There is an Israeli military strategy called the “fog procedure”. First used during the second intifada, it’s an unofficial rule that requires soldiers guarding military posts in conditions of low visibility to shoot bursts of gunfire into the darkness, on the theory that an invisible threat might be lurking.
It’s violence licensed by blindness. Shoot into the darkness and call it deterrence. With the dawn of AI warfare, that same logic of chosen blindness has been refined, systematized, and handed off to a machine.
Israel’s recent war in Gaza has been described as the first major “AI war” – the first war in which AI systems have played a central role in generating Israel’s list of purported Hamas and Islamic jihad militants to target. Systems that processed billions of data points to rank the probability that any given person in the territory was a combatant.
The darkness in the watchtower was a condition of the terrain. The darkness inside the algorithm is a condition of the design. In both cases, the blindness was chosen. It was chosen because blindness is useful: it creates deniability, it makes the violence feel inevitable, it moves the question of who decided from a person to a procedure. The fog did not lift. It was given a probability score and called intelligence.
It may have been chosen blindness that led, at the start of the US-Israeli Iran war, to the strike at the Shajareh Tayyebeh elementary school in Minab, in southern Iran. At least 168 people were killed, most of them children, girls aged seven to 12.
The weapons were precise. Munitions experts described the targeting as “incredibly accurate”, each building individually struck, nothing missed. The problem was not the execution. The problem was intelligence. The school had been separated from an adjacent Revolutionary Guard base by a fence and repurposed for civilian use nearly a decade ago. Somewhere in the targeting cycle, it seems that fact was never updated.
The exact role of AI in the strike on Minab has not been officially confirmed. What is known is that the targeting infrastructure in which those systems operate has no reliable mechanism for flagging when the underlying intelligence is a decade out of date.
Whether or not an algorithm selected this school, it was selected by a system that algorithmic targeting built. To strike 1,000 targets in the first 24 hours of the campaign in Iran, the US military relied on AI systems to generate, prioritize, and rank the target list at a speed no human team could replicate.
Gaza was the laboratory. Minab is the market. The result is a world in which the most consequential targeting decisions in modern warfare are made by systems that cannot explain themselves, supplied by companies that answer to no one, in…
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