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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},
}