What all of these have in common is that they are all low-probability, high-impact events — the “long-tail” phenomenon, to use the jargon of risk modelers, referring to the far ends of the traditional bell curve of probabilities, or “black swans,” to use the metaphor popularized by former Wall Street trader Nassim Nicholas Taleb.
Such calamitous events have been a regular part of the human experience since Noah and the flood, some of them natural, others manmade. In spite of that, however, we continue to underestimate their frequency and severity.
To a degree, that is a good thing. If we were to focus too much of our attention on all the really, really bad things that could befall us, we’d never get out of bed in the morning.
But the same psychological trait that allows us to go about our daily business also creates blind spots. Although we observe that calamities happen, we assume that they won’t happen to us, or they won’t happen again. And if it has been a long time since the calamity, we are apt to take false comfort that we have beaten the odds.
There was no better example of this memory lapse than in the weeks after the Gulf Coast oil spill, when political leaders were jumping up and down demanding that the federal government move more aggressively to contain what they described as a life- and economy-altering disaster, even while expressing outrage over a temporary moratorium on other drilling. Similarly, nine months after Hurricane Katrina, a survey of more than 1,000 residents of coastal areas found that 85 percent had taken no precautions to protect themselves from a similar storm.
Even those who say they can assess risks and probabilities to the third decimal point have a history of wildly overestimating their predictive powers. By their calculation, the BP spill could never happen. Nor could the collapse of national real estate prices or the nuclear crisis in Japan.
Part of the problem is that we don’t know what we don’t know. The other part is that small miscalculations of probabilities can have large effects on outcomes when dealing with long periods of time. Think of the sailor who sets off on a voyage a few degrees off course. A few miles out, the error is small, but by the time he crosses the ocean, he may find himself hundreds of miles from the intended destination.
Our reward structures don’t encourage spending the time or the money to deal with low-probability disasters. The chief executive of Citigroup acknowledged as much when he told a reporter in 2007 that he would lose his job if he gave up profit and market share to shield his bank from the obviously excessive risk-taking that everyone knew was going on. And you can only imagine the outcry from the industry and those Gulf Coast politicians if government regulators back in 2009 had ordered oil companies to spend millions of dollars to have enough boats and booms at the ready to deal with a BP-sized oil spill from deepwater drilling.