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At the same time, it was not immediately clear how some of the other groundbreaking work, like language models that better understand natural conversation or that can break down a task into logical smaller steps, will ultimately lead to the next generation of computing that Google has touted.

Much of those capabilities are powered by the deep technological work Google has done for years using so-called machine learning, image recognition and natural language understanding. It’s a sign of an evolution rather than revolution for Google and other large tech giants.

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

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

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

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

the very existence of tweets about an event can make that event seem newsworthy—by virtue of having garnered tweets. This supposed newsworthiness can then result in literal news stories, written by journalists and based on inspiration or sourcing from tweets themselves, or it can entail the further spread of a tweet’s message by on-platform engagement, such as likes and quote tweets. Either way, the nature of Twitter is to assert the importance of tweets.

Tweets appear more meaningful when amplified, and when amplified they inspire more tweets in the same vein. A thing becomes “tweetworthy” when it spreads but then also justifies its value both on and beyond Twitter by virtue of having spread. This is the “famous for being famous” effect

This propensity is not unique to Twitter—all social media possesses it. But the frequency and quantity of posts on Twitter, along with their brevity, their focus on text, and their tendency to be vectors of news, official or not, make Twitter a particularly effective amplification house of mirrors

At least in theory. In practice, Twitter is more like an asylum, inmates screaming at everyone and no one in particular, histrionics displacing reason, posters posting at all costs because posting is all that is possible

Twitter shapes an epistemology for users under its thrall. What can be known, and how, becomes infected by what has, or can, be tweeted.

Producers of supposedly actual news see the world through tweet-colored glasses, by transforming tweets’ hypothetical status as news into published news—which produces more tweeting in turn.

For them, and others on this website, it has become an awful habit. Habits feel normal and even justified because they are familiar, not because they are righteous.

Twitter convinced us that it mattered, that it was the world’s news service, or a vector for hashtag activism, or a host for communities without voices, or a mouthpiece for the little gal or guy. It is those things, sometimes, for some of its users. But first, and mostly, it is a habit.

We never really tweeted to say something. We tweeted because Twitter offered a format for having something to say, over and over again. Just as the purpose of terrorism is terror, so the purpose of Twitter is tweeting.

When viewed with the Inflation Reduction Act, which the House is poised to pass later this week, and last year’s bipartisan infrastructure law, a major shift in congressional climate spending comes into focus. According to the RMI analysis, these three laws are set to more than triple the federal government’s average annual spending on climate and clean energy this decade, compared with the 2010s.

Within a few years, when the funding has fully ramped up, the government will spend roughly $80 billion a year on accelerating the development and deployment of zero-carbon energy and preparing for the impacts of climate change. That exceeds the GDP of about 120 of the 192 countries that have signed the Paris Agreement on Climate Change

By the end of the decade, the federal government will have spent more than $521 billion

the bill’s programs focus on the bleeding edge of the decarbonization problem, investing money in technology that should lower emissions in the 2030s and beyond.

The International Energy Association has estimated that almost half of global emissions reductions by 2050 will come from technologies that exist only as prototypes or demonstration projects today.

To get those technologies ready in time, we need to deploy those new ideas as fast as we can, then rapidly get them to commercial scale, Carey said. “What used to take two decades now needs to take six to 10 years.” That’s what the CHIPS Act is supposed to do

The law, for instance, establishes a new $20 billion Directorate for Technology, which will specialize in pushing new technologies from the prototype stage into the mass market. It is meant to prevent what happened with the solar industry—where America invented a new technology, only to lose out on commercializing it—from happening again

Congress has explicitly tasked the new office with studying “natural and anthropogenic disaster prevention or mitigation” as well as “advanced energy and industrial efficiency technologies,” including next-generation nuclear reactors.

The bill also directs about $12 billion in new research, development, and demonstration funding to the Department of Energy, according to RMI’s estimate. That includes doubling the budget for ARPA-E, the department’s advanced-energy-projects skunk works.

it allocates billions to upgrade facilities at the government’s in-house defense and energy research institutes, including the National Renewable Energy Laboratory, the Princeton Plasma Physics Laboratory, and Berkeley Lab, which conducts environmental-science research.

RMI’s estimate of the climate spending in the CHIPS bill should be understood as just that: an estimate. The bill text rarely specifies how much of its new funding should go to climate issues.

When you add CHIPS, the IRA, and the infrastructure law together, Washington appears to be unifying behind a new industrial policy, focused not only on semiconductors and defense technology but clean energy

The three bills combine to form a “a coordinated, strategic policy for accelerating the transition to the technologies that are going to define the 21st century,”

scholars and experts have speculated about whether industrial policy—the intentional use of law to nurture and grow certain industries—might make a comeback to help fight climate change. Industrial policy was central to some of the Green New Deal’s original pitch, and it has helped China develop a commanding lead in the global solar industry.

“Industrial policy,” he said, “is back.”

Scruton’s argument in many of his essays and books amounted to a deep critique of liberalism as mistaken about human beings, about society, about politics. That critique was especially valuable when it could be read as a friendly corrective to liberalism’s errors, excesses, and contradictions

today, with liberalism under threat, it comes across more like an indictment of liberalism—an indictment that has apparently been taken up as a foundational text by fascists.

Pappin extols Hungary as “a traditional Christian society,” going on to say “as an anti-liberal, I think that’s good.” Pappin then defends altering the Constitution to tilt power toward the right and strip protections from groups he feels have undermined American traditional values.

at some point, you have to start asking hard questions. In art, we divorce the work from both its creator and its legacy. You judge the work for the work and do not hold it responsible if the artist, or its fans, turn out to be bad people.

I’m not certain that this is how it is—or should be—in the world of ideas.

In Scruton’s place and time, it did seem like liberalism was ascendant and that its overreach and failings needed conservative correction.

In our day, though, liberalism needs correction less than it needs protection—including protection from the would-be authoritarians sipping espresso in the Scruton café.

The best thing it could do for society would be to implode.

Twitter hooks people in much the same way slot machines do, with what experts call an “intermittent reinforcement schedule.” Most of the time, it’s repetitive and uninteresting, but occasionally, at random intervals, some compelling nugget will appear. Unpredictable rewards, as the behavioral psychologist B.F. Skinner found with his research on rats and pigeons, are particularly good at generating compulsive behavior.

“I don’t know that Twitter engineers ever sat around and said, ‘We are creating a Skinner box,’” said Natasha Dow Schüll, a cultural anthropologist at New York University and author of a book about gambling machine design. But that, she said, is essentially what they’ve built. It’s one reason people who should know better regularly self-destruct on the site — they can’t stay away.

Twitter is not, obviously, the only social media platform with addictive qualities. But with its constant promise of breaking news, it feeds the hunger of people who work in journalism and politics, giving it a disproportionate, and largely negative, impact on those fields, and hence on our national life.

Twitter is much better at stoking tribalism than promoting progress.

According to a 2021 study, content expressing “out-group animosity” — negative feelings toward disfavored groups — is a major driver of social-media engagement

That builds on earlier research showing that on Twitter, false information, especially about politics, spreads “significantly farther, faster, deeper and more broadly than the truth.”

The company’s internal research has shown that Twitter’s algorithm amplifies right-wing accounts and news sources over left-wing ones.

This dynamic will probably intensify quite a bit if Musk takes over. Musk has said that Twitter has “a strong left bias,” and that he wants to undo permanent bans, except for spam accounts and those that explicitly call for violence. That suggests figures like Alex Jones, Steve Bannon and Marjorie Taylor Greene will be welcomed back.

But as one of the people who texted Musk pointed out, returning banned right-wingers to Twitter will be a “delicate game.” After all, the reason Twitter introduced stricter moderation in the first place was that its toxicity was bad for business

For A-list entertainers, The Washington Post reports, Twitter “is viewed as a high-risk, low-reward platform.” Plenty of non-celebrities feel the same way; I can’t count the number of interesting people who were once active on the site but aren’t anymore.

An influx of Trumpists is not going to improve the vibe. Twitter can’t be saved. Maybe, if we’re lucky, it can be destroyed.

Most servers are funded by the people who use them.

The servers that Mastodon oversees — Mastodon Social and Mastodon Online — are funded through Patreon, a membership and subscription service platform often used by content creators.

Although Mastodon visually resembles Twitter, its user experience is more akin to that of Discord, a talking and texting app where people also join servers that have their own cultures and rules.

Unlike Twitter and Discord, Mastodon does not have the ability to make its users, or the people who create servers, do anything.

But servers can dictate how they interact with one another — or whether they interact at all in a shared stream of posts. For example, when Gab used Mastodon’s code, Mastodon Social and other independent servers blocked Gab’s server, so posts from Gab did not appear on the feeds of people using those servers.

Like an email account, your username includes the name of the server itself. For example, a possible username on Mastodon Social would be janedoe@mastodon.social. Regardless of which server you sign up with, you can interact with people who use other Mastodon servers, or you can switch to another one

Once you sign up for an account, you can post “toots,” which are Mastodon’s version of tweets. You can also boost other people’s toots, the equivalent of a retweet.

If you didn’t study Jane Austen while you were here, you probably lack the capacity to think clearly about making a marriage decision. If you didn’t read George Eliot, then you missed a master class on how to judge people’s character. If you didn’t read Nietzsche, you are probably unprepared to handle the complexities of atheism—and if you didn’t read Augustine and Kierkegaard, you’re probably unprepared to handle the complexities of faith.

The list goes on. If you didn’t read de Tocqueville, you probably don’t understand your own country. If you didn’t study Gibbon, you probably lack the vocabulary to describe the rise and fall of cultures and nations.

The wisdom of the ages is your inheritance; it can make your life easier. These resources often fail to get shared because universities are too careerist, or because faculty members are more interested in their academic specialties or politics than in teaching undergraduates, or because of a host of other reasons

What are you putting into your mind? Our culture spends a lot less time worrying about this, and when it does, it goes about it all wrong.

my worry is that, especially now that you’re out of college, you won’t put enough really excellent stuff into your brain.

I worry that it’s possible to grow up now not even aware that those upper registers of human feeling and thought exist.

The theory of maximum taste says that each person’s mind is defined by its upper limit—the best that it habitually consumes and is capable of consuming.

After college, most of us resolve to keep doing this kind of thing, but we’re busy and our brains are tired at the end of the day. Months and years go by. We get caught up in stuff, settle for consuming Twitter and, frankly, journalism. Our maximum taste shrinks.

I’m worried about the future of your maximum taste. People in my and earlier generations, at least those lucky enough to get a college education, got some exposure to the classics, which lit a fire that gets rekindled every time we sit down to read something really excellent.

the “theory of maximum taste.” This theory is based on the idea that exposure to genius has the power to expand your consciousness. If you spend a lot of time with genius, your mind will end up bigger and broader than if you spend your time only with run-of-the-mill stuff.

the whole culture is eroding the skill the UCLA scholar Maryanne Wolf calls “deep literacy,” the ability to deeply engage in a dialectical way with a text or piece of philosophy, literature, or art.

“To the extent that you cannot perceive the world in its fullness, to the same extent you will fall back into mindless, repetitive, self-reinforcing behavior, unable to escape.”

I can’t say that to you, because it sounds fussy and elitist and OK Boomer. And if you were in front of me, you’d roll your eyes.

The fact that Thomas was very likely nominated because he was Black and because he opposed affirmative action posed a conundrum for many supporters of racial preferences. Was being Black enough? Or did you have to be “the right kind” of Black person? It’s a question Carter openly wrestles with in his book.

What immediately struck me on rereading it was how prescient Carter was about these debates 32 years ago. What role affirmative action should take was playing out then in ways that continue to reverberate.

The demise of affirmative action, in Carter’s view, was both necessary and inevitable. “We must reject the common claim that an end to preferences ‘would be a disastrous situation, amounting to a virtual nullification of the 1954 desegregation ruling,’” he wrote, quoting the activist and academic Robert Allen. “The prospect of its end should be a challenge and a chance.”

Like many people today — both proponents and opponents of affirmative action — he expressed reservations about relying on diversity as the constitutional basis for racial preferences.

Carter bristled at the judgment of many of his Black peers, describing several situations in which he found himself accused of being “inauthentically” Black, as if people of a particular race were a monolith and that those who deviated from it were somehow shirking their duty. He said he didn’t want to be limited in what he was allowed to say by “an old and vicious form of silencing.”

But the implication of recruiting for diversity, Carter explained, had less to do with admitting Black students to redress past discrimination and more to do with supporting and reinforcing essentialist notions about Black people.

An early critic of groupthink, Carter warned against “the idea that Black people who gain positions of authority or influence are vested a special responsibility to articulate the presumed views of other people who are Black — in effect, to think and act and speak in a particular way, the Black way — and that there is something peculiar about Black people who insist on doing anything else.”

A graduate of Stanford and Yale Law, Carter was a proud beneficiary of affirmative action. Yet he acknowledged the personal toll it took (“a decidedly mixed blessing”) as well as affirmative action’s sometimes troubling effects on Black people as the programs evolved.

, it’s hard to imagine Carter welcoming the current vogue for white allyship, with its reductive assumption that all Black people have the same interests and values

He disparaged what he called “the peculiar relationship between Black intellectuals and the white ones who seem loath to criticize us for fear of being branded racists — which is itself a mark of racism of a sort.”

In the past, such ideas might have been seen as “frankly racist,” Carter noted. “Now, however, they are almost a gospel for people who want to show their commitment to equality.”

Carter took issue with the belief, now practically gospel in academic, cultural and media circles, that heightened race consciousness would be central to overcoming racism

However well intentioned you may be, when you reduce people to their race-based identity rather than view them as individuals in their full, complex humanity, you risk making sweeping assumptions about who they are. This used to be called stereotyping or racism.

he rejected all efforts to label him, insisting that intellectuals should be “politically unpredictable.

“Critics who attempt to push (or pull) Carter into the ranks of the Black right wing will be making a mistake. He is not a conservative, neo- or otherwise. He is an honest Black scholar — the product of the pre-politically correct era — who abhors the stifling of debate by either wing or by people of any hue.”

This strikes me as the greatest difference between reading the book today and reading it as an undergrad at a liberal Ivy League college: the attitude toward debating controversial views. “Reflections” offers a vigorous and unflinching examination of ideas, something academia, media and the arts still prized in 1991.

Today, a kind of magical thinking has seized ideologues on both the left and the right, who seem to believe that stifling debate on difficult questions will make them go away

Most A.I. researchers agree that models trained using R.L.H.F. are better behaved than models without it. But some argue that fine-tuning a language model this way doesn’t actually make the underlying model less weird and inscrutable. In their view, it’s just a flimsy, friendly mask that obscures the mysterious beast underneath.

In a nutshell, the joke was that in order to prevent A.I. language models from behaving in scary and dangerous ways, A.I. companies have had to train them to act polite and harmless. One popular way to do this is called “reinforcement learning from human feedback,” or R.L.H.F., a process that involves asking humans to score chatbot responses, and feeding those scores back into the A.I. model.

Shoggoths are fictional creatures, introduced by the science fiction author H.P. Lovecraft in his 1936 novella “At the Mountains of Madness.” In Lovecraft’s telling, Shoggoths were massive, blob-like monsters made out of iridescent black goo, covered in tentacles and eyes.

@TetraspaceWest said, wasn’t necessarily implying that it was evil or sentient, just that its true nature might be unknowable.

And it reinforces the notion that what’s happening in A.I. today feels, to some of its participants, more like an act of summoning than a software development process. They are creating the blobby, alien Shoggoths, making them bigger and more powerful, and hoping that there are enough smiley faces to cover the scary parts.

“I was also thinking about how Lovecraft’s most powerful entities are dangerous — not because they don’t like humans, but because they’re indifferent and their priorities are totally alien to us and don’t involve humans, which is what I think will be true about possible future powerful A.I.”

when Bing’s chatbot became unhinged and tried to break up my marriage, an A.I. researcher I know congratulated me on “glimpsing the Shoggoth.” A fellow A.I. journalist joked that when it came to fine-tuning Bing, Microsoft had forgotten to put on its smiley-face mask.

@TetraspaceWest, the meme’s creator, told me in a Twitter message that the Shoggoth “represents something that thinks in a way that humans don’t understand and that’s totally different from the way that humans think.”

In any case, the Shoggoth is a potent metaphor that encapsulates one of the most bizarre facts about the A.I. world, which is that many of the people working on this technology are somewhat mystified by their own creations. They don’t fully understand the inner workings of A.I. language models, how they acquire new capabilities or why they behave unpredictably at times. They aren’t totally sure if A.I. is going to be net-good or net-bad for the world.

That some A.I. insiders refer to their creations as Lovecraftian horrors, even as a joke, is unusual by historical standards. (Put it this way: Fifteen years ago, Mark Zuckerberg wasn’t going around comparing Facebook to Cthulhu.)

If it’s an A.I. safety researcher talking about the Shoggoth, maybe that person is passionate about preventing A.I. systems from displaying their true, Shoggoth-like nature.

A great many people are dismissive of suggestions that any of these systems are “really” thinking, because they’re “just” doing something banal (like making statistical predictions about the next word in a sentence). What they fail to appreciate is that there is every reason to suspect that human cognition is “just” doing those exact same things. It matters not that birds flap their wings but airliners don’t. Both fly. And these machines think. And, just as airliners fly faster and higher and farther than birds while carrying far more weight, these machines are already outthinking the majority of humans at the majority of tasks. Further, that machines aren’t perfect thinkers is about as relevant as the fact that air travel isn’t instantaneous. Now consider: we’re well past the Wright flyer level of thinking machine, past the early biplanes, somewhere about the first commercial airline level. Not quite the DC-10, I think. Can you imagine what the AI equivalent of a 777 will be like? Fasten your seatbelts.

@thomas h. You make my point perfectly. You’re observing that the way a plane flies — by using a turbine to generate thrust from combusting kerosene, for example — is nothing like the way that a bird flies, which is by using the energy from eating plant seeds to contract the muscles in its wings to make them flap. You are absolutely correct in that observation, but it’s also almost utterly irrelevant. And it ignores that, to a first approximation, there’s no difference in the physics you would use to describe a hawk riding a thermal and an airliner gliding (essentially) unpowered in its final descent to the runway. Further, you do yourself a grave disservice in being dismissive of the abilities of thinking machines, in exactly the same way that early skeptics have been dismissive of every new technology in all of human history. Writing would make people dumb; automobiles lacked the intelligence of horses; no computer could possibly beat a chess grandmaster because it can’t comprehend strategy; and on and on and on. Humans aren’t nearly as special as we fool ourselves into believing. If you want to have any hope of acting responsibly in the age of intelligent machines, you’ll have to accept that, like it or not, and whether or not it fits with your preconceived notions of what thinking is and how it is or should be done … machines can and do think, many of them better than you in a great many ways. b&

@BLA. You are incorrect. Everything has nature. Its nature is manifested in making humans react. Sure, no humans, no nature, but here we are. The writer and various sources are not attributing nature to AI so much as admitting that they don’t know what this nature might be, and there are reasons to be scared of it. More concerning to me is the idea that this field is resorting to geek culture reference points to explain and comprehend itself. It’s not so much the algorithm has no soul, but that the souls of the humans making it possible are stupendously and tragically underdeveloped.

When even tech companies are saying AI is moving too fast, and the articles land on page 1 of the NYT (there's an old reference), I think the greedy will not think twice about exploiting this technology, with no ethical considerations, at all.

@nome sane? The problem is it isn't data as we understand it. We know what the datasets are -- they were used to train the AI's. But once trained, the AI is thinking for itself, with results that have surprised everybody.

The unique feature of a shoggoth is it can become whatever is needed for a particular job. There's no actual shape so it's not a bad metaphor, if an imperfect image. Shoghoths also turned upon and destroyed their creators, so the cautionary metaphor is in there, too. A shame more Asimov wasn't baked into AI. But then the conflict about how to handle AI in relation to people was key to those stories, too.

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.”

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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