Risks and Side Effects of Data Science and Data Technology

  • Clemens H. CapEmail author


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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  1. Anderson, C. W. (1989). Learning to control an inverted pendulum using neural networks. IEEE Control System Magazine, 9(3), 1989.CrossRefGoogle Scholar
  2. Borasio, G. (2016). Selbstbestimmt sterben. München: DTV Verlagsgesellschaft.Google Scholar
  3. Bornstein, A. M. (2017). Are algorithms building the new infrastructure of racism? Nautilus, 55.
  4. Brandeis, L., & Warren, S. (1890–1891). The right to privacy. Harvard Law Review, 4, 193–220.CrossRefGoogle Scholar
  5. Braschler, M., Stadelmann, T., & Stockinger, K. (2019). Data science. In M. Braschler, T. Stadelmann, & K. Stockinger (Eds.), Applied data science – Lessons learned for the data-driven business. Berlin: Springer.Google Scholar
  6. Cap, C. H. (2016). Verpflichtung der Hersteller zur Mitwirkung bei informationeller Selbstbestimmung. In M. Friedewald, J. Lamla, & A. Roßnagel (Eds.), Informationelle Selbstbestimmung im digitalen Wandel. Wiesbaden: Springer Vieweg, DuD-Fachbeiträge.Google Scholar
  7. Cap, C. H. (2017). Vertrauen in der Krise: Vom Feudalismus 2.0 zur Digitalen Aufklärung. In M. Haller (Ed.), Öffentliches Vertrauen in der Mediengesellschaft. Köln: Halem Verlag.Google Scholar
  8. Dwork, C., & Mulligan, D. (2013, September). It’s not privacy, and it’s not fair. Stanford Law Review.
  9. Esguerra, R. (2009, December 10). Google CEO Eric Schmidt dismisses the importance of privacy. Electronic Frontier Foundation.
  10. Executive Office of the President. (2016, May). Big data: A report on algorithmic systems, opportunity, and civil rights. The Whitehouse.
  11. Friedman, L. (2014, April 22). IBM’s Watson supercomputer may soon be the best doctor in the world. Business Insider.
  12. Galeon, D. (2016, October 28). IBM’s Watson AI recommends same treatment as doctors in 99% of cancer cases. Futurism.
  13. Grassegger, H., & Krogerus, M. (2016, December 3). Ich habe nur gezeigt, dass es die Bombe gibt. Das Magazin Nr. 48.
  14. Han, B.-C. (2010). Müdigkeitsgesellschaft. Berlin: Matthes & Seitz.Google Scholar
  15. Helbing, D., et al. (2015). Eine Strategie für das digitale Zeitalter, 12.11.2015, Spektrum Verlag,
  16. Hofstetter, Y. (2016). Sie wissen alles: Wie Big Data in unser Leben eindringt und warum wir um unsere Freiheit kämpfen müssen. München: Penguin.Google Scholar
  17. Hosain, S. Z. (2016). Reality check: 50B IoT devices connected by 2020 – Beyond hype and into reality. RCRWirelessNews, 28th June 2016.
  18. Konrath, S., O’Brien, E., & Hsing, C. (2011). Changes in dispositional empathy in American college students over time. Personality and Social Psychology Review, 15(2), 180–198.CrossRefGoogle Scholar
  19. Kree, I., & Earle, J. (2013, September 2013). Prediction, preemption, presumption: How big data threatens big picture privacy. Stanford Law Review.
  20. Lewis, C. S. (1972). God in the dock. Essays on theology and ethics. Grand Rapids: Eerdmans Publishing.Google Scholar
  21. Marr, B. (2015, September 28). The biggest risks of big data.
  22. Miller-Merell, J. (2012, September 27). Hiring by algorithm. The new self-checkout of HR. SmartRecruiters Blog.
  23. Nichols, S. (2017, January 7). TV anchor says live on-air ‘Alexa, order me a dollhouse’. The Register.
  24. O’Connor, A. (2011, February 15). Watson dominates Jeopardy but stumbles over geography. New York Times.
  25. Park, J., Seo, D., et al. (2014). Practical human resource allocation in software projects using genetic algorithm. In SEKE 2014, pp. 688–694.
  26. Root-Bernstein, R., & Root-Bernstein, M. (1999). Sparks of genius – The thirteen thinking tools of the world’s most creative people. Boston: Houghton Mifflin.Google Scholar
  27. Saltelli, A., & Funtowicz, S. (2017). What is science’s crisis really about? Futures, 91, 5–11.CrossRefGoogle Scholar
  28. Schönholzer, F. (2017). Digitale Pfadfinder. UZH News, 14.11.2017.
  29. Shattuck, R. (1997). Forbidden knowledge: From prometheus to pornography. Harvest Book. Here quoted from Wikiquote
  30. Teller, E. (1998). Science and morality. Science, 280(5367), 1200–1201.CrossRefGoogle Scholar
  31. Thöns, M. (2016). Patient ohne Verfügung: Das Geschäft mit dem Lebensende. München: Piper.Google Scholar
  32. Tierny, J. (2013, February 11). A match made in the code. The New York Times.
  33. Turnbull, S. (2016). Defining and achieving good governance. In G. Aras & C. Ingley (Eds.), Corporate behavior and sustainability. New York: Gower.Google Scholar
  34. Waldrop, M. (2016). The chips are down for Moore’s law. Nature, 530, 144–147.CrossRefGoogle Scholar
  35. Warriar, L., Roberts, A., & Lewis, J. (2002). 2002- Surveillance – An analysis of Jeremy Bentham Michel Foucault and their present day relevance.
  36. Watzlawik, P. (2005). Vom Schlechten des Guten oder Hekates Lösungen. München: Piper.Google Scholar
  37. Watzlawik, P. (2009). Anleitung zum Unglücklichsein. München: Piper.Google Scholar
  38. Watzlawik, P., et al. (1979). Lösungen. Zur Theorie und Praxis menschlichen Wandels. Bern: Hans Huber.Google Scholar
  39. Wehling, E. (2016). Politisches Framing: Wie eine Nation sich ihr Denken einredet – und daraus Politik macht. Köln: Halem.Google Scholar
  40. Weizenbaum, J. (1976). Computer power and human reason: From judgement to calculation. New York: Freeman.Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universität RostockRostockGermany

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