At one level, this is about why we didn’t see COVID-19 coming. At another, it is using that as a case study of a whole class of decisions which depend on making judgements about uncertain futures – which is to say most of the ones that matter. The problem is not a shortfall in prediction skills, which is just as well because prediction is a tricky game. It is instead presented as a shortfall in probabilistic reasoning skills, which in turn relates to the classic risk management scales of likelihood and impact. Low likelihood, high impact events matter a great deal – which is why the insurance industry exists. If there is a 10% chance of an imminent global pandemic, it is well worth investing in mitigation, even if it turns out that the pandemic fizzles out – which is why it made sense to stockpile large quantities of flu vaccine in 2009 which turned out not to be needed.
But, slightly less explicitly in the article, there is another step which is essential before any of this becomes useful, as opposed to merely interesting. Probabilistic reasoning can be a good pointer to action, but it has succeeded only if appropriate action is in fact taken. So perhaps those showing greatest wisdom back in January and February were not either those who dismissed what was happening in Wuhan as far away and unimportant, or those who jumped immediately to proclaiming imminent global catastrophe – but those who saw from an apparently moderate risk, an immediate need to take precautionary actions.
There is, of course, a political dimension to this as well. Back in 2009, the then French Health Minister was heavily criticised for the money spent – money apparently wasted – on one of those vaccine stockpiles. She is quite rightly unapologetic, but it’s another reason why understanding the concept of risk and its mitigation is important. As Alexander observes,
Uncertainty about the world doesn’t imply uncertainty about the best course of action!