People Analytics in privatrechtlichen Arbeitsverhältnissen
Author(s)
Kasper, Gabriel
Collection
Swiss National Science Foundation (SNF)Language
EnglishAbstract
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.
Keywords
People Analytics; Big Data; Datenschutz; Arbeitsrecht; Diskriminierung; ÜberwachungDOI
10.3256/978-3-03929-009-3ISBN
9783039290093, 9783039290093Publisher
Dike Verlag AGPublication date and place
Zürich/St. Gallen, 2021Classification
Law