As an MBA student, I learned the wonders of creating forecasts on an excel spreadsheet. Change this assumption and, voila, you can make the projection as large or small as you want. But by the time I graduated, I realized the shortcomings of this practice and thought it was better to follow the advice of my prof Edwards Deming to use data & statistics to focus on improving the process. The goal is to spend resources on maximizing the outcomes of what you can control rather than trying to predict the completely uncertain future that no human or AI software can model.
Too bad our policymakers never learned this vital lesson! Today, we find government leaders implementing life-changing policies based upon forecasts modeled by the “experts”. A glaring example of this is the government’s decision to execute unprecedented lockdowns because of covid models that forecast a massive death toll. The policy was led by very influential forecasts out of Imperial College London which produced a 54% to 70% overestimation of US deaths and a 51% to 68% overestimation in the UK. The ramifications of those ill-advised lockdowns are still reverberating throughout the economy.
Now we are being told by some climate forecasters that the world is soon to end if we don’t make radical changes to our society. These models are driving life-altering changes in industry and lifestyles-based upon very uncertain assumptions. Have you noticed the difficulty meteorologists have in telling us what the weather will be like this weekend? We can use their shaky track record to make our own projections about the accuracy of climate forecasts over the next 300 years (notice the forecast variability in the climate model below). In any case, why must the government always create policy based on the worst-case scenario when we have no idea what tomorrow will bring?
Everyone agrees that scientific advancements are most welcome and vital to the progress of a healthy society. However, we must distinguish between fact-based scientific discovery and the unreliable ART of forecasting. Yes, we want to improve the process of containing covid among those at risk. Also, we are eager to learn how to improve the process of minimizing air, water & terrestrial pollution. Just save us from these awful doomsday forecasts that are best suited to scaring otherwise productive people witless!