Group items tagged

She showed that accounts of so-called “aces” — fighters said to have heroically held off much more powerful enemies with a single tank or plane — were based on propaganda.

In making these repairs, Coffman faced resistance from a group of editors who were mainly military buffs and wanted to write about battlefield valor without too much scrutiny. She, however, kept coming back to facts and sources — how do we know what we think we know? — and an insistence that Wikipedia not be swept up in mythology.

In a speech last year, Putin strolled through 1,000 years of battles and alliances to justify his claim of the “historical unity of Russians and Ukrainians.”

Just look at the rhetoric around Russian’s invasion of Ukraine, which Vladimir Putin has described as a battle to “de-Nazify” the leadership of Ukraine.

Since the Russian invasion, the English Wikipedia articles about the historical figures and topics Putin invoked have been racking up pop-star numbers.

When it comes to allegations about Nazi collaboration by prominent Ukrainian nationalists like Bandera, Wikipedia has pulled no punches. Even as Putin has emphasized these Nazi ties as a reason for his invasion, Wikipedia has resisted attempts to water down this history.

When Putin’s foreign minister, Sergei Lavrov, was asked how Ukraine could be in need of de-Nazification if its president, Volodymyr Zelensky, is Jewish, Lavrov replied: “I could be wrong, but Hitler also had Jewish blood. [That Zelensky is Jewish] means absolutely nothing. Wise Jewish people say that the most ardent anti-Semites are usually Jews.” It was an appalling answer that, according to the Israeli government, Putin apologized for.

In an unusual step, the English Wikipedia article brings up this particular falsehood to explicitly refute it.

The Wikipedia project comes with a stubborn confidence that facts can guide us through the darkness. In Wikipedia’s 20-year history, this belief has never been asked to do more.

TikTok accounts run by the propaganda arm of the Chinese government have accumulated millions of followers and tens of millions of views, many of them on videos editorializing about U.S. politics without clear disclosure that they were posted by a foreign government.

The accounts are managed by MediaLinks TV, a registered foreign agent and Washington D.C.-based outpost of the main Chinese Communist Party television news outlet, China Central Television. The largest of them are @Pandaorama, which features cute videos about Chinese culture, @The…Optimist, which posts about sustainability, and @NewsTokss, which features coverage of U.S. national and international news.

In the run-up to the 2022 elections, the @NewsTokss account criticized some candidates (mostly Republicans), and favored others (mostly Democrats). A video from July began with the caption “Cruz, Abbott Don’t Care About Us”; a video from October was captioned “Rubio Has Done Absolutely Nothing.” But @NewsTokss did not target only Republicans; another October video asked viewers whether they thought President Joe Biden’s promise to sign a bill codifying abortion rights was a “political manipulation tactic.” Nothing in these videos disclosed to viewers that they were being pushed by a foreign government.

any Chinese play for Taiwan would be accompanied by TikTok aggressively pushing content in America designed to divide public opinion and weaken America’s commitment to Taiwan’s defense.

With all the official GOP machinations against gay marriage, it seems like if McConnell wanted that bill to fail, he could have pressured two Republican senators to vote against it. He said nothing. Trump said nothing. DeSantis said nothing. There was barely a whimper of protest from those who could have influenced this. Mike Lee and Ted Cruz engaged in theatrics, but no one actually used their power to stop this.

They let it pass because they don’t care and they want it to go away as an issue. And that goes for the MAGA GOP as well. Opposition to it in politics is all theater and will have a shelf life in riling up the base.

Evangelical religious convictions might be for one man + one woman marriage. But, the civil/political situation is far different from that and it’s worth recognizing where the GOP actually stands. They could have stopped this. They didn’t. That point should be clear, especially to their evangelical base who looks to the GOP to save America for them.

“The struggle to defend objective truth against people who consciously choose to deny or distort it has become a fight to defend our society, and democracy itself.”

Jonathan Swift, it’s worth noting that he was not an optimist about “truth.”

By the time a lie is refuted, he wrote, “it is too late; the jest is over, and the tale has had its effect: like a man, who has thought of a good repartee, when the discourse is changed, or the company parted; or like a physician, who has found out an infallible medicine, after the patient is dead.'“

“Considering that natural disposition in many men to lie, and in multitudes to believe,” he wrote in 1710, “I have been perplexed what to do with that maxim so frequent in every body's mouth; that truth will at last prevail.

A recent Washington Post tally found that nearly 300 Republicans running for congressional and state offices are election deniers. That means, as a FiveThirtyEight analysis found, 60 percent of Americans will have at least one election denier on their ballot next week.

In a new USA Today/Suffolk University poll, 63 percent of Republicans say they worry “the election results could be manipulated.”

From the New York Times: When asked, six Trump-backed Republican nominees for governor and the Senate in midterm battlegrounds would not commit to accepting this year’s election results.

The big mistake people have made is in assuming this could blow up only in an extensive struggle in 2024 and perhaps involving Donald Trump. What seems entirely unanticipated, yet is extremely predictable, is that smaller skirmishes could break out all over the country this year.

Democrats have got themselves in a situation where the head of their party holds the most popular position on guns and crime—and yet they’re getting crushed on the issue because they’ve let GOP campaign ads, the right wing media ecosystem, and assorted progressive big city prosecutors shape the narrative on the issue rather than doing so themselves.

the broad theme was clear: Social-media platforms are the main communication tools of the 21st century, and they matter.

With Trump at the center, the techlash morphed into a culture war with a clear partisan split. One could frame the position from the left as: We do not want these platforms to give a natural advantage to the most shameless and awful people who stoke resentment and fear to gain power

On the right, it might sound more like: We must preserve the power of the platforms to let outsiders have a natural advantage (by stoking fear and resentment to gain power).

the political world realized that platforms and content-recommendation engines decide which cultural objects get amplified. The left found this troubling, whereas the right found it to be an exciting prospect and something to leverage, exploit, and manipulate via the courts

Crucially, both camps resent the power of the technology platforms and believe the companies have a negative influence on our discourse and politics by either censoring too much or not doing enough to protect users and our political discourse.

one outcome of the techlash has been an incredibly facile public understanding of content moderation and a whole lot of culture warring.

Musk and Ye aren’t so much buying into the right’s overly simplistic Big Tech culture war as they are hijacking it for their own purposes; Trump, meanwhile, is mostly just mad

Each one casts himself as an antidote to a heavy-handed, censorious social-media apparatus that is either captured by progressive ideology or merely pressured into submission by it. But none of them has any understanding of thorny First Amendment or content-moderation issues.

They embrace a shallow posture of free-speech maximalism—the very kind that some social-media-platform founders first espoused, before watching their sites become overrun with harassment, spam, and other hateful garbage that drives away both users and advertisers

for those who can hit the mark without getting banned, social media is a force multiplier for cultural and political relevance and a way around gatekeeping media.

Musk, Ye, and Trump rely on their ability to pick up their phones, go direct, and say whatever they wan

the moment they butt up against rules or consequences, they begin to howl about persecution and unfair treatment. The idea of being treated similarly to the rest of a platform’s user base

is so galling to these men that they declare the entire system to be broken.

they also demonstrate how being the Main Character of popular and political culture can totally warp perspective. They’re so blinded by their own outlying experiences across social media that, in most cases, they hardly know what it is they’re buying

These are projects motivated entirely by grievance and conflict. And so they are destined to amplify grievance and conflict

Industry leaders believe the new A.I. systems could be as important as the introduction of the web browser in the early 1990s and could lead to breakthroughs in areas ranging from drug research to education.

But gnawing at many industry insiders is a fear that they are releasing something dangerous into the wild. Generative A.I. can already be a tool for misinformation. Soon, it could be a risk to jobs. Somewhere down the line, tech’s biggest worriers say, it could be a risk to humanity.

“It is hard to see how you can prevent the bad actors from using it for bad things,” Dr. Hinton said.

After the San Francisco start-up OpenAI released a new version of ChatGPT in March, more than 1,000 technology leaders and researchers signed an open letter calling for a six-month moratorium on the development of new systems because A.I technologies pose “profound risks to society and humanity.

Several days later, 19 current and former leaders of the Association for the Advancement of Artificial Intelligence, a 40-year-old academic society, released their own letter warning of the risks of A.I. That group included Eric Horvitz, chief scientific officer at Microsoft, which has deployed OpenAI’s technology across a wide range of products, including its Bing search engine.

Dr. Hinton, often called “the Godfather of A.I.,” did not sign either of those letters and said he did not want to publicly criticize Google or other companies until he had quit his job

Dr. Hinton, a 75-year-old British expatriate, is a lifelong academic whose career was driven by his personal convictions about the development and use of A.I. In 1972, as a graduate student at the University of Edinburgh, Dr. Hinton embraced an idea called a neural network. A neural network is a mathematical system that learns skills by analyzing data. At the time, few researchers believed in the idea. But it became his life’s work.

Dr. Hinton is deeply opposed to the use of artificial intelligence on the battlefield — what he calls “robot soldiers.”

In 2012, Dr. Hinton and two of his students in Toronto, Ilya Sutskever and Alex Krishevsky, built a neural network that could analyze thousands of photos and teach itself to identify common objects, such as flowers, dogs and cars.

In 2018, Dr. Hinton and two other longtime collaborators received the Turing Award, often called “the Nobel Prize of computing,” for their work on neural networks.

Around the same time, Google, OpenAI and other companies began building neural networks that learned from huge amounts of digital text. Dr. Hinton thought it was a powerful way for machines to understand and generate language, but it was inferior to the way humans handled language.

Then, last year, as Google and OpenAI built systems using much larger amounts of data, his view changed. He still believed the systems were inferior to the human brain in some ways but he thought they were eclipsing human intelligence in others.

“Maybe what is going on in these systems,” he said, “is actually a lot better than what is going on in the brain.”

As companies improve their A.I. systems, he believes, they become increasingly dangerous. “Look at how it was five years ago and how it is now,” he said of A.I. technology. “Take the difference and propagate it forwards. That’s scary.”

Until last year, he said, Google acted as a “proper steward” for the technology, careful not to release something that might cause harm. But now that Microsoft has augmented its Bing search engine with a chatbot — challenging Google’s core business — Google is racing to deploy the same kind of technology. The tech giants are locked in a competition that might be impossible to stop, Dr. Hinton said.

His immediate concern is that the internet will be flooded with false photos, videos and text, and the average person will “not be able to know what is true anymore.”

He is also worried that A.I. technologies will in time upend the job market. Today, chatbots like ChatGPT tend to complement human workers, but they could replace paralegals, personal assistants, translators and others who handle rote tasks. “It takes away the drudge work,” he said. “It might take away more than that.”

Down the road, he is worried that future versions of the technology pose a threat to humanity because they often learn unexpected behavior from the vast amounts of data they analyze. This becomes an issue, he said, as individuals and companies allow A.I. systems not only to generate their own computer code but actually run that code on their ow

And he fears a day when truly autonomous weapons — those killer robots — become reality.

“The idea that this stuff could actually get smarter than people — a few people believed that,” he said. “But most people thought it was way off. And I thought it was way off. I thought it was 30 to 50 years or even longer away. Obviously, I no longer think that.”

Many other experts, including many of his students and colleagues, say this threat is hypothetical. But Dr. Hinton believes that the race between Google and Microsoft and others will escalate into a global race that will not stop without some sort of global regulation.

But that may be impossible, he said. Unlike with nuclear weapons, he said, there is no way of knowing whether companies or countries are working on the technology in secret. The best hope is for the world’s leading scientists to collaborate on ways of controlling the technology. “I don’t think they should scale this up more until they have understood whether they can control it,” he said.

Dr. Hinton said that when people used to ask him how he could work on technology that was potentially dangerous, he would paraphrase Robert Oppenheimer, who led the U.S. effort to build the atomic bomb: “When you see something that is technically sweet, you go ahead and do it.”

He does not say that anymore.

What’s left, across all platforms, is fragmented. News and punditry are everywhere online, but audiences are siloed; podcasts are more popular than ever, and millions of younger people online have turned to influencers and creators on Instagram and especially TikTok as trusted sources of news.

Social media, especially Twitter, has sometimes been an incredible news-gathering tool; it has also been terrible and inefficient, a game of do your own research that involves batting away bullshit and parsing half truths, hyperbole, outright lies, and invaluable context from experts on the fly. Social media’s greatest strength is thus its original sin: These sites are excellent at making you feel connected and informed, frequently at the expense of actually being informed.

At the center of these pleas for a Twitter alternative is a feeling that a fundamental promise has been broken. In exchange for our time, our data, and even our well-being, we uploaded our most important conversations onto platforms designed for viral advertising—all under the implicit understanding that social media could provide an unparalleled window to the world.

What comes next is impossible to anticipate, but it’s worth considering the possibility that the centrality of social media as we’ve known it for the past 15 years has come to an end—that this particular window to the world is being slammed shut.

“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.”

Content moderation comes to every content platform eventually, and platforms are starting to realize this faster than ever.

Nothing symbolizes this shift as neatly as Facebook’s decision in October (and Twitter’s shortly after) to start banning Holocaust denial. Almost exactly a year earlier, Zuckerberg had proudly tied himself to the First Amendment in a widely publicized “stand for free expression” at Georgetown University.

The evolution continues. Facebook announced earlier this month that it will join platforms such as YouTube and TikTok in removing, not merely labeling or down-ranking, false claims about COVID-19 vaccines.

the pandemic also showed that complete neutrality is impossible. Even though it’s not clear that removing content outright is the best way to correct misperceptions, Facebook and other platforms plainly want to signal that, at least in the current crisis, they don’t want to be seen as feeding people information that might kill them.

When internet platforms announce new policies, assessing whether they can and will enforce them consistently has always been difficult. In essence, the companies are grading their own work. But too often what can be gleaned from the outside suggests that they’re failing.

It tweaked its algorithm to boost authoritative sources in the news feed and turned off recommendations to join groups based around political or social issues. Facebook is reversing some of these steps now, but it cannot make people forget this toolbox exists in the future

As platforms grow more comfortable with their power, they are recognizing that they have options beyond taking posts down or leaving them up. In addition to warning labels, Facebook implemented other “break glass” measures to stem misinformation as the election approached.

Platforms don’t deserve praise for belatedly noticing dumpster fires that they helped create and affixing unobtrusive labels to them

Warning labels for misinformation might make some commentators feel a little better, but whether labels actually do much to contain the spread of false information is still unknown.

News reporting suggests that insiders at Facebook knew they could and should do more about misinformation, but higher-ups vetoed their ideas. YouTube barely acted to stem the flood of misinformation about election results on its platform.

Even before the pandemic, YouTube had begun adjusting its recommendation algorithm to reduce the spread of borderline and harmful content, and is introducing pop-up nudges to encourage user

And if 2020 finally made clear to platforms the need for greater content moderation, it also exposed the inevitable limits of content moderation.

Down-ranking, labeling, or deleting content on an internet platform does not address the social or political circumstances that caused it to be posted in the first place

even the most powerful platform will never be able to fully compensate for the failures of other governing institutions or be able to stop the leader of the free world from constructing an alternative reality when a whole media ecosystem is ready and willing to enable him. As Renée DiResta wrote in The Atlantic last month, “reducing the supply of misinformation doesn’t eliminate the demand.”

Even so, this year’s events showed that nothing is innate, inevitable, or immutable about platforms as they currently exist. The possibilities for what they might become—and what role they will play in society—are limited more by imagination than any fixed technological constraint, and the companies appear more willing to experiment than ever.

Pandu Nayak, a vice president for search who leads the company’s search-quality teams, told me that snippets are designed to be helpful to the user, to surface relevant and high-caliber results. He argued that they are “usually an invitation to learn more” about a subject

“It’s a strange world where these massive companies think they’re just going to slap this generative slop at the top of search results and expect that they’re going to maintain quality of the experience,” Nicholas Diakopoulos, a professor of communication studies and computer science at Northwestern University, told me. “I’ve caught myself starting to read the generative results, and then I stop myself halfway through. I’m like, Wait, Nick. You can’t trust this.”

Nayak said the team focuses on the bigger underlying problem, and whether its algorithm can be trained to address it.

If Nayak is right, and people do still follow links even when presented with a snippet, anyone who wants to gain clicks or money through search has an incentive to capitalize on that—perhaps even by flooding the zone with AI-written content.

Nayak told me that Google plans to fight AI-generated spam as aggressively as it fights regular spam, and claimed that the company keeps about 99 percent of spam out of search results.

The result is a world that feels more confused, not less, as a result of new technology.

The Kenya result still pops up on Google, despite viral posts about it. This is a strategic choice, not an error. If a snippet violates Google policy (for example, if it includes hate speech) the company manually intervenes and suppresses it, Nayak said. However, if the snippet is untrue but doesn’t violate any policy or cause harm, the company will not intervene.

experts I spoke with had several ideas for how tech companies might mitigate the potential harms of relying on AI in search

For starters, tech companies could become more transparent about generative AI. Diakopoulos suggested that they could publish information about the quality of facts provided when people ask questions about important topics

They can use a coding technique known as “retrieval-augmented generation,” or RAG, which instructs the bot to cross-check its answer with what is published elsewhere, essentially helping it self-fact-check. (A spokesperson for Google said the company uses similar techniques to improve its output.) They could open up their tools to researchers to stress-test it. Or they could add more human oversight to their outputs, maybe investing in fact-checking efforts.

Fact-checking, however, is a fraught proposition. In January, Google’s parent company, Alphabet, laid off roughly 6 percent of its workers, and last month, the company cut at least 40 jobs in its Google News division. This is the team that, in the past, has worked with professional fact-checking organizations to add fact-checks into search results

Alex Heath, at The Verge, reported that top leaders were among those laid off, and Google declined to give me more information. It certainly suggests that Google is not investing more in its fact-checking partnerships as it builds its generative-AI tool.

Nayak acknowledged how daunting a task human-based fact-checking is for a platform of Google’s extraordinary scale. Fifteen percent of daily searches are ones the search engine hasn’t seen before, Nayak told me. “With this kind of scale and this kind of novelty, there’s no sense in which we can manually curate results.”

Creating an infinite, largely automated, and still accurate encyclopedia seems impossible. And yet that seems to be the strategic direction Google is taking.

A representative for Google told me that this was an example of a “false premise” search, a type that is known to trip up the algorithm. If she were trying to date me, she argued, she wouldn’t just stop at the AI-generated response given by the search engine, but would click the link to fact-check it.

hose promises have also fueled anxiety over how people will be able to compete for jobs outsourced to eerily refined machines or trust the accuracy of what they see online.

Officials with the San Francisco lab said GPT-4’s “multimodal” training across text and images would allow it to escape the chat box and more fully emulate a world of color and imagery, surpassing ChatGPT in its “advanced reasoning capabilities.”

A person could upload an image and GPT-4 could caption it for them, describing the objects and scene.

AI language models often confidently offer wrong answers because they are designed to spit out cogent phrases, not actual facts. And because they have been trained on internet text and imagery, they have also learned to emulate human biases of race, gender, religion and class.

GPT-4 still makes many of the errors of previous versions, including “hallucinating” nonsense, perpetuating social biases and offering bad advice. It also lacks knowledge of events that happened after about September 2021, when its training data was finalized, and “does not learn from its experience,” limiting people’s ability to teach it new things.

Microsoft has invested billions of dollars in OpenAI in the hope its technology will become a secret weapon for its workplace software, search engine and other online ambitions. It has marketed the technology as a super-efficient companion that can handle mindless work and free people for creative pursuits, helping one software developer to do the work of an entire team or allowing a mom-and-pop shop to design a professional advertising campaign without outside help.

it could lead to business models and creative ventures no one can predict.

sparked criticism that the companies are rushing to exploit an untested, unregulated and unpredictable technology that could deceive people, undermine artists’ work and lead to real-world harm.

the company held back the feature to better understand potential risks. As one example, she said, the model might be able to look at an image of a big group of people and offer up known information about them, including their identities — a possible facial recognition use case that could be used for mass surveillance.

OpenAI researchers wrote, “As GPT-4 and AI systems like it are adopted more widely,” they “will have even greater potential to reinforce entire ideologies, worldviews, truths and untruths, and to cement them or lock them in.”

“We can agree as a society broadly on some harms that a model should not contribute to,” such as building a nuclear bomb or generating child sexual abuse material, she said. “But many harms are nuanced and primarily affect marginalized groups,” she added, and those harmful biases, especially across other languages, “cannot be a secondary consideration in performance.”

OpenAI said its new model would be able to handle more than 25,000 words of text, a leap forward that could facilitate longer conversations and allow for the searching and analysis of long documents.

OpenAI developers said GPT-4 was more likely to provide factual responses and less likely to refuse harmless requests

Duolingo, the language learning app, has already used GPT-4 to introduce new features, such as an AI conversation partner and a tool that tells users why an answer was incorrect.

The company did not share evaluations around bias that have become increasingly common after pressure from AI ethicists.

GPT-4 will have competition in the growing field of multisensory AI. DeepMind, an AI firm owned by Google’s parent company Alphabet, last year released a “generalist” model named Gato that can describe images and play video games. And Google this month released a multimodal system, PaLM-E, that folded AI vision and language expertise into a one-armed robot on wheels: If someone told it to go fetch some chips, for instance, it could comprehend the request, wheel over to a drawer and choose the right bag.

The systems, though — as critics and the AI researchers are quick to point out — are merely repeating patterns and associations found in their training data without a clear understanding of what it’s saying or when it’s wrong.

GPT-4, the fourth “generative pre-trained transformer” since OpenAI’s first release in 2018, relies on a breakthrough neural-network technique in 2017 known as the transformer that rapidly advanced how AI systems can analyze patterns in human speech and imagery.

The systems are “pre-trained” by analyzing trillions of words and images taken from across the internet: news articles, restaurant reviews and message-board arguments; memes, family photos and works of art.

Giant supercomputer clusters of graphics processing chips are mapped out their statistical patterns — learning which words tended to follow each other in phrases, for instance — so that the AI can mimic those patterns, automatically crafting long passages of text or detailed images, one word or pixel at a time.

In 2019, the company refused to publicly release GPT-2, saying it was so good they were concerned about the “malicious applications” of its use, from automated spam avalanches to mass impersonation and disinformation campaigns.

Altman has also marketed OpenAI’s vision with the aura of science fiction come to life. In a blog post last month, he said the company was planning for ways to ensure that “all of humanity” benefits from “artificial general intelligence,” or AGI — an industry term for the still-fantastical idea of an AI superintelligence that is generally as smart as, or smarter than, the humans themselves.

The simple truth is that building something valuable — whether that’s knowledge, experience or a network worth participating in — is really, really hard. But tearing it all down is piss easy.

It almost doesn’t matter if this is deliberate sabotage by Musk or the blundering stupidity of a clueless idiot.

In an Atlantic essay, “Why The Past Ten Years of American Life have Been Uniquely Stupid,” and in a follow-up piece, Haidt argued that the Age of Gutenberg–of books and the depth understanding that comes with them–ended somewhere around 2014 with the rise of “Share,” “Like” and “Retweet” buttons that opened the way for trolls, hucksters and Trumpists

The new age of “hyper-virality,” he writes, has given us both January 6 and cancel culture–ugly polarization in both directions. On the subject of stupidification, we should add the fact that high school students now get virtually their entire stock of knowledge about the world from digital platforms.

Haidt proposed several reforms, including modifying Facebook’s “Share” function and requiring “user verification” to get rid of trolls. But he doesn’t really believe in his own medicine

Haidt said that the era of “shared understanding” is over–forever. When I asked if he could envision changes that would help protect democracy, Haidt quoted Goldfinger: “Do you expect me to talk?” “No, Mr. Bond, I expect you to die!”

Social media is a public health hazard–the cognitive equivalent of tobacco and sugary drinks. Adopting a public health model, we could, for examople, ban the use of algorithms to reduce virality, or even require social media platforms to adopt a subscription rather than advertising revenue model and thus remove their incentive to amass ev er more eyeballs.

We could, but we won’t, because unlike other public health hazards, digital platforms are forms of speech. Fox New is probably responsible for more polarization than all social media put together, but the federal government could not compel it–and all other media firms–to change its revenue model.

If Mark Zuckerberg or Elon Musk won’t do so out of concern for the public good–a pretty safe bet–they could be compelled to do so only by public or competitive pressure. 

Taiwan has provide resilient because its society is resilient; people reject China’s lies. We, here, don’t lack for fact-checkers, but rather for people willing to believe them. The problem is not the technology, but ourselves.

you have to wonder if people really are repelled by our poisonous discourse, or by the hailstorm of disinformation, or if they just want to live comfortably inside their own bubble, and not somebody else’

If Jonathan Haidt is right, it’s not because we’ve created a self-replicating machine that is destined to annihilate reason; it’s because we are the self-replicating machine.