The Israel Defense Forces (IDF) have reportedly been using an artificial intelligence (AI) system called Habsora to select targets in the war on Hamas in Gaza. This has raised questions about the implications of using AI targeting systems in conflict. AI is already changing the nature of warfare by making soldiers more efficient and increasing the speed and lethality of war. However, the use of AI in war raises ethical concerns, such as the dehumanization of adversaries and the disconnect between wars and the societies they are fought in. AI systems can contribute to mis- or disinformation, creating dangerous misunderstandings during times of war. They may also increase the tendency to trust suggestions from machines, raising uncertainty about how much to trust autonomous systems. One of the most significant changes driven by AI is the increase in the speed of warfare, which may affect military deterrence and decision-making. The IDF’s Habsora system, for example, can produce 100 bombing targets a day, along with real-time recommendations for which ones to attack. However, the idea of more precise targeting through AI has not been successful in the past, as civilian casualties from the global war on terror demonstrate. The distinction between combatants and civilians is often unclear, and technology does not change this fundamental truth. The inclusion of AI in war may exacerbate harm and lead to increasing disconnection between militaries, soldiers, and civilians. As AI becomes more common in war, countermeasures will be developed, leading to escalating militarization. Controlling AI development and regulating machine learning algorithms is challenging. The law may never match the speed of technological change, and estimating likely numbers of civilian deaths does not provide insight into the ethical and legal dimensions of targeting. Trust in governments, institutions, and militaries needs to be restored if AI is to be applied ethically in military practices. Critical ethical and political analysis is necessary to understand the effects of emerging technologies in warfare. Until then, machine learning algorithms should be kept separate from targeting practices, although the world’s armies are moving in the opposite direction.