Normative Epistemology for Lethal Autonomous Weapons Systems

TL;DR

This paper explores how epistemic models can guide the design, evaluation, and deployment of Lethal Autonomous Weapons Systems, emphasizing systematic review, justification under uncertainty, and transparency in ethical AI development.

Contribution

It introduces a Bayesian virtue epistemology framework to improve justification, transparency, and systematic review processes for LAWS based on epistemic principles.

Findings

Proposes a Bayesian virtue epistemology for LAWS

Suggests epistemic models improve review and transparency

Highlights role of epistemology in ethical AI deployment

Abstract

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.