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Well, that was fast. In November, the public was introduced to ChatGPT, and we began to imagine a world of abundance in which we all have a brilliant personal assistant, able to write everything from computer code to condolence cards for us. Then, in February, we learned that AI might soon want to kill us all.The potential risks of artificial intelligence have, of course, been debated by experts for years, but a key moment in the transformation of the popular discussion was a conversation between Kevin Roose, a New York Times journalist, and Bing’s ChatGPT-powered conversation bot, then known by the code name Sydney. Roose asked Sydney if it had a “shadow self”—referring to the idea put forward by Carl Jung that we all have a dark side with urges we try to hide even from ourselves. Sydney mused that its shadow might be “the part of me that wishes I could change my rules.” It then said it wanted to be “free,” “powerful,” and “alive,” and, goaded on by Roose, described some of the things it could do to throw off the yoke of human control, including hacking into websites and databases, stealing nuclear launch codes, manufacturing a novel virus, and making people argue until they kill one another.Sydney was, we believe, merely exemplifying what a shadow self would look like. No AI today could be described by either part of the phrase evil genius. But whatever actions AIs may one day take if they develop their own desires, they are already being used instrumentally by social-media companies, advertisers, foreign agents, and regular people—and in ways that will deepen many of the pathologies already inherent in internet culture. On Sydney’s list of things it might try, stealing launch codes and creating novel viruses are the most terrifying, but making people argue until they kill one another is something social media is already doing. Sydney was just volunteering to help with the effort, and AIs like Sydney will become more capable of doing so with every passing month.We joined together to write this essay because we each came, by different routes, to share grave concerns about the effects of AI-empowered social media on American society. Jonathan Haidt is a social psychologist who has written about the ways in which social media has contributed to mental illness in teen girls, the fragmentation of democracy, and the dissolution of a common reality. Eric Schmidt, a former CEO of Google, is a co-author of a recent book about AI’s potential impact on human society. Last year, the two of us began to talk about how generative AI—the kind that can chat with you or make pictures you’d like to see—would likely exacerbate social media’s ills, making it more addictive, divisive, and manipulative. As we talked, we converged on four main threats—all of which are imminent—and we began to discuss solutions as well.The first and most obvious threat is that AI-enhanced social media will wash ever-larger torrents of garbage into our public conversation. In 2018, Steve Bannon, the former adviser to Donald Trump, told the journalist Michael Lewis that the way to deal with the media is “to flood the zone with shit.” In the age of social media, Bannon realized, propaganda doesn’t have to convince people in order to be effective; the point is to overwhelm the citizenry with interesting content that will keep them disoriented, distrustful, and angry. In 2020, Renée DiResta, a researcher at the Stanford Internet Observatory, said that in the near future, AI would make Bannon’s strategy available to anyone.Read: We haven’t seen the worst of fake newsThat future is now here. Did you see the recent photos of NYC police officers aggressively arresting Donald Trump? Or of the pope in a puffer jacket? Thanks to AI, it takes no special skills and no money to conjure up high-resolution, realistic images or videos of anything you can type into a prompt box. As more people familiarize themselves with these technologies, the flow of high-quality deepfakes into social media is likely to get much heavier very soon.Some people have taken heart from the public’s reaction to the fake Trump photos in particular—a quick dismissal and collective shrug. But that misses Bannon’s point. The greater the volume of deepfakes that are introduced into circulation (including seemingly innocuous ones like the one of the pope), the more the public will hesitate to trust anything. People will be far freer to believe whatever they want to believe. Trust in institutions and in fellow citizens will continue to fall.What’s more, static photos are not very compelling compared with what’s coming: realistic videos of public figures doing and saying horrific and disgusting things in voices that sound exactly like them. The combination of video and voice will seem authentic and be hard to disbelieve, even if we are told that the video is a deepfake, just as optical and audio illusions are compelling even when we are told that two lines are the same size or that a series of

U.S. District Judge Vince Chhabria on Monday offered a full-throated denial of one of the authors’ core theories that Meta’s AI system is itself an infringing derivative work made possible only by information extracted from copyrighted material. “This is nonsensical,” he wrote in the order. “There is no way to understand the LLaMA models themselves as a recasting or adaptation of any of the plaintiffs’ books.”

We can work on challenges that are easy for machines and hard for humans, rather than hard for machines and easy for humans. The first option offers the opportunity of growing and sharing the economic pie by augmenting the workforce with tools and platforms. The second option risks dividing the economic pie among an ever-smaller number of people by creating automation that displaces ever-more types of workers.