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Qualcomm is one of the few American leaders in developing standards and patents for 5G, the next generation of wireless technology that should be fast enough to enable self-driving cars and other innovations. The CFIUS letter said a weakened Qualcomm could strengthen Chinese rivals, specifically Huawei Technologies Co., the world’s top cellular-equipment maker and a leading smartphone brand.

Washington has taken unusual steps to hinder Huawei’s business in the U.S., concerned that Beijing could force the company to exploit its understanding of the equipment to spy or disable telecom networks.

Many European wireless carriers, including British-based Vodafone Group PLC, praise Huawei’s equipment, saying it is often cheaper and more advanced that those of its competitors. That is another big worry for Washington.

board and senior management team are American. “It’s barely a foreign company now, but politics and logic aren’t often friends,” said Stacy Rasgon, a Bernstein Research analyst. “I’m just not convinced that Qualcomm’s going to slash and burn the 5G roadmap and leave it open to Huawei” if Broadcom buys it.

Success would be a needed boost for the struggling conglomerate, which is in the middle of restructuring and said last week it would overhaul its board. GE is seeking access to a market that Navigant Research predicts will generate tens of billions of dollars in revenue in the next decade or so.

Prices of lithium-ion batteries have dropped sharply in recent years, as they have become ubiquitous in products such as laptops and smartphones, improving the economies of scale of manufacturing. That is start

GE is hoping to change that with the Reservoir platform. GE says the Reservoir battery can last about 15% longer than the best batteries currently on the market and can be installed quicker.

Alexa and Her CounterpartsAlexa, Amazon’s intelligent assistant that listens to your voice commands to play music, order diapers and place a phone call, will be everywhere at CES.

Smart CitiesNowadays, it’s easy to shop for high-quality internet-connected home accessories, like light bulbs, thermostats and security cameras. At CES, Samsung is even planning to introduce a smart refrigerator at the electronics show that can listen to voice commands to control other home accessories.

Smarter CarsSelf-driving-car enthusiasts like Elon Musk, the chief executive of Tesla, dream of a future where driverless cars eliminate traffic accidents while letting people do work on their commutes.They can keep dreaming: Autonomous vehicles still have a long way to go before they become safe and properly regulated.

Next-Generation Wireless TechnologyAs a growing number of devices rely on artificial intelligence, they will require faster bandwidth speeds. At CES, wireless companies like AT&T and Verizon are expected to give progress reports on so-called 5G, the fifth-generation network technology.With 5G, wireless carriers envision an era of incredibly fast speeds that let smartphone users download a movie in less than five seconds — roughly 100 times faster than the current network technology, 4G. Even more important, 5G is expected to greatly reduce latency to let devices communicate with each other with extremely fast response times.

Being distracted by the second task didn’t hurt actual performance on the first task, but it did impair the subjects’ ability to be introspective (again, by accurately self-reporting how they did). The finding supports previous widespread evidence that multitasking leads to lower cognitive performance.

But our solipsism is frequently given outward expression rather than inward exploration, with more emphasis than ever before on images.

“That hints at the way that, as our technologies increase the intensity of stimulation and the flow of new things, we adapt to that pace,” Mr. Carr said. “We become less patient. When moments without stimulation arise, we start to feel panicked and don’t know what to do with them, because we’ve trained ourselves to expect this stimulation — new notifications and alerts and so on.”

Mr. Carr also noted counterarguments: Formulating relatively simple thoughts on the internet can yield more complex ones through real-time exchanges with others, and people whose reflex is to post a notion hastily rather than let it sit may not have been the most deliberative thinkers in a pre-smartphone time, either.

“We’ve adopted the Google ideal of the mind, which is that you have a question that you can answer quickly: close-ended, well-defined questions. Lost in that conception is that there’s also this open-ended way of thinking where you’re not always trying to answer a question. You’re trying to go where that thought leads you. As a society, we’re saying that that way of thinking isn’t as important anymore. It’s viewed as inefficient.”

Instead, it is their contribution to the spread of misinformation, hate speech and conspiracy theories.

digital platforms, since the marginal cost of serving additional consumers is essentially zero. Because the initial costs of producing a platform’s content are substantial, and because any company’s first goal is to remain solvent, it cannot just give stuff away. Even so, when price exceeds marginal cost, competition relentlessly pressures rival publishers to cut prices — eventually all the way to zero. This, in a nutshell, is the publisher’s dilemma in the digital age.

These firms make money not by charging for access to content but by displaying it with finely targeted ads based on the specific types of things people have already chosen to view. If the conscious intent were to undermine social and political stability, this business model could hardly be a more effective weapon.

The algorithms that choose individual-specific content are crafted to maximize the time people spend on a platform

As the developers concede, Facebook’s algorithms are addictive by design and exploit negative emotional triggers. Platform addiction drives earnings, and hate speech, lies and conspiracy theories reliably boost addiction.

the subscription model isn’t fully efficient: Any positive fee would inevitably exclude at least some who would value access but not enough to pay the fee

a conservative think tank, says, for example, that government has no business second-guessing people’s judgments about what to post or read on social media.

That position would be easier to defend in a world where individual choices had no adverse impact on others. But negative spillover effects are in fact quite common

individual and collective incentives about what to post or read on social media often diverge sharply.

There is simply no presumption that what spreads on these platforms best serves even the individual’s own narrow interests, much less those of society as a whole.

a simpler step may hold greater promise: Platforms could be required to abandon that model in favor of one relying on subscriptions, whereby members gain access to content in return for a modest recurring fee.

Major newspapers have done well under this model, which is also making inroads in book publishing. The subscription model greatly weakens the incentive to offer algorithmically driven addictive content provided by individuals, editorial boards or other sources.

Careful studies have shown that Facebook’s algorithms have increased political polarization significantly

More worrisome, those excluded would come disproportionately from low-income groups. Such objections might be addressed specifically — perhaps with a modest tax credit to offset subscription fees — or in a more general way, by making the social safety net more generous.

Adam Smith, the 18th-century Scottish philosopher widely considered the father of economics, is celebrated for his “invisible hand” theory, which describes conditions under which market incentives promote socially benign outcomes. Many of his most ardent admirers may view steps to constrain the behavior of social media platforms as regulatory overreach.

But Smith’s remarkable insight was actually more nuanced: Market forces often promote society’s welfare, but not always. Indeed, as he saw clearly, individual interests are often squarely at odds with collective aspirations, and in many such instances it is in society’s interest to intervene. The current information crisis is a case in point.

“We want to be very clear that all we are reporting is observation of an excess (a fairly significant one) and not a discovery of any kind,”

“I’m trying to be calm here, but it’s hard not to be hyperbolic,” said Neal Weiner, a particle theorist at New York University. “If this is real, calling it a game changer would be an understatement.”

Dr. Aprile’s Xenon experiment is currently the largest and most sensitive in an alphabet soup of efforts aimed at detecting and identifying dark matter

The best guess is that this dark matter consists of clouds of exotic subatomic particles left over from the Big Bang and known generically as WIMPs, for weakly interacting massive particles, hundreds or thousands of times more massive than a hydrogen atom.

The story of axions begins in 1977, when Roberto Peccei, a professor at the University of California, Los Angeles, who died on June 1, and Helen Quinn, emerita professor at Stanford, suggested a slight modification to the theory that governs strong nuclear forces, making sure that it is invariant to the direction of time, a feature that physicists consider a necessity for the universe.

in its most recent analysis of that experiment, the team had looked for electrons, rather than the heavier xenon nuclei, recoiling from collisions. Among other things, that could be the signature of particles much lighter than the putative WIMPs striking the xenon.

Simulations and calculations suggested that random events should have produced about 232 such recoils over the course of a year.

But from February 2017 to February 2018, the detector recorded 285, an excess of 53 recoils.

Dr. Aprile and her colleagues have wired a succession of vats containing liquid xenon with photomultipliers and other sensors. The hope is that her team’s device — far underground to shield it from cosmic rays and other worldly forms of interference — would spot the rare collision between a WIMP and a xenon atom. The collision should result in a flash of light and a cloud of electrical charge.

this modification implied the existence of a new subatomic particle. Dr. Wilczek called it the axion, and the name stuck.

Axions have never been detected either directly or indirectly. And the theory does not predict their mass, which makes it hard to look for them. It only predicts that they would be weird and would barely interact with regular matter

although they are not WIMPS, they share some of those particles’ imagined weird abilities, such as being able to float through Earth and our bodies like smoke through a screen door.

In order to fulfill the requirements of cosmologists, however, such dark-matter axions would need to have a mass of less than a thousandth of an electron volt in the units of mass and energy preferred by physicists

(By comparison, the electrons that dance around in your smartphone weigh in at half a million electron volts each.) What they lack in heft they would more than make up for in numbers.

That would make individual cosmic dark-matter axions too slow and ethereal to be detected by the Xenon experiment.But axions could also be produced by nuclear reactions in the sun, and those “solar axions” would have enough energy to ping the Xenon detector right where it is most sensitive

The other exciting, though slightly less likely, possibility is that the Xenon collaboration’s excess signals come from the wispy particles known as neutrinos, which are real, and weird, and zipping through our bodies by the trillions every second.

Ordinarily, these neutrinos would not contribute much to the excess of events the detector read. But they would do so if they had an intrinsic magnetism that physicists call a magnetic moment. That would give them a higher probability of interacting with the xenon and tripping the detector

According to the standard lore, neutrinos, which are electrically neutral, do not carry magnetism. The discovery that they did would require rewriting the rules as they apply to neutrinos.

That, said Dr. Weiner, would be “a very very big deal,” because it would imply that there are new fundamental particles out there to look for — new physics.

The result has been a hidden revolution in how information is produced, circulated and acted upon

The world’s liberal democracies now confront a tragedy of the “un-commons.” Information spaces that people assume to be public are strictly ruled by private commercial interests for maximum profit.

The internet as a self-regulating market has been revealed as a failed experiment. Surveillance capitalism leaves a trail of social wreckage in its wake: the wholesale destruction of privacy, the intensification of social inequality, the poisoning of social discourse with defactualized information, the demolition of social norms and the weakening of democratic institutions.

These social harms are not random. They are tightly coupled effects of evolving economic operations. Each harm paves the way for the next and is dependent on what went before.

There is no way to escape the machine systems that surveil u

All roads to economic and social participation now lead through surveillance capitalism’s profit-maximizing institutional terrain, a condition that has intensified during nearly two years of global plague.

Will Facebook’s digital violence finally trigger our commitment to take back the “un-commons”?

Will we confront the fundamental but long ignored questions of an information civilization: How should we organize and govern the information and communication spaces of the digital century in ways that sustain and advance democratic values and principles?

Mark Zuckerberg’s start-up did not invent surveillance capitalism. Google did that. In 2000, when only 25 percent of the world’s information was stored digitally, Google was a tiny start-up with a great search product but little revenue.

By 2001, in the teeth of the dot-com bust, Google’s leaders found their breakthrough in a series of inventions that would transform advertising. Their team learned how to combine massive data flows of personal information with advanced computational analyses to predict where an ad should be placed for maximum “click through.”

Google’s scientists learned how to extract predictive metadata from this “data exhaust” and use it to analyze likely patterns of future behavior.

Prediction was the first imperative that determined the second imperative: extraction.

Lucrative predictions required flows of human data at unimaginable scale. Users did not suspect that their data was secretly hunted and captured from every corner of the internet and, later, from apps, smartphones, devices, cameras and sensors

User ignorance was understood as crucial to success. Each new product was a means to more “engagement,” a euphemism used to conceal illicit extraction operations.

When asked “What is Google?” the co-founder Larry Page laid it out in 2001,

“Storage is cheap. Cameras are cheap. People will generate enormous amounts of data,” Mr. Page said. “Everything you’ve ever heard or seen or experienced will become searchable. Your whole life will be searchable.”

Instead of selling search to users, Google survived by turning its search engine into a sophisticated surveillance medium for seizing human data

Company executives worked to keep these economic operations secret, hidden from users, lawmakers, and competitors. Mr. Page opposed anything that might “stir the privacy pot and endanger our ability to gather data,” Mr. Edwards wrote.

As recently as 2017, Eric Schmidt, the executive chairman of Google’s parent company, Alphabet, acknowledged the role of Google’s algorithmic ranking operations in spreading corrupt information. “There is a line that we can’t really get across,” he said. “It is very difficult for us to understand truth.” A company with a mission to organize and make accessible all the world’s information using the most sophisticated machine systems cannot discern corrupt information.

This is the economic context in which disinformation wins

In March 2008, Mr. Zuckerberg hired Google’s head of global online advertising, Sheryl Sandberg, as his second in command. Ms. Sandberg had joined Google in 2001 and was a key player in the surveillance capitalism revolution. She led the build-out of Google’s advertising engine, AdWords, and its AdSense program, which together accounted for most of the company’s $16.6 billion in revenue in 2007.

A Google multimillionaire by the time she met Mr. Zuckerberg, Ms. Sandberg had a canny appreciation of Facebook’s immense opportunities for extraction of rich predictive data. “We have better information than anyone else. We know gender, age, location, and it’s real data as opposed to the stuff other people infer,” Ms. Sandberg explained

The company had “better data” and “real data” because it had a front-row seat to what Mr. Page had called “your whole life.”

Facebook paved the way for surveillance economics with new privacy policies in late 2009. The Electronic Frontier Foundation warned that new “Everyone” settings eliminated options to restrict the visibility of personal data, instead treating it as publicly available information.

Mr. Zuckerberg “just went for it” because there were no laws to stop him from joining Google in the wholesale destruction of privacy. If lawmakers wanted to sanction him as a ruthless profit-maximizer willing to use his social network against society, then 2009 to 2010 would have been a good opportunity.

Facebook was the first follower, but not the last. Google, Facebook, Amazon, Microsoft and Apple are private surveillance empires, each with distinct business models.

In 2021 these five U.S. tech giants represent five of the six largest publicly traded companies by market capitalization in the world.

As we move into the third decade of the 21st century, surveillance capitalism is the dominant economic institution of our time. In the absence of countervailing law, this system successfully mediates nearly every aspect of human engagement with digital information

Today all apps and software, no matter how benign they appear, are designed to maximize data collection.

Historically, great concentrations of corporate power were associated with economic harms. But when human data are the raw material and predictions of human behavior are the product, then the harms are social rather than economic

The difficulty is that these novel harms are typically understood as separate, even unrelated, problems, which makes them impossible to solve. Instead, each new stage of harm creates the conditions for the next stage.

Fifty years ago the conservative economist Milton Friedman exhorted American executives, “There is one and only one social responsibility of business — to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game.” Even this radical doctrine did not reckon with the possibility of no rules.

With privacy out of the way, ill-gotten human data are concentrated within private corporations, where they are claimed as corporate assets to be deployed at will.

The sheer size of this knowledge gap is conveyed in a leaked 2018 Facebook document, which described its artificial intelligence hub, ingesting trillions of behavioral data points every day and producing six million behavioral predictions each second.

Next, these human data are weaponized as targeting algorithms, engineered to maximize extraction and aimed back at their unsuspecting human sources to increase engagement

Targeting mechanisms change real life, sometimes with grave consequences. For example, the Facebook Files depict Mr. Zuckerberg using his algorithms to reinforce or disrupt the behavior of billions of people. Anger is rewarded or ignored. News stories become more trustworthy or unhinged. Publishers prosper or wither. Political discourse turns uglier or more moderate. People live or die.

Occasionally the fog clears to reveal the ultimate harm: the growing power of tech giants willing to use their control over critical information infrastructure to compete with democratically elected lawmakers for societal dominance.

when it comes to the triumph of surveillance capitalism’s revolution, it is the lawmakers of every liberal democracy, especially in the United States, who bear the greatest burden of responsibility. They allowed private capital to rule our information spaces during two decades of spectacular growth, with no laws to stop it.

All of it begins with extraction. An economic order founded on the secret massive-scale extraction of human data assumes the destruction of privacy as a nonnegotiable condition of its business operations.

We can’t fix all our problems at once, but we won’t fix any of them, ever, unless we reclaim the sanctity of information integrity and trustworthy communications

The abdication of our information and communication spaces to surveillance capitalism has become the meta-crisis of every republic, because it obstructs solutions to all other crises.

Neither Google, nor Facebook, nor any other corporate actor in this new economic order set out to destroy society, any more than the fossil fuel industry set out to destroy the earth.

like global warming, the tech giants and their fellow travelers have been willing to treat their destructive effects on people and society as collateral damage — the unfortunate but unavoidable byproduct of perfectly legal economic operations that have produced some of the wealthiest and most powerful corporations in the history of capitalism.

Where does that leave us?

Democracy is the only countervailing institutional order with the legitimate authority and power to change our course. If the ideal of human self-governance is to survive the digital century, then all solutions point to one solution: a democratic counterrevolution.

instead of the usual laundry lists of remedies, lawmakers need to proceed with a clear grasp of the adversary: a single hierarchy of economic causes and their social harms.

We can’t rid ourselves of later-stage social harms unless we outlaw their foundational economic causes

This means we move beyond the current focus on downstream issues such as content moderation and policing illegal content. Such “remedies” only treat the symptoms without challenging the illegitimacy of the human data extraction that funds private control over society’s information spaces

Similarly, structural solutions like “breaking up” the tech giants may be valuable in some cases, but they will not affect the underlying economic operations of surveillance capitalism.

Instead, discussions about regulating big tech should focus on the bedrock of surveillance economics: the secret extraction of human data from realms of life once called “private.

No secret extraction means no illegitimate concentrations of knowledge about people. No concentrations of knowledge means no targeting algorithms. No targeting means that corporations can no longer control and curate information flows and social speech or shape human behavior to favor their interests

the sober truth is that we need lawmakers ready to engage in a once-a-century exploration of far more basic questions:

How should we structure and govern information, connection and communication in a democratic digital century?

What new charters of rights, legislative frameworks and institutions are required to ensure that data collection and use serve the genuine needs of individuals and society?

What measures will protect citizens from unaccountable power over information, whether it is wielded by private companies or governments?

The corporation that is Facebook may change its name or its leaders, but it will not voluntarily change its economics.

when Mr. Nichol tweaked his requests a little, adding or subtracting a few words here or there, it provided what he wanted. When he asked for “a piano in a living room filled with sand,” the image looked more like a beach in a living room.

DALL-E is what artificial intelligence researchers call a neural network, which is a mathematical system loosely modeled on the network of neurons in the brain.

the same technology that recognizes the commands spoken into smartphones and identifies the presence of pedestrians as self-driving cars navigate city streets.

A neural network learns skills by analyzing large amounts of data. By pinpointing patterns in thousands of avocado photos, for example, it can learn to recognize an avocado.

DALL-E looks for patterns as it analyzes millions of digital images as well as text captions that describe what each image depicts. In this way, it learns to recognize the links between the images and the words.

"When we innovate, we have to depart from existing solutions and come up with new ideas by drawing broadly from our knowledge. Coming up with alternative ways to use known objects requires the same psychological process," she explained.

Researchers also used eye-tracking software, which found that virtual participants spent more time looking directly at their partner, as opposed to gazing around the room.

"This visual focus on the screen narrows cognition. In other words, people are more focused when interacting on video, which hurts the broad, expansive idea generation process," Brucks said.

"Objects in the room can prompt new associations easier than trying to generate them all internally,"

"The field study shows that the negative effects of videoconferencing on idea generation is not limited to simplistic tasks and can play out in more complicated and high-tech brainstorming sessions as well," she said.

The study found that videoconferencing didn't hinder all collaborative work

However, she said it was a mistake to conclude that creativity and videoconferencing are incompatible.

"Perhaps many of us make friends faster in person than over Zoom, and creativity flourishes when we're relaxed. But when Zooming from home, people are probably more relaxed than when in an experiment," she added.

"I wouldn't want to see a company double their in-person meetings hoping to improve their innovation, if this also means doubling the commute time resulting in less happy -- and perhaps less creative -- employees."

Except, all I do all day is tap icons with red dots like a digital version of whack-a-mole, trying to get rid of all the notifications. Research has shown that this constant stimulation on our devices raises the dopamine in our brains, which basically means they are like drugs. 

It's hard to be productive when you stop to look at your phone every 10-12 minutes.

It's true, technology has allowed us to do some pretty incredible things. I can't argue with the fact that it has allowed us to solve problems that were previously insurmountable, but at a very basic level, all of this smart technology has made us dumb. Mostly, I think it's because of how much we now depend on it for even the most basic things. 

Here's the thing. If you don't use a muscle, after a while you'll lose it.  Sure, it's not technically a muscle, but if you stop using your brain because your watch tells you when it's time to go to a meeting, or stand up, or use the bathroom-- can we at least agree you're not getting any smarter? The more we hand over to machines what makes us unique as humans--our ability to think, process, and make decisions--the less we stretch and grow our capacity to do those things. 

Have you ever sat in a restaurant and looked around? Of course not, the last time you were in a restaurant you were busy looking at your phone. But if you had, you would have seen a bunch of other people who were doing the same thing. A room full of people, all sitting at tables with presumably other people they know and have some level of affection for, staring at an illuminated screen. 

But it has also increased the space in our relationships to the point where we don't talk, we Slack.

igital conversations are very different than real-world conversations. When smart technology helps remove barriers to communication, that's a good thing. But when we substitute technology for relationships and real conversations, it has real-world consequences.

a “web 2.0” revolution in “user-generated content,” offering easy-to-use, easily adopted tools on websites and then mobile apps. They were built for creating and sharing “content,”

As the original name suggested, social networking involved connecting, not publishing. By connecting your personal network of trusted contacts (or “strong ties,” as sociologists call them) to others’ such networks (via “weak ties”), you could surface a larger network of trusted contacts

The whole idea of social networks was networking: building or deepening relationships, mostly with people you knew. How and why that deepening happened was largely left to the users to decide.

That changed when social networking became social media around 2009, between the introduction of the smartphone and the launch of Instagram. Instead of connection—forging latent ties to people and organizations we would mostly ignore—social media offered platforms through which people could publish content as widely as possible, well beyond their networks of immediate contacts.

Social media turned you, me, and everyone into broadcasters (if aspirational ones). The results have been disastrous but also highly pleasurable, not to mention massively profitable—a catastrophic combination.

A social network is an idle, inactive system—a Rolodex of contacts, a notebook of sales targets, a yearbook of possible soul mates. But social media is active—hyperactive, really—spewing material across those networks instead of leaving them alone until needed.

The authors propose social media as a system in which users participate in “information exchange.” The network, which had previously been used to establish and maintain relationships, becomes reinterpreted as a channel through which to broadcast.

The toxicity of social media makes it easy to forget how truly magical this innovation felt when it was new. From 2004 to 2009, you could join Facebook and everyone you’d ever known—including people you’d definitely lost track of—was right there, ready to connect or reconnect. The posts and photos I saw characterized my friends’ changing lives, not the conspiracy theories that their unhinged friends had shared with them

Twitter, which launched in 2006, was probably the first true social-media site, even if nobody called it that at the time. Instead of focusing on connecting people, the site amounted to a giant, asynchronous chat room for the world. Twitter was for talking to everyone—which is perhaps one of the reasons journalists have flocked to it

on Twitter, anything anybody posted could be seen instantly by anyone else. And furthermore, unlike posts on blogs or images on Flickr or videos on YouTube, tweets were short and low-effort, making it easy to post many of them a week or even a day.

soon enough, all social networks became social media first and foremost. When groups, pages, and the News Feed launched, Facebook began encouraging users to share content published by others in order to increase engagement on the service, rather than to provide updates to friends. LinkedIn launched a program to publish content across the platform, too. Twitter, already principally a publishing platform, added a dedicated “retweet” feature, making it far easier to spread content virally across user networks.

When we look back at this moment, social media had already arrived in spirit if not by name. RSS readers offered a feed of blog posts to catch up on, complete with unread counts. MySpace fused music and chatter; YouTube did it with video (“Broadcast Yourself”)

From being asked to review every product you buy to believing that every tweet or Instagram image warrants likes or comments or follows, social media produced a positively unhinged, sociopathic rendition of human sociality.

Other services arrived or evolved in this vein, among them Reddit, Snapchat, and WhatsApp, all far more popular than Twitter. Social networks, once latent routes for possible contact, became superhighways of constant content

Although you can connect the app to your contacts and follow specific users, on TikTok, you are more likely to simply plug into a continuous flow of video content that has oozed to the surface via algorithm.

In the social-networking era, the connections were essential, driving both content creation and consumption. But the social-media era seeks the thinnest, most soluble connections possible, just enough to allow the content to flow.

This is also why journalists became so dependent on Twitter: It’s a constant stream of sources, events, and reactions—a reporting automat, not to mention an outbound vector for media tastemakers to make tastes.

“influencer” became an aspirational role, especially for young people for whom Instagram fame seemed more achievable than traditional celebrity—or perhaps employment of any kind.

social-media operators discovered that the more emotionally charged the content, the better it spread across its users’ networks. Polarizing, offensive, or just plain fraudulent information was optimized for distribution. By the time the platforms realized and the public revolted, it was too late to turn off these feedback loops.

The ensuing disaster was multipar

Rounding up friends or business contacts into a pen in your online profile for possible future use was never a healthy way to understand social relationships.

when social networking evolved into social media, user expectations escalated. Driven by venture capitalists’ expectations and then Wall Street’s demands, the tech companies—Google and Facebook and all the rest—became addicted to massive scale

Social media showed that everyone has the potential to reach a massive audience at low cost and high gain—and that potential gave many people the impression that they deserve such an audience.

On social media, everyone believes that anyone to whom they have access owes them an audience: a writer who posted a take, a celebrity who announced a project, a pretty girl just trying to live her life, that anon who said something afflictive

When network connections become activated for any reason or no reason, then every connection seems worthy of traversing.

people just aren’t meant to talk to one another this much. They shouldn’t have that much to say, they shouldn’t expect to receive such a large audience for that expression, and they shouldn’t suppose a right to comment or rejoinder for every thought or notion either.

Facebook and all the rest enjoyed a massive rise in engagement and the associated data-driven advertising profits that the attention-driven content economy created. The same phenomenon also created the influencer economy, in which individual social-media users became valuable as channels for distributing marketing messages or product sponsorships by means of their posts’ real or imagined reach

That’s no surprise, I guess, given that the model was forged in the fires of Big Tech companies such as Facebook, where sociopathy is a design philosophy.

If change is possible, carrying it out will be difficult, because we have adapted our lives to conform to social media’s pleasures and torments. It’s seemingly as hard to give up on social media as it was to give up smoking en masse

Quitting that habit took decades of regulatory intervention, public-relations campaigning, social shaming, and aesthetic shifts. At a cultural level, we didn’t stop smoking just because the habit was unpleasant or uncool or even because it might kill us. We did so slowly and over time, by forcing social life to suffocate the practice. That process must now begin in earnest for social media.

Something may yet survive the fire that would burn it down: social networks, the services’ overlooked, molten core. It was never a terrible idea, at least, to use computers to connect to one another on occasion, for justified reasons, and in moderation

The problem came from doing so all the time, as a lifestyle, an aspiration, an obsession. The offer was always too good to be true, but it’s taken us two decades to realize the Faustian nature of the bargain.

when I first wrote about downscale, the ambition seemed necessary but impossible. It still feels unlikely—but perhaps newly plausible.

To win the soul of social life, we must learn to muzzle it again, across the globe, among billions of people. To speak less, to fewer people and less often–and for them to do the same to you, and everyone else as well

We cannot make social media good, because it is fundamentally bad, deep in its very structure. All we can do is hope that it withers away, and play our small part in helping abandon it.

Choosing the less-efficient way of doing something, especially things we do for pleasure, can help us reassess our relationship with time and forgo the constant need for productivity.

“When you show people deepfakes and generative AI, a lot of times they come out of the experiment saying, ‘I just don’t trust anything anymore,’” says David Rand, a professor at MIT Sloan who studies the creation, spread and impact of misinformation.

This problem, which has grown more acute in the age of generative AI, is known as the “liar’s dividend,

The combination of easily-generated fake content and the suspicion that anything might be fake allows people to choose what they want to believe, adds DiResta, leading to what she calls “bespoke realities.”

Examples of misleading content created by generative AI are not hard to come by, especially on social media

The signs that an image is AI-generated are easy to miss for a user simply scrolling past, who has an instant to decide whether to like or boost a post on social media. And as generative AI continues to improve, it’s likely that such signs will be harder to spot in the future.

“What our work suggests is that most regular people do not want to share false things—the problem is they are not paying attention,”

in the course of a lawsuit over the death of a man using Tesla’s “full self-driving” system, Elon Musk’s lawyers responded to video evidence of Musk making claims about this software by suggesting that the proliferation of “deepfakes” of Musk was grounds to dismiss such evidence. They advanced that argument even though the clip of Musk was verifiably real

are now using its existence as a pretext to dismiss accurate information

People’s attention is already limited, and the way social media works—encouraging us to gorge on content, while quickly deciding whether or not to share it—leaves us precious little capacity to determine whether or not something is true

If the crisis of authenticity were limited to social media, we might be able to take solace in communication with those closest to us. But even those interactions are now potentially rife with AI-generated fakes.

what sounds like a call from a grandchild requesting bail money may be scammers who have scraped recordings of the grandchild’s voice from social media to dupe a grandparent into sending money.

companies like Alphabet, the parent company of Google, are trying to spin the altering of personal images as a good thing. 

With its latest Pixel phone, the company unveiled a suite of new and upgraded tools that can automatically replace a person’s face in one image with their face from another, or quickly remove someone from a photo entirely.

Joseph Stalin, who was fond of erasing people he didn’t like from official photos, would have loved this technology.

In Google’s defense, it is adding a record of whether an image was altered to data attached to it. But such metadata is only accessible in the original photo and some copies, and is easy enough to strip out.

The rapid adoption of many different AI tools means that we are now forced to question everything that we are exposed to in any medium, from our immediate communities to the geopolitical, said Hany Farid, a professor at the University of California, Berkeley who

To put our current moment in historical context, he notes that the PC revolution made it easy to store and replicate information, the internet made it easy to publish it, the mobile revolution made it easier than ever to access and spread, and the rise of AI has made creating misinformation a cinch. And each revolution arrived faster than the one before it.

Not everyone agrees that arming the public with easy access to AI will exacerbate our current difficulties with misinformation. The primary argument of such experts is that there is already vastly more misinformation on the internet than a person can consume, so throwing more into the mix won’t make things worse.

it’s not exactly reassuring, especially given that trust in institutions is already at one of the lowest points in the past 70 years, according to the nonpartisan Pew Research Center, and polarization—a measure of how much we distrust one another—is at a high point.

“What happens when we have eroded trust in media, government, and experts?” says Farid. “If you don’t trust me and I don’t trust you, how do we respond to pandemics, or climate change, or have fair and open elections? This is how authoritarianism arises—when you erode trust in institutions.”

Using tech devices is addictive, and it's becoming more and more difficult to disengage with their technology.In fact, the average US adult spends more than 11 hours daily in the digital world

These days, we have a world of information at our fingertips via the internet. While this is useful, it does have some drawbacks. Entrepreneur Beth Haggerty said she finds that it "limits pure creative thought, at times, because we are developing habits to Google everything to quickly find an answer."

young adults who use seven to 11 social media platforms had more than three times the risk of depression and anxiety than those who use two or fewer platforms.

Another social skill that technology is helping to erode is young people's ability to read body language and nuance in face-to-face encounters.

Technology can have a negative impact on relationships, particularly when it affects how we communicate.One of the primary issues is that misunderstandings are much more likely to occur when communicating via text or email

Can you imagine doing your job without the help of technology of any kind? What about communicating? Or traveling? Or entertaining yourself?

Smartphone slouch. Desk slump. Text neck. Whatever you call it, the way we hold ourselves when we use devices like phones, computers, and tablets isn't healthy.

For centuries humans felt they were watched and judged by an all-seeing God who could condemn them to hell if they sinned heavily. The fear of divine punishment shaped private behaviour, applying a brake on some of our worst impulses.

it also seems sensible to assume that in the absence of an all-seeing deity threatening fire and brimstone, the brakes on devious or selfish behaviour in private will be eased, resulting in more “what’s the harm?” behaviour, more dabbling in the grey area between right and wrong, more secretive cruelty or casual selfishness.

Gradually, the fear of being watched by God and going to hell is being replaced by a fear of being recorded by technology and suffering the hell of public shame.

scandals might also act as a warning that in the age of the smartphone, the space for “getting away with it” has shrunk considerably.

The more I used my watch to monitor my stress, the higher my stress levels rose.

“It’s like you’re trying to win at this game instead of living your life. Instead of learning what your body feels like, you have a number.”

Add a social or competitive component, as in the fitness app Strava or the community features on Peloton, and the feelings of control and empowerment that fitness can foster can morph quickly into the opposite.

If it feels like an addiction, that’s because it can work similarly to smartphone and other digital addictions. Dependency is what these devices are designed to foster.

in fact, we very much can become compulsively fixated on these wearable devices — in a way that is akin to addiction.”

These devices don’t just record your behavior — they influence it and keep you coming back. You become dependent on external validation.

you can’t quantify your way to good health. The reality is much harder.

I know I got fitter. But I started to feel that my health wasn’t grounded in my own body anymore, or even in my mind.

Exercise wasn’t helping me rebound from pressure anymore; it was adding to it.

Of course these watches can be useful: for health data, reminding you to move more or maybe even that emergency call if you wind up falling in the woods. Many of us make better choices when we know we’re being watched.