Autonomous Cyber Weapons as AI-Enabled Digital Harms: A Platform Accountability Framework

Abstract

Governments govern AI-generated online harms from commercial platforms (EU DSA, AI Act, UK Online Safety Act), yet the most severe class remains ungoverned: autonomous cyber weapons (ACWs) deployed by nation-states against civilian infrastructure. We address this gap with three contributions: a digital-harm taxonomy (six ACW modes $\times$ five harm categories); the Meaningful Human Control (MHC) Model, a governance-compliance function with a closed-form IHL threshold and a proved weight-sensitivity bound; and a platform accountability architecture with treaty language grounded in ARSIWA state-responsibility doctrine, not Rome Statute individual responsibility. Applied to eleven documented state-attributed operations and one hypothetical defensive AI system, every documented case falls in an accountability vacuum; the threshold is target-dependent, and against wholly civilian targets no system studied clears it, including the hypothetical. Three further incidents are correctly excluded on autonomy/attribution grounds, a discriminant-validity check. The weights and threshold parameters are illustrative, not fitted.

arXiv comment15 pages, 2 figures. Presented at the 2026 IDeaS Conference (Carnegie Mellon University)