We seek meaning in most any action, so we sometimes mislead ourselves. Even when simply shown circles, triangles and other geometric objects randomly moving about on a screen, we tend to give them human attributes. Then we instinctively attempt to determine what their behavior means. For example, observers described the larger triangle as “aggressive, belligerent and angry.” Such quick conclusions were sometimes life-saving to our ancient ancestors. “It was safer to mistake a twig for a snake than vice versa,” suggests ”psychologists Fritz Heider and Marianne Simmel. Our primitive brain still controls much of our perceptions yet analytics may alter that instinct.
We can overcome our natural tendency to make the world more knowable and secure by seeking patterns and coincidences where there are none, Kenneth Cukier and Viktor Mayer-Schonberger believe. In their new book, Big Data: A Revolution That Will Transform How We Live, Work and Think, they describe how our increasing access, as organizations and individuals to the results of Big Data processing, helps us overcome our quick instinct to falsely see correlation and causality, famously described by Daniel Kahneman Thinking, Fast and Slow.
As Mayer-Schonberger and Cukier explain, we can “step back from looking at causes and instead look at correlations. Consider the what rather than the why, because that is often good enough.
“Which paint color is most likely to tell you that a used car is in good shape?” is one of the intriguing questions cited in the book’s promotion, along with these: “How can officials identify the most dangerous New York City manholes before they explode? And how did Google searches predict the spread of the H1N1 flu outbreak?” See the rest of the column at Forbes’ Quotable and Connected.”