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Data Positivism Since World War II (2018) [pdf] (columbia.edu)
39 points by benbreen 23 days ago | hide | past | web | favorite | 6 comments



To anyone who upvoted this: can you explain what you found interesting about it? I read the entire thing and found it to be rather rambling with no clear point. I’m trying to keep an open mind though, so I’m interested to hear some context or another view that might make it more clear.


For me, this was the key paragraph (the paper is basically a history of how the second "culture" mentioned here came to predominate in data science):

"In 2001, the renegade statistician Leo Breiman described 'two cultures' of using statistical models 'to reach conclusions from data.' The first 'assumes that the data are generated by a given stochastic data model.' The second 'uses algorithmic models and treats the data mechanisms as unknown.' This essay sketches the diverse sources of this second algorithmic culture, one stemming more from an engineering culture of predictive utility than from a scientific culture of truth."

As an historian, I was also interested by the part in the conclusion that drew a parallel between recent conceptual shifts among historians of science and data scientists.* Plus I just think it's cool that historians are now starting to really dig into the intellectual history of machine learning in the same way that they study, say, the history of biology or physics.

*This passage: "For at least three decades, professional historians of science have pushed against a vision of science modeled on theoretical physics; we now celebrate the diverse forms of knowledge focused on the careful empirical study of particular things. Exponents of data-focused computational science have a sur- prisingly similar evolution. Just as history of science embraced the study of the particular as it disconnected from a Cold War prioritizing of theory, the data sciences moved beyond the aggregates of mathematical statistics to draw upon granular data sets to characterize particular things—individual people, diseases, films. In a key manifesto celebrating the 'unreasonable effectivenessof data,' three Google researchers argued in terms that echo humanist denun- ciations of reductionist knowledge: “sciences that involve human beings rather than elementary particles have proven more resistant to elegant mathematics.” Something else is needed. 'Perhaps when it comes to natural language proces- sing and related fields, we’re doomed to complex theories that will never have the elegance of physics equations. But if that’s so, we should...embrace complexity and make use of the best ally we have: the unreasonable effective- ness of data.'"


That second culture being instrumentalism, which has a very long wikipedia page. I didn't enjoy reading the article, because it's overly vague, inflated with intellectualism, but it's interesting to know that a non-instrumentalist mindset was dominant before WWII, changed by the practical needs of the military. I never thought about it, that there could be a different way to think about data, a more theoretical, less practical-application driven outlook.

https://en.wikipedia.org/wiki/Instrumentalism


Or, how US upper class culture became one of mindless empiracism suffering replication crises and unable to do the imaginative long-term planning that requires confidence in theory.


Yeah except ... Market Driven Empiricism won over Soviet marxist theory driven socialist control. Not to forget enormous social progress from civil rights to lgbt rights.


Hey, at least you understand I was contrasting with German philosophical traditions. Now Hayek and probably others in the Austrian school were also wary of empiricism, and what we have in the US is neither free market or welfare state, but some zombie compromise which has much of the downsides of both.




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