On Philosophy, Science, and Data by Jim Harris.
From the post:
Ever since Melinda Thielbar helped me demystify data science on OCDQ Radio, I have been pondering my paraphrasing of an old idea: Science without philosophy is blind; Philosophy without science is empty; Data needs both science and philosophy.
“A philosopher’s job is to find out things about the world by thinking rather than observing,” the philosopher Bertrand Russell once said. One could say a scientist’s job is to find out things about the world by observing and experimenting. In fact, Russell observed that “the most essential characteristic of scientific technique is that it proceeds from experiment, not from tradition.”
Russell also said that “science is what we know, and philosophy is what we don’t know.” However, Stuart Firestein, in his book Ignorance: How It Drives Science, explained “there is no surer way to screw up an experiment than to be certain of its outcome.”
Although it seems it would make more sense for science to be driven by what we know, by facts, “working scientists,” according to Firestein, “don’t get bogged down in the factual swamp because they don’t care that much for facts. It’s not that they discount or ignore them, but rather that they don’t see them as an end in themselves. They don’t stop at the facts; they begin there, right beyond the facts, where the facts run out. Facts are selected for the questions they create, for the ignorance they point to.”
In this sense, philosophy and science work together to help us think about and experiment with what we do and don’t know.
Some might argue that while anyone can be a philosopher, being a scientist requires more rigorous training. A commonly stated requirement in the era of big data is to hire data scientists, but this begs the question: Is data science only for data scientists?
“Is data science only for data scientists?”
Let me answer that question with a story.
There is a book, originally published in 1965, called “How to Avoid Probate.” (Legal proceedings that may follow after death.) It claimed to tell “regular folks” how to avoid this difficulty and was marketed in a number of states.
Well, except that the laws concerning property, inheritance, etc., vary from state to state and even lawyers who don’t practice inheritance law in a state will send you to someone who does.
There were even rumors that the state bar associations were funding its publication.
If you think lawyers are expensive, try self-help. Your fees could easily double or triple, if not more.
The answer to: “Is data science only for data scientists?” depends on the result you want.
If you want a high quality, reliable results, then you need to spend money on hiring data scientists.
If you want input from the managers of the sixty percent (60%) of your projects that fail, you know who to call.
BTW, be able to articulate what “success” would look like from a data science project before hiring data scientists.
If you can’t, use your failing project managers.
There isn’t enough data science talent to do around and it should not be wasted.
PS: Those who argue anyone can be a philosopher get the sort of philosophy they deserve.