Toward a Physics of Interdependence for Autonomous Human-Machine Systems: The Case of the Uber Fatal Accident, 2018

Abstract

Computational autonomy has begun to receive significant attention, but neither the theory nor the physics is sufficiently able to design and operate an autonomous human-machine team or system (HMS). In this physics-in-progress, we review the shift from laboratory studies, which have been unable to advance the science of autonomy, to a theory of autonomy in open and uncertain environments based on autonomous human systems along with supporting evidence in the field. We attribute the need for this shift to the social sciences being primarily focused on a science of individual agents, whether for humans or machines, a focus that has been unable to generalize to new situations, new applications, and new theory. Specifically, the failure of traditional systems predicated on the individual to observe, replicate, or model what it means to even be the social is at the very heart of the impediment to be conquered and overcome as a prelude to the mathematical physics we explore. As part of this review, we present case studies but with a focus on how an autonomous human system investigated the first self-driving car fatality; how a human-machine team failed to prevent that fatality; and how an autonomous human-machine system might approach the same problem in the future. To advance the science, we reject the aggregation of independence among teammates as a viable scientific approach for teams, and instead explore what we know about a physics of interdependence for an HMS. We discuss our review, the theory of interdependence, and we close with generalizations and future plans.