1. Take a bunch of easily available data (which hasn’t been validated for completeness, accuracy, bias, etc)
2. Apply some easily available algorithmic analysis (that the author doesn’t have a deep understand of)
3. Put it in an easily available visualization (that has been chosen primarily to look nice)
4. Draw some conclusions and assert that is backed by data
They feel rigorous because “wow so much data” and novel because “you couldn’t do this before computers + internet” but there are so many ways to get it wrong and reach different conclusions if your data is bad or your algorithms are misapplied.
It felt like some parent's personal blog ruminating on an idea, not an "article".
Claude followed links on a single Wikipedia article and visualized the results geographically for one image so the author could keep talking about how we (and he) know basically nothing.
Doesn't seem like it belongs on HN.
Well, the conclusion of the article is that humans cannot either, it's not like humans have some magical conduit towards truth.