Aggregative Contingent Estimation (ACE)

Intelligence analysts are often asked to forecast significant events on the basis of limited quantitative data. It is common for such events to be contingent upon earlier events or actions. Generally, forecasts are prepared using expert judgment by individuals and small groups. Empirical research outside the intelligence community has shown that the accuracy of judgment-based forecasts is consistently improved by mathematically aggregating many independent judgments. The goal of the ACE Program is to dramatically enhance the accuracy, precision, and timeliness of forecasts for a broad range of event types, through the development of advanced techniques that elicit, weight, and combine the judgments of many intelligence analysts.

The ACE Program seeks technical innovations in the following areas:

• Efficient elicitation of probabilistic judgments, including conditional probabilities for contingent events.
• Mathematical aggregation of judgments by many individuals, based on factors that may include past performance, expertise, cognitive style, metaknowledge, and other attributes predictive of accuracy.
• Effective representation of aggregated probabilistic forecasts and their distributions.

The ACE Program will build upon technical achievements of past research and on state-of-the-art systems used today for generating probabilistic forecasts from widely-dispersed individuals. The program will involve empirical testing of forecasting accuracy against real events.

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