11. Machines Can't Learn

Unfortunately both the self taught and classically trained machine learning engineer, work in a field whose name is made up of two words that when combined in that order result in a logical contradiction. This contradiction arises from the logical structure of the world which is (partly) determined by how the words in the language we use to describe it are defined. The (accepted by most) definitions of the words “machine” and “learning” preclude a machine (or any abiotic entity/being/thing/concept) from having the ability to learn. Simply put if a machines could learn it would no longer be a machine. Like data science, the so called science which does not use nor require the use of the scientific method, machine learning has been saddled with a name which does a grave disservice to those who work in the profession and the bulk of the non technical public. Both are laboring under the assumption that Machine learning engineers and data scientists are doing something that they are not in fact doing (building/programming intelligent machines that can learn and practicing science). They are each being deceived, the first by themselves and the second by the first and their cheerleaders in the mass media and bus/tech blogosphere.

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