What’s happening: In a recent MIT study, thousands of participants were asked whether an AV should kill a driver or a pedestrian, a homeless man or an executive, and so on, sorting people into categories as specific as male athlete, female doctor, small child, or baby in a stroller.
- Participants' choices were assembled into a preference scale, ranking who is most preferable to spare or kill.
- This study and earlier research have been widely publicized as capturing essential ethical insights that should be built into AVs.
The National Science Foundation, meanwhile, funded a group of philosophers working on computer modeling of how AVs could respond to different scenarios, depending on their ethical coding.
Between the lines:
- There is no evidence that human drivers encounter instant decisions between two fatal outcomes with no alternative options. Programming AVs to anticipate such scenarios would not improve safety.
- "Driverless dilemmas" mischaracterize AV capabilities. It's unlikely an AV could detect personal details, let alone a person's profession. Instead, AVs are being taught to track everything around them, and swerve or slow down to avoid hitting anyone.
- Publicity of this research could be contributing to public distrust of AVs. It suggests that AVs will be unrealistically influenced by the ethics of their developers.
Yes, but: While AVs are not likely to face forced-choice ethical dilemmas, they may be taught to prioritize detecting and avoiding vulnerable road users, like pedestrians, over stationary objects, like parked cars.
- In that sense, ethical choices would factor into programming, but in a context that aligns with how people are taught to drive in order to avoid harm.
Sam Anthony is co-founder and CTO of Perceptive Automata. Julian De Freitas is a doctoral candidate in psychology at Harvard University.
Go deeper: Read the full paper responding to driverless dilemmas.
