Updated: Apr 5, 2020
In certain fields of study, such as structural analysis, or motion dynamics, modeling can be very accurate. The reason is, enough factors are known, which contribute to the outcome being predicted. For instance, if you want to know under what load a structural beam will break, there's enough knowledge about the physics of the material under test to make an accurate THEORETICAL prediction.
If you want to know at what speed a car will turn over going around a curve, there's enough information about the car's size, weight and shape, and the characteristics of the road, to make an accurate prediction.
With the right information, an engineer or scientist can create a model, simulate tests on it in a computer, and verify if predictions are accurate. Ultimately, REALITY is the final judge. In other words, actual tests can, and should, be performed on a beam in the case of predictions about structural strength. Crash dummies can be used in remote control cars to test predictions about unsafe speeds on curves.
What's more, these tests can be reported, carried out by others, and peer reviewed for verification or calling B.S.
The problem with models in biology and climate science is that we don't have enough knowledge and data about ALL the factors that go into making an accurate prediction in these areas. That's why you hear predictions like, "There could be between 500,000 and 30 MILLION DEAD" or "The earth's temperate will rise between .2 and 4 degrees over by the end of the century." Those are HUGE ranges!
Given the above, a lot more science is required before we should trust these types of models, particularly those that would cause tremendous damage to our economy. This not only impacts our way of life, but our ability to respond to crises.
A Facebook friend of my created this equation, UNWEALTHY=UNHEALTHY, which basically means, we need wealth (products and services) to solve big problems. Even sustainable charity is impossible without wealth.
Models are tools, which can be very valuable in the right situation. However, like any tool, a model must be used wisely, and controlled by humans. Were models used properly in our current COVID-19 situation? Did nations do the right thing in shutting down the worldwide economy on the predictions of models? Would the dreaded curve, as shown above, have really risen to overwhelm us, as was predicted by the models, had we taken a different course of action? Time will tell.
Moving forward, let's ensure models don't become our masters.