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Quality of data sets that feed AI and big data applications for law enforcement

Martyna Kusak (UGent)
(2022) ERA-FORUM. 23(2). p.209-219
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Abstract
In the era of big data and artificial intelligence (AI), where aggregated data is used to learn about patterns and for decision-making, quality of input data seems to be of paramount importance. Poor data quality may lead not only to wrong outcomes, which will simply render the application useless, but more importantly to fundamental rights breaches and undermined trust in the public authorities using such applications. In law enforcement as in other sectors the question of how to ensure that data used for the development of big data and AI applications meet quality standards remains. This paper provides an overview of this topic, reporting selected issues stemming from big data, nonpersonal data and regulatory contexts. It concludes that the topic is still underexplored and sets areas for further research.
Keywords
Law enforcement, Big data, Artificial intelligence, Data quality, Data protection, Directive 2016/680

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Citation

Please use this url to cite or link to this publication:

MLA
Kusak, Martyna. “Quality of Data Sets That Feed AI and Big Data Applications for Law Enforcement.” ERA-FORUM, vol. 23, no. 2, 2022, pp. 209–19, doi:10.1007/s12027-022-00719-4.
APA
Kusak, M. (2022). Quality of data sets that feed AI and big data applications for law enforcement. ERA-FORUM, 23(2), 209–219. https://doi.org/10.1007/s12027-022-00719-4
Chicago author-date
Kusak, Martyna. 2022. “Quality of Data Sets That Feed AI and Big Data Applications for Law Enforcement.” ERA-FORUM 23 (2): 209–19. https://doi.org/10.1007/s12027-022-00719-4.
Chicago author-date (all authors)
Kusak, Martyna. 2022. “Quality of Data Sets That Feed AI and Big Data Applications for Law Enforcement.” ERA-FORUM 23 (2): 209–219. doi:10.1007/s12027-022-00719-4.
Vancouver
1.
Kusak M. Quality of data sets that feed AI and big data applications for law enforcement. ERA-FORUM. 2022;23(2):209–19.
IEEE
[1]
M. Kusak, “Quality of data sets that feed AI and big data applications for law enforcement,” ERA-FORUM, vol. 23, no. 2, pp. 209–219, 2022.
@article{01GX39GEADXYT7GSNK7YRWTYRY,
  abstract     = {{In the era of big data and artificial intelligence (AI), where aggregated data is used to learn about patterns and for decision-making, quality of input data seems to be of paramount importance. Poor data quality may lead not only to wrong outcomes, which will simply render the application useless, but more importantly to fundamental rights breaches and undermined trust in the public authorities using such applications. In law enforcement as in other sectors the question of how to ensure that data used for the development of big data and AI applications meet quality standards remains. This paper provides an overview of this topic, reporting selected issues stemming from big data, nonpersonal data and regulatory contexts. It concludes that the topic is still underexplored and sets areas for further research.}},
  author       = {{Kusak, Martyna}},
  issn         = {{1612-3093}},
  journal      = {{ERA-FORUM}},
  keywords     = {{Law enforcement,Big data,Artificial intelligence,Data quality,Data protection,Directive 2016/680}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{209--219}},
  title        = {{Quality of data sets that feed AI and big data applications for law enforcement}},
  url          = {{http://doi.org/10.1007/s12027-022-00719-4}},
  volume       = {{23}},
  year         = {{2022}},
}

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