Correlation vs causation has sort of become a cultural trapdoor to all new claims. In reality, it is very hard to find the actual cause of many things we take for granted. Its often that the first event that sets off the chain of events is mentioned as the cause itself. Sometimes even if one doesn't know the mechanism, as long as you can reliably reproduce or predict the same, its seen as good enough for practical purposes, if not for textbook teaching.
For example, not drinking water for a day tends to make me thirsty. Thats a correlation. Is it the cause? Not really. It just sets off a chain of events, which triggers dehydration, and eventually neuro chemical triggers of thirst somewhere in my brain centre.Even that centre is probably not well understood. But we still say "not drinking water causes thirst". it may be possible to mess with that circuitry to avoid these feelings. In fact a lot of neurological drugs prey on this fact.
Causality is a very philosopical subject. But I would argue that for most practical purposes, reproducibility and predictability are often good enough to be useful, even if mechanism is currently unknown.
See manipulation theories in causality (along with some intro on causality calculus) if you really want to dig deep into the beast known as causality.
For example, not drinking water for a day tends to make me thirsty. Thats a correlation. Is it the cause? Not really. It just sets off a chain of events, which triggers dehydration, and eventually neuro chemical triggers of thirst somewhere in my brain centre.Even that centre is probably not well understood. But we still say "not drinking water causes thirst". it may be possible to mess with that circuitry to avoid these feelings. In fact a lot of neurological drugs prey on this fact.
Causality is a very philosopical subject. But I would argue that for most practical purposes, reproducibility and predictability are often good enough to be useful, even if mechanism is currently unknown.
See manipulation theories in causality (along with some intro on causality calculus) if you really want to dig deep into the beast known as causality.