Today, the Special Competitive Studies Project (SCSP) released jointly with the Australian Strategic Policy Institute a report entitled “The Future of Intelligence Analysis: AI and Human-Machine Teaming.”
Drawing on discussions from a series of workshops between technologists, intelligence community and Department of Defense representatives held in Washington, DC and Canberra, the report argues that rapid advances in the development of artificial intelligence (AI) technologies over the last few years, particularly large language models (LLMs), have demonstrated the potential for AI to revolutionize how the intelligence community (IC) does all-source analysis. Therefore, the U.S. and Australian ICs should aim to build high-performance Human-Machine Teams (HMTs) that enable intelligence analysts to leverage generative artificial intelligence (GenAI) for some tasks while maintaining overall human oversight over analytic assessments. If the ICs can effectively and safely incorporate GenAI into their workflows, there would be substantial gains in the breadth and depth of their analytic work and, in turn, their ability to deliver critical insights to decision-makers. To make this argument, the report focuses on three key aspects of the integration of HMTs into intelligence analysis:
- First, unpacking the potential of GenAI to improve efficiency and effectiveness throughout the analytic workflow. To do so, it is important to first establish the current state-of-play for LLMs, including understanding their requirements and limitations, and how they can be leveraged at different stages of intelligence analysis.
- Second, assessing the expected trajectory of GenAI advancements over the short-, medium-, and long-term such that analytic leadership in the ICs can make reasoned bets about where they should make critical investments in order to keep a persistent competitive advantage.
- Third, to prepare for this future, we make five key recommendations to analytic leadership regarding the creation of a comprehensive strategy for the deployment of AI tools: designing for continuous AI model improvements, immediately starting the automation of portions of the analytic workflow, building human-machine analytic teams, creating AI-ready training and incentive structures for the analytic workforce, and collaborating to develop a shared U.S.-Australian analytic AI roadmap.
“Time is of the essence. If the U.S. Intelligence Community and its partners do not begin integrating generative AI tools into their workflow, we will always be vulnerable to our adversaries,” said SCSP President Ylli Bajraktari.
“Generative AI has the potential to transform the business of intelligence. This report uniquely blends perspectives from intelligence professionals and technologists working to develop large language models to render a set of specific and achievable recommendations for the U.S. and Australian intelligence communities to consider” said SCSP’s Senior Director for Intelligence William Usher.
“AI human-machine teaming will enable human intelligence analysts to focus on where they can best apply their expertise to maintain a competitive edge—clearly a vital priority in an increasingly contested strategic environment. Condensing fresh insights from intelligence practitioners and tech industry experts, this report makes a convincing case for agencies to get ahead of the AI curve and outlines the practical steps they need to take,” said ASPI Executive Director Justn Bassi.
For more information about the report, please contact SCSP Senior Director of Communications and Public Affairs, Tara Rigler, at tmr@scsp.ai. For more information about SCSP, visit us on our website, and subscribe for regular newsletter and podcast updates at 2-2-2.