Yet another example of why data science is not science. Research in actual science is not about finding the “right” information. Research is about hypothesizing a possible solution to a problem or hypothesizing what a problem is and then experimenting to generate data that might strengthen or weaken the hypothesis. We do this without preconceptions about what the “right” answer might be. After the experiments are completed, the results are analyzed to determine how well they fit the hypothesis. If the data fit the hypothesis it is said to be strong or plausible, but it is never said to be the right answer. In actual science we can never find the right answer, we can only find the most plausible hypothesis. At the same time we can continually eliminate those which are falsifiable. Eventually we are left with the strongest hypothesis which can eventually be codified into a law if it is strong enough to answer every challenge. Nowhere in the process is a right answer ever sought or found. Data science is a tool of science, it is not science. This is no value judgement on it’s importance or power it is simply the fact of the matter. Being a great data “scientist” is a worthy goal but it will not make you a great scientist because you will not be a scientist no matter how good you become at data “science.” For more see below links.

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Research scientist (Ph.D. micro/mol biology), Thought middle manager, Everyday junglist, Selecta (Ret.), Boulderer, Cat lover, Fish hater

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