Automated Ethics

Bridle-drone

Tom Chatfield in Aeon:

Back in August 2012, Google announced that it had achieved 300,000 accident-free miles testing its self-driving cars. The technology remains some distance from the marketplace, but the statistical case for automated vehicles is compelling. Even when they’re not causing injury, human-controlled cars are often driven inefficiently, ineptly, antisocially, or in other ways additive to the sum of human misery.

What, though, about more local contexts? If your vehicle encounters a busload of schoolchildren skidding across the road, do you want to live in a world where it automatically swerves, at a speed you could never have managed, saving them but putting your life at risk? Or would you prefer to live in a world where it doesn’t swerve but keeps you safe? Put like this, neither seems a tempting option. Yet designing self-sufficient systems demands that we resolve such questions. And these possibilities take us in turn towards one of the hoariest thought-experiments in modern philosophy: the trolley problem.

In its simplest form, coined in 1967 by the English philosopher Philippa Foot, the trolley problem imagines the driver of a runaway tram heading down a track. Five men are working on this track, and are all certain to die when the trolley reaches them. Fortunately, it’s possible for the driver to switch the trolley’s path to an alternative spur of track, saving all five. Unfortunately, one man is working on this spur, and will be killed if the switch is made.

In this original version, it’s not hard to say what should be done: the driver should make the switch and save five lives, even at the cost of one. If we were to replace the driver with a computer program, creating a fully automated trolley, we would also instruct it to pick the lesser evil: to kill fewer people in any similar situation. Indeed, we might actively prefer a program to be making such a decision, as it would always act according to this logic while a human might panic and do otherwise.

More here.