Aggregative Contingent Estimation (ACE)
For information contact: firstname.lastname@example.org
The goal of the ACE Program is to dramatically enhance the accuracy, precision, and timeliness of intelligence 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: (a) efficient elicitation of probabilistic judgments, including conditional probabilities for contingent events; (b) 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; and (c) 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 experts. The program will involve empirical testing of forecasting accuracy against real events.
Performers (Prime Contractors)
Applied Research Associates, Inc.; Charles Stark Draper Laboratory, Inc.; George Mason University; Jacobs Strategic Solutions Group, Inc.; University of California, Berkeley
- Human judgment
- Machine learning
- Logic & critical thinking
To access ACE program-related publications, please visit Google Scholar.
- The NBA Finals Are Here. Even Superforecasters are Surprised
- Does Your Company Have Good Judgement?
- Superforecasting for the Farm
- Are You a Good Forecaster? The Good Judgment Project Needs You
- The Best Bet in Crowd Prediction
- How 'Superforecasters' Think About the Future
- U.S. Dabbles in Forecasting the Future
- Superforecaster's success raises the question: Why are most of us so bad at predicting things?
- Could you be a ‘super-forecaster’?
- Do you have what it takes to be a superforecaster?
- Book review: 'Superforecasting: The Art and Science of Prediction' by Philip Tetlock and Dan Gardner
- How The Two Parties Are Horrible At Predicting the Future
- Can Businesses Learn 'Superforecasting'? Easier Said Than Done
- Seeing Into The Future