Here on Less Wrong there are a significant number of mathematically inclined software engineers who know some probability theory, meaning they've read/worked through at least one of Jaynes and Pearl but may not have gone to graduate school. How could someone with this background contribute to making causal inference more accessible to researchers? Any tools that are particularly under-developed or missing?
I am not sure I know what the most impactful thing to do is, by edu level. Let me think about it.
My intuition is the best thing for "raising the sanity waterline" is what the LW community would do with any other bias: just preaching association/causation to the masses that would otherwise read bad scientific reporting and conclude garbage about e.g. nutrition. Scientists will generally not outright lie, but are incentivized to overstate a bit, and reporters are incentivized to overstate a bit more. In general, we trust scientific output too ...
This thread is for asking any questions that might seem obvious, tangential, silly or what-have-you. Don't be shy, everyone has holes in their knowledge, though the fewer and the smaller we can make them, the better.
Please be respectful of other people's admitting ignorance and don't mock them for it, as they're doing a noble thing.
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