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fuse data controllers’ mind, therefore more detailed explanations should be delivered by the EU regarding implementation of the GDPR on certain technologies, such as AI. As we presented in the example of applying differential privacy methods ensuring GDPR’s principles at some level could be one path to the solution of some of the issues, but the effect of this would be to decrease the efficiency of the AI system. Finally, we suggest that the EU Institutions may put more weight on assessing the streamlined and practical applicability of the GDPR to the AI systems. Acknowledgments This research was supported by the project nr. EFOP-3.6.2-16-2017-00007, titled Aspects on the development of intelligent, sustainable and inclusive society: social, technological, innovation networks in employment and digital economy. The project has been supported by the European Union, co-financed by the European Social Fund and the budget of Hungary. References [1] Reinsel, D., Gantz, J., Rydning, J., Data Age 2025: The Digitization of the World From Edge to Core, IDC (2018). [2] The Future Computed: Artificial Intelligence and its role in society Microsoft Corporation Redmond, Washington, 2018. [3] M. Lewis, D. Yarats, Y. N. Dauphin, D. Parikh, D. Batra, Deal or no deal? Training AI bots to ne- gotiate, Facebook Code, (2017) https://code.fb.com/ml-applications/deal-or-no-deal-training-ai-bots-to- negotiate/. [4] D. Kamarinou, C. Millard, J. Singh, Machine Learning with Personal Data Queen Mary School of Law Legal Studies Research Paper, (2016), 247, https://papers.ssrn.com/sol3/papers.cfm?abstractid142865811. [5] M. Taddy, The Technological Elements of Artificial Intelligence, in The Economics of Artificial Intelli- gence: An Agenda , A. K. Agrawal, J. Gans, and A. Goldfarb, eds, University of Chicago Press, 2018 http://www.nber.org/chapters/c14021. [6] COM (2018) 795 final. [7] European Commission High-Level Expert Group on Artificial Intelligence, A definition of AI Main capabilities and scientific disciplines, (2019). [8] K.P.L. Coopamootoo, T. Gro, Why Privacy is All but Forgotten: An Empirical Study of Privacy Sharing Attitude, Proceedings on Privacy Enhancing Technologies, 2017 4, 3960. [9] Le Metayer, S. Monteleone, Automated consent through privacy agents: Legal requirements and techni- cal architecture, Computer LawSecurity Review (2009) 136-144. [10] Article 29 Data Protection Working Party Opinion 15/2011 on the definition of consent. [11] C. Mulligan, Revenge Against Robots, S.C.L Rev., 69 (3), (2018), 579-596. [12] Wachter, B. Mittelstadt, L. Floridi, Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation, International Data Privacy Law, 7 (2), (2017), 76-99. [13] A. D. Selbst, J. Powles, Meaningful information and the right to explanation International Data Privacy Law, 7(4), (2017), 233242. [14] N. Laoutaris, Data Transparency: Concerns and Prospects, Proceedinds of the IEEE, 106 (11) (2018), 1867 - 1871. [15] T. Kim, P. Hinds, Who Should I Blame? Effects of Autonomy and Transparency on Attributions in Human-Robot Interaction, The 15th IEEE International Symposium on Robot and Human Interactive Communication (ROMAN 2006), 2007, 80-85. [16] AI Now Report, 2018, https://ainowinstitute.org/AINow2018Report.pdf. G.GultekinVarkonyi /Operability of theGDPR’sConsent Rule in Intelligent Systems214
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Intelligent Environments 2019 Workshop Proceedings of the 15th International Conference on Intelligent Environments
Titel
Intelligent Environments 2019
Untertitel
Workshop Proceedings of the 15th International Conference on Intelligent Environments
Autoren
Andrés Muñoz
Sofia Ouhbi
Wolfgang Minker
Loubna Echabbi
Miguel Navarro-Cía
Verlag
IOS Press BV
Datum
2019
Sprache
deutsch
Lizenz
CC BY-NC 4.0
ISBN
978-1-61499-983-6
Abmessungen
16.0 x 24.0 cm
Seiten
416
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Intelligent Environments 2019