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What method would you use to yield scientific knowledge in the sense of cause-reaction? Many important processes really do have large numbers of causal factors
by ppod 8y ago
What method would you use to yield scientific knowledge in the sense of cause-reaction? Many important processes really do have large numbers of causal factors that interact non-linearly. If we want to try to learn about that, some statistical method that deals with many parameters will be needed. Such models are generally referred to as "Machine Learning". Their generalisation or causal inference properties are particular to each implementation and identification strategy, but you can't just say "ML will never yield scientific knowledge".
- fock 8y agoA tool called Mathematics which can exactly describe this interactions. And if those processes have a lot of variables, a ML-model might certainly be useful, but it will never be generally applicable! This probably also contributes to "scientific knowledge" but it's not the same as scientific facts (or whatever you call universally transferable results).
- ppod 8y agoYou're building your mathematical model based on the knowledge you have, which is from the data you have, and there is still the same risk that your theory won't generalize to new observations.