About 20 years ago my wife and I were living in Washington DC. I read that a well-known political analyst would soon be speaking at American University on global affairs and I decided to go to hear his talk.
He spoke compellingly about a variety of forces underway around the world and predicted that the Internet will become a tool for recruitment by terrorists overseas.
Wait. What?
This was 1996; the public was just learning about the Internet (the Web browser had been introduced only two years earlier); and global terrorism, while certainly on any political analyst’s radar, was also not a front and center issue for the rest of us, certainly compared to post 9-11.
Over the years, that statement from this analyst stuck in my mind. It seemed so out of the blue and, in retrospect, so eerily prescient. Unfortunately, I had forgotten his name.
Just a couple weeks ago, the name “Kaplan” popped into my mind. I did a couple quick Google searches, and confirmed, that yes, Atlantic magazine writer, author, and think tank political strategist Robert D. Kaplan was in fact the person I heard make that prophecy nearly 20 years ago.
He spoke compellingly about a variety of forces underway around the world and predicted that the Internet will become a tool for recruitment by terrorists overseas.
Wait. What?
This was 1996; the public was just learning about the Internet (the Web browser had been introduced only two years earlier); and global terrorism, while certainly on any political analyst’s radar, was also not a front and center issue for the rest of us, certainly compared to post 9-11.
Over the years, that statement from this analyst stuck in my mind. It seemed so out of the blue and, in retrospect, so eerily prescient. Unfortunately, I had forgotten his name.
Just a couple weeks ago, the name “Kaplan” popped into my mind. I did a couple quick Google searches, and confirmed, that yes, Atlantic magazine writer, author, and think tank political strategist Robert D. Kaplan was in fact the person I heard make that prophecy nearly 20 years ago.
I quickly found out that Kaplan is considered one of the top analysts in the world on international affairs, is situated in the political “realist” camp, and has written several highly acclaimed books on global affairs. I got hold of an early book of essays, The Coming Anarchy published in 2000. The first chapter, published in the Atlantic in 1994, was a deep examination of forces underway in failed states in parts of Africa in the early 1990s, accompanied by his analyses that the world will soon see the rise of new types of terrorism, whose origins and tactics he outlined in great detail. In fact, terrorist operations with those characteristics and strategies have manifested themselves in recent years in the form of groups like ISIS and Boko Haram, as Kaplan’s book chillingly predicted.
We are living in an age where everything must be boiled down to a measurable metric, and where with the right sensors, software, algorithm, big data set and dashboard, we are supposed to be able to predict everything from the day of the week a customer is most likely to churn, to how many minutes to a probable equipment failure, to which pilot television series is going to succeed among viewers and much more.
And there is no question that big data is a big deal and if the analytics are done correctly, the data will reveal meaningful hidden patterns that can lead to greater insights about what is most likely to occur under what circumstances, and therefore lead to better business decisions.
But as the late media and technology sage, scholar and author Neil Postman noted, when trying to determine the best way to research and understand a phenomenon, it’s worth considering the difference between a blink and a wink. The former is a physiological process, so when trying to determine how to best understand it, it is appropriate to apply quantitative analyses and analytics. The latter is a social behavior, where discerning meaning is complex, unpredictable and derives from messy human behavior and intentions. Understanding the meaning of a wink, and say, predicting when someone is likely to wink again, can better be done by non-quantitative methods like storytelling, based on deep immersion and experience in the relevant social behaviors.
Kaplan spent decades living around the globe, embedding himself in failed states and talking to ordinary people who could tell and show him what was going on in their world. He used this experience and his insights to tell us his stories and to apply what he learned to tell us what he thought what was most likely to occur. And he was good at it—apparently really good at it. Could an algorithm have done this?
Big data can be a powerful tool for predicting the future. But experience, insight, and storytelling remain at least as powerful for helping us understand how and why people are behaving the way they are and what kind of future those actions will likely bring to pass.
Your thoughts?
We are living in an age where everything must be boiled down to a measurable metric, and where with the right sensors, software, algorithm, big data set and dashboard, we are supposed to be able to predict everything from the day of the week a customer is most likely to churn, to how many minutes to a probable equipment failure, to which pilot television series is going to succeed among viewers and much more.
And there is no question that big data is a big deal and if the analytics are done correctly, the data will reveal meaningful hidden patterns that can lead to greater insights about what is most likely to occur under what circumstances, and therefore lead to better business decisions.
But as the late media and technology sage, scholar and author Neil Postman noted, when trying to determine the best way to research and understand a phenomenon, it’s worth considering the difference between a blink and a wink. The former is a physiological process, so when trying to determine how to best understand it, it is appropriate to apply quantitative analyses and analytics. The latter is a social behavior, where discerning meaning is complex, unpredictable and derives from messy human behavior and intentions. Understanding the meaning of a wink, and say, predicting when someone is likely to wink again, can better be done by non-quantitative methods like storytelling, based on deep immersion and experience in the relevant social behaviors.
Kaplan spent decades living around the globe, embedding himself in failed states and talking to ordinary people who could tell and show him what was going on in their world. He used this experience and his insights to tell us his stories and to apply what he learned to tell us what he thought what was most likely to occur. And he was good at it—apparently really good at it. Could an algorithm have done this?
Big data can be a powerful tool for predicting the future. But experience, insight, and storytelling remain at least as powerful for helping us understand how and why people are behaving the way they are and what kind of future those actions will likely bring to pass.
Your thoughts?
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