Edited by Ryan Calo, A. Michael Froomkin and Ian Kerr
Chapter 2: Allocating the risk of physical injury from “sophisticated robots”: Efficiency, fairness, and innovation
AbstractAs they become increasingly mobile, sophisticated robots will transform the way we live. They will have higher levels of connectivity, autonomy, and intelligence. They will also have the potential to cause serious bodily harm to individuals. The existing legal system is an efficient, fair system to provide compensation to those injured by robots and correctly balances the need for innovation with the concern for physical safety. The chapter first discusses the need for technological innovation and summarizes current approaches to safety design. Currently, liability law attempts to balance the concern for physical safety with the desire for innovation. It does so by making sellers liable for injuries caused by a failure to use a safer approach where it costs less than the injuries it prevents. Sophisticated robots undoubtedly present difficulties for allocating responsibility for injuries on the basis of fault. Robots may have emergent or unpredictable learned behavior, interconnection with other sophisticated technology and systems, and use technology made from multiple suppliers of hardware and software. These issues can be addressed by current legal doctrines through existing liability analysis and supported by the use of expert testimony. The author recommends that innovators should design machines with product safety analyses in mind, provide warnings, push for both private and governmental standards, and decide on the appropriate mix of product liability insurance and self-insurance for their products. Proposals for alternative systems, such as no-fault insurance schemes or limiting liability through immunity or pre-emption, assume that the current system is problematic and that it should be addressed in a way that abandons the concern for balance. The current liability-based system for product-caused injury is balanced, fair, efficient, and flexible enough to adapt to the increased sophistication of robots.
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