Risks and Control Measures for Building Trustworthy Autonomous Weapon Systems

Abstract

This research examines the risks and control measures associated with building trustworthy Autonomous Weapon Systems (AWS), a rapidly evolving technology with various implications for military operations and international security. While AWS present advantages in precision and efficiency, they also imply operational, technical, and ethical challenges. Through a comprehensive analysis of relevant studies, this article identifies key risks inherent in AWS development, including algorithmic biases, unintended engagements, and cyber security vulnerabilities. For these, control measures are proposed to mitigate and avoid them, such as advanced fail-safe mechanisms, multi-layered human oversight protocols, and robust cyber security solutions. Particular attention is given to the role of meaningful human control as a fundamental mechanism for enhancing AWS trustworthiness without compromising operational effectiveness. The findings highlight the need for a dynamic, proactive, multidisciplinary risk-based approach to AWS development as trustworthy systems, emphasising the importance of international collaboration in establishing standardised risk assessment methodologies, trustworthiness benchmarks, and certification processes. Moreover, by systematically analysing both risks and control measures, this research provides a design framework for addressing the complex challenges of building trustworthy AWS in the context of evolving warfare technologies.