Normative Epistemology for Lethal Autonomous Weapons Systems
This work addresses the problem of ensuring systematic and evaluable design for LAWS, which is incremental as it adapts existing epistemological concepts to a specific domain.
The paper tackles the challenge of designing and evaluating Lethal Autonomous Weapons Systems (LAWS) by applying epistemic frameworks, such as Bayesian virtue epistemology, to guide actions under uncertainty and meet legal and ethical requirements like Article 36 reviews.
The rise of human-information systems, cybernetic systems, and increasingly autonomous systems requires the application of epistemic frameworks to machines and human-machine teams. This chapter discusses higher-order design principles to guide the design, evaluation, deployment, and iteration of Lethal Autonomous Weapons Systems (LAWS) based on epistemic models. Epistemology is the study of knowledge. Epistemic models consider the role of accuracy, likelihoods, beliefs, competencies, capabilities, context, and luck in the justification of actions and the attribution of knowledge. The aim is not to provide ethical justification for or against LAWS, but to illustrate how epistemological frameworks can be used in conjunction with moral apparatus to guide the design and deployment of future systems. The models discussed in this chapter aim to make Article 36 reviews of LAWS systematic, expedient, and evaluable. A Bayesian virtue epistemology is proposed to enable justified actions under uncertainty that meet the requirements of the Laws of Armed Conflict and International Humanitarian Law. Epistemic concepts can provide some of the apparatus to meet explainability and transparency requirements in the development, evaluation, deployment, and review of ethical AI.