AI devices and liability

We propose a new theoretical framework to analyze the incentives provided by different allocations of liability in the case of (semi)autonomous devices which are a source of risk of accident. We consider three key agents, an AI provider (scientist), a producer and a consumer, and look at the effect of different rules of sharing liability on the decision making of each type of agent. In addition we test the theoretical predictions in an original lab experiment. We show that liability on the scientist and the producer is efficient in reducing their misbehaviors. We also find that liability on the consumer increases her incentives to control the risk of an accident (in case of a semi-autonomous device). However, the absence of consumer’s control (full autonomous device) and liability decreases the consumer’s propensity to buy the good. We complete our study by making a social welfare analysis. It highlights the importance of letting the producer liable in order to provide the consumer with confidence in the technology, especially in the case of a full autonomy of the good.