I have no special mistrust of climate models, I mistrust all models of complex systems. Here are six reasons why.
Reason #1: My cousin runs an advisory service for institutional investors (hedge funds, retirement funds, stock market funds etc. etc.) Here is the beginning of his latest post 16 June ’17
”
|
Serious money was spent developing these models. Do you think that climate is in some way simpler than the US economy, so that they are more likely to be accurate? I do not.
Reason #2: Americans are getting fatter yet living longer, contradicting the model that being mildly overweight is bad for you. It is far too long to go into so here’s the link — https://luysii.wordpress.com/2013/05/30/something-is-wrong-with-the-model-take-2/.
The first part is particularly fascinating, in that data showed that overweight (not obese) people tended to live longer. The article describes how people who had spent their research careers telling the public that being overweight was bad, tried to discount the data. The best quote in the article is the following ““We’re scientists. We pay attention to data, we don’t try to un-explain them.”,
Reason #3: The economic predictions of the Congressional Budget Office on just about anything –inflation, gross national product, economic growth, the deficit — are consistently wrong — http://www.ncpa.org/sub/dpd/?Article_ID=21516.
Addendum 28 June “White house economists overestimated annual economic growth by about 80 percent on average for a six year stretch during Barack Obama’s presidency, according to Freedom Works economic consultant Stephen Moore.
Economists predicted growth between 3.2 to 4.6 percent for the years 2010 through 2015. Actual economic growth never hit above 2.6 percent.”
Reason #4: Animal models of stroke: There were at least 60, in which some therapy or other was of benefit. None of them worked in people. It got so bad I stopped reading the literature about it. We still have no useful treatment for garden variety strokes
Reason #5: The Club of Rome, — dire prediction based on a computer model which got a lot of play in the 70s. For details see — https://luysii.wordpress.com/2017/06/01/a-bit-of-history/. The post also has a lot about “The Population Bomb” and its failed predictions and also a review of a book about “The Bet” between Paul Ehrlich and Simon
Reason #6: Live by the model, die by the model. A fascinating book “Shattered” about the Hillary Clinton campaign, explains why the campaign did no polling in the final 3 weeks of the campaign. The man running the ‘data analytics’ (translation: model) Robby Mook, thought the analytics were better and more accurate (p. 367).
Comments
Leaving aside the questions of the reliability of models in different subjects, and whether all of your six reasons truly relate to models, I have one core question: Without models, how can we have any idea about what the future might hold? Models may not always be right – but as long as they have some level of predictive skill they can often at least be a guide.