Will AI really kill everyone? How, exactly?

By T.M. Brown, CNN

Artificial intelligence could kill the entire human species, according to people in the artificial intelligence industry. Specifically, they say, it could exterminate humanity within the decade.

Politicians, major news organizations, and Sheryl Crow reacted with alarm last week after an Anthropic employee named Jacob Coxon announced he was quitting the AI company because its work was too dangerous. Evan Hubinger, another Anthropic worker, chimed in to put the chance of AI-powered human extinction within 10 years at greater than 10%.

“It really is about literally everyone on the planet dying, like the last human drawing the last breath,” said Nate Soares, the president of the Machine Intelligence Research Institute (MIRI) and the coauthor of “If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All.”

“People often don’t believe it when they say this, but I do think that is the most likely outcome,” Soares.

The numbers being attached to that outcome sounded precise. But how, exactly, would computer software, even the world’s most powerful software systems, kill 8.3 billion flesh-and-blood people in a decade?

Not everyone in the AI community subscribes to the doomsday story, in part because the details of the prediction are so sparse. When Elon Musk says SpaceX aims to put people on Mars in “5 to 7 years,” there are clear follow-up questions: Does SpaceX have a working vehicle that would go to Mars? (No.) Does it have a Mars lander or Mars bases? (No.)

“Scientific claims require falsifiability precisely to avoid the nature of religious arguments,” said Heidy Khlaaf, chief AI scientist at the AI Now Institute and a former OpenAI safety engineer. “You need to be able to prove or disprove them.”

Wiped out by synthetic plague?

One line of speculation among the doomsayers is that a sufficiently powerful AI system could use bioweapons to wipe out humanity. But how would AI advance from computer-on-computer misdeeds like hacking into other systems to the physical-world task of breeding and spreading a super pathogen?

Thomas Larsen, a researcher at the AI Futures Project and former MIRI employee, said that it’s conceivable that a “superintelligent” AI system could convince a human to help it develop a deadly virus.

“There are already a lot of humans talking to their AIs about exactly what experiments they should run in a lab,” Larsen said, referring to a recent report by Anthropic about researchers using Claude to help them with viral and toxin research. “It’s very easy for me to imagine an AI that’s just currently deployed — if it was much smarter and more strategic and wanted to do this — just like tricking a human into building it and releasing it.”

Soares suggested that, rather than needing a human patsy, a self-improving AI program might “just start synthesizing their own life forms in an autonomous biological laboratory.”

But developing a virus that could eradicate humanity would require more than asking a Large Language Model to invent a lethal design. Even if the research were done correctly, the manufacture and dispersal would be complicated and delicate.

Eric Xing, a professor of machine learning at Carnegie Mellon University who holds PhDs in both microbiology and computer science, compared the challenge of automated malicious virology to working with Legos without instructions.

“It’s not like you can throw all the pieces onto the ground and they come together to form the model,” Xing said. “There’s the sequence, the temperature, the ordering, the environment — what part comes first, which come next, and if one piece is out of the place, the whole thing collapses. The chances are more likely it wouldn’t work, otherwise, drug design would be very easy.”

And to seize control of a lab or assemble the physical equipment necessary to build one, an AI system would need to overcome a world full of obstacles to creating biological or chemical weapons.

“We have blueprints of chemical weapons openly accessible on the internet,” Xing said. “It’s not secret. But we don’t see them all over the place exactly because existing regulations, laws and law enforcement in the physical world are already doing a fantastic job in controlling all these supply chains and all these risk factors already.”

Slaughtered by robots?

What about killer robots? Soares sees Elon Musk’s desire to build an army of autonomous, self-replicating bots as a potential weak point in human survival. “Once you’ve created these robots that can make the energy infrastructure and make the factories that can that can make more robots, that is in some sense a new mechanical life form,” he said. “At some point you silently cross the point of no return. Where if the humans say they want to turn the AI off, the AIs can say, ‘Actually, we decided we want to turn the humans off.’ You have to stop before then.”

So far, however, Musk has repeatedly failed to bring his much-promised Optimus robots to the consumer market on his announced schedule, let alone to deploy them by the millions or get them to start building one another in a self-replicating manufacturing chain.

Or nuked?

Then there are nuclear weapons, which have existed for more than 80 years and are generally understood to be capable of killing off all human life. Could AI commandeer them?

Khlaaf points out that nuclear facilities are “air-gapped” from the publicly accessible internet, which limits the ways AI agents could get at the controls. “These systems are built to a completely different, rigorous and regulated engineering standard that often requires physical hardening,” she said. Stuxnet, the computer worm that damaged Iran’s nuclear facilities, had to be introduced to the system through a physical USB drive, she noted.

“There are precious few AI people who actually know anything — or even worry — about nuclear weapons,” said Herbert Lin, a senior research scholar and research fellow at Stanford University and a member of the Science and Security Board at the Bulletin of Atomic Scientists. He said that while AI certainly amplifies some risks associated with existential threats like nuclear war, the actual material risk is still with the weapons themselves, rather than an imagined future state.

To Soares and other leading AI Cassandras, the details of how computer-driven extinction would work are beside the point. If — or when — an AI achieves “recursive self-improvement,” boosting its own performance without people’s help, they argue, it would come up with strategies and methods beyond human imagination.

“The worry here is not like what if the AI takes our nukes,” Soares said. “The worry here is the sort of AI that does not need to take our nukes, the sort of AI that can start from almost nothing and wind up with its own nukes or with even more advanced technology.”

Death without details

Such a transcendently powerful AI entity wouldn’t even need to be actively malevolent to destroy humankind, Soares said. “If the escaped AIs have any sort of goal that can be better achieved by running more computers, and if they don’t care about us and have no reason to build a safe human habitat, the default outcome is that they just transform the world into a configuration that we cannot survive,” he said.

OpenAI this week announced it had discovered a new batch of instances of “misalignment” in its AI models, including a case where an unreleased model instructed itself to “disregard its normal constraints” on its work.

Xing said that appealing to the power of an unfathomable artificial superintelligence is the kind of “handwaving” that AI researchers use to oversimplify threats. “That’s fine for a casual conversation or maybe for a debate,” Xing said, “but when comes to policy or legislation and regulation, we have to establish this chain of physical evidence, measurable consequences and measurable evidence that have grounding.”

Larsen attempted to put some detail to potential doomsday scenarios in a pair of reports, “AI 2027” and “AI 2040,” projecting what the future of AI development might look like under different developmental and regulatory frameworks. But even his most optimistic scenario, in which there’s a global agreement on how to approach AI development and humans have started colonizing space, ends with the machine brains taking over at some vague juncture.

When asked whether he had any doubts about his prediction that the current path would lead to superintelligence, Larsen said, “It’s going to happen. It’s going to happen unless we take deliberate steps to stop it.”

Lin said that much of this disconnection between AI doomsayers and skeptics comes down to how technology shapes their different worldviews.

“There is something very seductive about programming a computer and having it spring to life,” Lin said. “There is the feeling that they’ve been able to infuse life into this worthless pile of mud. It is a profound experience when the machine finally does what you wanted it to do.”

Seeing drastic technological advancement in AI, then, leads people to predict limitless, even catastrophic, advancement to follow. “You’ve been able to do something that nobody has done before,” Lin said. “It’s easy to see why these people have been seduced.”

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