The solution, then, is to change the way we think about A.I. Instead of building machines that exist to achieve their objectives, we want a model that looks like this:

“Machines are beneficial to the extent that their actions can be expected to achieve our objectives.”

This fix might seem small, but it is crucial. Machines that have our objectives as their only guiding principle will be necessarily uncertain about what these objectives are, because they are in us — all eight billion of us, in all our glorious variety, and in generations yet unborn — not in the machines.

Uncertainty about objectives might sound counterproductive, but it is actually an essential feature of safe intelligent systems. It implies that no matter how intelligent they become, machines will always defer to humans. They will ask permission when appropriate, they will accept correction, and, most important, they will allow themselves to be switched off — precisely because they want to avoid doing whatever it is that would give humans a reason to switch them off.

Once the focus shifts from building machines that are “intelligent” to ones that are “beneficial,” controlling them will become a far easier feat. Consider it the difference between nuclear power and nuclear explosions: a nuclear explosion is nuclear power in an uncontrolled form, and we greatly prefer the controlled form.

Of course, actually putting a model like this into practice requires a great deal of research. We need “minimally invasive” algorithms for decision making that prevent machines from messing with parts of the world whose value they are unsure about, as well as machines that learn more about our true, underlying preferences for how the future should unfold. Such machines will then face an age-old problem of moral philosophy: how to apportion benefits and costs among different individuals with conflicting desires.

All this could take a decade to complete — and even then, regulations will be required to ensure provably safe systems are adopted while those that don’t conform are retired. This won’t be easy. But it’s clear that this model must be in place before the abilities of A.I. systems exceed those of humans in the areas that matter.

If we manage to do that, the result will be a new relationship between humans and machines, one that I hope will enable us to navigate the next few decades successfully.

If we fail, we may face a difficult choice: curtail A.I. research and forgo the enormous benefits that will flow from it, or risk losing control of our own future.

Some skeptics within the A.I. community believe they see a third option: continue with business as usual, because superintelligent machines will never arrive. But that’s as if a bus driver, with all of humanity as passengers, said, “Yes, I’m driving as fast as I can toward a cliff, but trust me, we’ll run out of gas before we get there!” I’d rather not take the risk.

Stuart Russell is the author of “Human Compatible: Artificial Intelligence and the Problem of Control.”

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