治理自动化战略情报
Governing Automated Strategic Intelligence
AI总结：
本文研究多模态基础模型自动化军事情报分析的战略影响，通过初步实证评估提出地面真值问题分类与能力决定模型，并为国家保持战略竞争力提供建议。
AI中文摘要：
民族国家之间的军事和经济战略竞争力将日益由其前沿人工智能模型的能力和成本来定义。此类系统所带来的地缘政治优势的首批领域之一将是军事情报的自动化。大量讨论集中在使能新军事形态的人工智能系统上，例如致命性自主武器，或用于做出战略决策。然而，一个国家拥有“数据中心里的中情局分析员”以大规模综合多样化数据的能力及其影响，尚未得到充分探索。多模态基础模型似乎正走在自动化此前由人类完成的战略分析的道路上。它们将能够把当今丰富的卫星图像、手机定位轨迹、社交媒体记录和书面文件融合到一个可查询的系统中。我们开展了一项初步的提升研究，以实证评估这些能力，随后提出了这些系统将回答的地面真值问题类型的分类法，给出了该系统人工智能能力决定因素的高层模型，并为民族国家在自动化情报新范式下保持战略竞争力提供了建议。
英文摘要：
Military and economic strategic competitiveness between nation-states will increasingly be defined by the capability and cost of their frontier artificial intelligence models. Among the first areas of geopolitical advantage granted by such systems will be in automating military intelligence. Much discussion has been devoted to AI systems enabling new military modalities, such as lethal autonomous weapons, or making strategic decisions. However, the ability of a country of "CIA analysts in a data-center" to synthesize diverse data at scale, and its implications, have been underexplored. Multimodal foundation models appear on track to automate strategic analysis previously done by humans. They will be able to fuse today's abundant satellite imagery, phone-location traces, social media records, and written documents into a single queryable system. We conduct a preliminary uplift study to empirically evaluate these capabilities, then propose a taxonomy of the kinds of ground truth questions these systems will answer, present a high-level model of the determinants of this system's AI capabilities, and provide recommendations for nation-states to remain strategically competitive within the new paradigm of automated intelligence.
