Intelligence analysts need not fear 'Watson,' study shows

March 8, 2011

A Mercyhurst College study on the future of predictive analytics, which examined the outlook for intelligence analysis in the computerized age, shows machines not yet capable of detecting deliberately deceptive data.

The artificial intelligence program "" may have outsmarted human competitors on the television quiz show "!" recently, but it would have to go a long way to best an intelligence analyst, according to Kristan Wheaton, J.D., associate professor of intelligence studies at Mercyhurst College.

On Feb. 14-16, the reigning champions of Jeopardy! – Ken Jennings and Brad Rutter – faced a formidable new competitor – a supercomputer named Watson under development by IBM for four years. Watson defeated his adversaries handily.

Wheaton's graduate students recently completed a study on the future of predictive analytics, which examined the outlook for intelligence analysis in the computerized age, including emerging technologies similar to IBM's "Watson." They delivered their findings Feb. 21 to a representative of one of the nation's leading analytic organizations, which sponsored the study as part of Wheaton's Strategic Intelligence class. For security reasons, the organization declined to be publicly identified.

In their study, Wheaton's students' discovered that the technologies that would completely replace humans with machines in the field of intelligence analysis are not looming on the horizon.

"What you saw on Jeopardy would not play out the same in the world of intelligence analysis today because none of these new technologies – including Watson - deal well with deliberately deceptive data," Wheaton said.

Lindy Smart, one of the student analysts on the project, explained why. "While there are technologies that can extract data from unstructured sources like e-mails and blogs, they are unable to identify the validity of those sources," she said."For example, let's say you want to do a search about mining practices in African countries. The software could extract data from every single type of source identifying mining practices in Africa. However, it would not identify what data came from state-run news sources that would most likely have skewed the data. Humans are still needed to identify and weed out which sources are deceptive and how reliable the data is."

Wheaton added, "The technologies are improving rapidly, though, and there might be machines capable of mimicking human intelligence at some point, but the last job I think they are going to get is that of the intelligence analyst."

Explore further: Mercyhurst pioneers game-based learning in teaching strategic intelligence

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not rated yet Mar 08, 2011
The greatest deception is yourself. If you have the ability to render any task you do as superseded and obsolete, you replace yourself. There is no motivation for this. There is no motivation to showing greater intelligence, if the result replaces you.
not rated yet Mar 08, 2011
If the intelligence analysts in the audience are as gifted as Wheaton says they are, I'll bet they saw right through that patronizing lecture.
not rated yet Mar 09, 2011
Last I checked, we tell if something is false by checking other information. That means we check other sources for confirmation of the information which could be false, if all information gathered confirms it, then it is true.

If a competent machine intelligence can collect all relevant sources for relevant information, then it can tell if something doesn't match up.

Really people.
not rated yet Mar 09, 2011
Ok, finished the article. Anyone have a degree from this fine institution? I'd like to take your picture in front of the article. say cheese... *flash*

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