Dan Drezner had a piece up recently noting that 2012 is the 50th anniversary of Thomas Kuhn‘s The Structure of Scientific Revolutions. It’s been more than 20 years since I read it as a young undergraduate and my memory at the time was that Kuhn took way to long to make a pretty simple point but I suppose he had to actually present some evidence for his central thesis (go figure).
Even though the book is geared towards scientific revolutions I’ve thought it’s just as relevant to the field of intelligence analysis. After all, fundamentally intelligence analysis and science are both about understanding the world around us. It doesn’t matter if we’re using a telescope or some social network analysis technique.
And just as in the physical sciences, the routine and incremental progress of understanding can take place and be valuable for extended periods of time (think the Cold War) but eventually the small inconsistencies, cognitive biases and errors begin to accumulate and eventually leave you with a description of the environment that no longer resembles reality.
Like Ptolemy’s successors you can keep postulate more and more bizarre orbits to celestial bodies so that they conform to your visual observations or like old CIA hands you can continue to come up with explanations for why a parade of geriatric Soviet leaders and signs of a crumbling economy and military don’t mean the USSR is about to collapse. Eventually, however, reality will catch up to you.
You can wait for that to happen to you (as we did with the Soviet Union) or you can consider alternate (often radically different) explanations for the observed phenomenon.
If you haven’t read the book, I encourage you to do so. Be warned, it’s not exactly a page turner. Rather it’s one of those books that’s ‘good for you’ 1 but it really is worth your time.
- Shorthand for pretty boring and you’ll be looking for excuses to do just about anything else ↩