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Scientists from fields that rely on data, like physics, often do well as data scientists. I myself like Information Science more than Data Science, but I do not care that much for semantics. There was a need to specify a role of someone who makes sense out of data, gathers insights, using the tools from mathematics, computer science, statistics, and information theory. It's also a different type of science, data-driven science, as opposed to theoretical/metaphysical, empirical, or computational science. There was an old joke that AI stood for Advanced Informatics. I think the commercialization of the term "AI" is a bit harmful and obfuscating. Companies tumble over one another to market their professionals as Applied AI or their products as AI. AI is the automation of human thought. It includes philosophy and cognitive science, both fields seem completely missing for applied AI. I know many AI researchers already switched to calling themselves ML researchers a few years back. This, because the field of AI became muddied with futurist adherents of the Singularity. Did not help that the public perception of AI is somewhere between "Skynet is coming!" and "AI will take my job". Nowadays, ML is also heavily saturated and hyped beyond repair. Meanwhile the field of AI has not even solved the common sense problem. https://en.wikipedia.org/wiki/Commonsense_knowledge_(artific... |