Microchipping Employees: Unlawful Monitoring Practice or a New Trend in the Workplace?
A specific technology has been making its way into a growing number of workplaces. In addition to computer screen recording, video surveillance, keystroke monitoring, location tracking and social media monitoring, employers can now use microchips as an ad
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Martin Ebers Marta Cantero Gamito Editors
Algorithmic Governance and Governance of Algorithms Legal and Ethical Challenges
Data Science, Machine Intelligence, and Law Volume 1
Series Editors Giovanni Comandè, Scuola Superiore Sant’Anna, Pisa, Italy Martin Ebers, University of Tartu, Tartu, Estonia Mimi Zou, University of Oxford, Oxford, UK
Data-driven technologies, such as AI systems and robotics, have the potential to improve our lives, our society and our economy. At the same time, the development and use of these technologies raise unresolved legal and ethical issues. Our new peer reviewed book series brings together works from different legal fields, dealing with the legal, social and economic impact of these technologies, exploring on the one hand the opportunities for law and legal practice, and on the other hand, the ethical and legal frameworks they require. The series especially welcomes book proposals dealing with the legal and/or ethical aspects of data science and the emerging discipline of machine intelligence, which encompasses perception (sensing), AI (planning) and robotics (acting). In this way, our book series aims to contribute to an informed dialogue across the various disciplines about the chances and risks of data-driven systems.
More information about this series at http://www.springer.com/series/16609
Martin Ebers • Marta Cantero Gamito Editors
Algorithmic Governance and Governance of Algorithms Legal and Ethical Challenges
Editors Martin Ebers Humboldt University of Berlin, Law Faculty Berlin, Germany University of Tartu, School of Law Tartu, Estonia
Marta Cantero Gamito CUNEF, Law Department Madrid, Spain University of Tartu, School of Law Tartu, Estonia
ISSN 2730-5899 ISSN 2730-5902 (electronic) Data Science, Machine Intelligence, and Law ISBN 978-3-030-50558-5 ISBN 978-3-030-50559-2 (eBook) https://doi.org/10.1007/978-3-030-50559-2 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the m
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