Learning from Automation in Targeting to Better Regulate Autonomous Weapon Systems: Target Lists, the Electronic Battlefield and Automation in Mines

Abstract

Autonomous weapon systems (AWS) are an emerging technology not currently subject to any specific regulation. This article examines the nature of automation in pre-cursor technologies for three different aspects of AWS to determine regulatory best practices that can be applied to these systems. Automation in target selection is explored in the context of pre-determined target lists, which function in similar ways to entering targets into the memory of an AWS. Automation in target engagement is considered using an example of ‘The Electronic Battlefield’ from the Vietnam War that, despite the less capable technologies of the time, demonstrates key elements of how AWS operate. The absence of human involvement is considered in relation to two types of mines that have been regulated on the international level and evaluates dimensions of control that could be useful to apply to AWS. Conclusions about automation for each aspect are used to determine best practices for regulating use of AWS. From these best practices, an outline of a legally required minimum level of human control is also developed.