OR and the intelligence community

The (security) intelligence community (IC) is mainly made up of people with a non-technical background (such as political science majors).  Although the IC makes tough decisions under uncertainty given limited information (one of the things that OR does so well), the IC manly uses intuition and expert judgment to make decisions.  Ed Kaplan, who gave the  Philip McCord Morse lecture at INFORMS 2010, spoke about the intelligence community and the role that OR needs to play in the IC.

There are clear needs to use advanced analytical methods in the IC.  The NSA, for example,  collects 1.7B emails per day.  How do they determine which emails to read and analyze?  Clearly, they only have the resources to read a few.  How should they allocate their resources between collecting new data and analyzing the data?  The good news is that the NSA hires OR people (they even have a summer program for graduate students in OR), and the CIA is starting to hire OR people too.

Kaplan reminds us that intelligence is not just an operations problem.  People with language and cultural skills are needed to interpret the nuances and make tough judgments that no algorithm can do.  Human agents have been highly successful at using non-analytical techniques at detection suicide bombing attempts in Israel, which resulted in a plummeting number of successful suicide attacks.  OR cannot replace the human element, but it can certainly aid it.  And often it’s routine law enforcement–not intelligence–that makes the difference.

There have been some attempts at using OR to solve intelligence problems.  Ed Kaplan introduced two obscure articles that were a lot of fun.  A 1967 article in a classified CIA journal (unclassified in 1994) applies Bayes rule to the Cuban missile crisis.  The paper uses the input from 200 agents in the field that reported that they believed that the Soviets were up to something in Cuba, even though none had visual evidence.  The odds started out as 10-to-1 against the Soviets building missiles in early 1962, and slowly increased to 3-to-1 and then 50/50 (1-to-1) based on successive applications of Bayes rule.

J. Michael Steele published a paper in Management Science entitled “Models for Managing Secrets” based on the Tom Clancy Theorem, which states that the time to detect a secret is inversely proportional to the square of the people that know it (stated without proof in the Hunt for Red October).  The paper applies Poisson processes to “prove” Tom Clancy’s theorem.  It also analyzes countermeasures according to how they would result in a secret being kept for longer.

Kaplan has written a few papers on intelligence, including his recent paper Terror Queues, which applies queuing models to determine how agents (servers) can interdict (serve) terrorists (customers) before the terrorists complete an attack (leave the queue).

Kaplan finished the lecture by encouraging researchers to continue to examine the many problems in IC from an OR perspective.  How do you think OR could be used by the IC?


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