Thought experiment: If a bicycle cannot fly, is it a defective bicycle?
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Analogies can sometimes teach a point. The point here is that you can't rationally judge the effectiveness of a thing if you don't know what it was designed to do in the first place. And models are not designed to be "right."
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If anyone could create a complex model with lots of sensitive variables that could predict the future -- of anything -- during the fog of war period of a new challenge, that person would be a trillionaire by now. No one can do that. No model can do that. It isn't a thing.
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What models CAN do for you is show the potential size of a problem and persuade non-experts that it is worth fixing. The
#coronavirus models did just that. If there was an award for "best prediction model of all time," the#coronavirus models would be contenders.Show this thread -
The lower bounds of the models said 100K deaths but now have been revised to 60K. That's a 40% change! Terrible models! Fire everyone involved! Right?
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Keep in mind the models had a range from 100K at the low end, with mitigation, to over 1 million without. If the actual death toll comes in at 140K with mitigation, would you say the models were wrong or right? I think you would say they were damned good.
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But if we miss the bottom estimate by exactly the same amount on the low side, and the final tally is 60K dead, you call that a gross miss. Yet it would be a miss by exactly as much as the 140K, only in the other direction.
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I contend there is an illusion here that is skewing opinions. If you compare the revised 60K estimate to 100K, it looks like a big difference. But if you consider the range of uncertainty was 900K, depending on mitigation, then 60K and 100K are in the same ballpark.
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End of conversation
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Good analogies can be persuasive.
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Analogies convince me all the time. If they make sense.
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