فراتر از خطای الگوریتم: بازاندیشی مسئولیت در سامانه‌های هوش مصنوعی نظامی (مطالعه موردی حادثه میناب)

The growing use of artificial intelligence (AI) systems in military operations has raised new legal and ethical questions concerning responsibility for errors and consequences arising from their deployment. The attack on the Shajareh Tayyebeh School in Minab, during the military strikes conducted by the United States and Israel against Iran, resulted in the deaths of approximately 168 schoolchildren. Although media reports and expert analyses have suggested the possible involvement of AI-based systems in the targeting process or related failures, no official or independently verifiable evidence has confirmed their use. Using a descriptive-analytical method and a case-study approach, this article examines whether attributing the incident to an "AI error" is consistent with international humanitarian law and contemporary frameworks of legal responsibility, and assesses the implications of this narrative for attributing responsibility to human and organizational actors.
The theoretical framework is based on the concepts of the responsibility gap, networked causation, risk-creation theory, meaningful human control, and networked responsibility. The analysis demonstrates that, even assuming AI systems were involved in the targeting process, the incident cannot be reduced to an algorithmic error. Instead, it should be understood as the outcome of a complex decision-making process in which system designers, data providers, operators, military commanders, and institutional structures may each bear a share of legal responsibility.
The originality of this study lies in proposing networked responsibility as an analytical framework for understanding the distribution of responsibility in complex AI-enabled military systems while emphasizing the need to preserve and strengthen meaningful human control over the use of force. It argues that reducing such incidents to an "AI error," without examining the available evidence, decision-making structures, and the roles of human actors, risks obscuring human and institutional accountability and undermining legal accountability.