Target Practice | Sophia Goodfriend

Recent reports highlight the expansion of artificial intelligence within the Israeli military infrastructure. Research indicates that systems initially designed for surveillance in Palestinian territories now serve as core components of modern targeting operations.

In a 2024 discussion, a senior military official known as Colonel Yoav described how Unit 8200 uses data science to identify targets. The official claimed that algorithms allowed the military to generate two hundred targets during the 2021 conflict in Gaza, a volume of output that previously required nearly a year of human analysis. The military refers to these automated processes as a way to find militants who form groups.

Beyond military applications, domestic policy in Israel has shifted to accommodate increased surveillance. Current regulations permit security services to access private closed-circuit television cameras when officials identify national security concerns. New legislative proposals under consideration would further expand these powers by allowing police to install spyware directly on civilian mobile devices.

These developments reflect a broader integration of machine learning into state security practices. Scholars note that the history of these systems is rooted in long-standing surveillance efforts, which have now scaled into automated warfare. The shift toward high-speed, algorithmic target selection represents a departure from traditional intelligence collection methods, raising significant questions about the long-term impact on privacy and conflict conduct.