IARPA in the News


The Intelligence Advanced Research Projects Activity has launched a research project to explore the human brain’s conceptual knowledge in a move aimed at helping the intelligence community analyze data. IARPA intends for the multi-year Knowledge Representation in Neural Systems program to identify how the brain organizes conceptual knowledge in order to build new tools and techniques for intelligence analysts and linguists, the Office of the Director of National Intelligence said Monday.

The New Yorker

In 1982, the decision analysts Marc Alpert and Howard Raiffa asked students in their classes at Harvard to estimate figures like the number of eggs produced daily in the United States. They were each asked to give a range so wide that they believed there was a ninety-eight-per-cent chance it would include the right answer. Instead, the correct figures fell inside the students’ ranges less than a third of the time.


Like a lot of fellow geopolitics and technology trend spotters, we have maintained a keen interest in the projections the US National Intelligence Council (NIC) makes public every five years or so. These projections typically try to gaze into the analytical crystal ball and predict the shape of the world, the relative power structures and various scenarios for the medium term future (typically, fifteen years). The latest NIC report released late last year Global Trends 2030: Alternative Worlds has proved to be one of the most disseminated and read of such reports.

Military and Aerospace Electronics

Artificial intelligence experts at Teledyne Scientific & Imaging LLC in Thousand Oaks, Calif., are joining those at the Siemens Corp. Corporate Research And Technology Division in Princeton, N.J., Carnegie Mellon University in Pittsburgh and HRL Laboratories LLC in Malibu, Calif., on an intelligence research project to unlock secrets in the nature of knowledge in an effort to improve tools and training available to intelligence analysts.

The Washington Post

The Economist’s The World in 2014 issue just hit newsstands, focusing international attention on the geopolitical outcomes we can expect to see over the next 12-14 months. The issue features an article by University of Pennsylvania psychologist Phil Tetlock and journalist Dan Gardner on the Good Judgment Project, a research study funded by the Intelligence Advanced Research Projects Activity (IARPA, the U.S. government’s analog to DARPA), which makes such geopolitical predictions every day.

The Economist

In the late 1980s one of us (Philip Tetlock) launched such a tournament. It involved 284 economists, political scientists, intelligence analysts and journalists and collected almost 28,000 predictions. The results were startling. The average expert did only slightly better than random guessing. Even more disconcerting, experts with the most inflated views of their own batting averages tended to attract the most media attention. Their more self-effacing colleagues, the ones we should be heeding, often don’t get on to our radar screens.

That project proved to be a pilot for a far more ambitious tournament currently sponsored by the Intelligence Advanced Research Projects Activity (IARPA), part of the American intelligence world. Over 5,000 forecasters have made more than 1m forecasts on more than 250 questions, from euro-zone exits to the Syrian civil war. Results are pouring in and they are revealing. We can discover who has better batting averages, not take it on faith; discover which methods of training promote accuracy, not just track the latest gurus and fads; and discover methods of distilling the wisdom of the crowd....


Identifying people from video streams or boatloads of images can be a daunting task for humans and computers. But a 4-year development program set to start in April 2014 known as Janus aims to develop software and algorithms that erase those problems and could radically alter the facial recognition world as we know it. Funded by the Office of the Director of National Intelligence's "high-risk, high-payoff research" group, Intelligence Advanced Research Projects Activity (IARPA) Janus "seeks to improve face recognition performance using representations developed from real-world video and images instead of from calibrated and constrained collections."