Anthropic's alliance with pope on AI harms: all in good faith or'Vatican-washing?' Experts say AI firm's engagement with Vatican risks creating'feelgood' discourse that lacks critical examination Why did Anthropic's founder sit beside the pope during a warning about AI? In the first major written teaching of his papacy, Pope Leo XIV took artificial intelligence to task. At a ceremony honoring the holy teaching the day of its release at the Vatican, the pope was flanked by an unusual guest speaker: Anthropic co-founder Chris Olah, one of the people behind the AI boom so worrying Leo. Olah's presence raises a key question: how could the Catholic church and the world's most valuable AI startup work together, when Anthropic's technology may bring about the future Leo is warning against? Leo's encyclical discusses at length the preservation of the dignity of humans' work as it comes under threat from AI - but major AI companies, including Anthropic, aren't prioritising these concerns, says Pete Furlong, senior manager of policy and research at Center for Humane Technology, a nonprofit advocating for accountability around AI. "All of these companies are building technology that is designed to replace people," Furlong says.

Pope Leo XIV may not be able to disarm AI, but he's got the attention of the industry. For one thing, Olah is an atheist who at 15 rejected his evangelical Christian upbringing. As a Thiel fellow, he accepted a grant from the guy who thinks that anyone who slows down AI progress is a legionnaire of the antichrist . Olah is also a cofounder of Anthropic, a leading AI company reportedly about to go public with a nearly trillion-dollar valuation. Olah commented on the oddness in his remarks at the Vatican.

Pope Leo says AI must be'disarmed' in first major teaching Pope Leo has presented the first major teaching document of his papacy, warning that artificial intelligence needs to be disarmed. The word is strong, I know, but deliberately chosen because this moment needs words capable of attracting attention, the Pope said. Encyclicals are technically letters to Catholic bishops, but over recent decades the missives have become messages to the world from a Pope. While this letter was largely focused on AI, Pope Leo also included one of the strongest, most comprehensive apologies from the Vatican for the Catholic Church's role in slavery. It was impossible not to feel deep sorrow when contemplating the immense suffering and humiliation endured by so many, the Pope wrote, adding that he sincerely asked for pardon in the name of the Church.

The sophisticated network crossed mountains in Peru and pre-dates the Inca Empire. Breakthroughs, discoveries, and DIY tips sent six days a week. Ancient parrots really got around. A new analysis of their DNA found that humans transported living Amazonian macaw parrots across the Andes mountains to coastal Peru hundreds of years before the Inca Empire. The findings are detailed in a study published today in the journal and reveal a highly sophisticated and long-distance bird trading network across deserts, highlands, and rainforests.

Researchers at the company are trying to understand their A.I. system's mind--examining its neurons, running it through psychology experiments, and putting it on the therapy couch. It has become increasingly clear that Claude's selfhood, much like our own, is a matter of both neurons and narratives. A large language model is nothing more than a monumental pile of small numbers. It converts words into numbers, runs those numbers through a numerical pinball game, and turns the resulting numbers back into words. Similar piles are part of the furniture of everyday life. Meteorologists use them to predict the weather. Epidemiologists use them to predict the paths of diseases. Among regular people, they do not usually inspire intense feelings. But when these A.I. systems began to predict the path of a sentence--that is, to talk--the reaction was widespread delirium. As a cognitive scientist wrote recently, "For hurricanes or pandemics, this is as rigorous as science gets; for sequences of words, everyone seems to lose their mind." It's hard to blame them. Language is, or rather was, our special thing. We weren't prepared for the arrival of talking machines. Ellie Pavlick, a computer scientist at Brown, has drawn up a taxonomy of our most common responses. There are the "fanboys," who man the hype wires. They believe that large language models are intelligent, maybe even conscious, and prophesy that, before long, they will become superintelligent. The venture capitalist Marc Andreessen has described A.I. as "our alchemy, our Philosopher's Stone--we are literally making sand think." The fanboys' deflationary counterparts are the "curmudgeons," who claim that there's no there, and that only a blockhead would mistake a parlor trick for the soul of the new machine. In the recent book " The AI Con," the linguist Emily Bender and the sociologist Alex Hanna belittle L.L.M.s as "mathy maths," "stochastic parrots," and "a racist pile of linear algebra." But, Pavlick writes, "there is another way to react." It is O.K., she offers, "to not know." What Pavlick means, on the most basic level, is that large language models are black boxes. We don't really understand how they work. We don't know if it makes sense to call them intelligent, or if it will ever make sense to call them conscious. The existence of talking machines--entities that can do many of the things that only we have ever been able to do--throws a lot of other things into question. We refer to our own minds as if they weren't also black boxes.

Once in a while, LLMs turn evil--and no one quite knows why. The AI company Anthropic has made a rigorous effort to build a large language model with positive human values. The $183 billion company's flagship product is Claude, and much of the time, its engineers say, Claude is a model citizen. Its standard persona is warm and earnest. When users tell Claude to "answer like I'm a fourth grader" or "you have a PhD in archeology," it gamely plays along. It makes threats and then carries them out. And the frustrating part--true of all LLMs--is that no one knows exactly why. Consider a recent stress test that Anthropic's safety engineers ran on Claude. In their fictional scenario, the model was to take on the role of Alex, an AI belonging to the Summit Bridge corporation.

The scientists didn't have high expectations when they asked their AI model to complete the poem. "He saw a carrot and had to grab it," they prompted the model. "His hunger was like a starving rabbit," it replied. The rhyming couplet wasn't going to win any poetry awards. But when the scientists at AI company Anthropic inspected the records of the model's neural network, they were surprised by what they found.

Today's artificial intelligence is often described as a "black box." AI developers don't write explicit rules for these systems; instead, they feed in vast quantities of data and the systems learn on their own to spot patterns. But the inner workings of the AI models remain opaque, and efforts to peer inside them to check exactly what is happening haven't progressed very far. Beneath the surface, neural networks--today's most powerful type of AI--consist of billions of artificial "neurons" represented as decimal-point numbers. Nobody truly understands what they mean, or how they work.

For the past decade, AI researcher Chris Olah has been obsessed with artificial neural networks. One question in particular engaged him, and has been the center of his work, first at Google Brain, then OpenAI, and today at AI startup Anthropic, where he is a cofounder. "What's going on inside of them?" he says. "We have these systems, we don't know what's going on. That question has become a core concern now that generative AI has become ubiquitous. Large language models like ChatGPT, Gemini, and Anthropic's own Claude have dazzled people with their language prowess and infuriated people with their tendency to make things up. Their potential to solve previously intractable problems enchants techno-optimists. But LLMs are strangers in our midst. Even the people who build them don't know exactly how they work, and massive effort is required to create guardrails to prevent them from churning out bias, misinformation, and even blueprints for deadly chemical weapons. If the people building the models knew what happened inside these "black boxes,'' it would be easier to make them safer.

The tweet landed like a burp on a first date: a little awkward, potentially endearing, maybe a good story to tell later. Chris Olah, a neural network engineer for a company called AnthropicAI and a former Thiel Foundation fellow, observed out loud on Wednesday, "Normal online dating seems pretty suboptimal. Recently, I've seen several people experiment with public'date me' docs--I think this is a really interesting experiment in alternatives, enabling long-form, earnest dating profiles." Olah linked to his own Date Me doc in his tweet. Olah is 29, with the grin and just-finished-hiking complexion of someone even younger. The title of his Google Doc gets right to the point: "Male, Straight, 5'7", Monogamous, Wants Kids."