• DocumentCode
    2031407
  • Title

    Decoding, hacking, and optimizing societies: Exploring potential applications of human data analytics in sociological engineering, both internally and as offensive weapons

  • Author

    Maus, Gregory

  • fYear
    2015
  • fDate
    28-30 July 2015
  • Firstpage
    538
  • Lastpage
    547
  • Abstract
    Today´s unprecedented wealth of data on human activities, augmented by proven reliable methods of algorithmically extrapolating personal information from limited data, and the means to store and analyze it opens up new vistas for in-depth understanding of individuals, as well as the potential generation of predictive models for the dynamics of human functions on individual, group, and societal scales. This has already proven to have applications in successfully forecasting behavior, techniques which are only likely to improve. To the extent that the science can move beyond a correlative understanding of the data to a causal understanding of the factors affecting behavior, it will allow new means for (perhaps covertly and deniably) influencing behavior, possibly through long causal chains that could conceal the influence of the manipulator. This offers an immense variety of applications, but this paper will particularly consider them as tools in governmental control over their citizens and as a new form of weaponry.
  • Keywords
    Big Data; computer crime; data analysis; social sciences computing; Big Data; forecasting behavior; governmental control; human data analytics; human function dynamics; offensive weapons; personal information extrapolation; predictive models; society decoding; society hacking; society optimization; sociological engineering; Accuracy; Facebook; Forecasting; Government; Media; Prediction algorithms; Predictive models; big data; cognitive security; computational sociology; machine learning; privacy; sentiment analysis; surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Science and Information Conference (SAI), 2015
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/SAI.2015.7237195
  • Filename
    7237195