Group items tagged

By the end of World War II, however, American corporations were facing severe talent shortages. Their senior executives were growing old, and a dearth of hiring from the Depression through the war had resulted in a shortfall of able, well-trained managers. Finding people who had the potential to rise quickly through the ranks became an overriding preoccupation of American businesses. They began to devise a formal hiring-and-management system based in part on new studies of human behavior, and in part on military techniques developed during both world wars, when huge mobilization efforts and mass casualties created the need to get the right people into the right roles as efficiently as possible. By the 1950s, it was not unusual for companies to spend days with young applicants for professional jobs, conducting a battery of tests, all with an eye toward corner-office potential.

But companies abandoned their hard-edged practices for another important reason: many of their methods of evaluation turned out not to be very scientific.

this regime, so widespread in corporate America at mid-century, had almost disappeared by 1990. “I think an HR person from the late 1970s would be stunned to see how casually companies hire now,”

Many factors explain the change, he said, and then he ticked off a number of them: Increased job-switching has made it less important and less economical for companies to test so thoroughly. A heightened focus on short-term financial results has led to deep cuts in corporate functions that bear fruit only in the long term. The Civil Rights Act of 1964, which exposed companies to legal liability for discriminatory hiring practices, has made HR departments wary of any broadly applied and clearly scored test that might later be shown to be systematically biased.

about a quarter of the country’s corporations were using similar tests to evaluate managers and junior executives, usually to assess whether they were ready for bigger roles.

He has encouraged the company’s HR executives to think about applying the games to the recruitment and evaluation of all professional workers.

Knack makes app-based video games, among them Dungeon Scrawl, a quest game requiring the player to navigate a maze and solve puzzles, and Wasabi Waiter, which involves delivering the right sushi to the right customer at an increasingly crowded happy hour. These games aren’t just for play: they’ve been designed by a team of neuroscientists, psychologists, and data scientists to suss out human potential. Play one of them for just 20 minutes, says Guy Halfteck, Knack’s founder, and you’ll generate several megabytes of data, exponentially more than what’s collected by the SAT or a personality test. How long you hesitate before taking every action, the sequence of actions you take, how you solve problems—all of these factors and many more are logged as you play, and then are used to analyze your creativity, your persistence, your capacity to learn quickly from mistakes, your ability to prioritize, and even your social intelligence and personality. The end result, Halfteck says, is a high-resolution portrait of your psyche and intellect, and an assessment of your potential as a leader or an innovator.

When the results came back, Haringa recalled, his heart began to beat a little faster. Without ever seeing the ideas, without meeting or interviewing the people who’d proposed them, without knowing their title or background or academic pedigree, Knack’s algorithm had identified the people whose ideas had panned out. The top 10 percent of the idea generators as predicted by Knack were in fact those who’d gone furthest in the process.

What Knack is doing, Haringa told me, “is almost like a paradigm shift.” It offers a way for his GameChanger unit to avoid wasting time on the 80 people out of 100—nearly all of whom look smart, well-trained, and plausible on paper—whose ideas just aren’t likely to work out.

Aptitude, skills, personal history, psychological stability, discretion, loyalty—companies at the time felt they had a need (and the right) to look into them all. That ambit is expanding once again, and this is undeniably unsettling. Should the ideas of scientists be dismissed because of the way they play a game? Should job candidates be ranked by what their Web habits say about them? Should the “data signature” of natural leaders play a role in promotion? These are all live questions today, and they prompt heavy concerns: that we will cede one of the most subtle and human of skills, the evaluation of the gifts and promise of other people, to machines; that the models will get it wrong; that some people will never get a shot in the new workforce.

scoring distance from work could violate equal-employment-opportunity standards. Marital status? Motherhood? Church membership? “Stuff like that,” Meyerle said, “we just don’t touch”—at least not in the U.S., where the legal environment is strict. Meyerle told me that Evolv has looked into these sorts of factors in its work for clients abroad, and that some of them produce “startling results.”

consider the alternative. A mountain of scholarly literature has shown that the intuitive way we now judge professional potential is rife with snap judgments and hidden biases, rooted in our upbringing or in deep neurological connections that doubtless served us well on the savanna but would seem to have less bearing on the world of work.

We may like to think that society has become more enlightened since those days, and in many ways it has, but our biases are mostly unconscious, and they can run surprisingly deep. Consider race. For a 2004 study called “Are Emily and Greg More Employable Than Lakisha and Jamal?,” the economists Sendhil Mullainathan and Marianne Bertrand put white-sounding names (Emily Walsh, Greg Baker) or black-sounding names (Lakisha Washington, Jamal Jones) on similar fictitious résumés, which they then sent out to a variety of companies in Boston and Chicago. To get the same number of callbacks, they learned, they needed to either send out half again as many résumés with black names as those with white names, or add eight extra years of relevant work experience to the résumés with black names.

a sociologist at Northwestern, spent parts of the three years from 2006 to 2008 interviewing professionals from elite investment banks, consultancies, and law firms about how they recruited, interviewed, and evaluated candidates, and concluded that among the most important factors driving their hiring recommendations were—wait for it—shared leisure interests.

Lacking “reliable predictors of future performance,” Rivera writes, “assessors purposefully used their own experiences as models of merit.” Former college athletes “typically prized participation in varsity sports above all other types of involvement.” People who’d majored in engineering gave engineers a leg up, believing they were better prepared.

the prevailing system of hiring and management in this country involves a level of dysfunction that should be inconceivable in an economy as sophisticated as ours. Recent survey data collected by the Corporate Executive Board, for example, indicate that nearly a quarter of all new hires leave their company within a year of their start date, and that hiring managers wish they’d never extended an offer to one out of every five members on their team

In the late 1990s, as these assessments shifted from paper to digital formats and proliferated, data scientists started doing massive tests of what makes for a successful customer-support technician or salesperson. This has unquestionably improved the quality of the workers at many firms.

In 2010, however, Xerox switched to an online evaluation that incorporates personality testing, cognitive-skill assessment, and multiple-choice questions about how the applicant would handle specific scenarios that he or she might encounter on the job. An algorithm behind the evaluation analyzes the responses, along with factual information gleaned from the candidate’s application, and spits out a color-coded rating: red (poor candidate), yellow (middling), or green (hire away). Those candidates who score best, I learned, tend to exhibit a creative but not overly inquisitive personality, and participate in at least one but not more than four social networks, among many other factors. (Previous experience, one of the few criteria that Xerox had explicitly screened for in the past, turns out to have no bearing on either productivity or retention

When Xerox started using the score in its hiring decisions, the quality of its hires immediately improved. The rate of attrition fell by 20 percent in the initial pilot period, and over time, the number of promotions rose. Xerox still interviews all candidates in person before deciding to hire them, Morse told me, but, she added, “We’re getting to the point where some of our hiring managers don’t even want to interview anymore”

Gone are the days, Ostberg told me, when, say, a small survey of college students would be used to predict the statistical validity of an evaluation tool. “We’ve got a data set of 347,000 actual employees who have gone through these different types of assessments or tools,” he told me, “and now we have performance-outcome data, and we can split those and slice and dice by industry and location.”

Evolv’s tests allow companies to capture data about everybody who applies for work, and everybody who gets hired—a complete data set from which sample bias, long a major vexation for industrial-organization psychologists, simply disappears. The sheer number of observations that this approach makes possible allows Evolv to say with precision which attributes matter more to the success of retail-sales workers (decisiveness, spatial orientation, persuasiveness) or customer-service personnel at call centers (rapport-building)

There are some data that Evolv simply won’t use, out of a concern that the information might lead to systematic bias against whole classes of people

the idea that hiring was a science fell out of favor. But now it’s coming back, thanks to new technologies and methods of analysis that are cheaper, faster, and much-wider-ranging than what we had before

what most excites him are the possibilities that arise from monitoring the entire life cycle of a worker at any given company.

Now the two companies are working together to marry pre-hire assessments to an increasing array of post-hire data: about not only performance and duration of service but also who trained the employees; who has managed them; whether they were promoted to a supervisory role, and how quickly; how they performed in that role; and why they eventually left.

What begins with an online screening test for entry-level workers ends with the transformation of nearly every aspect of hiring, performance assessment, and management.

I turned to Sandy Pentland, the director of the Human Dynamics Laboratory at MIT. In recent years, Pentland has pioneered the use of specialized electronic “badges” that transmit data about employees’ interactions as they go about their days. The badges capture all sorts of information about formal and informal conversations: their length; the tone of voice and gestures of the people involved; how much those people talk, listen, and interrupt; the degree to which they demonstrate empathy and extroversion; and more. Each badge generates about 100 data points a minute.

he tried the badges out on about 2,500 people, in 21 different organizations, and learned a number of interesting lessons. About a third of team performance, he discovered, can usually be predicted merely by the number of face-to-face exchanges among team members. (Too many is as much of a problem as too few.) Using data gathered by the badges, he was able to predict which teams would win a business-plan contest, and which workers would (rightly) say they’d had a “productive” or “creative” day. Not only that, but he claimed that his researchers had discovered the “data signature” of natural leaders, whom he called “charismatic connectors” and all of whom, he reported, circulate actively, give their time democratically to others, engage in brief but energetic conversations, and listen at least as much as they talk.

His group is developing apps to allow team members to view their own metrics more or less in real time, so that they can see, relative to the benchmarks of highly successful employees, whether they’re getting out of their offices enough, or listening enough, or spending enough time with people outside their own team.

Torrents of data are routinely collected by American companies and now sit on corporate servers, or in the cloud, awaiting analysis. Bloomberg reportedly logs every keystroke of every employee, along with their comings and goings in the office. The Las Vegas casino Harrah’s tracks the smiles of the card dealers and waitstaff on the floor (its analytics team has quantified the impact of smiling on customer satisfaction). E‑mail, of course, presents an especially rich vein to be mined for insights about our productivity, our treatment of co-workers, our willingness to collaborate or lend a hand, our patterns of written language, and what those patterns reveal about our intelligence, social skills, and behavior.

people analytics will ultimately have a vastly larger impact on the economy than the algorithms that now trade on Wall Street or figure out which ads to show us. He reminded me that we’ve witnessed this kind of transformation before in the history of management science. Near the turn of the 20th century, both Frederick Taylor and Henry Ford famously paced the factory floor with stopwatches, to improve worker efficiency.

“The quantities of data that those earlier generations were working with,” he said, “were infinitesimal compared to what’s available now. There’s been a real sea change in the past five years, where the quantities have just grown so large—petabytes, exabytes, zetta—that you start to be able to do things you never could before.”

People analytics will unquestionably provide many workers with more options and more power. Gild, for example, helps companies find undervalued software programmers, working indirectly to raise those people’s pay. Other companies are doing similar work. One called Entelo, for instance, specializes in using algorithms to identify potentially unhappy programmers who might be receptive to a phone cal

He sees it not only as a boon to a business’s productivity and overall health but also as an important new tool that individual employees can use for self-improvement: a sort of radically expanded The 7 Habits of Highly Effective People, custom-written for each of us, or at least each type of job, in the workforce.

the most exotic development in people analytics today is the creation of algorithms to assess the potential of all workers, across all companies, all the time.

The way Gild arrives at these scores is not simple. The company’s algorithms begin by scouring the Web for any and all open-source code, and for the coders who wrote it. They evaluate the code for its simplicity, elegance, documentation, and several other factors, including the frequency with which it’s been adopted by other programmers. For code that was written for paid projects, they look at completion times and other measures of productivity. Then they look at questions and answers on social forums such as Stack Overflow, a popular destination for programmers seeking advice on challenging projects. They consider how popular a given coder’s advice is, and how widely that advice ranges.

The algorithms go further still. They assess the way coders use language on social networks from LinkedIn to Twitter; the company has determined that certain phrases and words used in association with one another can distinguish expert programmers from less skilled ones. Gild knows these phrases and words are associated with good coding because it can correlate them with its evaluation of open-source code, and with the language and online behavior of programmers in good positions at prestigious companies.

having made those correlations, Gild can then score programmers who haven’t written open-source code at all, by analyzing the host of clues embedded in their online histories. They’re not all obvious, or easy to explain. Vivienne Ming, Gild’s chief scientist, told me that one solid predictor of strong coding is an affinity for a particular Japanese manga site.

Gild’s CEO, Sheeroy Desai, told me he believes his company’s approach can be applied to any occupation characterized by large, active online communities, where people post and cite individual work, ask and answer professional questions, and get feedback on projects. Graphic design is one field that the company is now looking at, and many scientific, technical, and engineering roles might also fit the bill. Regardless of their occupation, most people leave “data exhaust” in their wake, a kind of digital aura that can reveal a lot about a potential hire.

professionally relevant personality traits can be judged effectively merely by scanning Facebook feeds and photos. LinkedIn, of course, captures an enormous amount of professional data and network information, across just about every profession. A controversial start-up called Klout has made its mission the measurement and public scoring of people’s online social influence.

Mullainathan expressed amazement at how little most creative and professional workers (himself included) know about what makes them effective or ineffective in the office. Most of us can’t even say with any certainty how long we’ve spent gathering information for a given project, or our pattern of information-gathering, never mind know which parts of the pattern should be reinforced, and which jettisoned. As Mullainathan put it, we don’t know our own “production function.”

Over time, better job-matching technologies are likely to begin serving people directly, helping them see more clearly which jobs might suit them and which companies could use their skills. In the future, Gild plans to let programmers see their own profiles and take skills challenges to try to improve their scores. It intends to show them its estimates of their market value, too, and to recommend coursework that might allow them to raise their scores even more. Not least, it plans to make accessible the scores of typical hires at specific companies, so that software engineers can better see the profile they’d need to land a particular job

Knack, for its part, is making some of its video games available to anyone with a smartphone, so people can get a better sense of their strengths, and of the fields in which their strengths would be most valued. (Palo Alto High School recently adopted the games to help students assess careers.) Ultimately, the company hopes to act as matchmaker between a large network of people who play its games (or have ever played its games) and a widening roster of corporate clients, each with its own specific profile for any given type of job.

When I began my reporting for this story, I was worried that people analytics, if it worked at all, would only widen the divergent arcs of our professional lives, further gilding the path of the meritocratic elite from cradle to grave, and shutting out some workers more definitively. But I now believe the opposite is likely to happen, and that we’re headed toward a labor market that’s fairer to people at every stage of their careers

For decades, as we’ve assessed people’s potential in the professional workforce, the most important piece of data—the one that launches careers or keeps them grounded—has been educational background: typically, whether and where people went to college, and how they did there. Over the past couple of generations, colleges and universities have become the gatekeepers to a prosperous life. A degree has become a signal of intelligence and conscientiousness, one that grows stronger the more selective the school and the higher a student’s GPA, that is easily understood by employers, and that, until the advent of people analytics, was probably unrivaled in its predictive powers.

the limitations of that signal—the way it degrades with age, its overall imprecision, its many inherent biases, its extraordinary cost—are obvious. “Academic environments are artificial environments,” Laszlo Bock, Google’s senior vice president of people operations, told The New York Times in June. “People who succeed there are sort of finely trained, they’re conditioned to succeed in that environment,” which is often quite different from the workplace.

because one’s college history is such a crucial signal in our labor market, perfectly able people who simply couldn’t sit still in a classroom at the age of 16, or who didn’t have their act together at 18, or who chose not to go to graduate school at 22, routinely get left behind for good. That such early factors so profoundly affect career arcs and hiring decisions made two or three decades later is, on its face, absurd.

I spoke with managers at a lot of companies who are using advanced analytics to reevaluate and reshape their hiring, and nearly all of them told me that their research is leading them toward pools of candidates who didn’t attend college—for tech jobs, for high-end sales positions, for some managerial roles. In some limited cases, this is because their analytics revealed no benefit whatsoever to hiring people with college degrees; in other cases, and more often, it’s because they revealed signals that function far better than college history,

Google, too, is hiring a growing number of nongraduates. Many of the people I talked with reported that when it comes to high-paying and fast-track jobs, they’re reducing their preference for Ivy Leaguers and graduates of other highly selective schools.

This process is just beginning. Online courses are proliferating, and so are online markets that involve crowd-sourcing. Both arenas offer new opportunities for workers to build skills and showcase competence. Neither produces the kind of instantly recognizable signals of potential that a degree from a selective college, or a first job at a prestigious firm, might. That’s a problem for traditional hiring managers, because sifting through lots of small signals is so difficult and time-consuming.

all of these new developments raise philosophical questions. As professional performance becomes easier to measure and see, will we become slaves to our own status and potential, ever-focused on the metrics that tell us how and whether we are measuring up? Will too much knowledge about our limitations hinder achievement and stifle our dreams? All I can offer in response to these questions, ironically, is my own gut sense, which leads me to feel cautiously optimistic.

Google’s understanding of the promise of analytics is probably better than anybody else’s, and the company has been changing its hiring and management practices as a result of its ongoing analyses. (Brainteasers are no longer used in interviews, because they do not correlate with job success; GPA is not considered for anyone more than two years out of school, for the same reason—the list goes on.) But for all of Google’s technological enthusiasm, these same practices are still deeply human. A real, live person looks at every résumé the company receives. Hiring decisions are made by committee and are based in no small part on opinions formed during structured interviews.

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.”

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.”

That’s the latest among several recent studies by economists working independently, all arriving at similar findings: A few “superstar firms” have grown to dominate their industries, crowding out competitors and controlling markets to a degree not seen in many decades.

Let’s look beyond such obvious winner-take-all examples as Apple or Alphabet, the parent of Google.

Consider real-estate services. In 1997, according to Profs. Grullon, Larkin and Michaely, that sector had 42 publicly traded companies; the four largest generated 49% of the group’s total revenue. By 2014, only 20 public firms were left, and the top four— CBRE Group, Jones Lang LaSalle, Realogy Holdings and Wyndham Worldwide—commanded 78% of the group’s combined revenue.

Or look at supermarkets. In 1997, there were 36 publicly traded companies in that industry, with the top four accounting for more than half of total sales. By 2014, only 11 were left. The top four—Kroger, Supervalu, Whole Foods Market and Roundy’s (since acquired by Kroger)—held 89% of the pie.

The U.S. had more than 7,000 public companies 20 years ago, the professors say; nowadays, it’s fewer than 4,000.

The winners are also grabbing most of the profits

At the end of 1996, the 25 companies in the S&P 500 with the highest net profit margins—income as a percentage of revenue—earned a median of just under 21 cents on every dollar of sales. Last year, the top 25 such companies earned a median of 39 cents on the dollar.

Two decades ago, the median net margin among all S&P 500 members was 6.7%. By the end of 2016, that had increased to 9.7%.

So while companies as a whole became more profitable over the past 20 years, the winners have become vastly more profitable, nearly doubling the gains they got on each dollar of sales.

Why might it be easier now for winners to take all? Prof. Michaely suggests two theories. Declining enforcement of antitrust rules has led to bigger mergers, less competition and higher profits.

The other is technology. “If you want to compete with Google or Amazon,” he says, “you’ll have to invest not just billions, but tens of billions of dollars.”

Still, history offers a warning. Many times in the past, winners have taken all but seldom for long.

By removing the tangible product from the center of commerce, surveillance capitalism upsets the equilibrium. Whenever we use free apps and online services, it’s often said, we become the products, our attention harvested and sold to advertisers

this truism gets it wrong. Surveillance capitalism’s real products, vaporous but immensely valuable, are predictions about our future behavior — what we’ll look at, where we’ll go, what we’ll buy, what opinions we’ll hold — that internet companies derive from our personal data and sell to businesses, political operatives, and other bidders.

Unlike financial derivatives, which they in some ways resemble, these new data derivatives draw their value, parasite-like, from human experience.To the Googles and Facebooks of the world, we are neither the customer nor the product. We are the source of what Silicon Valley technologists call “data exhaust” — the informational byproducts of online activity that become the inputs to prediction algorithms

Another 2015 study, appearing in the Journal of Computer-Mediated Communication, showed that when people hear their phone ring but are unable to answer it, their blood pressure spikes, their pulse quickens, and their problem-solving skills decline.

The smartphone has become a repository of the self, recording and dispensing the words, sounds and images that define what we think, what we experience and who we are. In a 2015 Gallup survey, more than half of iPhone owners said that they couldn’t imagine life without the device.

So what happens to our minds when we allow a single tool such dominion over our perception and cognition?

Not only do our phones shape our thoughts in deep and complicated ways, but the effects persist even when we aren’t using the devices. As the brain grows dependent on the technology, the research suggests, the intellect weakens.

he has seen mounting evidence that using a smartphone, or even hearing one ring or vibrate, produces a welter of distractions that makes it harder to concentrate on a difficult problem or job. The division of attention impedes reasoning and performance.

internet companies operate in what Zuboff terms “extreme structural independence from people.” When databases displace goods as the engine of the economy, our own interests, as consumers but also as citizens, cease to be part of the negotiation. We are no longer one of the forces guiding the market’s invisible hand. We are the objects of surveillance and control.

Social skills and relationships seem to suffer as well.

In both tests, the subjects whose phones were in view posted the worst scores, while those who left their phones in a different room did the best. The students who kept their phones in their pockets or bags came out in the middle. As the phone’s proximity increased, brainpower decreased.

In subsequent interviews, nearly all the participants said that their phones hadn’t been a distraction—that they hadn’t even thought about the devices during the experiment. They remained oblivious even as the phones disrupted their focus and thinking.

The researchers recruited 520 undergraduates at UCSD and gave them two standard tests of intellectual acuity. One test gauged “available working-memory capacity,” a measure of how fully a person’s mind can focus on a particular task. The second assessed “fluid intelligence,” a person’s ability to interpret and solve an unfamiliar problem. The only variable in the experiment was the location of the subjects’ smartphones. Some of the students were asked to place their phones in front of them on their desks; others were told to stow their phones in their pockets or handbags; still others were required to leave their phones in a different room.

the “integration of smartphones into daily life” appears to cause a “brain drain” that can diminish such vital mental skills as “learning, logical reasoning, abstract thought, problem solving, and creativity.”

 Smartphones have become so entangled with our existence that, even when we’re not peering or pawing at them, they tug at our attention, diverting precious cognitive resources. Just suppressing the desire to check our phone, which we do routinely and subconsciously throughout the day, can debilitate our thinking.

They found that students who didn’t bring their phones to the classroom scored a full letter-grade higher on a test of the material presented than those who brought their phones. It didn’t matter whether the students who had their phones used them or not: All of them scored equally poorly.

A study of nearly a hundred secondary schools in the U.K., published last year in the journal Labour Economics, found that when schools ban smartphones, students’ examination scores go up substantially, with the weakest students benefiting the most.

Data, the novelist and critic Cynthia Ozick once wrote, is “memory without history.” Her observation points to the problem with allowing smartphones to commandeer our brains

Because smartphones serve as constant reminders of all the friends we could be chatting with electronically, they pull at our minds when we’re talking with people in person, leaving our conversations shallower and less satisfying.

In a 2013 study conducted at the University of Essex in England, 142 participants were divided into pairs and asked to converse in private for ten minutes. Half talked with a phone in the room, half without a phone present. The subjects were then given tests of affinity, trust and empathy. “The mere presence of mobile phones,” the researchers reported in the Journal of Social and Personal Relationships, “inhibited the development of interpersonal closeness and trust” and diminished “the extent to which individuals felt empathy and understanding from their partners.”

The evidence that our phones can get inside our heads so forcefully is unsettling. It suggests that our thoughts and feelings, far from being sequestered in our skulls, can be skewed by external forces we’re not even aware o

 Scientists have long known that the brain is a monitoring system as well as a thinking system. Its attention is drawn toward any object that is new, intriguing or otherwise striking — that has, in the psychological jargon, “salience.”

even in the history of captivating media, the smartphone stands out. It is an attention magnet unlike any our minds have had to grapple with before. Because the phone is packed with so many forms of information and so many useful and entertaining functions, it acts as what Dr. Ward calls a “supernormal stimulus,” one that can “hijack” attention whenever it is part of our surroundings — and it is always part of our surroundings.

Imagine combining a mailbox, a newspaper, a TV, a radio, a photo album, a public library and a boisterous party attended by everyone you know, and then compressing them all into a single, small, radiant object. That is what a smartphone represents to us. No wonder we can’t take our minds off it.

The irony of the smartphone is that the qualities that make it so appealing to us — its constant connection to the net, its multiplicity of apps, its responsiveness, its portability — are the very ones that give it such sway over our minds.

Phone makers like Apple and Samsung and app writers like Facebook, Google and Snap design their products to consume as much of our attention as possible during every one of our waking hours

Social media apps were designed to exploit “a vulnerability in human psychology,” former Facebook president Sean Parker said in a recent interview. “[We] understood this consciously. And we did it anyway.”

A quarter-century ago, when we first started going online, we took it on faith that the web would make us smarter: More information would breed sharper thinking. We now know it’s not that simple.

As strange as it might seem, people’s knowledge and understanding may actually dwindle as gadgets grant them easier access to online data stores

In a seminal 2011 study published in Science, a team of researchers — led by the Columbia University psychologist Betsy Sparrow and including the late Harvard memory expert Daniel Wegner — had a group of volunteers read forty brief, factual statements (such as “The space shuttle Columbia disintegrated during re-entry over Texas in Feb. 2003”) and then type the statements into a computer. Half the people were told that the machine would save what they typed; half were told that the statements would be erased.

Afterward, the researchers asked the subjects to write down as many of the statements as they could remember. Those who believed that the facts had been recorded in the computer demonstrated much weaker recall than those who assumed the facts wouldn’t be stored. Anticipating that information would be readily available in digital form seemed to reduce the mental effort that people made to remember it

The researchers dubbed this phenomenon the “Google effect” and noted its broad implications: “Because search engines are continually available to us, we may often be in a state of not feeling we need to encode the information internally. When we need it, we will look it up.”

as the pioneering psychologist and philosopher William James said in an 1892 lecture, “the art of remembering is the art of thinking.”

Only by encoding information in our biological memory can we weave the rich intellectual associations that form the essence of personal knowledge and give rise to critical and conceptual thinking. No matter how much information swirls around us, the less well-stocked our memory, the less we have to think with.

As Dr. Wegner and Dr. Ward explained in a 2013 Scientific American article, when people call up information through their devices, they often end up suffering from delusions of intelligence. They feel as though “their own mental capacities” had generated the information, not their devices. “The advent of the ‘information age’ seems to have created a generation of people who feel they know more than ever before,” the scholars concluded, even though “they may know ever less about the world around them.”

That insight sheds light on society’s current gullibility crisis, in which people are all too quick to credit lies and half-truths spread through social media. If your phone has sapped your powers of discernment, you’ll believe anything it tells you.

A second experiment conducted by the researchers produced similar results, while also revealing that the more heavily students relied on their phones in their everyday lives, the greater the cognitive penalty they suffered.

When we constrict our capacity for reasoning and recall or transfer those skills to a gadget, we sacrifice our ability to turn information into knowledge. We get the data but lose the meaning

We need to give our minds more room to think. And that means putting some distance between ourselves and our phones.

Google’s once-patient investors grew restive, demanding that the founders figure out a way to make money, preferably lots of it.

nder pressure, Page and Brin authorized the launch of an auction system for selling advertisements tied to search queries. The system was designed so that the company would get paid by an advertiser only when a user clicked on an ad. This feature gave Google a huge financial incentive to make accurate predictions about how users would respond to ads and other online content. Even tiny increases in click rates would bring big gains in income. And so the company began deploying its stores of behavioral data not for the benefit of users but to aid advertisers — and to juice its own profits. Surveillance capitalism had arrived.

Google’s business now hinged on what Zuboff calls “the extraction imperative.” To improve its predictions, it had to mine as much information as possible from web users. It aggressively expanded its online services to widen the scope of its surveillance.

Through Gmail, it secured access to the contents of people’s emails and address books. Through Google Maps, it gained a bead on people’s whereabouts and movements. Through Google Calendar, it learned what people were doing at different moments during the day and whom they were doing it with. Through Google News, it got a readout of people’s interests and political leanings. Through Google Shopping, it opened a window onto people’s wish lists,

The company gave all these services away for free to ensure they’d be used by as many people as possible. It knew the money lay in the data.

the organization grew insular and secretive. Seeking to keep the true nature of its work from the public, it adopted what its CEO at the time, Eric Schmidt, called a “hiding strategy” — a kind of corporate omerta backed up by stringent nondisclosure agreements.

Page and Brin further shielded themselves from outside oversight by establishing a stock structure that guaranteed their power could never be challenged, neither by investors nor by directors.

What’s most remarkable about the birth of surveillance capitalism is the speed and audacity with which Google overturned social conventions and norms about data and privacy. Without permission, without compensation, and with little in the way of resistance, the company seized and declared ownership over everyone’s information

The companies that followed Google presumed that they too had an unfettered right to collect, parse, and sell personal data in pretty much any way they pleased. In the smart homes being built today, it’s understood that any and all data will be beamed up to corporate clouds.

Google conducted its great data heist under the cover of novelty. The web was an exciting frontier — something new in the world — and few people understood or cared about what they were revealing as they searched and surfed. In those innocent days, data was there for the taking, and Google took it

Google also benefited from decisions made by lawmakers, regulators, and judges — decisions that granted internet companies free use of a vast taxpayer-funded communication infrastructure, relieved them of legal and ethical responsibility for the information and messages they distributed, and gave them carte blanche to collect and exploit user data.

Consider the terms-of-service agreements that govern the division of rights and the delegation of ownership online. Non-negotiable, subject to emendation and extension at the company’s whim, and requiring only a casual click to bind the user, TOS agreements are parodies of contracts, yet they have been granted legal legitimacy by the court

Law professors, writes Zuboff, “call these ‘contracts of adhesion’ because they impose take-it-or-leave-it conditions on users that stick to them whether they like it or not.” Fundamentally undemocratic, the ubiquitous agreements helped Google and other firms commandeer personal data as if by fiat.

n the choices we make as consumers and private citizens, we have always traded some of our autonomy to gain other rewards. Many people, it seems clear, experience surveillance capitalism less as a prison, where their agency is restricted in a noxious way, than as an all-inclusive resort, where their agency is restricted in a pleasing way

Zuboff makes a convincing case that this is a short-sighted and dangerous view — that the bargain we’ve struck with the internet giants is a Faustian one

but her case would have been stronger still had she more fully addressed the benefits side of the ledger.

there’s a piece missing. While Zuboff’s assessment of the costs that people incur under surveillance capitalism is exhaustive, she largely ignores the benefits people receive in return — convenience, customization, savings, entertainment, social connection, and so on

hat the industries of the future will seek to manufacture is the self.

Behavior modification is the thread that ties today’s search engines, social networks, and smartphone trackers to tomorrow’s facial-recognition systems, emotion-detection sensors, and artificial-intelligence bots.

All of Facebook’s information wrangling and algorithmic fine-tuning, she writes, “is aimed at solving one problem: how and when to intervene in the state of play that is your daily life in order to modify your behavior and thus sharply increase the predictability of your actions now, soon, and later.”

“The goal of everything we do is to change people’s actual behavior at scale,” a top Silicon Valley data scientist told her in an interview. “We can test how actionable our cues are for them and how profitable certain behaviors are for us.”

This goal, she suggests, is not limited to Facebook. It is coming to guide much of the economy, as financial and social power shifts to the surveillance capitalists

Combining rich information on individuals’ behavioral triggers with the ability to deliver precisely tailored and timed messages turns out to be a recipe for behavior modification on an unprecedented scale.

it was Facebook, with its incredibly detailed data on people’s social lives, that grasped digital media’s full potential for behavior modification. By using what it called its “social graph” to map the intentions, desires, and interactions of literally billions of individuals, it saw that it could turn its network into a worldwide Skinner box, employing psychological triggers and rewards to program not only what people see but how they react.

spying on the populace is not the end game. The real prize lies in figuring out ways to use the data to shape how people think and act. “The best way to predict the future is to invent it,” the computer scientist Alan Kay once observed. And the best way to predict behavior is to script it.

competition for personal data intensified. It was no longer enough to monitor people online; making better predictions required that surveillance be extended into homes, stores, schools, workplaces, and the public squares of cities and towns. Much of the recent innovation in the tech industry has entailed the creation of products and services designed to vacuum up data from every corner of our lives

“The typical complaint is that privacy is eroded, but that is misleading,” Zuboff writes. “In the larger societal pattern, privacy is not eroded but redistributed . . . . Instead of people having the rights to decide how and what they will disclose, these rights are concentrated within the domain of surveillance capitalism.” The transfer of decision rights is also a transfer of autonomy and agency, from the citizen to the corporation.

What we lose under this regime is something more fundamental than privacy. It’s the right to make our own decisions about privacy — to draw our own lines between those aspects of our lives we are comfortable sharing and those we are not

Other possible ways of organizing online markets, such as through paid subscriptions for apps and services, never even got a chance to be tested.

Online surveillance came to be viewed as normal and even necessary by politicians, government bureaucrats, and the general public

Google and other Silicon Valley companies benefited directly from the government’s new stress on digital surveillance. They earned millions through contracts to share their data collection and analysis techniques with the National Security Agenc

As much as the dot-com crash, the horrors of 9/11 set the stage for the rise of surveillance capitalism. Zuboff notes that, in 2000, members of the Federal Trade Commission, frustrated by internet companies’ lack of progress in adopting privacy protections, began formulating legislation to secure people’s control over their online information and severely restrict the companies’ ability to collect and store it. It seemed obvious to the regulators that ownership of personal data should by default lie in the hands of private citizens, not corporations.

The 9/11 attacks changed the calculus. The centralized collection and analysis of online data, on a vast scale, came to be seen as essential to national security. “The privacy provisions debated just months earlier vanished from the conversation more or less overnight,”

Microsoft leaders felt “enormous urgency” for it to be the company to bring this technology to market, because others around the world are working on similar tech but might not have the resources or inclination to build it as responsibly, says Sarah Bird, a leader on Microsoft’s responsible AI team.

One common starting point for such models is what is essentially a download or “scrape” of most of the internet. In the past, these language models were used to try to understand text, but the new generation of them, part of the revolution in “generative” AI, uses those same models to create texts by trying to guess, one word at a time, the most likely word to come next in any given sequence.

Wide-scale testing gives Microsoft and OpenAI a big competitive edge by enabling them to gather huge amounts of data about how people actually use such chatbots. Both the prompts users input into their systems, and the results their AIs spit out, can then be fed back into a complicated system—which includes human content moderators paid by the companies—to improve it.

, being first to market with a chat-based AI gives these companies a huge initial lead over companies that have been slower to release their own chat-based AIs, such as Google.

rarely has an experiment like Microsoft and OpenAI’s been rolled out so quickly, and at such a broad scale.

Among those who build and study these kinds of AIs, Mr. Altman’s case for experimenting on the global public has inspired responses ranging from raised eyebrows to condemnation.

The fact that we’re all guinea pigs in this experiment doesn’t mean it shouldn’t be conducted, says Nathan Lambert, a research scientist at the AI startup Huggingface.

“I would kind of be happier with Microsoft doing this experiment than a startup, because Microsoft will at least address these issues when the press cycle gets really bad,” says Dr. Lambert. “I think there are going to be a lot of harms from this kind of AI, and it’s better people know they are coming,” he adds.

Others, particularly those who study and advocate for the concept of “ethical AI” or “responsible AI,” argue that the global experiment Microsoft and OpenAI are conducting is downright dangerous

Celeste Kidd, a professor of psychology at University of California, Berkeley, studies how people acquire knowledge

Her research has shown that people learning about new things have a narrow window in which they form a lasting opinion. Seeing misinformation during this critical initial period of exposure to a new concept—such as the kind of misinformation that chat-based AIs can confidently dispense—can do lasting harm, she says.

Dr. Kidd likens OpenAI’s experimentation with AI to exposing the public to possibly dangerous chemicals. “Imagine you put something carcinogenic in the drinking water and you were like, ‘We’ll see if it’s carcinogenic.’ After, you can’t take it back—people have cancer now,”

Part of the challenge with AI chatbots is that they can sometimes simply make things up. Numerous examples of this tendency have been documented by users of both ChatGPT and OpenA

These models also tend to be riddled with biases that may not be immediately apparent to users. For example, they can express opinions gleaned from the internet as if they were verified facts

When millions are exposed to these biases across billions of interactions, this AI has the potential to refashion humanity’s views, at a global scale, says Dr. Kidd.

OpenAI has talked publicly about the problems with these systems, and how it is trying to address them. In a recent blog post, the company said that in the future, users might be able to select AIs whose “values” align with their own.

“We believe that AI should be a useful tool for individual people, and thus customizable by each user up to limits defined by society,” the post said.

Eliminating made-up information and bias from chat-based search engines is impossible given the current state of the technology, says Mark Riedl, a professor at Georgia Institute of Technology who studies artificial intelligence

He believes the release of these technologies to the public by Microsoft and OpenAI is premature. “We are putting out products that are still being actively researched at this moment,” he adds. 

in other areas of human endeavor—from new drugs and new modes of transportation to advertising and broadcast media—we have standards for what can and cannot be unleashed on the public. No such standards exist for AI, says Dr. Riedl.

To modify these AIs so that they produce outputs that humans find both useful and not-offensive, engineers often use a process called “reinforcement learning through human feedback.

that’s a fancy way of saying that humans provide input to the raw AI algorithm, often by simply saying which of its potential responses to a query are better—and also which are not acceptable at all.

Microsoft’s and OpenAI’s globe-spanning experiments on millions of people are yielding a fire hose of data for both companies. User-entered prompts and the AI-generated results are fed back through a network of paid human AI trainers to further fine-tune the models,

Huggingface’s Dr. Lambert says that any company, including his own, that doesn’t have this river of real-world usage data helping it improve its AI is at a huge disadvantage

In chatbots, in some autonomous-driving systems, in the unaccountable AIs that decide what we see on social media, and now, in the latest applications of AI, again and again we are the guinea pigs on which tech companies are testing new technology.

It may be the case that there is no other way to roll out this latest iteration of AI—which is already showing promise in some areas—at scale. But we should always be asking, at times like these: At what price?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

What none of these parents understand is that their children’s and teens’ destructive obsession with technology is the predictable consequence of a virtually unrecognized merger between the tech industry and psychology.

Dr. B.J. Fogg, is a psychologist and the father of persuasive technology, a discipline in which digital machines and apps — including smartphones, social media, and video games — are configured to alter human thoughts and behaviors. As the lab’s website boldly proclaims: “Machines designed to change humans.”

These parents have no idea that lurking behind their kids’ screens and phones are a multitude of psychologists, neuroscientists, and social science experts who use their knowledge of psychological vulnerabilities to devise products that capture kids’ attention for the sake of industry profit.

psychology — a discipline that we associate with healing — is now being used as a weapon against children.

This alliance pairs the consumer tech industry’s immense wealth with the most sophisticated psychological research, making it possible to develop social media, video games, and phones with drug-like power to seduce young users.

Likewise, social media companies use persuasive design to prey on the age-appropriate desire for preteen and teen kids, especially girls, to be socially successful. This drive is built into our DNA, since real-world relational skills have fostered human evolution.

Called “the millionaire maker,” Fogg has groomed former students who have used his methods to develop technologies that now consume kids’ lives. As he recently touted on his personal website, “My students often do groundbreaking projects, and they continue having impact in the real world after they leave Stanford… For example, Instagram has influenced the behavior of over 800 million people. The co-founder was a student of mine.”

Persuasive technology (also called persuasive design) works by deliberately creating digital environments that users feel fulfill their basic human drives — to be social or obtain goals — better than real-world alternatives.

Kids spend countless hours in social media and video game environments in pursuit of likes, “friends,” game points, and levels — because it’s stimulating, they believe that this makes them happy and successful, and they find it easier than doing the difficult but developmentally important activities of childhood.

While persuasion techniques work well on adults, they are particularly effective at influencing the still-maturing child and teen brain.

“Video games, better than anything else in our culture, deliver rewards to people, especially teenage boys,” says Fogg. “Teenage boys are wired to seek competency. To master our world and get better at stuff. Video games, in dishing out rewards, can convey to people that their competency is growing, you can get better at something second by second.”

it’s persuasive design that’s helped convince this generation of boys they are gaining “competency” by spending countless hours on game sites, when the sad reality is they are locked away in their rooms gaming, ignoring school, and not developing the real-world competencies that colleges and employers demand.

Persuasive technologies work because of their apparent triggering of the release of dopamine, a powerful neurotransmitter involved in reward, attention, and addiction.

As she says, “If you don’t get 100 ‘likes,’ you make other people share it so you get 100…. Or else you just get upset. Everyone wants to get the most ‘likes.’ It’s like a popularity contest.”

there are costs to Casey’s phone obsession, noting that the “girl’s phone, be it Facebook, Instagram or iMessage, is constantly pulling her away from her homework, sleep, or conversations with her family.

Casey says she wishes she could put her phone down. But she can’t. “I’ll wake up in the morning and go on Facebook just… because,” she says. “It’s not like I want to or I don’t. I just go on it. I’m, like, forced to. I don’t know why. I need to. Facebook takes up my whole life.”

B.J. Fogg may not be a household name, but Fortune Magazine calls him a “New Guru You Should Know,” and his research is driving a worldwide legion of user experience (UX) designers who utilize and expand upon his models of persuasive design.

“No one has perhaps been as influential on the current generation of user experience (UX) designers as Stanford researcher B.J. Fogg.”

the core of UX research is about using psychology to take advantage of our human vulnerabilities.

As Fogg is quoted in Kosner’s Forbes article, “Facebook, Twitter, Google, you name it, these companies have been using computers to influence our behavior.” However, the driving force behind behavior change isn’t computers. “The missing link isn’t the technology, it’s psychology,” says Fogg.

UX researchers not only follow Fogg’s design model, but also his apparent tendency to overlook the broader implications of persuasive design. They focus on the task at hand, building digital machines and apps that better demand users’ attention, compel users to return again and again, and grow businesses’ bottom line.

the “Fogg Behavior Model” is a well-tested method to change behavior and, in its simplified form, involves three primary factors: motivation, ability, and triggers.

“We can now create machines that can change what people think and what people do, and the machines can do that autonomously.”

Regarding ability, Fogg suggests that digital products should be made so that users don’t have to “think hard.” Hence, social networks are designed for ease of use

Finally, Fogg says that potential users need to be triggered to use a site. This is accomplished by a myriad of digital tricks, including the sending of incessant notifications

moral questions about the impact of turning persuasive techniques on children and teens are not being asked. For example, should the fear of social rejection be used to compel kids to compulsively use social media? Is it okay to lure kids away from school tasks that demand a strong mental effort so they can spend their lives on social networks or playing video games that don’t make them think much at all?

Describing how his formula is effective at getting people to use a social network, the psychologist says in an academic paper that a key motivator is users’ desire for “social acceptance,” although he says an even more powerful motivator is the desire “to avoid being socially rejected.”

the startup Dopamine Labs boasts about its use of persuasive techniques to increase profits: “Connect your app to our Persuasive AI [Artificial Intelligence] and lift your engagement and revenue up to 30% by giving your users our perfect bursts of dopamine,” and “A burst of Dopamine doesn’t just feel good: it’s proven to re-wire user behavior and habits.”

Ramsay Brown, the founder of Dopamine Labs, says in a KQED Science article, “We have now developed a rigorous technology of the human mind, and that is both exciting and terrifying. We have the ability to twiddle some knobs in a machine learning dashboard we build, and around the world hundreds of thousands of people are going to quietly change their behavior in ways that, unbeknownst to them, feel second-nature but are really by design.”

Programmers call this “brain hacking,” as it compels users to spend more time on sites even though they mistakenly believe it’s strictly due to their own conscious choices.

Banks of computers employ AI to “learn” which of a countless number of persuasive design elements will keep users hooked

A persuasion profile of a particular user’s unique vulnerabilities is developed in real time and exploited to keep users on the site and make them return again and again for longer periods of time. This drives up profits for consumer internet companies whose revenue is based on how much their products are used.

“The leaders of Internet companies face an interesting, if also morally questionable, imperative: either they hijack neuroscience to gain market share and make large profits, or they let competitors do that and run away with the market.”

Social media and video game companies believe they are compelled to use persuasive technology in the arms race for attention, profits, and survival.

Children’s well-being is not part of the decision calculus.

one breakthrough occurred in 2017 when Facebook documents were leaked to The Australian. The internal report crafted by Facebook executives showed the social network boasting to advertisers that by monitoring posts, interactions, and photos in real time, the network is able to track when teens feel “insecure,” “worthless,” “stressed,” “useless” and a “failure.”

The report also bragged about Facebook’s ability to micro-target ads down to “moments when young people need a confidence boost.”

These design techniques provide tech corporations a window into kids’ hearts and minds to measure their particular vulnerabilities, which can then be used to control their behavior as consumers. This isn’t some strange future… this is now.

The official tech industry line is that persuasive technologies are used to make products more engaging and enjoyable. But the revelations of industry insiders can reveal darker motives.

Revealing the hard science behind persuasive technology, Hopson says, “This is not to say that players are the same as rats, but that there are general rules of learning which apply equally to both.”

After penning the paper, Hopson was hired by Microsoft, where he helped lead the development of the Xbox Live, Microsoft’s online gaming system

“If game designers are going to pull a person away from every other voluntary social activity or hobby or pastime, they’re going to have to engage that person at a very deep level in every possible way they can.”

This is the dominant effect of persuasive design today: building video games and social media products so compelling that they pull users away from the real world to spend their lives in for-profit domains.

Persuasive technologies are reshaping childhood, luring kids away from family and schoolwork to spend more and more of their lives sitting before screens and phones.

“Since we’ve figured to some extent how these pieces of the brain that handle addiction are working, people have figured out how to juice them further and how to bake that information into apps.”

Today, persuasive design is likely distracting adults from driving safely, productive work, and engaging with their own children — all matters which need urgent attention

Still, because the child and adolescent brain is more easily controlled than the adult mind, the use of persuasive design is having a much more hurtful impact on kids.

But to engage in a pursuit at the expense of important real-world activities is a core element of addiction.

younger U.S. children now spend 5 ½ hours each day with entertainment technologies, including video games, social media, and online videos.

Even more, the average teen now spends an incredible 8 hours each day playing with screens and phones

U.S. kids only spend 16 minutes each day using the computer at home for school.

Quietly, using screens and phones for entertainment has become the dominant activity of childhood.

Younger kids spend more time engaging with entertainment screens than they do in school

teens spend even more time playing with screens and phones than they do sleeping

kids are so taken with their phones and other devices that they have turned their backs to the world around them.

many children are missing out on real-life engagement with family and school — the two cornerstones of childhood that lead them to grow up happy and successful

persuasive technologies are pulling kids into often toxic digital environments

A too frequent experience for many is being cyberbullied, which increases their risk of skipping school and considering suicide.

And there is growing recognition of the negative impact of FOMO, or the fear of missing out, as kids spend their social media lives watching a parade of peers who look to be having a great time without them, feeding their feelings of loneliness and being less than.

The combined effects of the displacement of vital childhood activities and exposure to unhealthy online environments is wrecking a generation.

as the typical age when kids get their first smartphone has fallen to 10, it’s no surprise to see serious psychiatric problems — once the domain of teens — now enveloping young kids

Self-inflicted injuries, such as cutting, that are serious enough to require treatment in an emergency room, have increased dramatically in 10- to 14-year-old girls, up 19% per year since 2009.

While girls are pulled onto smartphones and social media, boys are more likely to be seduced into the world of video gaming, often at the expense of a focus on school

it’s no surprise to see this generation of boys struggling to make it to college: a full 57% of college admissions are granted to young women compared with only 43% to young men.

Economists working with the National Bureau of Economic Research recently demonstrated how many young U.S. men are choosing to play video games rather than join the workforce.

The destructive forces of psychology deployed by the tech industry are making a greater impact on kids than the positive uses of psychology by mental health providers and child advocates. Put plainly, the science of psychology is hurting kids more than helping them.

Hope for this wired generation has seemed dim until recently, when a surprising group has come forward to criticize the tech industry’s use of psychological manipulation: tech executives

Tristan Harris, formerly a design ethicist at Google, has led the way by unmasking the industry’s use of persuasive design. Interviewed in The Economist’s 1843 magazine, he says, “The job of these companies is to hook people, and they do that by hijacking our psychological vulnerabilities.”

Marc Benioff, CEO of the cloud computing company Salesforce, is one of the voices calling for the regulation of social media companies because of their potential to addict children. He says that just as the cigarette industry has been regulated, so too should social media companies. “I think that, for sure, technology has addictive qualities that we have to address, and that product designers are working to make those products more addictive, and we need to rein that back as much as possible,”

“If there’s an unfair advantage or things that are out there that are not understood by parents, then the government’s got to come forward and illuminate that.”

Since millions of parents, for example the parents of my patient Kelly, have absolutely no idea that devices are used to hijack their children’s minds and lives, regulation of such practices is the right thing to do.

Another improbable group to speak out on behalf of children is tech investors.

How has the consumer tech industry responded to these calls for change? By going even lower.

Facebook recently launched Messenger Kids, a social media app that will reach kids as young as five years old. Suggestive that harmful persuasive design is now honing in on very young children is the declaration of Messenger Kids Art Director, Shiu Pei Luu, “We want to help foster communication [on Facebook] and make that the most exciting thing you want to be doing.”

the American Psychological Association (APA) — which is tasked with protecting children and families from harmful psychological practices — has been essentially silent on the matter

APA Ethical Standards require the profession to make efforts to correct the “misuse” of the work of psychologists, which would include the application of B.J. Fogg’s persuasive technologies to influence children against their best interests

Manipulating children for profit without their own or parents’ consent, and driving kids to spend more time on devices that contribute to emotional and academic problems is the embodiment of unethical psychological practice.

“Never before in history have basically 50 mostly men, mostly 20–35, mostly white engineer designer types within 50 miles of where we are right now [Silicon Valley], had control of what a billion people think and do.”

Some may argue that it’s the parents’ responsibility to protect their children from tech industry deception. However, parents have no idea of the powerful forces aligned against them, nor do they know how technologies are developed with drug-like effects to capture kids’ minds

Others will claim that nothing should be done because the intention behind persuasive design is to build better products, not manipulate kids

similar circumstances exist in the cigarette industry, as tobacco companies have as their intention profiting from the sale of their product, not hurting children. Nonetheless, because cigarettes and persuasive design predictably harm children, actions should be taken to protect kids from their effects.

in a 1998 academic paper, Fogg describes what should happen if things go wrong, saying, if persuasive technologies are “deemed harmful or questionable in some regard, a researcher should then either take social action or advocate that others do so.”

I suggest turning to President John F. Kennedy’s prescient guidance: He said that technology “has no conscience of its own. Whether it will become a force for good or ill depends on man.”

The APA should begin by demanding that the tech industry’s behavioral manipulation techniques be brought out of the shadows and exposed to the light of public awareness

Changes should be made in the APA’s Ethics Code to specifically prevent psychologists from manipulating children using digital machines, especially if such influence is known to pose risks to their well-being.

Moreover, the APA should follow its Ethical Standards by making strong efforts to correct the misuse of psychological persuasion by the tech industry and by user experience designers outside the field of psychology.

It should join with tech executives who are demanding that persuasive design in kids’ tech products be regulated

The APA also should make its powerful voice heard amongst the growing chorus calling out tech companies that intentionally exploit children’s vulnerabilities.

And there are so very many pastes to choose from. But most of these are produced by one of the three companies that dominate the market: Crest (20%), Colgate (21%) and Sensodyne (12%).

That said, the next five companies account for 30%: Honda, Nissan, Subaru, Hyundai and Kia. Here at least there seems to be some pretty robust competition, not least from overseas.

Companies get big by winning customers, and they win customers by providing a good product and/or service, which is the whole point of consumer markets.

Big companies dominate consumption. This is not a bad thing in itself.

consumers are often unaware that they are choosing between two products owned by the same company.

The problem comes if success leads to incumbency, with large, powerful companies able to use their power to shape regulations to suit them, rather than assist their competitors.

Being market-friendly is not the same thing as being business-friendly

so long as regulators remain faithful to consumers, rather than the companies serving them.

Facebook shut down the team in late 2019.

“We have a role to play, which is why we’ve built tools and controls to help people manage when and how they use our services,” she said in the statement. “Furthermore, we have a dedicated team working across our platforms to better understand these issues and ensure people are using our apps in ways that are meaningful to them.”

They wrote that they don’t consider the behavior to be a clinical addiction because it doesn’t affect the brain in the same way as gambling or substance abuse. In one document, they noted that “activities like shopping, sex and Facebook use, when repetitive and excessive, may cause problems for some people.”

In March 2020, several months after the well-being team was dissolved, researchers who had been on the team shared a slide deck internally with some of the findings and encouraged other teams to pick up the work.

The researchers estimated these issues affect about 12.5% of the flagship app’s more than 2.9 billion users, or more than 360 million people. About 10% of users in the U.S., one of Facebook’s most lucrative markets, exhibit this behavior

In the Philippines and in India, which is the company’s largest market, the employees put the figure higher, at around 25%.

“Why should we care?” the researchers wrote in the slide deck. “People perceive the impact. In a comparative study with competitors, people perceived lower well-being and higher problematic use on Facebook compared to any other service.

Facebook’s findings are consistent with what many external researchers have observed for years,