WSJ – U.S. Intelligence Community Explores More Rigorous Ways to Forecast Events

Logo-for-the-Wall-Street-JournalVery insightful WSJ article on the use of Big Data and predictive analytics – ‘U.S. Intelligence Community Explores More Rigorous Ways to Forecast Events’.

Journalist Jo Craven McGinty highlights how the “the government has taken the unusual step of running tournaments that invite people outside the intelligence community to develop better ways to forecast world events, and several have produced notable results”.

Notably, human judgment, while powerful, is subject to group think which degrades the power of accurate forecasting.  “Crowdsourcing, probability scores and machine learning” is being used to develop and test predictive models.  Moreover, the intelligence community is broadening its data inputs, turning to Big Data, vacuuming up  “large volumes of publicly available data, including online news, blogs, social media such as Twitter posts, Wikipedia pages, weather data, crime rates and images of, for example, parking lots outside hospitals—to name a few”.

The outcome – development of competing algorithms, instead of one structured approach.  The article is instructive to those seeking to challenge their traditional approaches of analysis.

To read the article on the Wall Street Journal web site, click here.

By Nick Mavrick

You can find Nick Mavrick on Google+

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