I am reminded of a quote from Winston Churchill during debate, “I admire the martial and commanding air with which the right honorable gentleman treats the facts. He stands no nonsense from them.”
For some time, I have been thinking through a blog post on the unreliability of human perceptions, shaky human reasoning in the arena of war and warfare, and resistance to data-driven analysis over legacy knowledge. “Legacy Knowledge” in any field usually begins with the stuff “everybody knows” – whether it’s at their mother’s knee, in a classroom, from a mentor, or from their experience, and if they’re smart – from the experience of others. History is replete with stories of conquering armies that accepted their own status quo for too long, only to be overturned by an upstart foe. One common element in that acceptance is a tendency to believe the legend.
As Vladimir Putin is now amply demonstrating, decisions about making war are frequently affected by mistaken perceptions regarding threats and miscalculations about the conduct of war. I have also seen at least one as yet unverified claim that the professional cadre of analysts at the FSB, Russia’s intelligence service, are putting out the word that they predicted this outcome, but Putin and his cronies ignored their warnings.
Some years ago, I went to see a movie called “Moneyball”, based on Michael Lewis’s bestselling book about the impact of data science on baseball. I finally got around to reading the actual book last year and recognized that this story echoed themes from similar earlier episodes, as well as numerous comments from operational analysts, conflict simulation/war game designers, and systems thinkers about the resistance to their observations from their uniformed services and associated civilian officials.
Previous to “Moneyball”, Steven Johnson wrote “The Ghost Map” about the cholera outbreak in 1854 London and how one persistent maverick physician tracked down its source by the careful collection of information about who was contracting cholera, where, when and looking for the how by systematic study of his data. His findings were rejected outright and ignored until another outbreak about 10 years later forced the issue.
These stories also bring to mind Thomas S. Kuhn’s “The Structure of Scientific Revolutions” (originally published in 1962) which offered insight into how our knowledge of physics advanced as new hypotheses and theories supplanted old ones. His study of how the scientific ‘establishment’ resisted new theories and new data contributed to a pattern of revolution in science when suddenly the establishment resistance to new thinking was finally swept away.
Kuhn argued that this concept was not applicable to other fields of human endeavor, I and others disagree with him and have found other fields of human activity in which ‘new’ knowledge faces similar challenges in the face of ‘legacy’ knowledge – for example, the ‘revolution in military affairs.’ The common thread linking these stories is the recurring contest in the human mind between ‘legacy knowledge’ and new data-driven ideas.
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