Supporting Ethical Decision-Making for Lethal Autonomous Weapons

This article describes a new and innovative methodology for calibrating trust in ethical actions by Lethal Autonomous Weapon Systems (LAWS). For the foreseeable future, LAWS will require human operators for mission planning, decision-making, and supervisory control; yet humans lack the cognitive bandwidth and processing speed to make prompt, real-time ethical decisions. As a result, trustworthy Artificial Intelligence (AI) will be required to support ethical decision-making. We use a Bayesian ethical decision model for: (1) human setting of ethical preferences and thresholds in accordance with Laws of War and tactical criteria; and (2) highlighting the factors that contribute to strike/no-strike recommendations for human evaluation. The model can perform an ethical analysis, provide a quantitative ethical strike/no-strike score, and recommend actions to reduce decision uncertainty. In this article, we describe successful initial evaluation trials of the Bayesian model and of a human interface for interaction with the model. Our Bayesian ethical decision model has an immediate application in wargames; the model can also be used to train operators in understanding the principles and key factors relevant to ethical decision-making; and it may eventually be used in actual military operations employing LAWS.