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@ARTICLE{Eickhoff:866494,
      author       = {Eickhoff, Simon and Langner, Robert},
      title        = {{N}euroimaging-based prediction of mental traits: {R}oad to
                      utopia or {O}rwell?},
      journal      = {PLoS biology},
      volume       = {17},
      number       = {11},
      issn         = {1545-7885},
      address      = {Lawrence, KS},
      publisher    = {PLoS},
      reportid     = {FZJ-2019-05596},
      pages        = {e3000497},
      year         = {2019},
      abstract     = {Predicting individual mental traits and behavioral
                      dispositions from brain imaging data through
                      machine-learning approaches is becoming a rapidly evolving
                      field in neuroscience. Beyond scientific and clinical
                      applications, such approaches also hold the potential to
                      gain substantial influence in fields such as human resource
                      management, education, or criminal law. Although several
                      challenges render real-life applications of such tools
                      difficult, future conflicts of individual, economic, and
                      public interests are preprogrammed, given the prospect of
                      improved personalized predictions across many domains. In
                      this Perspective paper, we thus argue for the need to engage
                      in a discussion on the ethical, legal, and societal
                      implications of the emergent possibilities for brain-based
                      predictions and outline some of the aspects for this
                      discourse.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571)},
      pid          = {G:(DE-HGF)POF3-571},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31725713},
      UT           = {WOS:000501223700028},
      doi          = {10.1371/journal.pbio.3000497},
      url          = {https://juser.fz-juelich.de/record/866494},
}