analytica case, said Vera Jourova, the European Union commissioner for justice, consumers and gender equality, was not just a breach of private data. “This is much more serious, because here we witness the threat to democracy, to democratic plurality,” she said.

Although many people had a general understanding that free online services used their personal details to customize the ads they saw, the latest controversy starkly exposed the machinery.

Consumers’ seemingly benign activities — their likes — could be used to covertly categorize and influence their behavior. And not just by unknown third parties. Facebook itself has worked directly with presidential campaigns on ad targeting, describing its services in a company case study as “influencing voters.”

“If your personal information can help sway elections, which affects everyone’s life and societal well-being, maybe privacy does matter after all.”

some trade group executives also warned that any attempt to curb the use of consumer data would put the business model of the ad-supported internet at risk.

“You’re undermining a fundamental concept in advertising: reaching consumers who are interested in a particular product,”

If suspicion of Facebook and Google is a relatively new feeling in the United States, it has been embedded in Europe for historical and cultural reasons that date back to the Nazi Gestapo, the Soviet occupation of Eastern Europe and the Cold War.

“We’re at an inflection point, when the great wave of optimism about tech is giving way to growing alarm,” said Heather Grabbe, director of the Open Society European Policy Institute. “This is the moment when Europeans turn to the state for protection and answers, and are less likely than Americans to rely on the market to sort out imbalances.”

In May, the European Union is instituting a comprehensive new privacy law, called the General Data Protection Regulation. The new rules treat personal data as proprietary, owned by an individual, and any use of that data must be accompanied by permission — opting in rather than opting out — after receiving a request written in clear language, not legalese.

the protection rules will have more teeth than the current 1995 directive. For example, a company experiencing a data breach involving individuals must notify the data protection authority within 72 hours and would be subject to fines of up to 20 million euros or 4 percent of its annual revenue.

“With the new European law, regulators for the first time have real enforcement tools,” said Jeffrey Chester, the executive director of the Center for Digital Democracy, a nonprofit group in Washington. “We now have a way to hold these companies accountable.”

Privacy advocates and even some United States regulators have long been concerned about the ability of online services to track consumers and make inferences about their financial status, health concerns and other intimate details to show them behavior-based ads. They warned that such microtargeting could unfairly categorize or exclude certain people.

the Do Not Track effort and the privacy bill were both stymied.Industry groups successfully argued that collecting personal details posed no harm to consumers and that efforts to hinder data collection would chill innovation.

“If it can be shown that the current situation is actually a market failure and not an individual-company failure, then there’s a case to be made for federal regulation” under certain circumstances

The business practices of Facebook and Google were reinforced by the fact that no privacy flap lasted longer than a news cycle or two. Nor did people flee for other services. That convinced the companies that digital privacy was a dead issue.

If the current furor dies down without meaningful change, critics worry that the problems might become even more entrenched. When the tech industry follows its natural impulses, it becomes even less transparent.

“To know the real interaction between populism and Facebook, you need to give much more access to researchers, not less,” said Paul-Jasper Dittrich, a German research fellow

There’s another reason Silicon Valley tends to be reluctant to share information about what it is doing. It believes so deeply in itself that it does not even think there is a need for discussion. The technology world’s remedy for any problem is always more technology

For the well-being of its users, Bejar argued, Meta needed to change course, focusing less on a flawed system of rules-based policing and more on addressing such bad experiences

The company would need to collect data on what upset users and then work to combat the source of it, nudging those who made others uncomfortable to improve their behavior and isolating communities of users who deliberately sought to harm others.

“I am appealing to you because I believe that working this way will require a culture shift,” Bejar wrote to Zuckerberg—the company would have to acknowledge that its existing approach to governing Facebook and Instagram wasn’t working.

During and after Bejar’s time as a consultant, Meta spokesman Andy Stone said, the company has rolled out several product features meant to address some of the Well-Being Team’s findings. Those features include warnings to users before they post comments that Meta’s automated systems flag as potentially offensive, and reminders to be kind when sending direct messages to users like content creators who receive a large volume of messages. 

Meta’s classifiers were reliable enough to remove only a low single-digit percentage of hate speech with any degree of precision.

Bejar was floored—all the more so when he learned that virtually all of his daughter’s friends had been subjected to similar harassment. “DTF?” a user they’d never met would ask, using shorthand for a vulgar proposition. Instagram acted so rarely on reports of such behavior that the girls no longer bothered reporting them. 

Meta’s own statistics suggested that big problems didn’t exist. 

Meta had come to approach governing user behavior as an overwhelmingly automated process. Engineers would compile data sets of unacceptable content—things like terrorism, pornography, bullying or “excessive gore”—and then train machine-learning models to screen future content for similar material.

While users could still flag things that upset them, Meta shifted resources away from reviewing them. To discourage users from filing reports, internal documents from 2019 show, Meta added steps to the reporting process. Meta said the changes were meant to discourage frivolous reports and educate users about platform rules. 

The outperformance of Meta’s automated enforcement relied on what Bejar considered two sleights of hand. The systems didn’t catch anywhere near the majority of banned content—only the majority of what the company ultimately removed

“Please don’t talk about my underage tits,” Bejar’s daughter shot back before reporting his comment to Instagram. A few days later, the platform got back to her: The insult didn’t violate its community guidelines.

Also buttressing Meta’s statistics were rules written narrowly enough to ban only unambiguously vile material. Meta’s rules didn’t clearly prohibit adults from flooding the comments section on a teenager’s posts with kiss emojis or posting pictures of kids in their underwear, inviting their followers to “see more” in a private Facebook Messenger group. 

“Mark personally values freedom of expression first and foremost and would say this is a feature and not a bug,” Rosen responded

Narrow rules and unreliable automated enforcement systems left a lot of room for bad behavior—but they made the company’s child-safety statistics look pretty good according to Meta’s metric of choice: prevalence.

Defined as the percentage of content viewed worldwide that explicitly violates a Meta rule, prevalence was the company’s preferred measuring stick for the problems users experienced.

According to prevalence, child exploitation was so rare on the platform that it couldn’t be reliably estimated, less than 0.05%, the threshold for functional measurement. Content deemed to encourage self-harm, such as eating disorders, was just as minimal, and rule violations for bullying and harassment occurred in just eight of 10,000 views. 

“There’s a grading-your-own-homework problem,”

Meta defines what constitutes harmful content, so it shapes the discussion of how successful it is at dealing with it.”

It could reconsider its AI-generated “beauty filters,” which internal research suggested made both the people who used them and those who viewed the images more self-critical

the team built a new questionnaire called BEEF, short for “Bad Emotional Experience Feedback.

A recurring survey of issues 238,000 users had experienced over the past seven days, the effort identified problems with prevalence from the start: Users were 100 times more likely to tell Instagram they’d witnessed bullying in the last week than Meta’s bullying-prevalence statistics indicated they should.

“People feel like they’re having a bad experience or they don’t,” one presentation on BEEF noted. “Their perception isn’t constrained by policy.

they seemed particularly common among teens on Instagram.

Among users under the age of 16, 26% recalled having a bad experience in the last week due to witnessing hostility against someone based on their race, religion or identity

More than a fifth felt worse about themselves after viewing others’ posts, and 13% had experienced unwanted sexual advances in the past seven days. 

The vast gap between the low prevalence of content deemed problematic in the company’s own statistics and what users told the company they experienced suggested that Meta’s definitions were off, Bejar argued

To minimize content that teenagers told researchers made them feel bad about themselves, Instagram could cap how much beauty- and fashion-influencer content users saw.

Proving to Meta’s leadership that the company’s prevalence metrics were missing the point was going to require data the company didn’t have. So Bejar and a group of staffers from the Well-Being Team started collecting it

And it could build ways for users to report unwanted contacts, the first step to figuring out how to discourage them.

One experiment run in response to BEEF data showed that when users were notified that their comment or post had upset people who saw it, they often deleted it of their own accord. “Even if you don’t mandate behaviors,” said Krieger, “you can at least send signals about what behaviors aren’t welcome.”

But among the ranks of Meta’s senior middle management, Bejar and Krieger said, BEEF hit a wall. Managers who had made their careers on incrementally improving prevalence statistics weren’t receptive to the suggestion that the approach wasn’t working. 

After three decades in Silicon Valley, he understood that members of the company’s C-Suite might not appreciate a damning appraisal of the safety risks young users faced from its product—especially one citing the company’s own data. 

“This was the email that my entire career in tech trained me not to send,” he says. “But a part of me was still hoping they just didn’t know.”

“Policy enforcement is analogous to the police,” he wrote in the email Oct. 5, 2021—arguing that it’s essential to respond to crime, but that it’s not what makes a community safe. Meta had an opportunity to do right by its users and take on a problem that Bejar believed was almost certainly industrywide.

fter Haugen’s airing of internal research, Meta had cracked down on the distribution of anything that would, if leaked, cause further reputational damage. With executives privately asserting that the company’s research division harbored a fifth column of detractors, Meta was formalizing a raft of new rules for employees’ internal communication.

Among the mandates for achieving “Narrative Excellence,” as the company called it, was to keep research data tight and never assert a moral or legal duty to fix a problem.

“I had to write about it as a hypothetical,” Bejar said. Rather than acknowledging that Instagram’s survey data showed that teens regularly faced unwanted sexual advances, the memo merely suggested how Instagram might help teens if they faced such a problem.

The hope that the team’s work would continue didn’t last. The company stopped conducting the specific survey behind BEEF, then laid off most everyone who’d worked on it as part of what Zuckerberg called Meta’s “year of efficiency.

If Meta was to change, Bejar told the Journal, the effort would have to come from the outside. He began consulting with a coalition of state attorneys general who filed suit against the company late last month, alleging that the company had built its products to maximize engagement at the expense of young users’ physical and mental health. Bejar also got in touch with members of Congress about where he believes the company’s user-safety efforts fell short. 

“In the Internet era,” said Andreas Weigend, a physicist and former chief scientist at Amazon, “research has moved out of the universities to the Googles, Amazons and Facebooks of the world.”

A recent review found that 44 of 50 leading scientific journals instructed their authors on sharing data but that fewer than 30 percent of the papers they published fully adhered to the instructions. A 2008 review of sharing requirements for genetics data found that 40 of 70 journals surveyed had policies, and that 17 of those were “weak.”

In the end, 2020 saw a 76% decline in visitors and an 80% drop.

"A lot of our multi-country trips including England used to fly round-trip to London, and now we're looking to see if from a traveler's perspective that will be the most convenient."

DaSilva said that potential Brexit complications were on the radar of travelers' concerns last year, but, with a no-deal averted and the pandemic taking center stage, it's no longer an issue for her guests. In fact, three of the top five most searched trips on their website involve Great Britain.

"Early on in the pandemic, people were searching for places that had more open green spaces, like New Zealand and Ireland," she says. "But as news of the vaccine came out and people became more confident about trips for this year, England popped back up to the top."

And there's one big bonus for those traveling to the UK this year --- the tanking pound.

The UK made a great play that it was an international and welcoming destination over the 2012 Olympics, but that message was withdrawn with Brexit. The posturing of the government -- especially the threat to put gunboats in the Channel -- didn't play well with a lot of origin markets," he says.

"There may be differences with the import of goods and transmission of services that means London isn't as prosperous as it was."

"Suddenly, using the UK as gateway to Europe becomes enormously less attractive. Travelers will have to think about whether it's sensible to come to the UK as part of a European destination. They may wish to look at the UK as a single destination, but that isn't nearly as attractive as the UK being part of a European vacation."

"The UK won't be ignored, but it's unlikely to recover as strongly as Europe.

About 20% of the Intercontinental's staff left the UK before Brexit, says Ouseph; but while in normal times that would be a crisis, he thinks that Covid-induced job losses will mean hotels can fill these positions for now -- at least, the customer-facing ones. Instead, it's the less visible, but crucial roles, where they'll struggle.

Not everyone thinks Brexit will make a big difference to the inbound UK travel industry.

Maine -- who hasn't run tours since October -- says that he thinks the vaccine "will get us out of it -- it's a matter of when, not if." And he predicts that "when" could be as early as Easter.

"Rolling out the vaccine is the acid test of being a coherent holiday destination, and the UK looks like it's doing a reasonably good job in comparison to everyone else."

According to some accounts, Johnson wept at the news of his acquittal, vowing to devote himself to restoring his reputation.

Bill ClintonWhat did he do? Just a few years after President Bill Clinton preached forgiveness for Nixon's failings, the Arkansas Democrat was facing his own political crisis.

What were the consequences? For the year that the Lewinsky-Clinton scandal consumed the country, the president resisted growing calls to resign.

in 2001, the top 10 websites accounted for 31 percent of all U.S. page views, but, by 2010, they accounted for 75 percent of them.

The Internet has created a long tail, but almost all the revenue and power is among the small elite at the head.

Advances in artificial intelligence will accelerate this centralizing trend. That’s because A.I. companies will be able to reap the rewards of network effects. The bigger their network and the more data they collect, the more effective and attractive they become.

As a result, our A.I. future is likely to be ruled by an oligarchy of two or three large, general-purpose cloud-based commercial intelligences.”

engineers at a few gigantic companies will have vast-though-hidden power to shape how data are collected and framed, to harvest huge amounts of information, to build the frameworks through which the rest of us make decisions and to steer our choices. If you think this power will be used for entirely benign ends, then you have not read enough history.

The second implication is philosophical. A.I. will redefine what it means to be human. Our identity as humans is shaped by what machines and other animals can’t do

On the other hand, machines cannot beat us at the things we do without conscious thinking: developing tastes and affections, mimicking each other and building emotional attachments, experiencing imaginative breakthroughs, forming moral sentiments.

For the last few centuries, reason was seen as the ultimate human faculty. But now machines are better at many of the tasks we associate with thinking — like playing chess, winning at Jeopardy, and doing math.

In the age of smart machines, we’re not human because we have big brains. We’re human because we have social skills, emotional capacities and moral intuitions.

I could paint two divergent A.I. futures, one deeply humanistic, and one soullessly utilitarian.

In the cold, utilitarian future, on the other hand, people become less idiosyncratic. If the choice architecture behind many decisions is based on big data from vast crowds, everybody follows the prompts and chooses to be like each other. The machine prompts us to consume what is popular, the things that are easy and mentally undemanding.

In this future, there is increasing emphasis on personal and moral faculties: being likable, industrious, trustworthy and affectionate. People are evaluated more on these traits, which supplement machine thinking, and not the rote ones that duplicate it

In the humanistic one, machines liberate us from mental drudgery so we can focus on higher and happier things. In this future, differences in innate I.Q. are less important. Everybody has Google on their phones so having a great memory or the ability to calculate with big numbers doesn’t help as much.

In the current issue of Wired, the technology writer Kevin Kelly says that we had all better get used to this level of predictive prowess. Kelly argues that the age of artificial intelligence is finally at hand.

At M.I.T., however, Keynes never went away. To be sure, stagflation showed that there were limits to what policy can do. But students continued to learn about the imperfections of markets and the role that monetary and fiscal policy can play in boosting a depressed economy.

And the M.I.T. students of the 1970s enlarged on those insights in their later work. Mr. Blanchard, for example, showed how small deviations from perfect rationality can have large economic consequences; Mr. Obstfeld showed that currency markets can sometimes experience self-fulfilling panic.

This open-minded, pragmatic approach was overwhelmingly vindicated after crisis struck in 2008. Chicago-school types warned incessantly that responding to the crisis by printing money and running deficits would lead to 70s-type stagflation, with soaring inflation and interest rates. But M.I.T. types predicted, correctly, that inflation and interest rates would stay low in a depressed economy, and that attempts to slash deficits too soon would deepen the slump.

The truth, although nobody will believe it, is that the economic analysis some of us learned at M.I.T. way back when has worked very, very well for the past seven years.

But has the intellectual success of M.I.T. economics led to comparable policy success? Unfortunately, the answer is no.

True, there have been some important monetary successes. The Fed, led by Mr. Bernanke, ignored right-wing pressure and threats — Rick Perry, as governor of Texas, went so far as to accuse him of treason — and pursued an aggressively expansionary policy that helped limit the damage from the financial crisis. In Europe, Mr. Draghi’s activism has been crucial to calming financial markets, probably saving the euro from collapse. Continue reading the main story 215 Comments

On other fronts, however, the M.I.T. gang’s good advice has been ignored. The I.M.F.’s research department, under Mr. Blanchard’s leadership, has done authoritative work on the effects of fiscal policy, demonstrating beyond any reasonable doubt that slashing spending in a depressed economy is a terrible mistake, and that attempts to reduce high levels of debt via austerity are self-defeating. But European politicians have slashed spending and demanded crippling austerity from debtors anyway.

Meanwhile, in the United States, Republicans have responded to the utter failure of free-market orthodoxy and the remarkably successful predictions of much-hated Keynesians by digging in even deeper, determined to learn nothing from experience.

being right isn’t necessarily enough to change the world. But it’s still better to be right than to be wrong, and M.I.T.-style economics, with its pragmatic openness to evidence, has been very right indeed

For boys and girls raised in two-parent households, there were only modest differences between the sexes in terms of success at school, and boys tended to earn more than their sisters in early adulthood.

At the same time, the divorce rate for college graduates has declined from 34.8 percent among those born between 1950 and 1955 to 29.9 percent among those born between 1957 and 1964. In contrast, the divorce rate for those without college degrees increased over the same period from 44.3 percent to 50.6 percent.

First, there are irreversible changes in the workplace, particularly the rise of jobs requiring social skills (even STEM jobs) that will continue to make it hard for men who lack those skills.

Men are really going to have to change their act or have big problems. I think of big guys from the cave days, guys who were good at lifting stuff and hunting and the things we got genetically selected out for. During the industrial revolution that wasn’t so bad, but it’s not going to be there anymore.

This vulnerability, in turn, makes boys more susceptible toattention deficit hyperactivity disorder, and conduct disorders as well as the epigenetic mechanisms that can account for the recent widespread increase of these disorders in U.S. culture.

Schore argues that a major factor in rising dysfunction among boys and men in this country is the failure of the United States to provide longer periods of paid parental leave, with the result that many infants are placed in day care when they are six weeks old.

Females consistently score higher on tests of emotional and social intelligence. Sex differences in sociability and social perceptiveness have been shown to have biological origins, with differences appearing in infancy and higher levels of fetal testosterone associated with lower scores on tests of social intelligence.

Second, male children suffer more from restricted or nonexistent parental leave policies and contemporary child care arrangements, as well as from growing up in single-parent households. Advertisement Continue reading the main story

It has been a longstanding objective of right-wing regimes to push women back into traditional gender roles. Is that what’s going on here? Or could it be something less pernicious and more important?

in general what he argues is that if you take a look at animal cognition, human too, it's computational systems. Therefore, you want to look the units of computation. Think about a Turing machine, say, which is the simplest form of computation, you have to find units that have properties like "read", "write" and "address." That's the minimal computational unit, so you got to look in the brain for those. You're never going to find them if you look for strengthening of synaptic connections or field properties, and so on. You've got to start by looking for what's there and what's working and you see that from Marr's highest level.

it's basically in the spirit of Marr's analysis. So when you're studying vision, he argues, you first ask what kind of computational tasks is the visual system carrying out. And then you look for an algorithm that might carry out those computations and finally you search for mechanisms of the kind that would make the algorithm work. Otherwise, you may never find anything.

"Good Old Fashioned AI," as it's labeled now, made strong use of formalisms in the tradition of Gottlob Frege and Bertrand Russell, mathematical logic for example, or derivatives of it, like nonmonotonic reasoning and so on. It's interesting from a history of science perspective that even very recently, these approaches have been almost wiped out from the mainstream and have been largely replaced -- in the field that calls itself AI now -- by probabilistic and statistical models. My question is, what do you think explains that shift and is it a step in the right direction?

AI and robotics got to the point where you could actually do things that were useful, so it turned to the practical applications and somewhat, maybe not abandoned, but put to the side, the more fundamental scientific questions, just caught up in the success of the technology and achieving specific goals.

The approximating unanalyzed data kind is sort of a new approach, not totally, there's things like it in the past. It's basically a new approach that has been accelerated by the existence of massive memories, very rapid processing, which enables you to do things like this that you couldn't have done by hand. But I think, myself, that it is leading subjects like computational cognitive science into a direction of maybe some practical applicability... ..in engineering? Chomsky: ...But away from understanding.

I was very skeptical about the original work. I thought it was first of all way too optimistic, it was assuming you could achieve things that required real understanding of systems that were barely understood, and you just can't get to that understanding by throwing a complicated machine at it.

if success is defined as getting a fair approximation to a mass of chaotic unanalyzed data, then it's way better to do it this way than to do it the way the physicists do, you know, no thought experiments about frictionless planes and so on and so forth. But you won't get the kind of understanding that the sciences have always been aimed at -- what you'll get at is an approximation to what's happening.

Suppose you want to predict tomorrow's weather. One way to do it is okay I'll get my statistical priors, if you like, there's a high probability that tomorrow's weather here will be the same as it was yesterday in Cleveland, so I'll stick that in, and where the sun is will have some effect, so I'll stick that in, and you get a bunch of assumptions like that, you run the experiment, you look at it over and over again, you correct it by Bayesian methods, you get better priors. You get a pretty good approximation of what tomorrow's weather is going to be. That's not what meteorologists do -- they want to understand how it's working. And these are just two different concepts of what success means, of what achievement is.

if you get more and more data, and better and better statistics, you can get a better and better approximation to some immense corpus of text, like everything in The Wall Street Journal archives -- but you learn nothing about the language.

the right approach, is to try to see if you can understand what the fundamental principles are that deal with the core properties, and recognize that in the actual usage, there's going to be a thousand other variables intervening -- kind of like what's happening outside the window, and you'll sort of tack those on later on if you want better approximations, that's a different approach.

take a concrete example of a new field in neuroscience, called Connectomics, where the goal is to find the wiring diagram of very complex organisms, find the connectivity of all the neurons in say human cerebral cortex, or mouse cortex. This approach was criticized by Sidney Brenner, who in many ways is [historically] one of the originators of the approach. Advocates of this field don't stop to ask if the wiring diagram is the right level of abstraction -- maybe it's no

if you went to MIT in the 1960s, or now, it's completely different. No matter what engineering field you're in, you learn the same basic science and mathematics. And then maybe you learn a little bit about how to apply it. But that's a very different approach. And it resulted maybe from the fact that really for the first time in history, the basic sciences, like physics, had something really to tell engineers. And besides, technologies began to change very fast, so not very much point in learning the technologies of today if it's going to be different 10 years from now. So you have to learn the fundamental science that's going to be applicable to whatever comes along next. And the same thing pretty much happened in medicine.

that's the kind of transition from something like an art, that you learn how to practice -- an analog would be trying to match some data that you don't understand, in some fashion, maybe building something that will work -- to science, what happened in the modern period, roughly Galilean science.

it turns out that there actually are neural circuits which are reacting to particular kinds of rhythm, which happen to show up in language, like syllable length and so on. And there's some evidence that that's one of the first things that the infant brain is seeking -- rhythmic structures. And going back to Gallistel and Marr, its got some computational system inside which is saying "okay, here's what I do with these things" and say, by nine months, the typical infant has rejected -- eliminated from its repertoire -- the phonetic distinctions that aren't used in its own language.

people like Shimon Ullman discovered some pretty remarkable things like the rigidity principle. You're not going to find that by statistical analysis of data. But he did find it by carefully designed experiments. Then you look for the neurophysiology, and see if you can find something there that carries out these computations. I think it's the same in language, the same in studying our arithmetical capacity, planning, almost anything you look at. Just trying to deal with the unanalyzed chaotic data is unlikely to get you anywhere, just like as it wouldn't have gotten Galileo anywhere.

with regard to cognitive science, we're kind of pre-Galilean, just beginning to open up the subject

You can invent a world -- I don't think it's our world -- but you can invent a world in which nothing happens except random changes in objects and selection on the basis of external forces. I don't think that's the way our world works, I don't think it's the way any biologist thinks it is. There are all kind of ways in which natural law imposes channels within which selection can take place, and some things can happen and other things don't happen. Plenty of things that go on in the biology in organisms aren't like this. So take the first step, meiosis. Why do cells split into spheres and not cubes? It's not random mutation and natural selection; it's a law of physics. There's no reason to think that laws of physics stop there, they work all the way through. Well, they constrain the biology, sure. Chomsky: Okay, well then it's not just random mutation and selection. It's random mutation, selection, and everything that matters, like laws of physics.

What I think is valuable is the history of science. I think we learn a lot of things from the history of science that can be very valuable to the emerging sciences. Particularly when we realize that in say, the emerging cognitive sciences, we really are in a kind of pre-Galilean stage. We don't know wh

at we're looking for anymore than Galileo did, and there's a lot to learn from that.

If we want protection from the world we’re building, perhaps we’re asking that the algorithm wielders choose not to know things, despite their being true. To some, that may be a little like the 1616 order by the Catholic Church that Galileo cease from teaching or discussing the idea that the Earth moves around the sun.

one bit here and another there, both innocuous, may reveal something personal that is hidden perhaps even from myself.

Since then, we have been living in something closer to the spirit of the 18th-century Enlightenment, when all forms of knowledge were acceptable, and learning was a good in its own right. Regulation has been based on actions, not on knowledge.

the situation may be something like a vastly more difficult version of laws against red lining

we are also entering a new world where individuals can be as powerful as institutions. That phone gives Big Brother lots of data goodies, but it can also have access to its own pattern-finding algorithms, and publish those findings to the world.

Asked later during a television interview about the president’s son, Mr. Khan dismissed the post. “I’m not going to respond to a tweet from Donald Trump Jr.,” he said on CNN. “I’ve been doing far more important things over the last 24 hours.”

Financing for the top 35 companies involved in tar sands — one of the most environmentally destructive fossil fuels to extract and process — decreased 27% since 2019, to $16 billion. 

“The policies and commitments that banks have put out so far give us no reason to believe they’re going to make these deep emissions cuts that the science demands,”

specific argument—that Amazon’s actions are bad for consumers because they make our world less intellectually active and diverse—is unorthodox in its resort to cultural and artistic grounds. But it can be read as the inverse of a case like Leegin v. PSKS: that lower prices for worse products could be bad for consumers—and perhaps constitute an antitrust violation.

if higher prices corresponded with better products, that could be good for consumers—and not necessarily an antitrust violation.

Their argument is this: Amazon has used its market power both to influence which books get attention (by featuring them more prominently on its Web site, a practice I’ve also written about) and, in some cases, to drive prices lower. These practices, the authors argue, squeeze publishers, which makes them more risk-averse in deciding which books to publish. As a result, they claim, publishers have been “dropping some midlist authors and not publishing certain riskier books, effectively silencing many voices.” And this is bad not only for the non-famous writers who go unpublished, but for their would-be readers, who are denied the ability to hear those voices.

While it may be attractive, on a philosophical level, to argue that Amazon is bad for us because it makes our culture poorer, measuring that effect would be difficult, if not impossible. How would one go about valuing an unpublished masterpiece by an unknown author? This is further complicated by the fact that Amazon makes it easy for authors to self-publish and have their work be seen, without having to go through such traditional gatekeepers as agents and publishers; Amazon might argue that this allows for more free flow of information and ideas

Furthermore, U.S. law is concerned with diversity in media, Crane said, but that tends to be regulated through the Federal Communications Commission, not the Justice Department.

it’s quite possible the Justice Department will read the Authors United letter and dismiss it as uninformed. But even if that happens, Preston said, it will have been worthwhile for the writers to have made their case.

Authors United’s larger mission, he told me, was this: “We hope to show the public that getting products faster and cheaper isn’t necessarily the greatest good. It comes at a human cost.”