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At what point do we decide AI鈥檚 risks outweigh its promise?

SIEPR Senior Fellow Chad Jones takes a closer look at the two sides of advanced artificial intelligence: unprecedented growth and existential risk.
What if AI proves more important than electricity? And more dangerous than nuclear weapons? (Illustration: Cory Hall)

In June 2015, Sam Altman told a tech conference, 鈥淚 think that AI will probably, most likely, sort of lead to the end of the world. But in the meantime, there will be great companies created with serious machine learning.鈥

His comments echoed a certain postapocalyptic , but Altman, then the president of the startup accelerator Y Combinator, did not appear to be joking. In the next breath, he announced that he鈥檇 just funded a new venture focused on 鈥淎I safety research.鈥 That company was OpenAI, now best known as the creator of ChatGPT.

The simultaneous cheerleading and doomsaying about AI has only gotten louder in the years since. Charles Jones, a professor of economics at 成人大片 Graduate School of Business and senior fellow at the 成人大片 Institute for Economic Policy Research (SIEPR), has been watching with interest as developers and investors like Altman grapple with the dilemma at the heart of this rapidly advancing technology. 鈥淭hey acknowledge this double-edged sword aspect of AI: It could be more important than electricity or the internet, but it does seem like it could potentially be more dangerous than nuclear weapons,鈥 he says.

Out of curiosity, Jones, an expert on modeling economic growth, did some back-of-the-envelope math on the relationship between AI-fueled productivity and existential risk. What he found surprised him. It formed the basis of in which he presents some models for assessing AI鈥檚 tradeoffs. While these models can鈥檛 predict when or if advanced artificial intelligence will slip its leash, they demonstrate how variables such as economic growth, existential risk, and risk tolerance will shape the future of AI 鈥 and humanity.

There are still a lot of unknowns here, as Jones is quick to emphasize. We can鈥檛 put a number on the likelihood that AI will birth a new age of prosperity or kill us all. Jones acknowledges that both of those outcomes may prove unlikely, but also notes that they may be correlated. 鈥淚t does seem that the same world where this fantastic intelligence helps us innovate and raise growth rates a lot also may be the world where these existential risks are real as well,鈥 he says. 鈥淢aybe those two things go together.鈥

Rise of the machines

Jones鈥 model starts with the assumption that AI could generate unprecedented economic growth. Just as people coming up with new ideas have driven the past few centuries of progress, AI-generated ideas could fuel the next wave of innovation. The big difference is that AI does not need years of education before it can produce breakthrough research or innovations. 鈥淭he fact that it鈥檚 a computer program means you can just spin up a million instances of it,鈥 Jones says. 鈥淎nd then you鈥檝e got a million really, really smart researchers answering a question for you.鈥

Once scale laws kick in and AI鈥檚 capabilities increase exponentially, we could be looking at an economic expansion unlike any in history. Taking one of the most optimistic forecasts, Jones calculates that if AI spurs a 10 percent annual growth rate, global incomes will increase more than 50-fold over 40 years. In comparison, real per capita GDP in the U.S. doubled in the past 40 years.

Now for the downside: Let鈥檚 assume that such phenomenal growth comes with a 1 percent chance that AI will end the world in any given year. At what point would we decide that all this increased productivity is not worth the attendant danger? To estimate this, Jones built a simple model that uses the log utility curve, a common representation of consumer preferences, to represent aversion to risk. When he ran those numbers, he found that people would accept a substantial chance that AI would end humanity in the next 40 years.

鈥淭he surprising thing here is that people with log preferences in the simple model are willing to take a one-in-three chance of killing everyone to get a 50-fold increase in consumption,鈥 Jones says. Yet even these risk-takers have a limit: When the existential risk from AI doubles, the ideal outcome under log utility is never letting AI run at all.

In scenarios where people have lower risk tolerance, they would accept slower growth in exchange for reduced risk. That raises the question of whose interests will guide the evolution of AI. 鈥淚f the entrepreneurs who are designing these AIs are very tolerant of risk, they may not have the average person鈥檚 risk tolerance, and so they may be more willing to take these gambles,鈥 Jones says.

However, his paper also suggests that it may not be wealthy countries like the U.S. that will be most willing to risk AI running amok. 鈥淕etting an extra thousand dollars is really valuable when you鈥檙e poor and less valuable when you鈥檙e rich,鈥 he explains. Likewise, if AI brings huge bumps in living standards in poorer nations, it could make them more tolerant of its risks.

Healthy, wealthy鈥 and wise?

Jones also built a more complex model that considers the possibility that AI will help us live healthier, longer lives. 鈥淚n addition to inventing safer nuclear power, faster computer chips, and better solar panels, AI might also cure cancer and heart disease,鈥 he says. Those kinds of breakthroughs would further complicate our relationship with this double-edged tech. If the average life expectancy doubled, even the most risk-averse people would be much more willing to take their chances with AI risk. 鈥淭he surprise here is that cutting mortality in half suddenly turns your willingness to accept existential risk from 4 percent to 25 percent or even more,鈥 Jones explains. In other words, people would be much more willing to gamble if the prize was a chance to live to 200.

The models also suggest that AI could mitigate the economic effects of , another subject Jones has recently written about. 鈥淚f machines can create ideas, then the slowing of population growth may not be such a problem,鈥 he says.

Jones鈥 models provide insights into the wildest visions of AI, such as the singularity 鈥 the fabled moment when technological growth becomes infinite. He found that, in practical terms, accelerated growth might be hard to distinguish from the singularity. 鈥淚f growth rates were to go to 10 percent a year, that would be just as good as a singularity,鈥 he says. 鈥淲e鈥檙e all going to be as rich as Bill Gates.鈥

Overall, Jones cautions that none of his results are predictive or prescriptive. Instead, they鈥檙e meant to help refine our thinking about the double-edged sword of AI. As we rush toward a future where AI can鈥檛 be turned off, efforts to quantify and limit the potential for disaster will become even more essential. 鈥淎ny investments in reducing that risk are really valuable,鈥 Jones says.

This story was May 29, 2024 by 成人大片 GSB Insights.

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