A self-driving taxi has no passengers, so it parks itself in a lot to reduce congestion and air pollution. After being hailed, the taxi heads out to pick up its passenger—and tragically strikes a pedestrian in a crosswalk on its way.
Who or what deserves praise for the car’s actions to reduce congestion and air pollution? And who or what deserves blame for the pedestrian’s injuries?
One possibility is the self-driving taxi’s designer or developer. But in many cases, they wouldn’t have been able to predict the taxi’s exact behavior. In fact, people typically want artificial intelligence to discover some new or unexpected idea or plan. If we know exactly what the system should do, then we don’t need to bother with AI.
Alternatively, perhaps the taxi itself should be praised and blamed. However, these kinds of AI systems are essentially deterministic: Their behavior is dictated by their code and the incoming sensor data, even if observers might struggle to predict that behavior. It seems odd to morally judge a machine that had no choice.
According to many modern philosophers, rational agents can be morally responsible for their actions, even if their actions were completely predetermined—whether by neuroscience or by code. But most agree that the moral agent must have certain capabilities that a self-driving taxi almost certainly lacks, such as the ability to shape its own values. AI systems fall in an uncomfortable middle ground between moral agents and nonmoral tools.
As a society, we face a conundrum: It seems that no one, or no one thing, is morally responsible for the AI’s actions—what philosophers call a responsibility gap. Present-day theories of moral responsibility simply do not seem appropriate for understanding situations involving autonomous or semiautonomous AI systems.
If current theories will not work, then perhaps we should look to the past—to centuries-old ideas with surprising resonance today.
