By James Pethokoukis

Despite running a car company trying to build fully autonomous vehicles, Elon Musk has often warned about the dangers of supersmart artificial intelligence that won’t have our best interests at heart. And in pretty dramatic terms. In a 2018 documentary, for instance, Musk spoke about the potential of AI to become “an immortal dictator from which we would never escape.” Humanity stuck forever in a neverending totalitarian North Korea. Not good.

But it could be worse. Turns out Musk now thinks AI is only the second greatest threat to the planet’s current bosses. As the father of six said at a conference back in September, “a lot of people think that there’s too many people on the planet, but I think there’s in fact too few, and that possibly the single greatest risk to human civilization is the rapidly diminishing [population] growth rate.” Later, according to GeekWire, Musk said “he now sees the potential for artificial intelligence to get out of control as the second-biggest threat facing humanity.”

Now I’m not sure how, exactly, Musk makes this calculation. That said, it has a lot going for it. Consider how great economic growth is, a force that has “lifted billions of people out of poverty [and] holds the promise of equally great advances in the future,” writes Stanford University economist Charles I. Jones in “The Past and Future of Economic Growth: A Semi-Endogenous Perspective.”

And not only is lots of economic growth great for people, lots of people are great for economic growth. People produce ideas, and ideas — which can be used by everybody — raise incomes. Jones: “This means that income per person depends on the number of researchers. But then the growth rate of income per person depends on the growth rate of researchers, which is in turn ultimately equal to the growth rate of the population.” Jones is aware of the same fertility trends as Musk, which is why he’s concerned those trends “could even lead to the stagnation of living standards for a vanishing population.”

Of course, these concerns are exactly the opposite of what many people still believe, stuck as they are in the old, 1970s thinking about an impending “population bomb” and such. But they’re wrong. This from the Financial Times:

The UN has slightly downgraded its peak population forecast — to 10.9bn by 2100 — and is already noting that the world population is growing at a slower pace than at any time since 1950 thanks to fast-falling fertility. So many countries have now fallen to or below replacement rates that the majority of population growth from now on “will be concentrated in just nine countries”, says the UN. However look down the list of those nine and you might wonder. One of the main drivers of the growth is supposed to be India. But India’s fertility rate is already down to 2.179. That’s barely over the replacement rate (of 2.1). A study from The Lancet last year suggested that the global population will in fact peak at 9.7bn in the 2060s and be well below 9bn by 2100.

All is not lost. Countries that do lots of research could import more people or create more people. Or we could have the machines do more research for us. Indeed, that’s already happening. For example: Alphabet, parent of Google, recently said it has created a company, Isomorphic Labs, to use AI for drug discovery. The new division was spun out of Alphabet’s AI subsidiary, DeepMind. Here’s how Demis Hassabis, founder and CEO of Isomorphic Labs (and DeepMind), recently described the venture:

Last year DeepMind’s breakthrough AI system AlphaFold2 was recognised as a solution to the 50-year-old grand challenge of protein folding, capable of predicting the 3D structure of a protein directly from its amino acid sequence to atomic-level accuracy. . . . Building on this advance, today, I’m thrilled to announce the creation of a new Alphabet company — Isomorphic Labs — a commercial venture with the mission to reimagine the entire drug discovery process from first principles with an AI-first approach and, ultimately, to model and understand some of the fundamental mechanisms of life. . . . At its most fundamental level, I think biology can be thought of as an information processing system, albeit an extraordinarily complex and dynamic one. Taking this perspective implies there may be a common underlying structure between biology and information science — an isomorphic mapping between the two — hence the name of the company. Biology is likely far too complex and messy to ever be encapsulated as a simple set of neat mathematical equations. But just as mathematics turned out to be the right description language for physics, biology may turn out to be the perfect type of regime for the application of AI.

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