6 karma · joined June 24, 2022
ilu
what i mean is that once i started running product experiments at scale in really hyperoptimized environments, my sense of what's realistically possible with small data sets collected by humans describing meatspace circumstances contracted fairly dramatically. I don't just mean replication crisis issues, although those are real; im instead skeptical of nearly all of the empirical work being done in nearly every social science field.
that is, im not arguing that tech does a great job facilitating research into eg maternity leave policies. rather, im saying i dont think anyone is learning much about them at all.
im happy to acknowledge that this is a minority view.
I just dont think this is true in practice. One of my industry-linked professors really turned me on to the stark difference in data availability in the private sector vs what academics (in social science to be clear!) have access to and it's night and day.
Economists frequently just rehash the same tired quarterly data sets with marginally different models or methods; meanwhile Amazon generates petabytes of incredibled detailed and realtime sales data every--what, month? And indeed they're making use of it: https://www.amazon.science/publications/new-goods-productivi...
Your model of science seems highly idealized compared to the reality that I experienced; and this isn't an ontological question, it's straightforwardly empirical. Social media sites have billions of users and graphed networks; academic psychologists have groups of 30 undergraduates. Economists have surveys and Fed data while Amazon has . . . Amazon's entire dataset, along with what was when I last checked the largest concentration of economics PhDs outside the Federal Reserve System.
I agree that industry isn't universally preferable to the academy and I definitely wasn't trying to make that claim.