Predictions – Foxes and Hedgehogs

By Guy Higgins

In 1953, Isaiah Berlin published an essay in which he philosophized on an ancient adage, “Foxes know many things, but hedgehogs know one important thing.” Sir Isaiah expanded on that adage by observing that some people (hedgehogs) view the entire world through the lens of their deep and narrow expertise (one important piece of knowledge) while other people (foxes) view the world through the lens of their broad knowledge (knowledge of many things).

The foundation of being prepared for business as unusual is predicting those situations or events that are serious enough to merit preparing for. Before getting back to those foxes and hedgehogs, I want to expand a little on “serious enough.” A potential event has two components: likelihood and impact. Probability theorists refer to these two factors as probability and payoff:

  • Probability is a mathematical term defined as the number of actual events divided by the some “population.” For example, if I want to develop an estimate of the probability that a tornado will occur in Boulder County, Colorado, I can research the number of tornadoes that have been documented within Boulder County in the last 62 years and find that there have been 11 tornadoes. Dividing the number of tornadoes by the time span gives me a rough probability of 0.17 or a 17 percent chance of a tornado in any given year.
  • Payoff is the mathematical term for the gain or loss associated with an event. If I go back to Boulder County tornado research, I can find that the largest of those eleven tornadoes was 440 yards wide, that the longest ground path was 6.71 miles and that there were no injuries and no fatalities associated with any of the tornadoes. The payoff isn’t zero, but neither is it very high. Again, an estimate.

Now, probability theorists and practitioners multiply those two factors to calculate a number they call “expected value.” Expected value is a number that can be used to create a prioritized list of risks. Since Colorado has never experienced a hurricane, the probability of one is 0.0. The impact would be huge since Colorado is completely (reasonably so) unprepared for a hurricane, but multiplying the two factors yields an expected value of 0.0.

Now, with a firm grasp of probability, payoff and expected value, we can discuss identifying and prioritizing risks. Enter the fox and the hedgehog. Sir Isaiah observed that people in the hedgehog category view the entire world through their deep expertise and tend to make wild predictions – something like, “More than 500 people have been killed in commercial airline accidents in the past two years. Commercial flying is dangerous.” The first sentence is true, but the conclusion is questionable. People in the fox category, who are inclined to make more “caveated” predictions taking into account much more information, would make a prediction more akin to, “While there have been more than 500 deaths in commercial aviation accidents in the past two years, the overall safety record for commercial aviation is exceptionally good. The investigations into the accidents in the past two years have not revealed any systemic safety issues, and, while there is always room to improve safety, there does not appear to be any reason to avoid air travel, although the wise traveler would be well advised to fly major airlines with established safety records.”

Interestingly, the hedgehog’s prediction is likely to get much more attention than the fox’s more circumspect prediction. Therein lies an issue for the preparedness planner. Identifying risks (probability and payoff) is critical, so it’s important to understand whether the information on which those risks are based is provided by hedgehogs or by foxes. The foxes’ predictions are much more constrained and low key – but they also tend to be far more accurate. Hedgehogs’ predictions are only occasionally correct – yet they garner huge amounts of attention. That attention does not, however, mean that risk analyses should give undue credence to high-profile predictions. My personal recommendation is to significantly discount or even ignore “wild” predictions – unless you have compelling and supporting information.

Making predictions is, again, the foundation of preparedness planning, but making those predictions useful means having an understanding of the sources of the information upon which those predictions are based and an understanding of the people developing predictions associated with that information. The constrained and “caveat’ed” individual predictions of foxes rarely drive preparedness decisions – in isolation – but when used in a solid analysis, these predictions will be far more useful than will the bold and assertive predictions from hedgehogs.

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One thought on “Predictions – Foxes and Hedgehogs

  1. My general perception is that decision-making driven by probabilities is an opportunity to stop “thinking.” Most things that happen are not “caused” by statistics: even the flip of a coin. If you were able to measure every influencing factor that drove the position and orientation a coin through its movement, you would be able to predict the outcome (as long as you could delay your bet until the instant before it settled into its final positon). If the big earthquake hits, and Colorado becomes beachfront to the Pacific Ocean, then one might disregard past statistics in predicting a hurricane. The comment: “unless you have compelling and supporting information” suggests an opportunity to continue to think.
    If you put adversarial humans into the influencing factors for your decisions, reliance on past statistics may place you at even more risk. Perhaps reliance on statistics yields the black swan events.
    Admittedly the world is complex and humans don’t really do much more that subconsciously apply probabilities in all decisions, but actually thinking about why things happen doesn’t seem to get much press.
    One might want to do a better job at determining whether you will be killed by a self-driving car than just looking at statistics. Perhaps you should want to understand why?

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