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            People Analytics in privatrechtlichen Arbeitsverhältnissen

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            Author(s)
            Kasper, Gabriel
            Collection
            Swiss National Science Foundation (SNF)
            Language
            English
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            Abstract
            This legal dissertation is dedicated to the topic of people analytics in private law employment relationships. People Analytics refers to the practice of personnel development in which digital data from internal and external sources relating to human capital are systematically evaluated using information technology in order to make decisions that increase the value of a company. The author begins by identifying the differences between people analytics and older forms of monitoring in the workplace as well as the resulting legal problems. After considering the various applicable fields of law, he focuses on the analysis of employment and data protection law. Key findings include the following three facts: that data protection regulations, which are predominantly procedural in nature, must be interpreted in a risk-oriented manner; that, in the work context, consent should be avoided as a reason to justify data processing; and that there are deficiencies in the enforcement of data protection in private law. Based on this, the author develops an improvement concept aimed at professionalising and democratising data protection law. He contrasts his theoretical considerations with the empirical data that he has collected as part of an interdisciplinary research project. In addition to the existing Swiss Data Protection Act, this dissertation takes into account the proposals for the future, fully revised Swiss Data Protection Act, the EU General Data Protection Regulation and selected aspects of US data protection law. The dissertation has won the Stefano Rodotà Award of the Council of Europe and the Professor Walther Hug Prize.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/152255
            Keywords
            People Analytics; Big Data; Datenschutz; Arbeitsrecht; Diskriminierung; Überwachung; thema EDItEUR::L Law
            DOI
            10.3256/978-3-03929-009-3
            ISBN
            9783039290093
            Publication date and place
            Zürich/St. Gallen, 2021
            Grantor
            • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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