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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

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.

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.

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

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

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.

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.

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

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

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.

In 2006, the man’s remains were exhumed, but DNA extracted from his teeth yielded no match with a list of people Navy officials thought might be his descendants. With few leads, the scientist who conducted the DNA test, Jeremy Austin, told the Navy about an emerging technique that could predict a person’s ancestry and physical traits from genetic material.

In Australia, forensic scientists are repurposing the technique to help link missing persons with unidentified remains in the hope of resolving long-running mysteries. In the case of the sailor, Dr. Austin sent the sample to researchers in Europe, who reported back that the man was of European ancestry and most likely had red hair and blue eyes.

That alone wasn’t enough to identify the sailor, but it narrowed the search. “In a ship full of 645 white guys, you wouldn’t expect to see more than two or three with this pigmentation,”

This forensic tool, which has been slowly advancing since the mid-2000s, is similar to genetic tests that estimate risks for certain diseases. About five years ago, scientists with the Australian Federal Police began developing their own version of the technology, which combines genomics, big data and machine learning. It became available for use last year.

The predictions from DNA phenotyping — whether a person had, say, brown hair and blue eyes — will be brought to life by a forensic artist, combining the phenotype information with renderings of bone structure to generate a three-dimensional digital facial reconstruction.

“It’s an investigative lead we’ve never had before,”

In the United States, police departments have for years been using private DNA phenotyping services, like one from the Virginia-based Parabon NanoLabs, to try to generate facial images of suspects. The images are sometimes distributed to the public to assist in investigations.

Many scientists, however, are skeptical of this application of the technology. “You cannot do a full facial prediction right now,” said Susan Walsh, a professor of biology at Indiana University-Purdue University Indianapolis who developed some of the earliest phenotyping methods for eye and hair color. “The foundation of the genetics is absolutely not there.”

Facial image prediction has been condemned by human rights organizations, including the A.C.L.U., which suggest that it risks being skewed by existing social prejudices.

The same DNA was then linked to dozens of serious crimes across Western Europe, prompting a theory that the perpetrator was a serial offender from a traveling Roma community.It turned out that the recurring genetic material belonged to a female Polish factory worker who had accidentally contaminated the cotton swabs used to collect the samples.

“The families want any and all techniques applied to these cases if it’s going to help answer the question of what happened,” she said.

Such was the case with the mystery sailor. After his genotype was sequenced and his phenotype predicted, a team of scientists across several Australian institutions, including Dr. Ward’s program, used this information to track down a woman they believed to be a living relative of the soldier. They checked her DNA and had a match.

I think that the age of the New Democrats, which was a very successful political project for the Democratic Party, has come to an end. The assumption of that politics, which began in earnest in the late 1980s and early 1990s, was that the Cold War had been settled, that democracy had prevailed, that the West was ascendant. But with China’s decision to take the route that they’ve gone on, with Russia now having waged this intense insurgency against the West, the assumption that that system is going to prevail in the world is now under question.

Rosenberg: Any honest assessment of the New Democrat project has to view it as wildly successful, because when I went to work for Clinton in 1992, Democrats had lost five out of the six previous presidential elections. And the central project of the New Democrats was to make the Democratic Party competitive at the presidential level again. Since then, we’ve won more votes in seven of eight presidential elections

I think that it’s birthing now for the United States a different era of politics, where we must be focused on two fundamental, existential questions. Can democracy prevail given the way that it’s being attacked from all sides? And can we prevent climate change from overwhelming the world that we know?

I want to try to write a book and to take the perspective of having been part of the beginning of the last big shift in American politics, the emergence of the New Democrats, and start imagining what’s going to come next for the center left in the United States and around the world.

Simon Rosenberg:

We’ve also seen three Democratic presidents that have served [since then]—Clinton, Barack Obama, and Joe Biden have also made the country materially better during their presidencies.

what’s the main lesson you take from his emergence?

Rosenberg: Yeah, it’s obviously disappointing. The emergence of what I call “Greater MAGA” has been a dark period in our history.

You have to recognize just how central to that is this narrative of the white tribe rallying around itself, and the sense of grievance, the sense of loss, the sense of decline. That’s what MAGA is. That’s all it is

We know from history, we know from other countries, when countries go into sectarian or tribal warfare, it can destroy a country, pull it apart. And Trump has created a domestic argument here that could potentially destroy the U.S. Look at Marjorie Taylor Greene this week—advocating for the country to split into two, red and blue.

Part of the reason I’m taking a step back from NDN is that I don’t think that we have yet figured out how to talk to the American people about the nature of the conflict we’re in right now, with rising authoritarianism around the world, the weakening of democratic institutions here and in other places.

My hope is that because Biden won’t be able to legislate very much for the next two years, he’ll spend his time talking to the American people and the West about the necessity of winning this conflict.

Rosenberg: The threat is still here. Look, I think [Florida Governor] Ron DeSantis is even more MAGA than Trump. This idea that in 2024, Republicans are going to end up with a moderate, center-right candidate and distance themselves from the insanity of the Trump years, that’s just fantasy talk.

DeSantis has decided to double down on extremism and on MAGA. We will learn in the next year and a half about how it all plays out. But I think he misread the room; he’s misread the moment in history. He needed to become an anti-Trump; instead, he became more Trump than Trump

In this last election, there were really two elections. There was a bluer election inside the battlegrounds, and there was a redder election outside the battlegrounds. We actually gained ground in seven battleground states: Arizona, Colorado, Georgia, Michigan, Minnesota, New Hampshire, and Pennsylvania. It’s an extraordinary achievement given high inflation, a low Biden approval rating, traditional midterm dynamics. My view is, that happened because the fear of MAGA has created a supercharged grass roots; our candidates are raising unprecedented amounts of money; we have more labor to work in these races than we’ve ever had before. And where we have these muscular campaigns, we were able to control the information environment. And also push turnout up through the roof.

But outside the battlegrounds, we fell back in New York and California, and in Florida and Texas, the four biggest states in the country. And the admonition to us is that we are still not competitive enough in the national daily discourse;

Republicans, because of this incredible noise machine that they built, are still far louder than we are. Democrats have to become obsessive about being more competitive in the daily political discourse in the country.

We have to build more media institutions. Republicans use ideological media to advance their politics in a way that we’ve never done. And we’re going to have to match that to some degree.

The second piece is that average Democratic activists have to recognize that they need to become information warriors daily

I think the way we have to think of the war room now, it’s 4 million proud patriots getting up every day, spending a little bit of their day putting good information into our daily discourse to try to crowd out the poisonous information and right-wing propaganda. There’s a lot that average citizens can do in this.

The key is to defeat MAGA in such a definitive and declarative way that Republicans move on to a different kind of politics and become something more like a traditional center-right political party.

We must stick together as a party because what will cause far-right political parties to succeed is when the prodemocracy coalition splits, and we can’t allow that to happen. As much as sometimes we want to have interfamily battles, those are self-indulgent at this point.

I don’t think that this emerging criticism is entirely wrong, but it’s only half right. The goal should be to expand, not to reposition. There are four areas that I think we have to bear down on in the next two years for a potential Democratic expansion: young voters, Latinos, Never-MAGA or -Trumpers, and young women, post-Dobbs.

The No. 1 job is we just need more young people voting, period. It’s more registration, more communications, targeting them more in our campaigns. In the Democratic Party, young people are still at the kids’ table; they have to become the center of our politics now.

I think that we’re favored in the presidential election. For us to win next year, the economy has to be good. And we have to look like we’ve been successful in Ukraine. Those two things are going to be paramount in him being able to say, “I’ve been a good president, and I may be a little bit old, but I still got 90 miles an hour on my fastball, and I’m able to get the job done right versus they’re still a little bit too crazy.”

What the Republicans should be worried about is we’ve had three consecutive elections where the battleground states have rejected MAGA. And so, if the Republicans present themselves as MAGA again, which looks almost inevitable, it’s going to be hard for them to win a presidential election in 2024 given that the battleground has muscle memory about MAGA and has voted now three times against it.

Starting from scratch is usually a bad idea. Too often, we assume innovative ideas and meaningful changes require a blank slate. When business projects fail, we say things like, “Let's go back to the drawing board.” When we consider the habits we would like to change, we think, “I just need a fresh start.” However, creative progress is rarely the result of throwing out all previous ideas and innovations and completely re-imagining of the world.

Some experts believe the feathers of birds evolved from reptilian scales. Through the forces of evolution, scales gradually became small feathers, which were used for warmth and insulation at first. Eventually, these small fluffs developed into larger feathers capable of flight.

The process of human flight followed a similar path. We typically credit Orville and Wilbur Wright as the inventors of modern flight. However, we seldom discuss the aviation pioneers who preceded them like Otto Lilienthal, Samuel Langley, and Octave Chanute. The Wright brothers learned from and built upon the work of these people during their quest to create the world's first flying machine.

The Toaster Project is an example of how we often fail to notice the complexity of our modern world. When you buy a toaster, you don't think about everything that has to happen before it appears in the store. You aren't aware of the iron being carved out of the mountain or the oil being drawn up from the earth.

For decades — and particularly since the 2008 recession — politicians in both parties have mounted a strident campaign against government funding for the liberal arts. They express a growing disdain for any courses not explicitly tailored to the job market and outright contempt for the role the liberal arts-focused university has played in American society.

Former Gov. Scott Walker’s assault on higher education in Wisconsin formed the bedrock of many later conservative attacks. His work severely undermined a state university system that was once globally admired. Mr. Walker reportedly attempted to cut phrases like “the search for truth” and “public service” — as well as a call to improve “the human condition” — from the University of Wisconsin’s official mission statement

But blue states also regularly cut higher education funding, sometimes with similar rationales. In 2016, Matt Bevin, the Republican governor of Kentucky at the time, suggested that students majoring in the humanities shouldn’t receive state funding. The current secretary of education, Miguel Cardona, a Democrat, seems to barely disagree. “Every student should have access to an education that aligns with industry demands and evolves to meet the demands of tomorrow’s global work force,” he wrote in December.

Federal funding reflects those priorities. The National Endowment for the Humanities’ budget in 2022 was just $180 million. The National Science Foundation’s budget was about 50 times greater, having nearly doubled within two decades.

What were students meant to think? As the cost of higher education rose, substantially outpacing inflation since 1990, students followed funding — and what politicians repeatedly said about employability — into fields like business and computer science. Even majors in mathematics were hit by the focus on employability.

Universities took note and began culling. One recent study showed that history faculty across 28 Midwestern universities had dropped by almost 30 percent in roughly the past decade. Classics programs, including the only one at a historically Black college, were often simply eliminated.

Higher education, with broad study in the liberal arts, is meant to create not merely good workers but good citizens

this is a grim and narrow view of the purpose of higher education, merely as a tool to train workers as replaceable cogs in America’s economic machine, to generate raw material for its largest companies.

Citizens with knowledge of their history and culture are better equipped to lead and participate in a democratic society; learning in many different forms of knowledge teaches the humility necessary to accept other points of view in a pluralistic and increasingly globalized society.

In 1947, a presidential commission bemoaned an education system where a student “may have gained technical or professional training” while being “only incidentally, if at all, made ready for performing his duties as a man, a parent and a citizen.” The report recommended funding to give as many Americans as possible the sort of education that would “give to the student the values, attitudes, knowledge and skills that will equip him to live rightly and well in a free society,” which is to say the liberal arts as traditionally understood. The funding followed.

The report is true today, too

the American higher education system is returning to what it once was: liberal arts finishing schools for the wealthy and privileged, and vocational training for the rest.

Reversing this decline requires a concerted effort by both government and educational actors

renewed funding for the liberal arts — and especially the humanities — would support beleaguered departments and show students that this study is valuable and valued.

At the university level, instituting general education requirements would guarantee that even students whose majors have nothing to do with the humanities emerged from college equipped to think deeply and critically across disciplines.

Liberal arts professors must also be willing to leave their crumbling ivory towers and the parochial debates about their own career path, in order to engage directly in public life

If all of this sounds familiar, it’s because we basically saw this same environmental dynamic play out several years ago with tech’s last big obsession: Crypto and web3. In that case, Bitcoin emerged as the industry’s obvious environmental sore spot due to the vast amounts of energy needed to mine coins in its proof of work model. Some estimates suggest Bitocin alone requires more energy every year than Norway’s annual electricity consumption.

rs of criticism from environmental activists however led the crypto industry to make some changes. Ethereum, the second largest currency on the blockchain, officially switched last year to a proof of stake model which supporters claim could reduce its power usage by over 99%. Other smaller coins similarly were designed with energy efficiency in mind. In the grand scheme of things, large language models are still in their infancy and it’s far from certain how its environmental report card will play out.

AI will usher in knowledgeable and friendly automated customer service any day now. But there is so much else on the innovation horizon: osmotic energy, geothermal, nuclear fusion, autonomous farming, photonic computing, human longevity. Plus all the stuff in research labs we haven’t heard of yet, let alone invented and brought to market.

Every industry is about to change, which will defy skeptics. Figure out how, and then, as Mr. Wozniak suggests, get your hands dirty. As always, the pain point is cost. Look for things that get cheaper—that’s the only way to clear the smoke and get new marvels into global consumer hands.

Mensch said his new model cost less than €20 million, the equivalent of roughly $22 million, to train. By contrast OpenAI Chief Executive Sam Altman said last year after the release of GPT-4 that training his company’s biggest models cost “much more than” $50 million to $100 million.

Brave Software made a free, open-source model from Mistral the default to power its web-browser chatbot, said Brian Bondy, Brave’s co-founder and chief technology officer. He said that the company finds the quality comparable with proprietary models, and Mistral’s open-source approach also lets Brave control the model locally.

“We want to be the most capital-efficient company in the world of AI,” Mensch said. “That’s the reason we exist.” 

Mensch joined the Google AI unit then called DeepMind in late 2020, where he worked on the team building so-called large language models, the type of AI system that would later power ChatGPT. By 2022, he was one of the lead authors of a paper about a new AI model called Chinchilla, which changed the field’s understanding of the relationship among the size of an AI model, how much data is used to build it and how well it performs, known as AI scaling laws.

Mensch took a role lobbying French policymakers, including French President Emmanuel Macron, against certain elements of the European Union’s new AI Act, which Mensch warned could slow down companies and would, in his view, do nothing to make AI safer. After changes to the text in Brussels, it will be a manageable burden for Mistral, Mensch says, even if he thinks the law should have remained focused on how AI is used rather than also regulating the underlying technology.  

For Mensch and his co-founders, releasing their initial AI systems as open source that anyone could use or adapt free of charge was an important principle. It was also a way to get noticed by developers and potential clients eager for more control over the AI they use

Mistral’s most advanced models, including the one unveiled Monday, aren’t available open source. 

That willingness is not reassuring. For example, it is not far-fetched to imagine insurers wanting to get their hands on this type of medical information in order to hike premiums. Data brokers of all kinds will be similarly keen to obtain people’s real-time health-chat records. Altman made a point to say that this theoretical product would not trick people into sharing information.

. Neither Altman nor Huffington had an answer to my most basic question—What would the product actually look like? Would it be a smartwatch app, a chatbot? A Siri-like audio assistant?—but Huffington suggested that Thrive’s AI platform would be “available through every possible mode,” that “it could be through your workplace, like Microsoft Teams or Slack.

This led me to propose a hypothetical scenario in which a company collects this information and stores it inappropriately or uses it against employees. What safeguards might the company apply then? Altman’s rebuttal was philosophical. “Maybe society will decide there’s some version of AI privilege,” he said. “When you talk to a doctor or a lawyer, there’s medical privileges, legal privileges. There’s no current concept of that when you talk to an AI, but maybe there should be.”

So much seems to come down to: How much do you want to believe in a future mediated by intelligent machines that act like humans? And: Do you trust these people?

A fundamental question has loomed over the world of AI since the concept cohered in the 1950s: How do you talk about a technology whose most consequential effects are always just on the horizon, never in the present? Whatever is built today is judged partially on its own merits, but also—perhaps even more important—on what it might presage about what is coming next.

the models “just want to learn”—a quote attributed to the OpenAI co-founder Ilya Sutskever that means, essentially, that if you throw enough money, computing power, and raw data into these networks, the models will become capable of making ever more impressive inferences. True believers argue that this is a path toward creating actual intelligence (many others strongly disagree). In this framework, the AI people become something like evangelists for a technology rooted in faith: Judge us not by what you see, but by what we imagine.

I found it outlandish to invoke America’s expensive, inequitable, and inarguably broken health-care infrastructure when hyping a for-profit product that is so nonexistent that its founders could not tell me whether it would be an app or not.

Thrive AI Health is profoundly emblematic of this AI moment precisely because it is nothing, yet it demands that we entertain it as something profound.

you don’t have to get apocalyptic to see the way that AI’s potential is always muddying people’s ability to evaluate its present. For the past two years, shortcomings in generative-AI products—hallucinations; slow, wonky interfaces; stilted prose; images that showed too many teeth or couldn’t render fingers; chatbots going rogue—have been dismissed by AI companies as kinks that will eventually be worked out

Faith is not a bad thing. We need faith as a powerful motivating force for progress and a way to expand our vision of what is possible. But faith, in the wrong context, is dangerous, especially when it is blind. An industry powered by blind faith seems particularly troubling.

The greatest trick of a faith-based industry is that it effortlessly and constantly moves the goal posts, resisting evaluation and sidestepping criticism. The promise of something glorious, just out of reach, continues to string unwitting people along. All while half-baked visions promise salvation that may never come.