"Effective Intelligence Analysis Is A Concept-driven Activity Rather Than A Data-driven One" (DTIC)

"The most telling result of the research is the clear implication that intelligence analysis is conceptually driven as opposed to data driven. What is critical is not just the data collected, but also what is added to those data in interpreting them via conceptual models in the analyst's store of knowledge."

In other words, how you think is more important than what you know.  This is one of the big take-aways from Philip Tetlock's wonderful Expert Political Judgment and you would be forgiven if you thought I was just touting his 2005 book again.

No, the quote above is from a 1979(!) INSCOM sponsored study into cognitive processes in intelligence analysis (called, amazingly enough, Cognitive Processes In Intelligence Analysis:  A Descriptive Model And Review Of The Literature.  It, and its companion piece, Human Processes In Intelligence Analysis:  Phase 1 Overview are available through DTIC or you can download them here and here from Scribd.  I wish I could say that I found them on my own but they come to me courtesy of Dalene Duvenage, who teaches intel analysis in South Africa, and the always useful IAFIE mailing list).

While much of the content in these two papers is probably more easily accessed by way of Dick Heuer's Psychology of Intelligence Analysis, there are some new gems here. One of my favorites is the reason for the studies.  

According to Dr. Joseph Zeidner, Chief Psychologist for the US Army in 1979, and MG William Rolya, the Commander of INSCOM at that time, "Intelligence collection systems have proliferated over the past several years, increasing in complexity and in volume of output.  However, there has been no corresponding improvement in the ability of intelligence personnel to analyze this flood of data."  Sound familiar?

Another interesting tidbit comes from the Human Processes paper which lays out the personality attributes of the ideal analyst.  These include:

• Is a technologist
• Is either a specialist or a generalist but not both
• Is an "information entrepreneur"
• Is comfortable with changing roles
• Can communicate (oral and written)
• Is a detective
• Is imaginative
• Is self-starting
• Has a profession (Intelligence analysis)

These criteria seem to strike a chord as well.  All in all, both papers are worth a look, if only because they seem to prove that the more things change, the more they stay the same...

The Gartner Hype Cycle: An Interesting Way To Think About The "Next Big Thing" In Tech (Gartner.com)

Every year I look forward to seeing the latest editions of a number of regularly published analytic reports. The DNI's Annual Threat Assessment and Transparency International's Corruption Perception Index fall into this category. Even the Aon Terrorism Threat Map, while not an annual publication, satisfies my itch for a regular update on the state of affairs within that functional area.

When it comes to technology trends, however, the best such product I know of is Gartner's annual "Hype Cycle" chart. Gartner is a large and well respected research company that tracks all sorts of technologies.

Their experience has been that new technologies follow a more or less predictable pattern over time that is best measured by the amount of "hype" (i.e. inflated expectations) associated with a particular technology. You can see the current version of the hype cycle below (and can get more detailed information about the cycle, the methodology and additional findings at Gartner's website):

For example, if you look at the image above you can see that biometric identification has exited the "trough of disillusionment" and has entered the "slope of enlightenment". For many inside the intel community, biometric devices are old hat but what the hype cycle seems to be saying is that these technologies are about to become old hat for all of us...

One of the surprises for me was to see predictive analytics so far out on the hype cycle. Of course, then I think about Hunch's Predict-o-matic (available only to Facebook users, unfortunately, and which scared the be-jeesus out of me...) or articles like this one and I understand exactly what they mean.

Even more interesting are those items at the top of the hype cycle; stuff like cloud computing, 3D flat panel displays and augmented reality. If Gartner is right, then, in the very near future, we should start to see mainstream news articles trashing these technologies not as the "next big thing" but as the most recent tech flop.

My favorite part of the hype cycle is the stuff entering in from the left hand side, the technologies that are just beginning to climb the first steep curve of unreasonable expectations. Here we find the way-out technologies -- autonomous vehicles and computer-brain interfaces.

I like to point out to students that these are the technologies that they will have to deal with over the course of their careers; that they will fight with their children not over whether they get earrings in their ears but whether they will get chips in their brains.