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This is not the article's topic, but the title immediately made me think of a cool data technique where you trace noise backwards to determine causality. If a -
by jmward01 11mo ago
This is not the article's topic, but the title immediately made me think of a cool data technique where you trace noise backwards to determine causality. If a -> b then the noise in a should be in b.
- viscousviolin 11mo agoSounds like a fun topic to dig into. Do you have any papers or books you'd recommend?
- jmward01 11mo agoI have no idea who/when/where the 'original' idea came from. I stumbled on it when I was thinking about history and trying to tell how languages or artifacts influenced one another. I remember reading (don't know where) about linguists creating timelines based on when features appeared and capturing the version of that feature at the time it was introduced compared to how it later evolved. Again, a long time ago so no real definitive answers there. A quick search brought this paper up.[1] I just skimmed it and it looks like it has the core idea in it but no promises. [1] Causal Inference from Noise https://onlinelibrary.wiley.com/doi/pdf/10.1111/nous.12300 https://onlinelibrary.wiley.com/doi/pdf/10.1111/nous.12300
- viscousviolin 11mo agoThanks! I'll go give it a look.