Publication type: Conference paper
Type of review: Peer review (publication)
Title: A comparative assessment and synthesis of twenty ethics codes on AI and big data
Authors: Loi, Michele
Heitz, Christoph
Christen, Markus
et. al: No
DOI: 10.1109/SDS49233.2020.00015
Published in: Proceedings of the 7th SDS
Page(s): 41
Pages to: 46
Conference details: 7th Swiss Conference on Data Science, Lucerne, Switzerland, 26 June 2020
Issue Date: 2020
Publisher / Ed. Institution: IEEE
ISBN: 978-1-7281-7177-7
Language: English
Subjects: Data ethic; Ethical guideline; Artificial intelligence
Subject (DDC): 006: Special computer methods
170: Ethics
Abstract: Up to date, more than 80 codes exist for handling ethical risks of artificial intelligence and big data. In this paper, we analyse where those codes converge and where they differ. Based on an in-depth analysis of 20 guidelines, we identify three procedural action types (1. control and document, 2. inform, 3. assign responsibility) as well as four clusters of ethical values whose promotion or protection is supported by the procedural activities. We achieve a synthesis of previous approaches with a framework of seven principles, combining the four principles of biomedical ethics with three distinct procedural principles: control, transparency and accountability.
URI: https://www.zora.uzh.ch/id/eprint/190563/
https://digitalcollection.zhaw.ch/handle/11475/24471
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in collections:Publikationen School of Engineering

Files in This Item:
There are no files associated with this item.
Show full item record
Loi, M., Heitz, C., & Christen, M. (2020). A comparative assessment and synthesis of twenty ethics codes on AI and big data [Conference paper]. Proceedings of the 7th SDS, 41–46. https://doi.org/10.1109/SDS49233.2020.00015
Loi, M., Heitz, C. and Christen, M. (2020) ‘A comparative assessment and synthesis of twenty ethics codes on AI and big data’, in Proceedings of the 7th SDS. IEEE, pp. 41–46. Available at: https://doi.org/10.1109/SDS49233.2020.00015.
M. Loi, C. Heitz, and M. Christen, “A comparative assessment and synthesis of twenty ethics codes on AI and big data,” in Proceedings of the 7th SDS, 2020, pp. 41–46. doi: 10.1109/SDS49233.2020.00015.
LOI, Michele, Christoph HEITZ und Markus CHRISTEN, 2020. A comparative assessment and synthesis of twenty ethics codes on AI and big data. In: Proceedings of the 7th SDS [online]. Conference paper. IEEE. 2020. S. 41–46. ISBN 978-1-7281-7177-7. Verfügbar unter: https://www.zora.uzh.ch/id/eprint/190563/
Loi, Michele, Christoph Heitz, and Markus Christen. 2020. “A Comparative Assessment and Synthesis of Twenty Ethics Codes on AI and Big Data.” Conference paper. In Proceedings of the 7th SDS, 41–46. IEEE. https://doi.org/10.1109/SDS49233.2020.00015.
Loi, Michele, et al. “A Comparative Assessment and Synthesis of Twenty Ethics Codes on AI and Big Data.” Proceedings of the 7th SDS, IEEE, 2020, pp. 41–46, https://doi.org/10.1109/SDS49233.2020.00015.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.