From: David Blum <[email protected]> You are cordially invited to my dissertation defense:
Date: Tuesday, Oct 23rd, 2012 Time: 1:30 pm Location: Encina Hall, CISAC East Conference Room (2nd Floor) Title: Probabilistic Models for Warning of National Security Crises Adviser: Elisabeth Pate-Cornell Abstract: Intelligence analysts have experimented with static forms of Bayesian inference of crises since the late 1960’s. However their static probabilistic approaches have proven unsuitable for warning analysis. In this dissertation I develop an analytic framework for crisis early warning that addresses four shortcomings of earlier efforts: (i) it has the flexibility to incorporate geographical variation; (ii) it reflects the dynamics of a crisis in order to enable lead time estimation; (iii) it incorporates conditional dependencies among signals and data; (iv) it treats an analyst’s decision of when to warn, and type of warning to give, in decision-theoretic terms. The framework is rooted in a general warning system developed by Pate-Cornell. The models comprising the framework are illustrated using a historical example, the lead up to Japan’s attack on Pearl Harbor in 1941. They are then demonstrated through a contemporary case study, the warning of violence against civilians in Guatemala being perpetrated by a transnational criminal organization. >From the Pearl Harbor illustration, I find that beginning on November 27, 1941, at no time would US intelligence analysts have been expected to believe that an attack on the US Pacific Fleet based in Oahu was more than one one-hundredth as likely as an attack on the US Asiatic Fleet based in Manila Bay. Yet, in the days preceding Japan’s December 7 attack, the expected disutility of an attack on Oahu may have exceeded that of an attack on Manila Bay by a factor upwards of ten, assuming risk neutrality and a discount rate driven by planned military deployments. Using parameters, some of which are entirely illustrative, the model would have issued an alert for an attack on Oahu on December 2, 1941. Despite the illustrative nature of the results, the exercise highlights the importance of incorporating decision analytic techniques in the warning process. It also demonstrates the process of entity tracking through signal inference, which is broadly applicable. >From the transnational criminal organization case study, I identify an allocation of Guatemalan military forces that satisfies a minimax criterion for interdicting drug traffic. I further identify three municipalities that consistently have high likelihood of being optimal targets for coercion between February 1 and August 31, 2012, for purposes of securing trafficking routes into Mexico. Lastly I identify two routes spanning the width of Guatemala, which, over the same period of time, are consistently the most secure smuggling routes given an uncertain military force deployment whose maximum likelihood satisfies a minimax criterion. Thanks, David Blum David Blum Ph.D candidate, Decision and Risk Analysis Group Department of Management Science & Engineering Predoctoral Science Fellow Center for International Security and Cooperation Stanford University 510-414-4450 (m) 415-230-0645 (skype) 815-301-3500 (fax) [email protected] http://cisac.stanford.edu/people/davidblum/
-- Unsubscribe, change to digest, or change password at: https://mailman.stanford.edu/mailman/listinfo/liberationtech
