The U.S. intelligence community has plenty of information about the countries and regions where its adversaries operate, but it needs more than that — it needs better ways to understand the context of that information, and how it changes over time, Samantha Ravich told attendees at GigaOM’s Structure:Data conference in New York on Thursday. Ravich, the co-chair of the National Commission for the Review of Research and Development in the Intelligence Community, said intelligence analysts need to work hand-in-hand with technologists and data scientists to find those new ways of understanding context.
Ravich used the example of Tunisian fruit vendor Mohammed Bouazizi, who set himself on fire two-and-a-half years ago as a way of protesting police brutality and corruption in his country and triggered a series of events that resulted in what many now call the “Arab Spring” — revolutions and uprisings in Egypt, Syria and other countries, and the toppling of dictators like Hosni Mubarak of Egypt and Libya’s Muammar Ghadafi. These events have fundamentally changed the political picture in the region, she said, but how they happened and why is still poorly understood by intelligence analysts.
Most intelligence, Ravich said, is still much more like a snapshot in time — a photograph rather than a video, or a snippet of conversation — and so it doesn’t provide the kind of understanding of the shifting flow of events that could help analysts see such events coming more easily, or even influence them.
The intelligence strategist also used a poem to illustrate her point, one that referred to a man in the water waving his arm — a man who turned out to be drowning, rather than just enjoying a swim. A photo of that man would make it virtually impossible to determine that he was drowning and not just waving, Ravich said, but if we could see him in motion, and put him in some kind of context, then we might have a better chance of figuring out whether to send rescue or simply wave back.
In order to solve those kinds of problems, she said, technologists and data scientists need to work together to come up with better tools that can take the vast quantities of information the world is constantly generating, and put that into some kind of context so that threats and potential courses of action become more obvious.
Check out the rest of our Structure:Data 2013 live coverage here, and a video embed of the session follows below:
A transcription of the video follows on the next page