Organizational and Cultural Criteria for Adversary Modeling (OCCAM)

We propose a Phase II program to develop and demonstrate an analyst decision aid that incorporates Organizational and Cultural Criteria in Adversary Modeling (OCCAM). OCCAM aids the PSYOP/IO analyst by leveraging known organizational and culturalknowledge to infer potential target biases and predict likely target behavior in data-sparse environments.Under Phase I, we demonstrated the feasibility of the proposed cultural profiling approach in the context of a culturally rich SASO scenario. Specifically, we identified individual and group attributes and organizational and cultural stereotypes, enablinga profiling approach that supports behavior prediction. Key elements of the approach include: the specification of organizational/cultural influence on target behavior; representation of organizational/cultural stereotypes; and the management ofuncertainty.Under Phase II, we propose to expand the decision aid's capabilities by: 1) developing and refining the organizational and cultural stereotypes across a broader range of scenario vignettes; 2) expanding target profiling capabilities by including a broaderset of AI inferencing techniques; 3) expanding the behavior prediction capabilities by incorporating situational factors, additional representational formalisms, and management and representation of meta-information (e.g., uncertainty, recency) about bothraw and inferred data; and 4) demonstrating and validating the OCCAM architecture and software prototype. We see considerable potential for application of the behavior prediction and decision-aid prototype in the commercial area, specifically in high volume, time critical financial transactions. These include the commodities futures market, local andnational stock exchanges, and international currency markets where much, if not all, of the market movements are governed by psychological and organizational factors, well beyond the ken of conventional financial and economic analysis. The focusedapplication of an adversary modeling tool in these arenas could have a significant impact on the perceptions of other players in the market and could translate to significant increases in profit margin for active traders.