The Power and Pitfalls of AI for US Intelligence Posted on : Jun 24 - 2022

FROM CYBER OPERATIONS to disinformation, artificial intelligence extends the reach of national security threats that can target individuals and whole societies with precision, speed, and scale. As the US competes to stay ahead, the intelligence community is grappling with the fits and starts of the impending revolution brought on by AI.

The US intelligence community has launched initiatives to grapple with AI’s implications and ethical uses, and analysts have begun to conceptualize how AI will revolutionize their discipline, yet these approaches and other practical applications of such technologies by the IC have been largely fragmented.

As experts sound the alarm that the US is not prepared to defend itself against AI by its strategic rival, China, Congress has called for the IC to produce a plan for integration of such technologies into workflows to create an “AI digital ecosystem” in the 2022 Intelligence Authorization Act.

The term AI is used for a group of technologies that solve problems or perform tasks that mimic humanlike perception, cognition, learning, planning, communication, or actions. AI includes technologies that can theoretically survive autonomously in novel situations, but its more common application is machine learning or algorithms that predict, classify, or approximate empiric-like results using big data, statistical models, and correlation.

While AI that can mimic humanlike sentience remains theoretical and impractical for most IC applications, machine learning is addressing fundamental challenges created by the volume and velocity of information that analysts are tasked with evaluating today.

At the National Security Agency, machine learning finds patterns in the mass of signals intelligence collects from global web traffic. Machine learning also searches international news and other publicly accessible reporting by the CIA's Directorate of Digital Innovation, responsible for advancing digital and cyber technologies in human and open-source collection, as well as its covert action and all-source analysis, which integrates all kinds of raw intelligence collected by US spies, whether technical or human. An all-source analyst evaluates the significance or meaning when that intelligence is taken together, memorializing it into finished assessments or reports for national security policymakers.

In fact, open source is key to the adoption of AI technologies by the intelligence community. Many AI technologies depend on big data to make quantitative judgments, and the scale and relevance of public data cannot be replicated in classified environments.

Capitalizing on AI and open source will enable the IC to utilize other finite collection capabilities, like human spies and signals intelligence collection, more efficiently. Other collection disciplines can be used to obtain the secrets that are hidden from not just humans but AI, too. In this context, AI may supply better global coverage of unforeseen or non-priority collection targets that could quickly evolve into threats. View more