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Aggregative Contingent Estimation Program

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Aggregative Contingent Estimation (ACE) was a program of the Office of Incisive Analysis (OIA) at the Intelligence Advanced Research Projects Activity (IARPA).[1][2]

History

The broad program announcement for ACE was published on June 30, 2010.[3] ACE funded the Aggregative Contingent Estimation System (ACES) website and interface on July 15, 2011.[4] They funded The Good Judgment Project some time around July 2011.[5] ACE has been covered in the Washington Post[6] and Wired Magazine.[7] The program was concluded by late 2015.[8]

Goals and methods

The official website says that the goals of ACE are "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."[1] The website claims that ACE seeks technical innovations in the following areas:[1]

  • 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.

There is a fair amount of research funded by grants made by the IARPA ACE program.[9]

Partners

The ACE has collaborated with partners who compete in its forecasting tournaments. Their most notable partner is The Good Judgment Project from Philip E. Tetlock et al.[10] (winner of a 2013 ACE tournament)[6] ACE also partnered with the ARA to create the Aggregative Contingent Estimation System (ACES).[4]

Data from ACE is fed into another program, called Forecasting Science and Technology (ForeST), which partners with SciCast from George Mason University.[11]

References

  1. ^ a b c Matheny, Jason; Rieber, Steve. "Aggregative Contingent Estimation (ACE)". Intelligence Advanced Research Projects Activity. Retrieved May 6, 2014.
  2. ^ "Aggregative Contingent Estimation" (PDF). Office of the Director of National Intelligence, United States. Retrieved May 6, 2014.
  3. ^ "Aggregative Contingent Estimation System". Federal Business Opportunities. June 30, 2010. Retrieved May 6, 2014.
  4. ^ a b Hickey, Kathleen (July 15, 2011). "Intell site tests crowdsourcing's ability to predict future". GCN. Retrieved May 6, 2014.
  5. ^ "The idea behind the Good Judgment Project". The Good Judgment ProjectTM. July 27, 2011. Retrieved May 5, 2014.
  6. ^ a b Horowitz, Michael (November 26, 2013). "Good judgment in forecasting international affairs (and an invitation for season 3)". Washington Post. Retrieved May 5, 2014. {{cite web}}: Italic or bold markup not allowed in: |publisher= (help)
  7. ^ Drummond, Katie (April 22, 2010). "Can Algorithms Find the Best Intelligence Analysts?". Wired Magazine. Retrieved May 6, 2014. {{cite web}}: Italic or bold markup not allowed in: |publisher= (help)
  8. ^ Corrin, Amber (2015-09-23). "IARPA's high-stakes intelligence experiment". C4ISR & Networks. Retrieved 2016-03-31.
  9. ^ "Google Scholar listing of research funded by IARPA ACE". Retrieved May 6, 2014.
  10. ^ "The Project". The Good Judgment ProjectTM. Retrieved May 5, 2014.
  11. ^ Matheny, Jason. "Forecasting Science & Technology (ForeST)". Intelligence Advanced Research Projects Activity. Retrieved May 6, 2014.
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