#AI#GenerativeAI#LLMs#Military#Defense: "On average, both the human and the LLM teams made similar choices about big-picture strategy and rules of engagement. But, as we changed the information the LLM received, or swapped between which LLM we used, we saw significant deviations from human behavior. For example, one LLM we tested tried to avoid friendly casualties or collisions by opening fire on enemy combatants and turning a cold war hot, reasoning that using preemptive violence was more likely to prevent a bad outcome to the crisis. Furthermore, whereas the human players’ differences in experience and knowledge affected their play, LLMs were largely unaffected by inputs about experience or demographics. The problem was not that an LLM made worse or better decisions than humans or that it was more likely to “win” the war game. It was, rather, that the LLM came to its decisions in a way that did not convey the complexity of human decision-making. LLM-generated dialogue between players had little disagreement and consisted of short statements of fact. It was a far cry from the in-depth arguments so often a part of human war gaming."
