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Effects of Unreliable Group Profiling by Means of Data Mining

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2843))

Abstract

With the rise of data mining technologies, group profiling -i.e. ascribing characteristics to groups of people- has increasingly become a useful tool for policy-making, direct marketing, etc. However, group profiles usually contain statistics and therefore the characteristics of group profiles may be valid for the group and for individuals as members of that group, though not for individuals as such. When individuals are judged by group characteristics they do not posses as individuals, this may strongly influence the advantages and disadvantages of using group profiles. However, striving for more reliable group profiles only provides a partial solution to this problem, since perfectly reliable group profiles may still result in unjustifiable treatment of people. A broader solution to deal with the disadvantages of group profiles may be found in developing new ethical, legal, and technological standards that adequately recognize the possible harmful consequences of particular types of information.

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© 2003 Springer-Verlag Berlin Heidelberg

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Custers, B. (2003). Effects of Unreliable Group Profiling by Means of Data Mining. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_25

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  • DOI: https://doi.org/10.1007/978-3-540-39644-4_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20293-6

  • Online ISBN: 978-3-540-39644-4

  • eBook Packages: Springer Book Archive

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