Cardozo Law Review
Harry Surden and Mary-Anne Williams, Technological Opacity, Predictability, and Self-Driving Cars, 38 Cardozo L. Rev. 121 (2016), available at https://scholar.law.colorado.edu/faculty-articles/24.
Autonomous or “self-driving” cars are vehicles that drive themselves without human supervision or input. Because of safety benefits that they are expected to bring, autonomous vehicles are likely to become more common. Notably, for the first time, people will share a physical environment with computer-controlled machines that can both direct their own activities and that have considerable range of movement. This represents a distinct change from our current context. Today people share physical spaces either with machines that have free range of movement, but are controlled by people (e.g. automobiles) or with machines that are controlled by computers, but highly constrained in their range of movement (e.g. elevators). The movements of today’s machines are thus broadly predictable. The unrestricted, computer-directed movement of autonomous vehicles is an entirely novel phenomenon that may challenge certain unarticulated assumptions in our existing legal structure.
Problematically, the movements of autonomous vehicles may be less predictable to the ordinary people who will share their physical environment—such as pedestrians—than the comparable movements of human-driven vehicles. Today, a great deal of physical harm that might otherwise occur is likely avoided through humanity’s collective ability to predict the movements of other people. In anticipating the behavior of others, we employ what psychologists call a “theory of mind.” Theory of mind cognitive mechanisms allow us to extrapolate from our own internal mental states in order to estimate what others are thinking or likely to do. These cognitive systems allow us to make instantaneous, unconscious judgments about the likely actions of people around us, and therefore, to keep ourselves safe in the driving context. However, the theory of mind mechanisms that allow us to accurately model the minds of other people and interpret their communicative signals of attention and intention will be challenged in the context of non-human, autonomous moving entities such as self-driving cars.
This Article explains in detail how self-driving vehicles work and how their movements may be hard to predict. It then explores the role that law might play in fostering more predictable autonomous moving systems such as self-driving cars, robots, and drones.
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