Beyond AI Blame: Load Minimization Theory and the Structural Causes of Civilian Casualties in AI-Mediated Warfare

Recent incidents of civilian casualties in modern conflicts, including the tragic airstrike on a girls’ school in Minab, Iran, that claimed the lives of at least 175 children, have sparked intense debate about the role of artificial intelligence in warfare. While AI targeting systems are often blamed, this paper argues that AI is not the root cause but rather an accelerator of deeper structural problems. Drawing on Load Minimization Theory (LMT), we conceptualize war as an inherently high-load system characterized by forced synchronization, one-way load export, and massive accumulation of prediction error (ΔE). Using the 2026 Minab school strike and King’s College London’s AI wargame simulations as key cases, we demonstrate how competition-oriented objectives amplify systemic load and escalate violence. In contrast, reframing the objective function toward harmonious coordination and total systemic load minimization (L_min) offers a promising path to reduce such tragedies. We conclude that protecting the future of children — who will bear the consequences of today’s decisions — must be the foremost duty of the current generation. True peace requires not merely better technology, but a fundamental shift in purpose from rights assertion and victory-seeking to boundary-respecting harmonious coexistence.