Liability for Robots

Francesco Parisi (University of Minnesota)


In robot torts, robots carry out activities that are partially controlled by a human operator. The care of the operator and the prospective victim can reduce the likelihood of an accident. The problem for a policymaker is to design liability regimes that incentivize both the operator’s and victim’s optimal care, while inducing manufacturers to improve the safety of robots by internalizing the expected cost of non-negligent accidents. In this paper, we suggest the possibility of blending negligence-based rules for robot operators and their potential victims, and strict liability rules robots by manufacturers, to create care incentives and R&D incentives for developing safer robots. We refer to these regimes as rules of “manufacturer residual liability.” By making both operators and victims liable for accidents due to their negligence, the rule incentivizes them to act diligently. Moreover, by making the manufacturers residually liable for non-negligent accidents, the rule incentivizes optimal investments in R&D for robots’ safety. In turn, this will minimize the market price of safer robots, driving unsafe technology out of the market. Thanks to the percolation effect of residual liability, operators (and victims) will also be incentivized to adopt optimal activity levels in robots’ usage.

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