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Learning not to trust the All-In podcast

(passingtime.substack.com)
342 points paulpauper | 1 comments | | HN request time: 0.875s | source
1. briantakita ◴[] No.42070968[source]
I have news for you. Don't trust anyone with data. Mistakes are made. Biases are confirmed. Reproducibility & criteria for falsifiability are not proven. Unknown unknowns exist. There are different ways of categorizing & counting things. Abstraction is a lie (the map is not the territory).

There are only two hard things in Computer Science: cache invalidation, naming things, and off by one errors...