Problem of (In)Explainability in Testing Fully Autonomous Weapon Systems for International Humanitarian Law Compliance
Fully autonomous weapon systems need to comply with International Humanitarian Law and underlying ethical principles. This requires the ability to recognize not only objects or persons to be targeted but also protected persons or objects. Such sophisticated object classification abilities, if achievable at all, would have to utilize machine learning techniques. These come with well-known limitations to predictability, reliability and explainability. This article argues such limitations could be
Record details
Published: 10 July 2026
Source: Minds and Machines
Category: Research
Topics: Regulation · Military & security · Transparency
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
TRACE-CTI: Auditable Post-Extraction Governance of TTP Claims with Knowledge Graphs
arXiv cs.AI · 27 July 2026
A First Look at Coding Agents' Compliance with AI Contribution Rules in Open-Source Communities
arXiv cs.AI · 29 July 2026
CEDAR-42001: From ISO/IEC 42001 Conformity to Architecture-Aware, Audit-Visible Assurance Posture for AI Cyber-Physical Systems
arXiv · 19 June 2026
Didact: A Cross-Domain Capability Discovery System for Defence
arXiv · 5 June 2026
Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework
arXiv · 4 June 2026
enclawed: A Configurable, Sector-Neutral Hardening Framework for Single-User AI Assistant Gateways
arXiv · 18 April 2026
How to cite this record
ethics.ai (10 July 2026), “Problem of (In)Explainability in Testing Fully Autonomous Weapon Systems for International Humanitarian Law Compliance,” evidence record 1968, https://ethics.ai/record/1968 (originally published by Minds and Machines).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.