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So, the challenge becomes how to recommend “new videos that users want to watch” when those videos are new to the system and low in views. (Finding fresh, potentially hot videos is important, YouTube researchers have written, for “propagating viral content.”)

more than 70 percent of the videos that YouTube recommended showed up on the list only once. It’s impossible to examine how hundreds of thousands of videos connect to each first random video when there are such limited data about each one.

People want to know if YouTube regularly radicalizes people with its recommendations, as the scholar Zeynep Tufekci has suggested. This study suggests that YouTube pushes an anonymous user toward more popular, not more fringe, content.

For my November magazine story about children’s YouTube, the company’s answer to these kinds of troubling suggestions was that YouTube isn’t for kids. Children, they told me, should be using only the YouTube Kids app, which has been built as a safe space for them

The algorithms are showing you things to see what you react to and showing you more of the things that prompt an emotional response, that make it harder to leave Facebook or Instagram or any of the other social networks.

really if your goal is to maximize engagement that is of course what you’d do since anger is a far more compelling and powerful emotion than appreciation.

Facebook didn’t do that. That’s coded into our neurology. Facebook really is an extremism generating machine. It’s really an inevitable part of the core engine.

it’s not just Facebook. Or perhaps you could say it’s not even Facebook at all. It’s the mix of machine learning and the business models of all the social networks

They have real upsides. They connect us with people. Show us fun videos. But they are also inherently destructive. And somehow we have to take cognizance of that – and not just as a matter of the business decisions of one company.

the social networks – meaning the mix of machine learning and advertising/engagement based business models – are really something new under the sun. They’re addiction and extremism generating systems. It’s what they’re designed to do.

Facebook shut down the team in late 2019.

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

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

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

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

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

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

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

said Brian Primack, a professor of public health and medicine and dean of the College of Education and Health Professions at the University of Arkansas

His research group followed about a thousand people over six months in a nationally representative survey and found that the amount of social media that a person used was the No. 1 predictor of the variables they measured for who became depressed.

In late 2017, a Facebook executive and a researcher wrote a public blog post that outlined some of the issues with social-media addiction. According to the post, the company had found that while passive consumption of social media could make you feel worse, the opposite was true of more active social-media use.

Inside Facebook, the researchers registered concern about the direction of Facebook’s focus on certain metrics, including the number of times a person logs into the app, which the company calls a session. “One of the worries with using sessions as a north star is we want to be extra careful not to game them by creating bad experiences for vulnerable populations,” a researcher wrote, referring to elements designed to draw people back to Facebook frequently, such as push notifications.

Facebook then made a switch to more heavily weigh “meaningful social interactions” in its news feed as a way to combat passive consumption. One side effect of that change, as outlined in a previous Journal article in The Facebook Files, was that the company’s algorithms rewarded content that was angry or sensational, because those posts increased engagement from users.

Facebook said any algorithm can promote objectionable or harmful content and that the company is doing its best to mitigate the problem.

“Every second that I wasn’t occupied by something I had to do I was fooling around on my phone scrolling through Facebook,” Ms. Gandy said. “Facebook took over my brain.”

“Actively interacting with people—especially sharing messages, posts and comments with close friends and reminiscing about past interactions—is linked to improvements in well-being,” the company said.

The well-being team, according to people familiar with the matter, was reshuffled at least twice since late 2017 before it was disbanded, and could get only about half of the resources the team requested to do its work.

In 2018, Facebook’s researchers surveyed 20,000 U.S. users and paired their answers with data about their behavior on Facebook. The researchers found about 3% of these users said they experienced “serious problems” in their sleep, work or relationships related to their time on Facebook that they found difficult to change. Some of the researchers’ work was published in a 2019 paper.

According to that study, the researchers also said that a liberal interpretation of the results would be that 14% of respondents spent “a lot more time on Facebook than they want to,” although they didn’t label this group problematic users.

In 2019, the researchers had come to a new figure: What they called problematic use affects 12.5% of people on Facebook, they said. This survey used a broader definition for the issue, including users who reported negative results on key aspects of their life as well as feelings of guilt or a loss of control, according to the documents.

The researchers also asked Facebook users what aspects of Facebook triggered them most. The users said the app’s many notifications sucked them in. “Red dots are toxic on the home screen,” a male young adult in the U.S. told the researchers, referring to the symbol that alerts a user to new content.

One entrepreneur came up with his own solution to some of these issues. In 2016, software developer Louis Barclay manually unfollowed all the people, pages and groups he saw on Facebook in an attempt to be more deliberate about how he used technology. The process, which isn’t the same as unfriending, took him days, but he was happy with the result: an empty newsfeed that no longer sucked him in for hours. He could still visit the profile pages of everyone he wanted to connect with on Facebook, but their content would no longer appear in the never-ending scroll of posts.

Thinking other people might benefit from a similar experience on Facebook, he built a tool that would enable anyone to automate the process. He created it as a piece of add-on software called a browser extension that anyone could download. He called it Unfollow Everything and made it available on Chrome’s web store free of charge.

In July, Facebook sent Mr. Barclay a cease-and-desist letter, which the inventor earlier wrote about for Slate, saying his tool was a breach of its terms of service for automating user interactions. It also permanently disabled Mr. Barclay’s personal Facebook and Instagram accounts.

Ms. Lever, the company spokeswoman, said Mr. Barclay’s extension could pose risks if abused, and said Facebook offers its own unfollow tool that allows users to manually unfollow accounts.

The company knows that strong negative emotions, which can be provoked by negative social comparison, keep users’ attention longer than other emotions—and Instagram’s algorithms are expressly designed to push teens toward toxic content so that they stay on the platform.

Instagram is peddling a false narrative that the platform is simply a reflection of its users’ interests and experiences, without distortion or manipulation by the platform. But Instagram knows full well that this not true. In fact, their very business model is predicated on how much they can manipulate users’ behavior to boost engagement and extend time spent on the platform, which the platform then monetizes to sell to advertisers.

The business model, which has proven itself to be exquisitely profitable, is self-reinforcing for investors and top management.

Although it’s a real struggle for parents to keep their kids off social media, they can set limits on its use, for instance by requiring that everyone’s phones go into a basket at mealtimes and at bedtime.

With all that we know today about the harmful effects of social media and its algorithms, combined with the powerful stories of teens, parents, and community advocates, we may finally have the opportunity to get meaningful federal regulation in place.

I believe “Twitter poisoning” is a real thing. It is a side effect that appears when people are acting under an algorithmic system that is designed to engage them to the max. It’s a symptom of being part of a behavior-modification scheme.

The same could be said about any number of other figures, including on the left. Examples are found in the excesses of cancel culture and joyless orthodoxies in fandom, in vain attention competitions and senseless online bullying.

The human brain did not evolve to handle modern chemicals or modern media technology and is vulnerable to addiction. That is true for me and for us all.

Behavioral changes occur as a side effect of something called operant conditioning, which is the underlying mechanism of social media addiction. This is the core mechanism analogous to the role alcohol plays in alcoholism.

In the case of digital platforms, the purpose is usually “engagement,” a concept that is hard to distinguish from addiction. People receive little positive and negative jolts of social feedback — getting followed or liked, or being ignored or even humiliated.

Before social media, that kind of tight feedback loop had rarely been present in human communications outside of laboratories or marriages. (This is part of why marriage can be hard, I suspect.)  

was around when Google and other companies that operate on the personalized advertising model were created, and I can say that at least in the early days, operant conditioning was not part of the plan.

What happened was that the algorithms that optimized the individualized advertising model found their way into it automatically, unintentionally rediscovering methods that had been tested on dogs and pigeons.

There is a childish insecurity, where before there was pride. Instead of being above it all, like traditional strongmen throughout history, the modern social media-poisoned alpha male whines and frets.

What do I think are the symptoms of Twitter poisoning?

o be clear, whiners are much better than Stalins. And yet there have been plenty of more mature and gracious leaders who are better than either

When we were children, we all had to negotiate our way through the jungle of human power relationships at the playground

When we feel those old humiliations, anxieties and sadisms again as adults — over and over, because the algorithm has settled on that pattern as a powerful way to engage us — habit formation restimulates old patterns that had been dormant. We become children again, not in a positive, imaginative sense, but in a pathetic way.

Twitter poisoning makes sufferers feel more oppressed than is reasonable in response to reasonable rules. The scope of fun is constricted to transgressions.

Unfortunately, scale changes everything. Taunts become dangerous hate when amplified. A Twitter-poisoned soul will often complain of a loss of fun when someone succeeds at moderating the spew of hate.

the afflicted lose all sense of proportion about their own powers. They can come to believe they have almost supernatural abilities

The degree of narcissism becomes almost absolute. Everything is about what someone else thinks of you.

These observations should inform our concerns about TikTok. The most devastating way China might use TikTok is not to misdirect our elections or to prefer pro-China posts, but to generally ramp up social media disease, so as to make Americans more divided, less able to talk to one another and less able to put up a coordinated, unified front.

uide society. Whether that idea appeals or not, when technology degrades the minds of those same engineers, then the result can only be dysfunction.

Jaron Lanier is a computer scientist who pioneered research in virtual reality and whose books include “Ten Arguments for Deleting Your Social Media Accounts Right Now.” He is Microsoft’s “prime unifying scientist” but does not speak for the company.

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.

the stage was set for the major transformation, which began in 2009: the intensification of viral dynamics.

Before 2009, Facebook had given users a simple timeline––a never-ending stream of content generated by their friends and connections, with the newest posts at the top and the oldest ones at the bottom

That began to change in 2009, when Facebook offered users a way to publicly “like” posts with the click of a button. That same year, Twitter introduced something even more powerful: the “Retweet” button, which allowed users to publicly endorse a post while also sharing it with all of their followers.

“Like” and “Share” buttons quickly became standard features of most other platforms.

Facebook developed algorithms to bring each user the content most likely to generate a “like” or some other interaction, eventually including the “share” as well.

Later research showed that posts that trigger emotions––especially anger at out-groups––are the most likely to be shared.

By 2013, social media had become a new game, with dynamics unlike those in 2008. If you were skillful or lucky, you might create a post that would “go viral” and make you “internet famous”

If you blundered, you could find yourself buried in hateful comments. Your posts rode to fame or ignominy based on the clicks of thousands of strangers, and you in turn contributed thousands of clicks to the game.

This new game encouraged dishonesty and mob dynamics: Users were guided not just by their true preferences but by their past experiences of reward and punishment,

As a social psychologist who studies emotion, morality, and politics, I saw this happening too. The newly tweaked platforms were almost perfectly designed to bring out our most moralistic and least reflective selves. The volume of outrage was shocking.

It was just this kind of twitchy and explosive spread of anger that James Madison had tried to protect us from as he was drafting the U.S. Constitution.

The Framers of the Constitution were excellent social psychologists. They knew that democracy had an Achilles’ heel because it depended on the collective judgment of the people, and democratic communities are subject to “the turbulency and weakness of unruly passions.”

The key to designing a sustainable republic, therefore, was to build in mechanisms to slow things down, cool passions, require compromise, and give leaders some insulation from the mania of the moment while still holding them accountable to the people periodically, on Election Day.

The tech companies that enhanced virality from 2009 to 2012 brought us deep into Madison’s nightmare.

a less quoted yet equally important insight, about democracy’s vulnerability to triviality.

Madison notes that people are so prone to factionalism that “where no substantial occasion presents itself, the most frivolous and fanciful distinctions have been sufficient to kindle their unfriendly passions and excite their most violent conflicts.”

Social media has both magnified and weaponized the frivolous.

It’s not just the waste of time and scarce attention that matters; it’s the continual chipping-away of trust.

a democracy depends on widely internalized acceptance of the legitimacy of rules, norms, and institutions.

when citizens lose trust in elected leaders, health authorities, the courts, the police, universities, and the integrity of elections, then every decision becomes contested; every election becomes a life-and-death struggle to save the country from the other side

The most recent Edelman Trust Barometer (an international measure of citizens’ trust in government, business, media, and nongovernmental organizations) showed stable and competent autocracies (China and the United Arab Emirates) at the top of the list, while contentious democracies such as the United States, the United Kingdom, Spain, and South Korea scored near the bottom (albeit above Russia).

The literature is complex—some studies show benefits, particularly in less developed democracies—but the review found that, on balance, social media amplifies political polarization; foments populism, especially right-wing populism; and is associated with the spread of misinformation.

When people lose trust in institutions, they lose trust in the stories told by those institutions. That’s particularly true of the institutions entrusted with the education of children.

Facebook and Twitter make it possible for parents to become outraged every day over a new snippet from their children’s history lessons––and math lessons and literature selections, and any new pedagogical shifts anywhere in the country

The motives of teachers and administrators come into question, and overreaching laws or curricular reforms sometimes follow, dumbing down education and reducing trust in it further.

young people educated in the post-Babel era are less likely to arrive at a coherent story of who we are as a people, and less likely to share any such story with those who attended different schools or who were educated in a different decade.

former CIA analyst Martin Gurri predicted these fracturing effects in his 2014 book, The Revolt of the Public. Gurri’s analysis focused on the authority-subverting effects of information’s exponential growth, beginning with the internet in the 1990s. Writing nearly a decade ago, Gurri could already see the power of social media as a universal solvent, breaking down bonds and weakening institutions everywhere it reached.

he notes a constructive feature of the pre-digital era: a single “mass audience,” all consuming the same content, as if they were all looking into the same gigantic mirror at the reflection of their own society. I

The digital revolution has shattered that mirror, and now the public inhabits those broken pieces of glass. So the public isn’t one thing; it’s highly fragmented, and it’s basically mutually hostile

Facebook, Twitter, YouTube, and a few other large platforms unwittingly dissolved the mortar of trust, belief in institutions, and shared stories that had held a large and diverse secular democracy together.

I think we can date the fall of the tower to the years between 2011 (Gurri’s focal year of “nihilistic” protests) and 2015, a year marked by the “great awokening” on the left and the ascendancy of Donald Trump on the right.

Twitter can overpower all the newspapers in the country, and stories cannot be shared (or at least trusted) across more than a few adjacent fragments—so truth cannot achieve widespread adherence.

fter Babel, nothing really means anything anymore––at least not in a way that is durable and on which people widely agree.

Politics After Babel

“Politics is the art of the possible,” the German statesman Otto von Bismarck said in 1867. In a post-Babel democracy, not much may be possible.

The ideological distance between the two parties began increasing faster in the 1990s. Fox News and the 1994 “Republican Revolution” converted the GOP into a more combative party.

So cross-party relationships were already strained before 2009. But the enhanced virality of social media thereafter made it more hazardous to be seen fraternizing with the enemy or even failing to attack the enemy with sufficient vigor.

What changed in the 2010s? Let’s revisit that Twitter engineer’s metaphor of handing a loaded gun to a 4-year-old. A mean tweet doesn’t kill anyone; it is an attempt to shame or punish someone publicly while broadcasting one’s own virtue, brilliance, or tribal loyalties. It’s more a dart than a bullet

from 2009 to 2012, Facebook and Twitter passed out roughly 1 billion dart guns globally. We’ve been shooting one another ever since.

“devoted conservatives,” comprised 6 percent of the U.S. population.

the warped “accountability” of social media has also brought injustice—and political dysfunction—in three ways.

First, the dart guns of social media give more power to trolls and provocateurs while silencing good citizens.

a small subset of people on social-media platforms are highly concerned with gaining status and are willing to use aggression to do so.

Across eight studies, Bor and Petersen found that being online did not make most people more aggressive or hostile; rather, it allowed a small number of aggressive people to attack a much larger set of victims. Even a small number of jerks were able to dominate discussion forums,

Additional research finds that women and Black people are harassed disproportionately, so the digital public square is less welcoming to their voices.

Second, the dart guns of social media give more power and voice to the political extremes while reducing the power and voice of the moderate majority.

The “Hidden Tribes” study, by the pro-democracy group More in Common, surveyed 8,000 Americans in 2017 and 2018 and identified seven groups that shared beliefs and behaviors.

Social media has given voice to some people who had little previously, and it has made it easier to hold powerful people accountable for their misdeeds

The group furthest to the left, the “progressive activists,” comprised 8 percent of the population. The progressive activists were by far the most prolific group on social media: 70 percent had shared political content over the previous year. The devoted conservatives followed, at 56 percent.

These two extreme groups are similar in surprising ways. They are the whitest and richest of the seven groups, which suggests that America is being torn apart by a battle between two subsets of the elite who are not representative of the broader society.

they are the two groups that show the greatest homogeneity in their moral and political attitudes.

likely a result of thought-policing on social media:

political extremists don’t just shoot darts at their enemies; they spend a lot of their ammunition targeting dissenters or nuanced thinkers on their own team.

Finally, by giving everyone a dart gun, social media deputizes everyone to administer justice with no due process. Platforms like Twitter devolve into the Wild West, with no accountability for vigilantes.

Enhanced-virality platforms thereby facilitate massive collective punishment for small or imagined offenses, with real-world consequences, including innocent people losing their jobs and being shamed into suicide

we don’t get justice and inclusion; we get a society that ignores context, proportionality, mercy, and truth.

Since the tower fell, debates of all kinds have grown more and more confused. The most pervasive obstacle to good thinking is confirmation bias, which refers to the human tendency to search only for evidence that confirms our preferred beliefs

search engines were supercharging confirmation bias, making it far easier for people to find evidence for absurd beliefs and conspiracy theorie

The most reliable cure for confirmation bias is interaction with people who don’t share your beliefs. They confront you with counterevidence and counterargument.

In his book The Constitution of Knowledge, Jonathan Rauch describes the historical breakthrough in which Western societies developed an “epistemic operating system”—that is, a set of institutions for generating knowledge from the interactions of biased and cognitively flawed individuals

English law developed the adversarial system so that biased advocates could present both sides of a case to an impartial jury.

Newspapers full of lies evolved into professional journalistic enterprises, with norms that required seeking out multiple sides of a story, followed by editorial review, followed by fact-checking.

Universities evolved from cloistered medieval institutions into research powerhouses, creating a structure in which scholars put forth evidence-backed claims with the knowledge that other scholars around the world would be motivated to gain prestige by finding contrary evidence.

Part of America’s greatness in the 20th century came from having developed the most capable, vibrant, and productive network of knowledge-producing institutions in all of human history

But this arrangement, Rauch notes, “is not self-maintaining; it relies on an array of sometimes delicate social settings and understandings, and those need to be understood, affirmed, and protected.”

This, I believe, is what happened to many of America’s key institutions in the mid-to-late 2010s. They got stupider en masse because social media instilled in their members a chronic fear of getting darted

it was so pervasive that it established new behavioral norms backed by new policies seemingly overnight

Participants in our key institutions began self-censoring to an unhealthy degree, holding back critiques of policies and ideas—even those presented in class by their students—that they believed to be ill-supported or wrong.

The stupefying process plays out differently on the right and the left because their activist wings subscribe to different narratives with different sacred values.

The “Hidden Tribes” study tells us that the “devoted conservatives” score highest on beliefs related to authoritarianism. They share a narrative in which America is eternally under threat from enemies outside and subversives within; they see life as a battle between patriots and traitors.

they are psychologically different from the larger group of “traditional conservatives” (19 percent of the population), who emphasize order, decorum, and slow rather than radical change.

The traditional punishment for treason is death, hence the battle cry on January 6: “Hang Mike Pence.”

Right-wing death threats, many delivered by anonymous accounts, are proving effective in cowing traditional conservatives

The wave of threats delivered to dissenting Republican members of Congress has similarly pushed many of the remaining moderates to quit or go silent, giving us a party ever more divorced from the conservative tradition, constitutional responsibility, and reality.

The stupidity on the right is most visible in the many conspiracy theories spreading across right-wing media and now into Congress.

The Democrats have also been hit hard by structural stupidity, though in a different way. In the Democratic Party, the struggle between the progressive wing and the more moderate factions is open and ongoing, and often the moderates win.

The problem is that the left controls the commanding heights of the culture: universities, news organizations, Hollywood, art museums, advertising, much of Silicon Valley, and the teachers’ unions and teaching colleges that shape K–12 education. And in many of those institutions, dissent has been stifled:

Liberals in the late 20th century shared a belief that the sociologist Christian Smith called the “liberal progress” narrative, in which America used to be horrifically unjust and repressive, but, thanks to the struggles of activists and heroes, has made (and continues to make) progress toward realizing the noble promise of its founding.

It is also the view of the “traditional liberals” in the “Hidden Tribes” study (11 percent of the population), who have strong humanitarian values, are older than average, and are largely the people leading America’s cultural and intellectual institutions.

when the newly viralized social-media platforms gave everyone a dart gun, it was younger progressive activists who did the most shooting, and they aimed a disproportionate number of their darts at these older liberal leaders.

Confused and fearful, the leaders rarely challenged the activists or their nonliberal narrative in which life at every institution is an eternal battle among identity groups over a zero-sum pie, and the people on top got there by oppressing the people on the bottom. This new narrative is rigidly egalitarian––focused on equality of outcomes, not of rights or opportunities. It is unconcerned with individual rights.

The universal charge against people who disagree with this narrative is not “traitor”; it is “racist,” “transphobe,” “Karen,” or some related scarlet letter marking the perpetrator as one who hates or harms a marginalized group.

The punishment that feels right for such crimes is not execution; it is public shaming and social death.

anyone on Twitter had already seen dozens of examples teaching the basic lesson: Don’t question your own side’s beliefs, policies, or actions. And when traditional liberals go silent, as so many did in the summer of 2020, the progressive activists’ more radical narrative takes over as the governing narrative of an organization.

This is why so many epistemic institutions seemed to “go woke” in rapid succession that year and the next, beginning with a wave of controversies and resignations at The New York Times and other newspapers, and continuing on to social-justice pronouncements by groups of doctors and medical associations

The problem is structural. Thanks to enhanced-virality social media, dissent is punished within many of our institutions, which means that bad ideas get elevated into official policy.

In a 2018 interview, Steve Bannon, the former adviser to Donald Trump, said that the way to deal with the media is “to flood the zone with shit.” He was describing the “firehose of falsehood” tactic pioneered by Russian disinformation programs to keep Americans confused, disoriented, and angry.

artificial intelligence is close to enabling the limitless spread of highly believable disinformation. The AI program GPT-3 is already so good that you can give it a topic and a tone and it will spit out as many essays as you like, typically with perfect grammar and a surprising level of coherence.

Renée DiResta, the research manager at the Stanford Internet Observatory, explained that spreading falsehoods—whether through text, images, or deep-fake videos—will quickly become inconceivably easy. (She co-wrote the essay with GPT-3.)

American factions won’t be the only ones using AI and social media to generate attack content; our adversaries will too.

In the 20th century, America’s shared identity as the country leading the fight to make the world safe for democracy was a strong force that helped keep the culture and the polity together.

In the 21st century, America’s tech companies have rewired the world and created products that now appear to be corrosive to democracy, obstacles to shared understanding, and destroyers of the modern tower.

What changes are needed?

I can suggest three categories of reforms––three goals that must be achieved if democracy is to remain viable in the post-Babel era.

We must harden democratic institutions so that they can withstand chronic anger and mistrust, reform social media so that it becomes less socially corrosive, and better prepare the next generation for democratic citizenship in this new age.

Harden Democratic Institutions

we must reform key institutions so that they can continue to function even if levels of anger, misinformation, and violence increase far above those we have today.

Reforms should reduce the outsize influence of angry extremists and make legislators more responsive to the average voter in their district.

One example of such a reform is to end closed party primaries, replacing them with a single, nonpartisan, open primary from which the top several candidates advance to a general election that also uses ranked-choice voting

A second way to harden democratic institutions is to reduce the power of either political party to game the system in its favor, for example by drawing its preferred electoral districts or selecting the officials who will supervise elections

These jobs should all be done in a nonpartisan way.

Reform Social Media

Social media’s empowerment of the far left, the far right, domestic trolls, and foreign agents is creating a system that looks less like democracy and more like rule by the most aggressive.

it is within our power to reduce social media’s ability to dissolve trust and foment structural stupidity. Reforms should limit the platforms’ amplification of the aggressive fringes while giving more voice to what More in Common calls “the exhausted majority.”

the main problem with social media is not that some people post fake or toxic stuff; it’s that fake and outrage-inducing content can now attain a level of reach and influence that was not possible before

Perhaps the biggest single change that would reduce the toxicity of existing platforms would be user verification as a precondition for gaining the algorithmic amplification that social media offers.

One of the first orders of business should be compelling the platforms to share their data and their algorithms with academic researchers.

Prepare the Next Generation

Childhood has become more tightly circumscribed in recent generations––with less opportunity for free, unstructured play; less unsupervised time outside; more time online. Whatever else the effects of these shifts, they have likely impeded the development of abilities needed for effective self-governance for many young adults

Depression makes people less likely to want to engage with new people, ideas, and experiences. Anxiety makes new things seem more threatening. As these conditions have risen and as the lessons on nuanced social behavior learned through free play have been delayed, tolerance for diverse viewpoints and the ability to work out disputes have diminished among many young people

Students did not just say that they disagreed with visiting speakers; some said that those lectures would be dangerous, emotionally devastating, a form of violence. Because rates of teen depression and anxiety have continued to rise into the 2020s, we should expect these views to continue in the generations to follow, and indeed to become more severe.

The most important change we can make to reduce the damaging effects of social media on children is to delay entry until they have passed through puberty.

The age should be raised to at least 16, and companies should be held responsible for enforcing it.

et them out to play. Stop starving children of the experiences they most need to become good citizens: free play in mixed-age groups of children with minimal adult supervision

while social media has eroded the art of association throughout society, it may be leaving its deepest and most enduring marks on adolescents. A surge in rates of anxiety, depression, and self-harm among American teens began suddenly in the early 2010s. (The same thing happened to Canadian and British teens, at the same time.) The cause is not known, but the timing points to social media as a substantial contributor—the surge began just as the large majority of American teens became daily users of the major platforms.

What would it be like to live in Babel in the days after its destruction? We know. It is a time of confusion and loss. But it is also a time to reflect, listen, and build.

In recent years, Americans have started hundreds of groups and organizations dedicated to building trust and friendship across the political divide, including BridgeUSA, Braver Angels (on whose board I serve), and many others listed at BridgeAlliance.us. We cannot expect Congress and the tech companies to save us. We must change ourselves and our communities.

when we look away from our dysfunctional federal government, disconnect from social media, and talk with our neighbors directly, things seem more hopeful. Most Americans in the More in Common report are members of the “exhausted majority,” which is tired of the fighting and is willing to listen to the other side and compromise. Most Americans now see that social media is having a negative impact on the country, and are becoming more aware of its damaging effects on children.

The Pew Research Center survey asked people different questions but found similar doubts about AI. Just 15 percent of respondents said they were more excited than concerned about the increasing use of AI in daily life.

“It’s fantastic that there is public skepticism about AI. There absolutely should be,” said Meredith Broussard, an artificial intelligence researcher and professor at New York University.

Broussard said there can be no way to design artificial intelligence software to make inherently human decisions, like grading students’ tests or determining the course of medical treatment.

Most Americans essentially agree with Broussard that AI has a place in our lives, but not for everything.

Most people said it was a bad idea to use AI for military drones that try to distinguish between enemies and civilians or trucks making local deliveries without human drivers. Most respondents said it was a good idea for machines to perform risky jobs such as coal mining.

Roman Yampolskiy, an AI specialist at the University of Louisville engineering school, told me he’s concerned about how quickly technologists are building computers that are designed to “think” like the human brain and apply knowledge not just in one narrow area, like recommending Netflix movies, but for complex tasks that have tended to require human intelligence.

“We have an arms race between multiple untested technologies. That is my concern,” Yampolskiy said. (If you want to feel terrified, I recommend Yampolskiy’s research paper on the inability to control advanced AI.)

The term “AI” is a catch-all for everything from relatively uncontroversial technology, such as autocomplete in your web search queries, to the contentious software that promises to predict crime before it happens. Our fears about the latter might be overwhelming our beliefs about the benefits from more mundane AI.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Is this all sounding rather familiar now? Does it remind you of something?

it quickly became clear that the GamerGate movement was a mess – an undefined mission to Make Video Games Great Again via undecided means.

fter all, the culture war that began in games now has a senior representative in The White House. As a founder member and former executive chair of Brietbart News, Steve Bannon had a hand in creating media monster Milo Yiannopoulos, who built his fame and Twitter following by supporting and cheerleading Gamergate. This hashtag was the canary in the coalmine, and we ignored it.

Gamergate was an online movement that effectively began because a man wanted to punish his ex girlfriend. Its most notable achievement was harassing a large number of progressive figures - mostly women – to the point where they felt unsafe or considered leaving the industry

The similarities between Gamergate and the far-right online movement, the “alt-right”, are huge, startling and in no way a coincidence

no one in the movement was willing to be associated with the abuse being carried out in its name. Prominent supporters on Twitter, in subreddits and on forums like 8Chan, developed a range of pernicious rhetorical devices and defences to distance themselves from threats to women and minorities in the industry: the targets were lying or exaggerating, they were too precious; a language of dismissal and belittlement was formed against them. Safe spaces, snowflakes, unicorns, cry bullies. Even when abuse was proven, the usual response was that people on their side were being abused too. These techniques, forged in Gamergate, have become the standard toolset of far-right voices online

In 2016, new wave conservative media outlets like Breitbart have gained trust with their audience by painting traditional news sources as snooty and aloof. In 2014, video game YouTube stars, seeking to appear in touch with online gaming communities, unscrupulously proclaimed that traditional old-media sources were corrupt. Everything we’re seeing now, had its precedent two years ago.

With 2014’s Gamergate, Breitbart seized the opportunity to harness the pre-existing ignorance and anger among disaffected young white dudes. With Trump’s movement in 2016, the outlet was effectively running his campaign: Steve Bannon took leave of his role at the company in August 2016 when he was hired as chief executive of Trump’s presidential campaign

young men converted via 2014’s Gamergate, are being more widely courted now. By leveraging distrust and resentment towards women, minorities and progressives, many of Gamergate’s most prominent voices – characters like Mike Cernovich, Adam Baldwin, and Milo Yiannopoulos – drew power and influence from its chaos

These figures gave Gamergate a new sense of direction – generalising the rhetoric: this was now a wider war between “Social Justice Warriors” (SJWs) and everyday, normal, decent people. Games were simply the tip of the iceberg – progressive values, went the argument, were destroying everything

The same voices moved into other geek communities, especially comics, where Marvel and DC were criticised for progressive storylines and decisions. They moved into science fiction with the controversy over the Hugo awards. They moved into cinema with the revolting kickback against the all-female Ghostbusters reboot.

Using 4chan (and then the more sympathetic offshoot 8Chan) to plan their subversions and attacks made Gamergate a terribly sloppy operation, leaving a trail of evidence that made it quite clear the whole thing was purposefully, plainly nasty. But the video game industry didn’t have the spine to react, and allowed the movement to coagulate – forming a mass of spiteful disappointment that Breitbart was only more than happy to coddle

Historically, that seems to be Breitbart’s trick - strongly represent a single issue in order to earn trust, and then gradually indoctrinate to suit wider purposes. With Gamergate, they purposefully went fishing for anti-feminists. 2016’s batch of fresh converts – the white extremists – came from enticing conspiracy theories about the global neoliberal elite secretly controlling the world.

The greatest strength of Gamergate, though, was that it actually appeared to represent many left-leaning ideals: stamping out corruption in the press, pushing for better ethical practices, battling for openness.

There are similarities here with many who support Trump because of his promises to put an end to broken neo-liberalism, to “drain the swamp” of establishment corruption. Many left-leaning supporters of Gamergate sought to intellectualise their alignment with the hashtag, adopting familiar and acceptable labels of dissent – identifying as libertarian, egalitarian, humanist.

At best they unknowingly facilitated abuse, defending their own freedom of expression while those who actually needed support were threatened and attacked.

Genuine discussions over criticism, identity and censorship were paralysed and waylaid by Twitter voices obsessed with rhetorical fallacies and pedantic debating practices. While the core of these movements make people’s lives hell, the outer shell – knowingly or otherwise – protect abusers by insisting that the real problem is that you don’t want to talk, or won’t provide the ever-shifting evidence they politely require.

In 2017, the tactics used to discredit progressive game critics and developers will be used to discredit Trump and Bannon’s critics. There will be gaslighting, there will be attempts to make victims look as though they are losing their grip on reality, to the point that they gradually even start to believe it. The “post-truth” reality is not simply an accident – it is a concerted assault on the rational psyche.

The strangest aspect of Gamergate is that it consistently didn’t make any sense: people chose to align with it, and yet refused responsibility. It was constantly demanded that we debate the issues, but explanations and facts were treated with scorn. Attempts to find common ground saw the specifics of the demands being shifted: we want you to listen to us; we want you to change your ways; we want you to close your publication down. This movement that ostensibly wanted to protect free speech from cry bully SJWs simultaneously did what it could to endanger sites it disagreed with, encouraging advertisers to abandon support for media outlets that published stories critical of the hashtag. The petulance of that movement is disturbingly echoed in Trump’s own Twitter feed.

Looking back, Gamergate really only made sense in one way: as an exemplar of what Umberto Eco called “eternal fascism”, a form of extremism he believed could flourish at any point in, in any place – a fascism that would extol traditional values, rally against diversity and cultural critics, believe in the value of action above thought and encourage a distrust of intellectuals or experts – a fascism built on frustration and machismo. The requirement of this formless fascism would – above all else – be to remain in an endless state of conflict, a fight against a foe who must always be portrayed as impossibly strong and laughably weak

2016 has presented us with a world in which our reality is being wilfully manipulated. Fake news, divisive algorithms, misleading social media campaigns.

The majority of people who voted for Trump will never take responsibility for his racist, totalitarian policies, but they’ll provide useful cover and legitimacy for those who demand the very worst from the President Elect. Trump himself may have disavowed the “alt-right”, but his rhetoric has led to them feeling legitimised. As with Gamergate, the press risks being manipulated into a position where it has to tread a respectful middle ground that doesn’t really exist.

Perhaps the true lesson of Gamergate was that the media is culturally unequipped to deal with the forces actively driving these online movements. The situation was horrifying enough two years ago, it is many times more dangerous now.

Facebook just opened up its Instant Articles feature to all publishers. The feature allows external outlets to publish their content directly onto Facebook’s platform, eliminating that pesky journey to their actual website. They can either place their own ads on the content or join a revenue-sharing program with Facebook. Facebook has touted this plan as one which provides a better user experience and has noted the ability for publishers to create ads on the platform as well.

The benefit to Facebook is obvious: It gets to keep people inside its house. They don’t have to leave for even a second. The publisher essentially has to accept this reality, sigh about the gradual death of websites and hope that everything works out on the financial side.

It’s all part of a much bigger story: that of how the internet, that supposed smasher of gates and leveler of playing fields, has coalesced around a mere handful of mega-giants in the space of just a couple of decades. The gates didn’t really come down. The identities of the gatekeepers just changed. Google, Facebook, Apple, Amazon

The difference between Open and Market is that Open folks believe that learning objects are not commodities to be bought and sold, but the public infrastructure of our culture

the biggest players in the Open movement generally believe that learning is a process of algorthmically delivering learning objects to consumers, and they frequently use "supply and demand" models to conceptualize their efforts

They view learning as the process of delivering learning objects for the individual consumption of students, and they have great faith that this delivery process can be optimized by algorithms and data mining. It is incredibly important for them that we have quantifiable outcomes of learning (standardized tests), since they can only optimize on quantitative metrics.

They'd like learning objects and the algorithms distributing those objects to be openly licensed and free for teachers to reuse, remix, and re-publish.

The "Dewey" people reject the notion of learning as "delivery" and the free market as the best platform for learning.

Dewey is a complex figure, but when most people invoke him, they mean that learning occurs through people's experiences and not through content delivery

Learning occurs when teachers and students work together to create or make something with meaning to to people in the real world

They tend to believe that the nuanced, contextual, social experiences that lead to the best learning experiences are easiest to facilitate when the curriculum is not overly prescriptive.

it’s impossible to know for sure, but, according to one publisher’s estimate, book sales in the U.S. now make up no more than seven per cent of the company’s roughly seventy-five billion dollars in annual revenue.

A monopoly is dangerous because it concentrates so much economic power, but in the book business the prospect of a single owner of both the means of production and the modes of distribution is especially worrisome: it would give Amazon more control over the exchange of ideas than any company in U.S. history.

“The key to understanding Amazon is the hiring process,” one former employee said. “You’re not hired to do a particular job—you’re hired to be an Amazonian. Lots of managers had to take the Myers-Briggs personality tests. Eighty per cent of them came in two or three similar categories, and Bezos is the same: introverted, detail-oriented, engineer-type personality. Not musicians, designers, salesmen. The vast majority fall within the same personality type—people who graduate at the top of their class at M.I.T. and have no idea what to say to a woman in a bar.”

According to Marcus, Amazon executives considered publishing people “antediluvian losers with rotary phones and inventory systems designed in 1968 and warehouses full of crap.” Publishers kept no data on customers, making their bets on books a matter of instinct rather than metrics. They were full of inefficiences, starting with overpriced Manhattan offices.

For a smaller house, Amazon’s total discount can go as high as sixty per cent, which cuts deeply into already slim profit margins. Because Amazon manages its inventory so well, it often buys books from small publishers with the understanding that it can’t return them, for an even deeper discount

According to one insider, around 2008—when the company was selling far more than books, and was making twenty billion dollars a year in revenue, more than the combined sales of all other American bookstores—Amazon began thinking of content as central to its business. Authors started to be considered among the company’s most important customers. By then, Amazon had lost much of the market in selling music and videos to Apple and Netflix, and its relations with publishers were deteriorating

In its drive for profitability, Amazon did not raise retail prices; it simply squeezed its suppliers harder, much as Walmart had done with manufacturers. Amazon demanded ever-larger co-op fees and better shipping terms; publishers knew that they would stop being favored by the site’s recommendation algorithms if they didn’t comply. Eventually, they all did.

Brad Stone describes one campaign to pressure the most vulnerable publishers for better terms: internally, it was known as the Gazelle Project, after Bezos suggested “that Amazon should approach these small publishers the way a cheetah would pursue a sickly gazelle.”

ithout dropping co-op fees entirely, Amazon simplified its system: publishers were asked to hand over a percentage of their previous year’s sales on the site, as “marketing development funds.”

The figure keeps rising, though less for the giant pachyderms than for the sickly gazelles. According to the marketing executive, the larger houses, which used to pay two or three per cent of their net sales through Amazon, now relinquish five to seven per cent of gross sales, pushing Amazon’s percentage discount on books into the mid-fifties. Random House currently gives Amazon an effective discount of around fifty-three per cent.

In December, 1999, at the height of the dot-com mania, Time named Bezos its Person of the Year. “Amazon isn’t about technology or even commerce,” the breathless cover article announced. “Amazon is, like every other site on the Web, a content play.” Yet this was the moment, Marcus said, when “content” people were “on the way out.”

In 2004, he set up a lab in Silicon Valley that would build Amazon’s first piece of consumer hardware: a device for reading digital books. According to Stone’s book, Bezos told the executive running the project, “Proceed as if your goal is to put everyone selling physical books out of a job.”

By 2010, Amazon controlled ninety per cent of the market in digital books—a dominance that almost no company, in any industry, could claim. Its prohibitively low prices warded off competition

Lately, digital titles have levelled off at about thirty per cent of book sales.

The literary agent Andrew Wylie (whose firm represents me) says, “What Bezos wants is to drag the retail price down as low as he can get it—a dollar-ninety-nine, even ninety-nine cents. That’s the Apple play—‘What we want is traffic through our device, and we’ll do anything to get there.’ ” If customers grew used to paying just a few dollars for an e-book, how long before publishers would have to slash the cover price of all their titles?

As Apple and the publishers see it, the ruling ignored the context of the case: when the key events occurred, Amazon effectively had a monopoly in digital books and was selling them so cheaply that it resembled predatory pricing—a barrier to entry for potential competitors. Since then, Amazon’s share of the e-book market has dropped, levelling off at about sixty-five per cent, with the rest going largely to Apple and to Barnes & Noble, which sells the Nook e-reader. In other words, before the feds stepped in, the agency model introduced competition to the market

But the court’s decision reflected a trend in legal thinking among liberals and conservatives alike, going back to the seventies, that looks at antitrust cases from the perspective of consumers, not producers: what matters is lowering prices, even if that goal comes at the expense of competition. Barry Lynn, a market-policy expert at the New America Foundation, said, “It’s one of the main factors that’s led to massive consolidation.”

The combination of ceaseless innovation and low-wage drudgery makes Amazon the epitome of a successful New Economy company. It’s hiring as fast as it can—nearly thirty thousand employees last year.

brick-and-mortar retailers employ forty-seven people for every ten million dollars in revenue earned; Amazon employs fourteen.

Since the arrival of the Kindle, the tension between Amazon and the publishers has become an open battle. The conflict reflects not only business antagonism amid technological change but a division between the two coasts, with different cultural styles and a philosophical disagreement about what techies call “disruption.”

Bezos told Charlie Rose, “Amazon is not happening to bookselling. The future is happening to bookselling.”

n Grandinetti’s view, the Kindle “has helped the book business make a more orderly transition to a mixed print and digital world than perhaps any other medium.” Compared with people who work in music, movies, and newspapers, he said, authors are well positioned to thrive. The old print world of scarcity—with a limited number of publishers and editors selecting which manuscripts to publish, and a limited number of bookstores selecting which titles to carry—is yielding to a world of digital abundance. Grandinetti told me that, in these new circumstances, a publisher’s job “is to build a megaphone.”

it offers an extremely popular self-publishing platform. Authors become Amazon partners, earning up to seventy per cent in royalties, as opposed to the fifteen per cent that authors typically make on hardcovers. Bezos touts the biggest successes, such as Theresa Ragan, whose self-published thrillers and romances have been downloaded hundreds of thousands of times. But one survey found that half of all self-published authors make less than five hundred dollars a year.

The business term for all this clear-cutting is “disintermediation”: the elimination of the “gatekeepers,” as Bezos calls the professionals who get in the customer’s way. There’s a populist inflection to Amazon’s propaganda, an argument against élitist institutions and for “the democratization of the means of production”—a common line of thought in the West Coast tech world

“Book publishing is a very human business, and Amazon is driven by algorithms and scale,” Sargent told me. When a house gets behind a new book, “well over two hundred people are pushing your book all over the place, handing it to people, talking about it. A mass of humans, all in one place, generating tremendous energy—that’s the magic potion of publishing. . . . That’s pretty hard to replicate in Amazon’s publishing world, where they have hundreds of thousands of titles.”

By producing its own original work, Amazon can sell more devices and sign up more Prime members—a major source of revenue. While the company was building the

Like the publishing venture, Amazon Studios set out to make the old “gatekeepers”—in this case, Hollywood agents and executives—obsolete. “We let the data drive what to put in front of customers,” Carr told the Wall Street Journal. “We don’t have tastemakers deciding what our customers should read, listen to, and watch.”

book publishers have been consolidating for several decades, under the ownership of media conglomerates like News Corporation, which squeeze them for profits, or holding companies such as Rivergroup, which strip them to service debt. The effect of all this corporatization, as with the replacement of independent booksellers by superstores, has been to privilege the blockbuster.

Publishers sometimes pass on this cost to authors, by redefining royalties as a percentage of the publisher’s receipts, not of the book’s list price. Recently, publishers say, Amazon began demanding an additional payment, amounting to approximately one per cent of net sales

the long-term outlook is discouraging. This is partly because Americans don’t read as many books as they used to—they are too busy doing other things with their devices—but also because of the relentless downward pressure on prices that Amazon enforces.

he digital market is awash with millions of barely edited titles, most of it dreck, while r

Amazon believes that its approach encourages ever more people to tell their stories to ever more people, and turns writers into entrepreneurs; the price per unit might be cheap, but the higher number of units sold, and the accompanying royalties, will make authors wealthier

In Friedman’s view, selling digital books at low prices will democratize reading: “What do you want as an author—to sell books to as few people as possible for as much as possible, or for as little as possible to as many readers as possible?”

The real talent, the people who are writers because they happen to be really good at writing—they aren’t going to be able to afford to do it.”

Seven-figure bidding wars still break out over potential blockbusters, even though these battles often turn out to be follies. The quest for publishing profits in an economy of scarcity drives the money toward a few big books. So does the gradual disappearance of book reviewers and knowledgeable booksellers, whose enthusiasm might have rescued a book from drowning in obscurity. When consumers are overwhelmed with choices, some experts argue, they all tend to buy the same well-known thing.

These trends point toward what the literary agent called “the rich getting richer, the poor getting poorer.” A few brand names at the top, a mass of unwashed titles down below, the middle hollowed out: the book business in the age of Amazon mirrors the widening inequality of the broader economy.

“If they did, in my opinion they would save the industry. They’d lose thirty per cent of their sales, but they would have an additional thirty per cent for every copy they sold, because they’d be selling directly to consumers. The industry thinks of itself as Procter & Gamble*. What gave publishers the idea that this was some big goddam business? It’s not—it’s a tiny little business, selling to a bunch of odd people who read.”

Bezos is right: gatekeepers are inherently élitist, and some of them have been weakened, in no small part, because of their complacency and short-term thinking. But gatekeepers are also barriers against the complete commercialization of ideas, allowing new talent the time to develop and learn to tell difficult truths. When the last gatekeeper but one is gone, will Amazon care whether a book is any good? ♦

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

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

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

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

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

On Tinder, there are no questionnaires to fill out. No discussion of your favorite hiking trail, star sign or sexual proclivities. You simply log in through Facebook, pick a few photos that best describe “you” and start swiping.It may seem that what happens next is predictable (the best-looking people draw the most likes, the rest are quickly dismissed), but relationships experts for Tinder say there is something entirely different going on.

“Research shows when people are evaluating photos of others, they are trying to access compatibility on not just a physical level, but a social level,” said Jessica Carbino, Tinder’s in-house dating and relationship expert. “They are trying to understand, ‘Do I have things in common with this person?' ”

She discovered that Tinder users decoded an array of subtle and not-so-subtle traits before deciding which way to swipe. For example, the style of clothing, the pucker of the lips and even the posture, Ms. Carbino said, tell us a lot about their social circle, if they like to party and their level of confidence.

Men also judge attractiveness on factors beyond just anatomy, though in general, men are nearly three times as likely to swipe “like” (in 46 percent of cases) than woman (14 percent).

“There is this idea that attraction stems from a very superficial outlook on people, which is false,” Mr. Rad said. “Everyone is able to pick up thousands of signals in these photos. A photo of a guy at a bar with friends around him sends a very different message than a photo of a guy with a dog on the beach.”

while computers have become incalculably smarter, the ability of machines and algorithms to match people has remained just as clueless in the view of independent scientists.

dating sites like eHarmony and Match.com are more like modern snake oil. “They are a joke, and there is no relationship scientist that takes them seriously as relationship science.”

Mr. Finkel worked for more than a year with a group of researchers trying to understand how these algorithm-based dating services could match people, as they claim to do. The team poured through more than 80 years of scientific research about dating and attraction, and was unable to prove that computers can indeed match people together.

some dating sites are starting to acknowledge that the only thing that matters when matching lovers is someone’s picture. Earlier this year, OKCupid examined its data and found that a person’s profile picture is, said a post on its Oktrends blog, “worth that fabled thousand words, but your actual words are worth... almost nothing.”

this doesn’t mean that the most attractive people are the only ones who find true love. Indeed, in many respects, it can be the other way around.

a graduate student, published a paper noting that a person’s unique looks are what is most important when trying to find a mate.

“There isn’t a consensus about who is attractive and who isn’t,” Mr. Eastwick said in an interview. “Someone that you think is especially attractive might not be to me. That’s true with photos, too.” Tinder’s data team echoed this, noting that there isn’t a cliquey, high school mentality on the site, where one group of users get the share of “like” swipes.

But the students also described a sense of loss.

A 15-year-old boy told me that someday he wanted to raise a family, not the way his parents are raising him (with phones out during meals and in the park and during his school sports events) but the way his parents think they are raising him — with no phones at meals and plentiful family conversation. One college junior tried to capture what is wrong about life in his generation. “Our texts are fine,” he said. “It’s what texting does to our conversations when we are together that’s the problem.”

One teacher observed that the students “sit in the dining hall and look at their phones. When they share things together, what they are sharing is what is on their phones.” Is this the new conversation? If so, it is not doing the work of the old conversation. The old conversation taught empathy. These students seem to understand each other less.

In 2010, a team at the University of Michigan led by the psychologist Sara Konrath put together the findings of 72 studies that were conducted over a 30-year period. They found a 40 percent decline in empathy among college students, with most of the decline taking place after 2000.

We’ve gotten used to being connected all the time, but we have found ways around conversation — at least from conversation that is open-ended and spontaneous, in which we play with ideas and allow ourselves to be fully present and vulnerable. But it is in this type of conversation — where we learn to make eye contact, to become aware of another person’s posture and tone, to comfort one another and respectfully challenge one another — that empathy and intimacy flourish. In these conversations, we learn who we are.

the trend line is clear. It’s not only that we turn away from talking face to face to chat online. It’s that we don’t allow these conversations to happen in the first place because we keep our phones in the landscape.

It’s a powerful insight. Studies of conversation both in the laboratory and in natural settings show that when two people are talking, the mere presence of a phone on a table between them or in the periphery of their vision changes both what they talk about and the degree of connection they feel. People keep the conversation on topics where they won’t mind being interrupted. They don’t feel as invested in each other. Even a silent phone disconnects us.

we have put this virtuous circle in peril. We turn time alone into a problem that needs to be solved with technology.

At a nightly cabin chat, a group of 14-year-old boys spoke about a recent three-day wilderness hike. Not that many years ago, the most exciting aspect of that hike might have been the idea of roughing it or the beauty of unspoiled nature. These days, what made the biggest impression was being phoneless. One boy called it “time where you have nothing to do but think quietly and talk to your friends.” The campers also spoke about their new taste for life away from the online feed. Their embrace of the virtue of disconnection suggests a crucial connection: The capacity for empathic conversation goes hand in hand with the capacity for solitude.

In solitude we find ourselves; we prepare ourselves to come to conversation with something to say that is authentic, ours. If we can’t gather ourselves, we can’t recognize other people for who they are. If we are not content to be alone, we turn others into the people we need them to be. If we don’t know how to be alone, we’ll only know how to be lonely.

Yalda T. Uhls was the lead author on a 2014 study of children at a device-free outdoor camp. After five days without phones or tablets, these campers were able to read facial emotions and correctly identify the emotions of actors in videotaped scenes significantly better than a control group. What fostered these new empathic responses? They talked to one another. In conversation, things go best if you pay close attention and learn how to put yourself in someone else’s shoes. This is easier to do without your phone in hand. Conversation is the most human and humanizing thing that we do.

People sometimes say to me that they can see how one might be disturbed when people turn to their phones when they are together. But surely there is no harm when people turn to their phones when they are by themselves? If anything, it’s our new form of being together.

But this way of dividing things up misses the essential connection between solitude and conversation. In solitude we learn to concentrate and imagine, to listen to ourselves. We need these skills to be fully present in conversation.

One start toward reclaiming conversation is to reclaim solitude. Some of the most crucial conversations you will ever have will be with yourself. Slow down sufficiently to make this possible. And make a practice of doing one thing at a time. Think of unitasking as the next big thing. In every domain of life, it will increase performance and decrease stress.

Multitasking comes with its own high, but when we chase after this feeling, we pursue an illusion. Conversation is a human way to practice unitasking.

Our phones are not accessories, but psychologically potent devices that change not just what we do but who we are. A second path toward conversation involves recognizing the degree to which we are vulnerable to all that connection offers. We have to commit ourselves to designing our products and our lives to take that vulnerability into account.

We can choose not to carry our phones all the time. We can park our phones in a room and go to them every hour or two while we work on other things or talk to other people. We can carve out spaces at home or work that are device-free, sacred spaces for the paired virtues of conversation and solitude.

Families can find these spaces in the day to day — no devices at dinner, in the kitchen and in the car.

Engineers are ready with more ideas: What if our phones were not designed to keep us attached, but to do a task and then release us? What if the communications industry began to measure the success of devices not by how much time consumers spend on them but by whether it is time well spent?

The young woman who is so clear about the seven minutes that it takes to see where a conversation is going admits that she often doesn’t have the patience to wait for anything near that kind of time before going to her phone. In this she is characteristic of what the psychologists Howard Gardner and Katie Davis called the “app generation,” which grew up with phones in hand and apps at the ready. It tends toward impatience, expecting the world to respond like an app, quickly and efficiently. The app way of thinking starts with the idea that actions in the world will work like algorithms: Certain actions will lead to predictable results.

This attitude can show up in friendship as a lack of empathy. Friendships become things to manage; you have a lot of them, and you come to them with tools

here is a first step: To reclaim conversation for yourself, your friendships and society, push back against viewing the world as one giant app. It works the other way, too: Conversation is the antidote to the algorithmic way of looking at life because it teaches you about fluidity, contingency and personality.

We have time to make corrections and remember who we are — creatures of history, of deep psychology, of complex relationships, of conversations, artless, risky and face to face.

when students become stuck on a problem, they are often too eager to throw up their hands in frustration, rather than buckle down and try to think creatively (in the words of Dan Meyer, students often lack patient problem solving skills).  Many students don't even think of mathematics as a subject that requires creativity

a website called Math Goes Pop!.

David Marr, a neuroscientist colleague of Chomsky's at MIT, defined a general framework for studying complex biological systems (like the brain) in his influential book Vision,

a complex biological system can be understood at three distinct levels. The first level ("computational level") describes the input and output to the system, which define the task the system is performing. In the case of the visual system, the input might be the image projected on our retina and the output might our brain's identification of the objects present in the image we had observed. The second level ("algorithmic level") describes the procedure by which an input is converted to an output, i.e. how the image on our retina can be processed to achieve the task described by the computational level. Finally, the third level ("implementation level") describes how our own biological hardware of cells implements the procedure described by the algorithmic level.

The emphasis here is on the internal structure of the system that enables it to perform a task, rather than on external association between past behavior of the system and the environment. The goal is to dig into the "black box" that drives the system and describe its inner workings, much like how a computer scientist would explain how a cleverly designed piece of software works and how it can be executed on a desktop computer.

As written today, the history of cognitive science is a story of the unequivocal triumph of an essentially Chomskyian approach over Skinner's behaviorist paradigm -- an achievement commonly referred to as the "cognitive revolution,"

While this may be a relatively accurate depiction in cognitive science and psychology, behaviorist thinking is far from dead in related disciplines. Behaviorist experimental paradigms and associationist explanations for animal behavior are used routinely by neuroscientists

Chomsky critiqued the field of AI for adopting an approach reminiscent of behaviorism, except in more modern, computationally sophisticated form. Chomsky argued that the field's heavy use of statistical techniques to pick regularities in masses of data is unlikely to yield the explanatory insight that science ought to offer. For Chomsky, the "new AI" -- focused on using statistical learning techniques to better mine and predict data -- is unlikely to yield general principles about the nature of intelligent beings or about cognition.

Chomsky acknowledged that the statistical approach might have practical value, just as in the example of a useful search engine, and is enabled by the advent of fast computers capable of processing massive data. But as far as a science goes, Chomsky would argue it is inadequate, or more harshly, kind of shallow