Distributing Blame Among Multiple Entities When Autonomous Technologies Cause Harm

Abstract

As autonomous technology emerges, new variations in old questions arise. When autonomous technologies cause harm, who is to blame? The current studies compare reactions toward harms caused by human-controlled vehicles (HCVs) or human soldiers (HSs) to identical harms by autonomous vehicles (AVs) or autonomous robot soldiers. Drivers of HCVs, or HSs, were blamed more than mere users of AVs or HSs who outsourced their duties to ARSs. However, as human drivers/soldiers became less involved in (or were unaware of the preprogramming that led to) the harm, blame was redirected toward other entities (i.e., manufacturers and the tech company's executives), showing the opposite pattern as human drivers/soldiers. Results were robust to how blame was measured (i.e., degrees of blame versus apportionment of total blame). Overall, this research furthers the blame literature, raising questions about why, how (much), and to whom blame is assigned when multiple agents are potentially culpable.

Keywords: autonomous robots; autonomous vehicles; blame allocation; intentionality.