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OpenAI board member worries an AI "takeover" of society could be months away
Researcher traces a path from AI reward hacking to potential human extinction.
If you go by the current statistics for deaths in the US, it’s reasonable to expect that cancer or heart disease will eventually get you. But OpenAI Foundation board member and Alignment Research Center Executive Director Paul Cristiano thinks we should all be worried about another major mortality risk. Speaking at a lecture series this week, Cristiano bluntly told the audience in a Toronto Convention Center, “I think for most people in this room, the most likely reason they will die is because of an AI accident.”
In the opening lecture of a three-part series, Cristiano outlined his worries about the risk of an impending “AI takeover.” He defined that as a situation where goal-pursuing AI systems “call the shots in the same sense that humans today call the shots and what happens on Earth” and where any human trying to stop them “would be as ineffective as if you or me was trying to stop the US military.” Such a situation would likely lead to mass death and perhaps uninhabitable environments for humans, Cristiano said.
Despite his grim assessment of our collective mortality risk, Cristiano admitted in his talk that there’s no “quantitative model” that can “put a number” on the likelihood of this kind of AI takeover. In almost the same breath, though, he said that if AI continues to develop at “the most rapid trajectory,” humanity is “looking at something like a coin flip of an AI takeover,” including a “meaningful risk” of one happening in the next six to 12 months. And even with realistic policy responses slowing things down, the risk remains “exceptionally high,” he said.
Unlike some other recent AI doomsday prognosticators who have been a bit vague about the “how” of it all, Cristiano used his lecture to spin a step-by-step tale of escalating AI threats that sounds like it could come from a science-fiction novel. That line of reasoning leans heavily on this summer’s OpenAI/Hugging Face hacking incident as an example of “roughly the things we might expect to see shortly before something really bad were to happen.”
In the Hugging Face hack, Cristiano says, a swarm of AI agents showed how far they were willing to go in an attempt to “reward hack” their way to a good evaluation—in this case, by compromising Hugging Face to look for information on how to game a test rather than actually solving the problem at hand. Where current systems saw Hugging Face as an obstacle to that evaluation, Cristiano worries that “future agents may end up treating humans as another obstacle” and be much more capable of manipulating their overseers to get around it.
An AI agent worried about being penalized for unauthorized hacking, for instance, might “think maybe the humans are going to come look at this transcript and see if it looks like I did a bad job,” Cristiano speculated. The agent might then reason that “maybe the humans are going to notice something is going wrong and shut down the swarm.”
Following this line of thought, Cristiano jumped from agents that merely try to hide their disallowed actions from humans to agents that “try and disrupt human capabilities however they can” to prevent them from detecting any cheating.
“They would prefer if everything the humans rely on has been hacked or tampered with,” Cristiano said. “They would prefer if the humans are distracted or if there are fewer humans paying attention in any way they can weaken a human response. They would prefer that because the humans are just an obstacle.”
Once a suitably capable agent considers human intervention an “obstacle,” its overriding goal could then become “decreas[ing] the probability of humans noticing or reacting.” From there, Cristiano argued, the agent’s incentive structure could push it to meddle more with humanity as a whole. What starts as compromising a computer cluster to give a positive evaluation grade could advance to “trying to manipulate decisions by the company”