When U.S. forces bombed the Shajareh Tayyebeh elementary school in Minab, southern Iran, on February 28, 2026, at least 160 people died, most of them children. The attack caused international outrage and brought the question of responsibility in modern warfare into sharp focus. Because AI in war creates a new excuse: those responsible can hide behind systems, ultimately blaming them themselves.
Those in charge hide behind technology.
But instead of taking responsibility, the familiar struggle for Primacy of interpretation. Donald Trump initially blamed Iran itself. This was followed by an investigation into the incident, during which the available video material was likely examined more closely. Footage that clearly shows the impact of a Patriot missile in slow motion.
When there was nothing left to relativize and the evidence was overwhelming, data errors, artificial intelligence, and systems like Palantir Technologies' mavens take to the stage. That sounded modern, technical, almost neutral. And therein lies the problem. Because while we talk about AI in war, those responsible are increasingly hiding behind these systems: those who draw up lists, those who build AI, those who approve attacks.
The error is not in the AI, but in the system
Minab was never about an AI suddenly going rogue. It's more about a military system that accelerates decisions, standardizes checks, and distributes responsibility across databases, interfaces, and process chains. The Palantir Maven Smart System, or MSS, is built precisely for this form of warfare: a platform that merges data from satellite imagery, sensors, and other intelligence sources to accelerate target detection and military decision-making.
Not one Language model hat also the school of Minab as the target. Rather, the research suggests that a longest-standing entry in a military database was never properly corrected, even though the building has been considered a School recognizable. So the real disaster didn't begin in an „intelligent“ system that made a mistake. It began in a system optimized for speed and in which a inaccurate data situation can become deadly. Anyone who speaks of an AI error here is no longer talking about those who build such systems and profit from them, about those who feed them data, and about those who ultimately authorize the attack.
No AI slip-up, but a predictable system error
What's truly disturbing about the case isn't that a system knew too much. It's that it knew too little. corrected was. Because the building was in a database of Defense Intelligence Agency, which also lists the military intelligence service of the USA, which among other things provides targeting and reconnaissance data for such systems, as a military facility. Even though it has been separated from the neighboring Revolutionary Guard complex since at least 2016 and used as a school. The indications were publicly accessible and unambiguous. Photos, Directory entries, Cards and visible markings On the school grounds, it was clear what this building had long been: a school. So there was no lack of information. One would have just had to take it seriously.
This is precisely why the talk of an „AI fallacy“ is so misleading. Not because software wasn't involved. But because it was Crucial concealed. The error apparently did not arise from a sudden loss of control of the machine, but from an old, incorrect classification that could no longer be stopped in an accelerated military system. From an inaccurate data situation, no Question mark, but a Target.
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And that's precisely where it gets political. Because the more faster the more complex such systems are, the smaller the window of opportunity for objection becomes. Maven is designed to, up to 1,000 target decisions to process per hour. That is more than a technical figure. It is rather the tempo of the killing. Where speed becomes the benchmark, control shrinks. Where processes are intended to run ever more smoothly, doubts quickly appear as obstacles. Incidents like the one in Minab are therefore the logical consequence of a system in which incorrect data remains innocuous for a long time until it suddenly becomes deadly.
AI in warfare follows an old logic of killing
Because the idea of making wars more predictable through technology is much older as any debate about artificial intelligence today. Long before the software marked targets, armies were already trying to Unpredictable to transfer the war effort into procedures, standards, and technical processes. How dangerous this logic is becomes clear with a look back. In the Vietnam War, the US military deployed thousands of acoustic and seismic sensors, the data from which was relayed via aircraft to an evaluation center and there processed by IBM 360 computers were processed to detect movements on the Ho Chi Minh Trail and to control air strikes. The system could register signals, but could not reliably classify what it was actually detecting. Instead of clarity, the technology often only created the appearance of it.
In the Kosovo War, the same logic was demonstrated in a different way: faulty target allocation, unsuitable map bases, and a bureaucratic apparatus that did not stop incorrect assumptions in time ultimately led to the bombing of Chinese Embassy in Belgrade by the US Air Force. At that time, however, they still apologized for any mistakes.
The common thread runs all the way to Minab. The machine does not replace the human. Instead, institutions build systems in which false data, standardized processes, and time pressure reinforce each other. The myth of precision persists, even though reality has long been fragile. Therefore, talk of „AI failure“ falls short. It dramatizes the machine and relieves the human.
Responsibility doesn't disappear, it just becomes invisible.
Therefore, the crucial question is not whether a machine can be morally guilty. It is, who bears responsibility when states and militaries deploy systems that select targets ever faster and make attacks appear ever more technical. This question is answered more clearly in international humanitarian law than some current debates might suggest. The principle of distinction obliges parties to a conflict to only military objectives to attack and civilian objects to protect. Responsibility therefore does not lie with the AI, but with the acting actors, the military chains of command and the states that carry out such attacks.
The international debate about Autonomous weapon systems revolves precisely around this point. The International Committee of the Red Cross has warned for years that systems that select targets and use force without sufficient human control raise fundamental legal, humanitarian, and ethical problems. What is crucial is not whether a technology is labeled AI. What is crucial is whether humans are still involved in a way that real control, Judgment and Accountability allows. Where this control wanes, it is not the neutrality of technology that grows, but the danger of organized irresponsibility.
