The Rear Vision Mirror
"Causal inference isn't
a subfield of statistics. Synthetic control methods are just propensity score
matching along the time dimension. G-computation is a stupid name. And DAGs are
mainly good for teaching." There you have it.
set me thinking. Why do people like looking in the
rear vision mirror only. They obviously don’t do it when they drive a car. What
about a mass of data convinces them there will be a different outcome to being
splattered on the shrubbery?
Yes, the picture may be clearer in the rear vision mirror, but the things you need to see to avert disaster can only be seen through the windscreen.
Button-up boots is a good example.
Sales were great, until someone invented a zipper –
a disruptor. Instead of poring over sales data, the time would have been better
spent checking relevant patent applications and anything else happening in the market
(cheap imports).
People who market the message – THE ANSWERS WE NEED
ARE EVERYWHERE. JUST ASK THE DATA – don’t help, but it is used to sell their
product, so it should be treated as self-serving baloney. The world is headed
for a period of turbulence with Climate Change, and has just been through a
period, with Covid, that had the same vibe – things would change, people would
accept that as the new normal, and things would change again, and more people
would die.
The Four Pieces Limit, by itself, says that relying on statistics is a bad thing to do - a crutch for a limitation that only increases the disability. A Cognitive Truck would be better.
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