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Theory-free inference is a hell of a drug. For years, Big Data advocates - the larval form of today's AI weirdos - have insisted that if you have enough data, you can infer causal relationships between complex phenomena without ever having to understand how x causes y, and thus, we can slay the dread "correlation is not causation" beast.

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Hi Cory. I would like to note something when you are writing about Inuit in the future. After working in comms for the Nunavut government, Inuit prefer you write "Inuit" rather than "Inuit people." For them, you are writing "people people." Many Inuit comms colleagues also told me it is unusual to write "Canadian people" when "Canadians" works.

Love what you write, and read the Pluralistic daily.

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Only idiots thought identified relationships would always be causal. If a clear relationship is detected between two sets of data, there might be a hidden third (etc.) data set that causes both. It is likely to alert you that there are things you don't know yet. Who would pass up the opportunity to expand the frontier of their known ignorance? I worked in IT system fault analysis where finding the common cause of seemingly unrelated errors is a dark art. Any help is welcome.