Follow the science, not the scientist

December 27, 2020. Science is the process of testing and either rejecting or affirming hypothesis. This requires observation, the formulation of an estimate -- a guess -- a hypothesis, careful description and measurement of the data, and an appropriate statistical analysis followed by an inference accompanied by a degree of confidence in that conclusion/estimate.

Being a 'scientist' means that you use the above-described scientific process upon which you base your 'expertise.' Without a tested and affirmed hypothesis, a scientist's expertise is primarily an opinion, and often a biased or even self-serving opinion.

To 'follow the science' you need to look at the data and the statistical proof and set aside your politics, biases and personal opinions before you speak or write -- unless you clearly identify as these being present in your words.

Claiming to 'follow the science' has often been used to mask fact with personal opinion, usually additionally masked by the previous words or even the 'science' of the person speaking or writing. The most significant examples of these abuses of 'science' can be found in the current Covid policy-induced crisis and in other significant world issues, from abortion to climate change.

Combine the relatively low level of understanding of science and the very high level of personal bias offered under the guise of journalism, leaves an even less educated and highly impressionable public at the mercy of 'journalists,' pundits, editorial page writers, politicians, and public officials, each typically embed with an intense value system that produces profound biases in what they say and write.

Listening to Bill Gates pontificate on epidemics is an example of both the bias of the media and the misattributing of expertise. As Gates' multi-billionaire pal Warren Buffet has noted, he won't speak to the media because they are only interested in words or opinions -- usually around bite -- that confirms the preconceived notion heard by the journalist, which is one of the worst forms of distortion of science, confirmatory bias.

There is a severe public policy problem when modeling trumps science. Take climate 'science,' which is primarily a field of computer models and projections, often using altered data and rarely offering testable hypotheses, and you can see the terrible misinformation and fear generated by computers and 'experts.' One clear give away of this bias can be found with the regular use of "in the next ten years the climate will be...," producing a non-falsifiable hypotheses, as 'the next ten years' never arrives, as shown by the examination of ten-year old predictions/hypotheses such as these which were shown to be false, which leads the author of the original claim to move the goal posts ahead another ten years. As to humans as the cause of 'climate change,' here is a good analysis of the absence of any scientific method in making this claim.

An expert's credibility might best be measured by his or her 'scorecard,' i.e., how often have they been correct in their predictions/hypotheses. Thomas Friedman, the New York Times pundit, regularly make predictions as to what he believes will happen "in the coming six months," but he offers no evidence of his predictions coming to fruition.

An academic colleague once bet that our dean would resign within the year, and when the year cam and the dean had not yet resigned, the colleague refused to accept her failed forecast and, instead, she wanted to extend her deadline. This created one of those non-falsifiabe hypotheses, meaning that her prediction can never be disproven or rejected because the time for accountability is always one year into the future. And, in her 'bet,' she can never lose, but she could win.