Following the devastating Hamas attack, Israel launched a military campaign targeting Gaza with relentless airstrikes. Initially, the IDF relied on its meticulously organized database, which included details of Hamas’ operational infrastructure, from tunnels to weapons storage sites and command centers. This database, built over years of intelligence collection, enabled targeted strikes from the first days of the war.
However, as the conflict continued, the Israeli military found that its “target bank” was rapidly dwindling. The intensity of the military campaign required additional targets at an accelerated pace. It was at this time that the Habsora system came into full force. Leveraging advanced machine learning and data analytics, it generated hundreds of new targets within hours. This capability allowed the IDF to maintain the campaign’s momentum, even as traditional intelligence-gathering methods struggled to keep pace.
Habsora’s deployment highlights the growing reliance on AI to augment and, in some cases, replace human decision-making in war. The system could quickly cross-reference data from various sources, including surveillance drones, signal intercepts and ground reports, to identify potential threats. Yet the lack of full human review has sparked concern about the accuracy and ethical implications of these decisions.
