https://www.americanthinker.com/articles/2020/04/climate_models_and_covid19_models.html
Computer models are seductive even though they are very often completely wrong. The more complicated they are the greater chance that they are wrong. Like children, they copy their parents — the model architects. Confirmation bias involves cherry picking facts to obtain a result consistent with preexisting beliefs. A complicated computer model with many degrees of freedom is a perfect environment for confirmation bias to have its way. The investigator usually will believe, or at least claim, that his model is objectively setup without bias entering into the effort.
Not all computer models are wrong. Sometimes they produce good predictions. But all too often they fail and the failures are not acknowledged because the modelers are emotionally or ideologically attached to their creation.
The claim of objectivity by academic modelers contrasts with the standard leftist or academic belief that practically everyone is a racist, driven by unconscious motives. Google “implicit bias” if you want to know more. When professors are pushing racial justice theories everybody is driven by unconscious forces. But when constructing computer models all is well.
Complicated models are always full of escape hatches that can explain away any failure. Climate models still enjoy support in spite of 30 years of failure. The failures are alleged to be due to things like chaotic variation or data that has to be adjusted because it does not agree with the model. COVID-19 models are new but have had notable failures. For example, the IMHE model predicted up to two million deaths but has been repeatedly adjusted and now is down to 60,000 deaths. Usually it is claimed that the model is not wrong, but deaths are lower because the American people have been good boys and girls.