The IC has an inherent need to anticipate and prepare for the future. Despite this need, the current processes for eliciting future scenarios are largely based on pen and paper exercises that are not well supported by technology or training. At the root of this limitation is the lack of scientific literature and fundamental knowledge surrounding the underlying cognitive mechanisms used to think about the future. This knowledge is necessary to measure how anticipation skills can be acquired, tested, and applied.
This exemplar will explore Anticipatory Thinking (AT). Recent efforts by IARPA’s Aggregate Contingency Estimation (ACE) project advanced the science of prediction based on answering questions of the form “This event will occur within this timeframe with this probability.” AT builds on this approach by focusing on the processes to generate these events. AT methods are concerned with how analysts generate ideas about the conditions under which events occur, their
2nd/3rd/nth order consequences, and the consideration of explicit alternatives to the future. There are three relevant areas of investigation.
- AT Assessments, which capture the cognitive processes of AT.
- AT Support – What properties of AT can be supported by structured analytic techniques and computing platforms? Structured Analytic Techniques (SAT) have long been recommended for future oriented tasks. However, no scientific studies have been performed to determine their efficacy, functional components, or user aptitudes. This effort will validate these SATs from a scientific perspective and explore computational models that capture AT properties.
- AT Training – Providing effective delivery mechanisms for AT is necessary to make it more accessible and widely used.