To address the question of ethics in any arena, including Data Science, first, we need to question ourselves what is the standard used to define what is “good” and “bad.” The importance of knowing such a standard is fundamental since choosing the wrong standard can generate false definitions for what is “good” and “bad” with a variety of consequences in society and, in this case, in the practice and use of Data Science. Hence, the standard must be absolute because if it changes, then the meaning of “good” and “bad” is lost, and we fall into a moral relativism situation.
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Principal Data Scientist