Group items tagged

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.”

The release cites a poll from something called the Center for Security Policy that claims 25 percent of Muslims surveyed said they were OK with violence against Americans and 51 percent "agreed that Muslims in America should have the choice of being governed according to Shariah." Those numbers sound too awful to be true, and there's evidence that they aren't—Georgetown's Bridge Initiative, which studies Islamophobia in America, has called the poll into question and noted that the CSP's founder Frank Gaffney once accused General David Petraeus, of all people, of "submission" to Islamic law.

the latest CNN poll had put The Donald in the lead in Iowa, a key early voting state, though another poll that used different sampling techniques showed Cruz ahead of Trump.

She became a science journalist. At first it was a lark, a way to get free press passes to conferences where she and her father could ask questions of the greatest minds in quantum mechanics, string theory and cosmology. But within a short time, as she started getting assignments, journalism became a calling, and an identity.

Tracking down the meaning of nothing — and, by extension, secrets about the origin of the universe and whether observer-independent reality exists — became the defining project of their lives. They spent hours together working on the puzzle, two dark heads bent over their physics books far into the night.

she has an epiphany — that for something to be real, it must be invariant — she flies home to share it with her father. They discuss her insight over breakfast at a neighborhood haunt, where they make a list on what they will affectionately call “the IHOP napkin.” They list all the possible “ingredients of ultimate reality,” planning to test each item for whether it is “real,” that is whether it is invariant and can exist in the absence of an observer.

their readings and interviews reveal that each item in turn is observer-dependent. Space? Observer-dependent, and therefore not real. Gravity, electromagnetism, angular momentum? No, no, and no. In the end, every putative “ingredient of ultimate reality” is eliminated, including one they hadn’t even bothered to put on the list because it seemed weird to: reality itself

What remained was an unsettling and essential insight: that “physics isn’t the machinery behind the workings of the world; physics is the machinery behind the illusion that there is a world.”

In the proposal, she clarifies how cosmology and quantum mechanics have evolved as scientists come to grips with the fact that things they had taken to be real — quantum particles, space-time, gravity, dimension — turn out to be ­observer-dependent.

In stage 1, they submit the introduction, methods, proposed analysis, and if necessary, pilot data. This manuscript then goes through the usual peer review process, and is assessed on criteria such as the soundness of the methods and analysis, and overall plausibility of the stated hypotheses.

Once researchers have passed through stage 1, they can then move on to data collection. In stage 2, they then submit the full manuscript – the introduction and agreed methods from stage 1, plus results and discussion sections. The results must include the outcome of the analyses agreed in stage 1, but the researchers are allowed to include additional analyses in a separate, ‘exploratory’ section (as long as they are justified).

Pre-registering scientific articles in this way helps to protect against a number of undesirable practices (such as p-hacking and HARKing) that can exaggerate statistical findings and make non-existent effects seem real. While this is a problem across psychology generally, it is a particularly extreme problem for violent video game research.

By outlining the intended methods and analysis protocols beforehand, Registered Reports protect against these problems, as the review process concentrates on the robustness of the proposed methods. And Registered Reports offer an additional advantage: because manuscripts are never accepted based on the outcome of the data analysis, the process is immune to researcher party lines. It doesn’t matter which research ‘camp’ you are in; your data – and just as importantly, your methods - will speak for themselves.

“The studies were biased,” he says. “Sometimes they were overtly biased. Sometimes it was difficult to see the bias, but it was there.” Researchers headed into their studies wanting certain results—and, lo and behold, they were getting them. We think of the scientific process as being objective, rigorous, and even ruthless in separating out what is true from what we merely wish to be true, but in fact it’s easy to manipulate results, even unintentionally or unconsciously. “At every step in the process, there is room to distort results, a way to make a stronger claim or to select what is going to be concluded,” says Ioannidis. “There is an intellectual conflict of interest that pressures researchers to find whatever it is that is most likely to get them funded.”

Ioannidis laid out a detailed mathematical proof that, assuming modest levels of researcher bias, typically imperfect research techniques, and the well-known tendency to focus on exciting rather than highly plausible theories, researchers will come up with wrong findings most of the time.

if you’re attracted to ideas that have a good chance of being wrong, and if you’re motivated to prove them right, and if you have a little wiggle room in how you assemble the evidence, you’ll probably succeed in proving wrong theories right. His model predicted, in different fields of medical research, rates of wrongness roughly corresponding to the observed rates at which findings were later convincingly refuted: 80 percent of non-randomized studies (by far the most common type) turn out to be wrong, as do 25 percent of supposedly gold-standard randomized trials, and as much as 10 percent of the platinum-standard large randomized trials.

He zoomed in on 49 of the most highly regarded research findings in medicine over the previous 13 years, as judged by the science community’s two standard measures: the papers had appeared in the journals most widely cited in research articles, and the 49 articles themselves were the most widely cited articles in these journals

Ioannidis was putting his contentions to the test not against run-of-the-mill research, or even merely well-accepted research, but against the absolute tip of the research pyramid. Of the 49 articles, 45 claimed to have uncovered effective interventions. Thirty-four of these claims had been retested, and 14 of these, or 41 percent, had been convincingly shown to be wrong or significantly exaggerated. If between a third and a half of the most acclaimed research in medicine was proving untrustworthy, the scope and impact of the problem were undeniable.

It seems there's an association between spending money on one's self and selfish conduct, and it doesn't require actual spending. In this 2009 paper Roy Y.J. Chua and Xi Zou, both professors of management, found that just getting people to think about that kind of spending was sufficient to make their decisions more selfish. The pair showed 87 university students pictures of shoes and watches and had them complete a survey about the products. Then they answered questions about how they would behave as a chief executive in each of three hypothetical business decisions. Half the group had seen pictures of simple, functional shoes and watches. The others had viewed, and then described, top-end luxury goods. Those who saw the luxury versions were significantly more likely to choose the selfish path in the business decisions. They were more inclined to OK the production of a car that would pollute the environment, the release of bug-riddled software, and the marketing of a videogame that would prompt kids to bash each other. That suggests, write Chua and Zou, that "mere exposure to luxury caused people to think more about themselves than others."

I continue to believe, to walk the paths of faith, because I believe a story and continue to choose to believe that story. More precisely, I believe in a grand sacred history that has been given embodiment in a plurality of diverse narratives, epistles, and other sacred writings. I interpret these writings in ways literal and figurative and in ways between. While I don’t look to the books of the New Testament for a historical transcript of the life of Christ, I cling to the hope that they reveal a Divine Person and give flesh and blood anew to impossible events, namely the Incarnation, the Crucifixion, the Resurrection, and the Ascension. On the one hand, my choice to believe the truth of these writings—writings that don’t perfectly add up, to be sure—is a decision to believe that an underlying thematic truth speaks through incredible, fantastical tales told to me by mostly unknown strangers, and passed down to me by figures holy and insidious, self-giving and power-hungry, saintly and vicious. On the other hand, I find some of those who have told and retold these stories, particularly the early Christian martyrs, to be credible witnesses. Those who have given their lives for Christ did so not merely in defiance of their murders, but as an act of witness embraced in the hope that their enemies would become their brothers and sisters. That kind of love strikes me as the height of love. And it’s been known to work wonders.

What does my faith give me? It gives me a love story. Not a story that explains love, but a story that gives birth to—and directs my heart, mind, and very being to—the fullest expression and fulfillment of love. It is a story that means everything if it means anything at all. It is a story about what it means to be human and what it means to be divine, both of which tell of what it means to love. My religion tells a love story about a humble God who reveals and who gives humanity, through the sacraments and other gifts, the grace to respond in faith, hope, and most importantly love. In this sacred romance, faith and hope are not ends in themselves, or even eternal things, but the temporal means to an eternal end. That end is love. According to this story, there is no need for faith or hope in heaven, and so you will not find them there. What you will find, if there is anything after death to find or a paradise to find it, is love.

My faith doesn’t free me from these unsettling possibilities. It doesn’t whisk me away from the battlefield like a protective Aphrodite. Instead, it fills me with fear and trembling and places me in the hopeless situation of not knowing what I love when I love my God. Yet I would not choose to be anywhere else. I’ve no interest in certainty, gnosis, or other false comforts. Nor do I wish to close the book of faith and place it on the bookshelf, unread, ignored and unlived. I intend to live according to a story I love, to share it with those I love, and to allow it to guide my steps and convert my soul, even though I journey to who knows where. And I intend as well to incline an ear to the voice of alterity, to reasons and rhymes that might expose my faith to its undoing.

driving is already one of the more dangerous activities Americans undertake on a daily basis. According to the National Highway Traffic Safety Administration, “drowsy driving” was a factor in 91,000 crashes, resulting in 50,000 people injured and 810 deaths in 2017, so it’s theoretically possible that what some of these videos are showing us is disaster averted, not disaster in motion.

Tesla once generated widespread good will by promising affordable electric cars that would make the world cleaner and safer. But over time, its image was tarnished by missed deadlines, worrying crash reports, signs of a cultlike corporate culture and a chief executive, Elon Musk, who habitually exaggerates progress while announcing extravagant new ideas. This was hardly the institution you would want determining the future of highway safety.

These technologies — and the companies that engineer them — keep turning out to be less benign than imagined. We fell in love with Amazon, but now we miss the local stores it closed. We couldn’t resist the convenience of Uber and Lyft, but now we’ve seen their effect on public transit and drivers. “Jetsons”-esque smart-home technology turned out to be riddled with glitches and vulnerable to hackers.

Tech companies have hollowed out old industries, shredded privacy, disregarded regulations and created new vectors for the spread of misinformation and extremism, and now there is a sense that choices we have already made — tectonic shifts already in motion, terms of service already accepted — may be changing us in ways that we are only beginning to process, ready to leap up and bite us in the collective behind.

It’s hard to imagine a more potent visual metaphor for this feeling than a human lulled to sleep inside a hunk of metal and glass, hurtling down a highway under the control of proprietary algorithms beamed on board from Palo Alto

These videos are magnetic not just because of the eerie images they contain, but also because, watching them, we can’t actually be sure what we’re seeing. Is this danger or safety or both at once? Perhaps in a different era we would have cried out in excitement: How cool! Today we are more tempted to gasp in shock and call out a warning: Wake up!

Plato and Aristotle: What an accident of history that two such contrasting orientations toward the physical world, animated by two such different aesthetic sensibilities, should have been pedagogically entangled with each other.

To read some semblance of our science into these ancients requires charitably imaginative interpretations that clarify their obscurities with insights toward which they were themselves, perhaps, groping. Some of us are prepared to extend such interpretations toward Plato. Leroi extends them toward Aris­totle, so much so that he would vehemently reject my statement that Aristotle, like Plato, was not the finished scientific article.

Leroi follows closely in the footsteps of such generous elucidators. The modern understanding of genetically encoded information is applied not only to Aristotle’s formal cause, his “eidos,” and to his notion that all change is potentiality actualized, but also to his notion of the soul. “Aristotle’s belief that we should attend less to the matter than to the informational structure of living things makes him seem like a molecular geneticist avant la lettre.”

“I have kept Aristotle’s theos in the shadows. It may even be that I have done so deliberately; that I have been reluctant to reveal the degree to which my hero’s scientific system is riddled with religion. Yet it is.”

At fifty-nine, Anderson is the chair of the University of Michigan’s department of philosophy and a champion of the view that equality and freedom are mutually dependent, enmeshed in changing conditions through time.

She has built a case, elaborated across decades, that equality is the basis for a free society

Because she brings together ideas from both the left and the right to battle increasing inequality, Anderson may be the philosopher best suited to this awkward moment in American life. She builds a democratic frame for a society in which people come from different places and are predisposed to disagree.

she sketched out the entry-level idea that one basic way to expand equality is by expanding the range of valued fields within a society.

The ability not to have an identity that one carries from sphere to sphere but, rather, to be able to slip in and adopt whatever values and norms are appropriate while retaining one’s identities in other domains?” She paused. “That is what it is to be free.”

How do you move from a basic model of egalitarian variety, in which everybody gets a crack at being a star at something, to figuring out how to respond to a complex one, where people, with different allotments of talent and virtue, get unequal starts, and often meet with different constraints along the way?

The problem, she proposed, was that contemporary egalitarian thinkers had grown fixated on distribution: moving resources from lucky-seeming people to unlucky-seeming people, as if trying to spread the luck around.

Egalitarians should agree about clear cases of blameless misfortune: the quadriplegic child, the cognitively impaired adult, the teen-ager born into poverty with junkie parents. But Anderson balked there, too. By categorizing people as lucky or unlucky, she argued, these egalitarians set up a moralizing hierarchy.

In Anderson’s view, the way forward was to shift from distributive equality to what she called relational, or democratic, equality: meeting as equals, regardless of where you were coming from or going to.

By letting the lucky class go on reaping the market’s chancy rewards while asking others to concede inferior status in order to receive a drip-drip-drip of redistributive aid, these egalitarians were actually entrenching people’s status as superior or subordinate.

To the ugly and socially awkward: . . . Maybe you won’t be such a loser in love once potential dates see how rich you are.

. To the stupid and untalented: Unfortunately, other people don’t value what little you have to offer in the system of production. . . . Because of the misfortune that you were born so poorly endowed with talents, we productive ones will make it up to you: we’ll let you share in the bounty of what we have produced with our vastly superior and highly valued abilities. . . 

she imagined some citizens getting a state check and a bureaucratic letter:

This was, at heart, an exercise of freedom. The trouble was that many people, picking up on libertarian misconceptions, thought of freedom only in the frame of their own actions.

To be truly free, in Anderson’s assessment, members of a society had to be able to function as human beings (requiring food, shelter, medical care), to participate in production (education, fair-value pay, entrepreneurial opportunity), to execute their role as citizens (freedom to speak and to vote), and to move through civil society (parks, restaurants, workplaces, markets, and all the rest).

Anderson’s democratic model shifted the remit of egalitarianism from the idea of equalizing wealth to the idea that people should be equally free, regardless of their differences.

A society in which everyone had the same material benefits could still be unequal, in this crucial sense; democratic equality, being predicated on equal respect, wasn’t something you could simply tax into existence. “People, not nature, are responsible for turning the natural diversity of human beings into oppressive hierarchies,”

Her first book, “Value in Ethics and Economics,” appeared that year, announcing one of her major projects: reconciling value (an amorphous ascription of worth that is a keystone of ethics and economics) with pluralism (the fact that people seem to value things in different ways).

Philosophers have often assumed that pluralistic value reflects human fuzziness—we’re loose, we’re confused, and we mix rational thought with sentimental responses.

She offered an “expressive” theory: in her view, each person’s values could be various because they were socially expressed, and thus shaped by the range of contexts and relationships at play in a life. Instead of positing value as a basic, abstract quality across society (the way “utility” functioned for economists), she saw value as something determined by the details of an individual’s history.

Like her idea of relational equality, this model resisted the temptation to flatten human variety toward a unifying standard. In doing so, it helped expand the realm of free and reasoned economic choice.

Anderson’s model unseated the premises of rational-choice theory, in which individuals invariably make utility-maximizing decisions, occasionally in heartless-seeming ways. It ran with, rather than against, moral intuition. Because values were plural, it was perfectly rational to choose to spend evenings with your family, say, and have guilt toward the people you left in the lurch at work.

The theory also pointed out the limits on free-market ideologies, such as libertarianism.

In ethics, it broke across old factional debates. The core idea “has been picked up on by people across quite a range of positions,” Peter Railton, one of Anderson’s longtime colleagues, says. “Kantians and consequentialists alike”—people who viewed morality in terms of duties and obligations, and those who measured the morality of actions by their effects in the world—“could look at it and see something important.”

Traditionally, the discipline is taught through a-priori thought—you start with basic principles and reason forward. Anderson, by contrast, sought to work empirically, using information gathered from the world, identifying problems to be solved not abstractly but through the experienced problems of real people.

“Dewey argued that the primary problems for ethics in the modern world concerned the ways society ought to be organized, rather than personal decisions of the individual,”

In 2004, the Stanford Encyclopedia of Philosophy asked Anderson to compose its entry on the moral philosophy of John Dewey, who helped carry pragmatist methods into the social realm. Dewey had an idea of democracy as a system of good habits that began in civil life. He was an anti-ideologue with an eye for pluralism.

She started working with historians, trying to hone her understanding of ideas by studying them in the context of their creation. Take Rousseau’s apparent support of direct democracy. It’s rarely mentioned that, at the moment when he made that argument, his home town of Geneva had been taken over by oligarchs who claimed to represent the public. Pragmatism said that an idea was an instrument, which naturally gave rise to such questions as: an instrument for what, and where, and when?

In “What Is the Point of Equality?,” Anderson had already started to drift away from what philosophers, following Rawls, call ideal theory, based on an end vision for a perfectly just society. As Anderson began a serious study of race in America, though, she found herself losing faith in that approach entirely.

Broadly, there’s a culturally right and a culturally left ideal theory for race and society. The rightist version calls for color blindness. Instead of making a fuss about skin and ethnicity, its advocates say, society should treat people as people, and let the best and the hardest working rise.

The leftist theory envisions identity communities: for once, give black people (or women, or members of other historically oppressed groups) the resources and opportunities they need, including, if they want it, civil infrastructure for themselves.

In “The Imperative of Integration,” published in 2010, Anderson tore apart both of these models. Sure, it might be nice to live in a color-blind society, she wrote, but that’s nothing like the one that exists.

But the case for self-segregation was also weak. Affinity groups provided welcome comfort, yet that wasn’t the same as power or equality, Anderson pointed out. And there was a goose-and-gander problem. Either you let only certain groups self-segregate (certifying their subordinate status) or you also permitted, say, white men to do it,

Anderson’s solution was “integration,” a concept that, especially in progressive circles, had been uncool since the late sixties. Integration, by her lights, meant mixing on the basis of equality.

in attending to these empirical findings over doctrine, she announced herself as a non-ideal theorist: a philosopher with no end vision of society. The approach recalls E. L. Doctorow’s description of driving at night: “You can see only as far as the headlights, but you can make the whole trip that way.”

or others, though, a white woman making recommendations on race policy raised questions of perspective. She was engaging through a mostly white Anglo-American tradition. She worked from the premise that, because she drew on folders full of studies, the limits of her own perspective were not constraining.

Some philosophers of color welcomed the book. “She’s taking the need for racial justice seriously, and you could hardly find another white political philosopher over a period of decades doing that,”

Recently, Anderson changed the way she assigns undergraduate essays: instead of requiring students to argue a position and fend off objections, doubling down on their original beliefs, she asks them to discuss their position with someone who disagrees, and to explain how and why, if at all, the discussion changed their views.

The challenge of pluralism is the challenge of modern society: maintaining equality amid difference in a culture given to constant and unpredictable change.

Rather than fighting for the ascendancy of certain positions, Anderson suggests, citizens should fight to bolster healthy institutions and systems—those which insure that all views and experiences will be heard. Today’s righteous projects, after all, will inevitably seem fatuous and blinkered from the vantage of another age.

Smith saw the markets as an escape from that order. Their “most important” function, he explained, was to bring “liberty and security” to those “who had before lived almost in a continual state of war with their neighbours, and of servile dependency upon their superiors.”

Anderson zeroed in on Adam Smith, whose “The Wealth of Nations,” published in 1776, is taken as a keystone of free-market ideology. At the time, English labor was subject to uncompensated apprenticeships, domestic servitude, and some measure of clerical dominion.

Smith, in other words, was an egalitarian. He had written “The Wealth of Nations” in no small part to be a solution to what we’d now call structural inequality—the intractable, compounding privileges of an arbitrary hierarchy.

It was a historical irony that, a century later, writers such as Marx pointed to the market as a structure of dominion over workers; in truth, Smith and Marx had shared a socioeconomic project. And yet Marx had not been wrong to trash Smith’s ideas, because, during the time between them, the world around Smith’s model had changed, and it was no longer a useful tool.

mages of free market society that made sense prior to the Industrial Revolution continue to circulate today as ideals, blind to the gross mismatch between the background social assumptions reigning in the seventeenth and eighteenth centuries, and today’s institutional realities. We are told that our choice is between free markets and state control, when most adults live their working lives under a third thing entirely: private government.

Today, people still try to use, variously, both Smith’s and Marx’s tools on a different, postindustrial world:

The unnaturalness of this top-heavy arrangement, combined with growing evidence of power abuses, has given many people reason to believe that something is fishy about the structure of American equality. Socialist and anti-capitalist models are again in vogue.

Anderson offers a different corrective path. She thinks it’s fine for some people to earn more than others. If you’re a brilliant potter, and people want to pay you more than the next guy for your pottery, great!

The problem isn’t that talent and income are distributed in unequal parcels. The problem is that Jeff Bezos earns more than a hundred thousand dollars a minute, while Amazon warehouse employees, many talented and hardworking, have reportedly resorted to urinating in bottles in lieu of a bathroom break. That circumstance reflects some structure of hierarchical oppression. It is a rip in the democratic fabric, and it’s increasingly the norm.

Andersonism holds that we don’t have to give up on market society if we can recognize and correct for its limitations—it may even be our best hope, because it’s friendlier to pluralism than most alternatives are.

we must be flexible. We must remain alert. We must solve problems collaboratively, in the moment, using society’s ears and eyes and the best tools that we can find.

“You can see that, from about 1950 to 1970, the typical American’s wages kept up with productivity growth,” she said. Then, around 1974, she went on, hourly compensation stagnated. American wages have been effectively flat for the past few decades, with the gains of productivity increasingly going to shareholders and to salaries for big bosses.

What changed? Anderson rattled off a constellation of factors, from strengthened intellectual-property law to winnowed antitrust law. Financialization, deregulation. Plummeting taxes on capital alongside rising payroll taxes. Privatization, which exchanged modest public-sector salaries for C.E.O. paydays. She gazed into the audience and blinked. “So now we have to ask: What has been used to justify this rather dramatic shift of labor-share of income?”

It was no wonder that industrial-age thinking was riddled with contradictions: it reflected what Anderson called “the plutocratic reversal” of classical liberal ideas. Those perversely reversed ideas about freedom were the ones that found a home in U.S. policy, and, well, here we were.

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?