Adjusting Your Bear Risk Assessment

Kerry Emanuel:

Let me illustrate this with a simple example. Suppose observations showed conclusively that the bear population in a particular forest had recently doubled. What would we think of someone who, knowing this, would nevertheless take no extra precautions in walking in the woods unless and until he saw a significant upward trend in the rate at which his neighbors were being mauled by bears?

The point here is that the number of bears in the woods is presumably much greater than the incidence of their contact with humans, so the overall bear statistics should be much more robust than any mauling statistics. The actuarial information here is the rate of mauling, while the doubling of the bear population represents a priori information. Were it possible to buy insurance against mauling, no reasonable firm supplying such insurance would ignore a doubling of the bear population, lack of any significant mauling trend notwithstanding. And even our friendly sylvan pedestrian, sticking to mauling statistics, would never wait for 95 percent confidence before adjusting his bear risk assessment. Being conservative in signal detection (insisting on high confidence that the null hypothesis is void) is the opposite of being conservative in risk assessment.

This is the response that FiveThirtyEight commissioned after the shit storm (no pun intended) that raged because of this FiveThirtyEight piece by Roger Pielke Jr. that declared, quite confidently, that:

In the last two decades, natural disaster costs worldwide went from about $100 billion per year to almost twice that amount. That’s a huge problem, right? Indicative of more frequent disasters punishing communities worldwide? Perhaps the effects of climate change? Those are the questions that Congress, the World Bank and, of course, the media are asking. But all those questions have the same answer: no.

After reading both, what it comes down to, and what Emanuel seems to agree with, is something I’ve maintained for a while now—I’d rather err on the cautious side of climate change, and be wrong, than ignore what we can observe and quantify, and be right.

That’s not politics; that’s common sense.