Abstract
In addition to the familiar and well-known privacy concerns, there are more serious general risks and side effects of data science and data technology. A full understanding requires a broader and more philosophical look on the defining frames and on the goals of data science. Is the aim of continuously optimizing decisions based on recorded data still helpful or have we reached a point where this mind-set produces problems? This contribution provides some arguments toward a skeptical evaluation of data science. The underlying conflict has the nature of a second order problem: It cannot be solved with the rational mind-set of data science as it might be this mind-set which produces the problem in the first run. Moreover, data science impacts society in the large—there is no laboratory in which its effects can be studied in a controlled series of experiments and where simple solutions can be generated and tested.
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Cap, C.H. (2019). Risks and Side Effects of Data Science and Data Technology. In: Braschler, M., Stadelmann, T., Stockinger, K. (eds) Applied Data Science. Springer, Cham. https://doi.org/10.1007/978-3-030-11821-1_6
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DOI: https://doi.org/10.1007/978-3-030-11821-1_6
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