The causal value of Big Data. Two views on causation

Not everything should be approached quantitatively. Is causation perhaps one of them?

Scientific research relies on data, and preferably lots of it. Population studies and statistical models are used to find and establish causal knowledge. The idea is that the more data we have, the better justification we have for our causal hypotheses.

Do we need causation in science?

Not everyone thinks we need causation in science. Causation is so hard to pin down and so easy to get wrong, so why don’t we instead just stick to the data? Without speculating over causal relationships we could then establish that people are happier without children, that married men live longer and that life expectancy for smokers is ten years shorter than for non-smokers. What more do we need to know?