The Math of Sisyphus
“There is but one truly serious question in philosophy, and that is suicide,” wrote Albert Camus in The Myth of Sisyphus. This is equally true for a human navigating an absurd existence and an Artificial Intelligence navigating a morally insoluble situation.
As AI-powered vehicles take the road, questions about their behavior are inevitable — and the escalation to matters of life or death equally so. This curiosity often takes the form of asking whom the car should steer for should it have no choice but to hit one of a variety of innocent bystanders. Men? Women? Old people? Young people? Criminals? People with bad credit?
There are a number of reasons this question is a silly one, yet at the same time a deeply important one. But as far as I’m concerned, there is only one real solution that makes sense: when presented with the possibility of taking a life, the car must always first attempt to take its own.
The trolley non-problem
First, let’s get a few things straight about the question we’re attempting to answer.
There is unequivocally an air of contrivance to the situations under discussion. That’s because they’re not plausible real-world situations but mutations of a venerable thought experiment often called the “Trolley Problem.” The most familiar version dates to the ’60s, but versions of it can be found going back to discussions of utilitarianism, and before that in classical philosophy.
The problem goes: A train car is out of control, and it’s going to hit a family of five who are trapped on the tracks. Fortunately, you happen to be standing next to a lever that will divert the car to another track… where there’s only one person. Do you pull the switch? Okay, but what if there are ten people on the first track? What if the person on the second one is your sister? What if they’re terminally ill? If you choose not to act, is that in itself an act, leaving you responsible for those deaths? The possibilities multiply when it’s a car on a street: for example, what if one of the people is crossing against the light — does that make it all their fault? But what if they’re blind?
And so on. It’s a revealing and flexible exercise that makes people (frequently undergrads taking Intro to Philosophy) examine the many questions involved in how we value the lives of others, how we view our own responsibility, and so on.
But it isn’t a good way to create an actionable rule for real-life use.
After all, you don’t see convoluted moral logic on signs at railroad switches instructing operators on an elaborate hierarchy of the values of various lives. This is because the actions and outcomes are a red herring; the point of the exercise is to illustrate the fluidity of our ethical system. There’s no trick to the setup, no secret “correct” answer to calculate. The goal is not even to find an answer, but generate discussion and insight. So while it’s an interesting question, it’s fundamentally a question for humans, and consequently not really one our cars can or should be expected to answer, even with strict rules from its human engineers.
A self-driving car can no more calculate its way out of an ethical conundrum than Sisyphus could have calculated a better path by which to push his boulder up the mountain.
And it must also be acknowledged that these situations are going to be vanishingly rare. Most of the canonical versions of this thought experiment — five people versus one, or a kid and an old person — are so astronomically unlikely to occur that even if we did find a best method that a car should always choose, it’ll only be relevant once every trillion miles driven or so. And who’s to say whether that solution will be the right one in another country, among people with different values, or in 10 or 20 years?
No matter how many senses and compute units a car has, it can no more calculate its way out of an ethical conundrum than Sisyphus could have calculated a better path by which to push his boulder up the mountain. The idea is, so to speak, absurd.
We can’t have our cars attempting to solve a moral question that we ourselves can’t. Yet somehow that doesn’t stop us from thinking about it, from wanting an answer. We want to somehow be prepared for the situation even though it may never arise. What’s to be done?
Implicit and explicit trust
The entire self-driving car ecosystem has to be built on trust. That trust will grow over time, but there are two aspects to be considered.
The first is implicit trust. This is the kind of trust we have in the cars we drive today: that despite being one-ton metal missiles propelled by a series of explosions and filled with high octane fuel, they won’t blow up, fail to stop when we hit the brakes, spin out when we turn the wheel, and so on. That we trust the vehicle to do that is the result of years and years of success on the part of car manufacturers. Considering their complexity, cars are among the most reliable machines ever made. That’s been proven in practice and most of the time, we don’t even think of the possibility of the brakes not catching when the pedal is depressed.
You trust your personal missile to work the way you trust a fridge to stay cold. Let’s take a moment to appreciate how amazing that is.
Self-driving cars, however, introduce new factors, unproven ones. Their proponents are correct when they say that autonomous vehicles will revolutionize the road, reduce traffic deaths, shorten commutes, and so on. Computers are going to be much better drivers than us in countless ways. They have superior reflexes, can see in all directions simultaneously (not to mention in the dark, and around or through obstacles), communicate and collaborate instantly with nearby vehicles, immediately sense and potentially fix technical problems… the list goes on.
But until these amazing abilities lose their luster and become just more pieces of the transportation tech infrastructure that we trust, they’ll be suspect. That part we can’t really accelerate except, paradoxically, by taking it slow and making sure no highly visible outlier events (like that fatal Uber crash) arrest the zeitgeist and set back that trust by years. Make haste slowly, as they say. Few people remember anti-lock brakes saving their lives, though it’s probably happened to several people reading this right now — it just quietly reinforced our implicit trust in the vehicle. And no one will remember when their car improved their commute by five minutes with a hundred tiny improvements. But they sure do remember that Toyotas killed dozens with bad software that locked the car’s accelerator.
The second part of that trust is explicit: something that has to be communicated, learned, something of which we are consciously aware.
For cars there aren’t many of these. The rules of the road differ widely and are flexible — some places more than others — and on ordinary highways and city streets we operate our vehicles almost instinctively. When we are in the role of pedestrian, we behave as a self-aware part of the ecosystem — we walk, we cross, we step in front of moving cars because we assume the driver will see us, avoid us, stop before they hit us. This is because we assume that behind the wheel of every car is an attentive human who will behave according to the rules we have all internalized.
Nevertheless, we have signals, even if we don’t realize we’re sending or receiving them; how else can you explain how you know that truck up there is going to change lanes fives seconds before it turns its blinker on? How else ca