“Very few models are a literal description of the real world.”
Despite all the warnings from political scientists that we might not see a clear winner of the presidential election on election night, the uncertainty of last night’s vote count felt disorientating, and many expressed frustration with polls and forecast models that suggested we might have a more definitive result.
Back in April, just weeks after Covid-19 was declared a pandemic, I spoke with Mervyn King, an economist, former governor of the Bank of England, and co-author of the book Radical Uncertainty. In our conversation, centering on the business response to the coronavirus outbreak, he explained why assigning probabilities to uncertain future outcomes isn’t helpful for decision-making, and that we should instead work toward building robustness and resilience in our systems to be better equipped to deal with a range of possible outcomes.
