⚖️ A Failure, But Not of Prediction →
April 17, 2020 • #This is the best piece I’ve seen on the swirling controversy around the coronavirus pandemic response: on experts, the WHO, government response. The problem is not that experts don’t always have the answer (which they clearly don’t), it’s that the mechanics of many institutions, but also individual reasoning methods, are incompatible with responding to data-poor situations.
People were presented with a new idea: a global pandemic might arise and change everything. They waited for proof. The proof didn’t arise, at least at first. I remember hearing people say things like “there’s no reason for panic, there are currently only ten cases in the US”. This should sound like “there’s no reason to panic, the asteroid heading for Earth is still several weeks away”. The only way I can make sense of it is through a mindset where you are not allowed to entertain an idea until you have proof of it. Nobody had incontrovertible evidence that coronavirus was going to be a disaster, so until someone does, you default to the null hypothesis that it won’t be.
Gallant wouldn’t have waited for proof. He would have checked prediction markets and asked top experts for probabilistic judgments. If he heard numbers like 10 or 20 percent, he would have done a cost-benefit analysis and found that putting some tough measures into place, like quarantine and social distancing, would be worthwhile if they had a 10 or 20 percent chance of averting catastrophe.
When we don’t have the luxury of running randomized control trials and building large experimental datasets, we have to work with what we’ve got more rationally than simply checking out completely if a test, response strategy, or piece of medical advice is “unproven.”
- Weekend Reading: The State and the Virus, Future of Work, and Stephen Wolfram's Setup — How should the state respond to the coronacrisis?, mapping the future of work, and Stephen Wolfram's deep dive on his productivity systems.