• Medientyp: E-Book
  • Titel: Machine Learning with Personal Data
  • Beteiligte: Kamarinou, Dimitra [VerfasserIn]; Millard, Christopher [Sonstige Person, Familie und Körperschaft]; Singh, Jatinder [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2016]
  • Erschienen in: Queen Mary School of Law Legal Studies Research Paper ; No. 247/2016
  • Umfang: 1 Online-Ressource (23 p)
  • Sprache: Englisch
  • Entstehung:
  • Anmerkungen: In: Queen Mary School of Law Legal Studies Research Paper No. 247/2016
    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 7, 2016 erstellt
  • Beschreibung: This paper provides an analysis of the impact of using machine learning to conduct profiling of individuals in the context of the EU General Data Protection Regulation.We look at what profiling means and at the right that data subjects have not to be subject to decisions based solely on automated processing, including profiling, which produce legal effects concerning them or significantly affect them. We also look at data subjects' right to be informed about the existence of automated decision-making, including profiling, and their right to receive meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing.The purpose of this paper is to explore the application of relevant data protection rights and obligations to machine learning, including implications for the development and deployment of machine learning systems and the ways in which personal data are collected and used. In particular, we consider what compliance with the first data protection principle of lawful, fair, and transparent processing means in the context of using machine learning for profiling purposes. We ask whether automated processing utilising machine learning, including for profiling purposes, might in fact offer benefits and not merely present challenges in relation to fair and lawful processing
  • Zugangsstatus: Freier Zugang