Artificial Intelligence and Machine Learning Powered Public Service Delivery in Estonia: Opportunities and Legal Challenges: 2 (Data Science, Machine Intelligence, and Law, 2) - Tapa dura

Ebers, Martin; Tupay, Paloma Krõõt

 
9783031196669: Artificial Intelligence and Machine Learning Powered Public Service Delivery in Estonia: Opportunities and Legal Challenges: 2 (Data Science, Machine Intelligence, and Law, 2)
Tapa dura
ISBN 10: 303119666X ISBN 13: 9783031196669
Editorial: Springer, 2023

Sinopsis

This book gives a comprehensive overview of the state of Artificial Intelligence (AI), especially machine learning (ML) applications in public service delivery in Estonia, discussing the manifold ethical and legal issues that arise under both European and Estonian law. Final conclusions and recommendations set out and analyze various policy options for the public sector, taking into account recent developments at the European level - such as the AIA proposal - as well as the experience of countries that have issued principles and guidelines or even laws for the use of ML in the public sector. 

"For two reasons, this study is relevant not only for an audience which is interested in Estonian administrative law. First, the authors base their legal analysis primarily on EU law and provide a state of the art-analysis of the relevant secondary legislation. This makes the book a reference text for the European debate on public sector AI governance. Second, this study is part of a larger research project in which four specific use cases of public sector AI have been developed and tested. The practical insights gained in these projects have provided the authors with an excellent understanding of the opportunities and risks of the technology, which distinguishes this legal analysis from similar enterprises." Excerpt from the foreword by Professor Thomas Wischmeyer (University of Bielefeld) 

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Acerca del autor

Martin Ebers is co-founder and president of the Robotics & AI Law Society (RAILS), Associate Professor of IT Law at the University of Tartu (Estonia) and as “Privatdozent” permanent member of the law faculty of the Humboldt University of Berlin (Germany). In addition, he is co-director of the German Institute for Energy and Competition Law in the Public Sector. Martin taught and presented at more than 100 international conferences, is a member of several national and international research networks and published 16 books and over 120 articles in the field of Law & Technology, esp. Artificial Intelligence, as well as in Commercial, Private, European, Comparative and International Law. His latest books are amongst others Algorithms and Law (Cambridge University Press, 2020); Algorithmic Governance and Governance of Algorithms (Springer Nature, 2021); and Contracting and Contract Law in the Age of Artificial Intelligence (Hart Publishing, 2022). In addition to research and teaching, Martin has been active in the field of legal consulting for many years. He is actively involved in the rapidly growing legal technology industry, as an advisor of legal tech companies and an organizer of the “Tech & Law Camps” offered by RAILS.

Paloma Krõõt Tupay teaches constitutional law at the University of Tartu in Estonia. In addition to questions of democratic state architecture, she focuses her research activities on issues of data protection, e-government and digital constitutionalism. She has co-authored a legal evaluation on questions of possibilities for the use of artificial intelligence in e-government and been part of a study on the impact of Artificial intelligence and big data on the fundamental rights in the EU requested by the European Union Agency for Fundamental Rights. Currently, she is working on the completion of a constitutional law textbook. Previously, she has worked as a legal advisor to the Estonian President and also to the Minister of Interior. Recentpublications include: Is European data protection toxic for innovative AI? – An Estonian perspective. Juridica International 2021, 99-110 (together with Martin Ebers; Jakob Juksaar; Kea Kohv); Estonia, the Digital Nation: Reflections on a Digital Citizen’s Rights in the European Union in: European Data Protection Law Review, 6 (2) 2020, 294-300.

De la contraportada

This book gives a comprehensive overview of the state of Artificial Intelligence (AI), especially machine learning (ML) applications in public service delivery in Estonia, discussing the manifold ethical and legal issues that arise under both European and Estonian law. Final conclusions and recommendations set out and analyze various policy options for the public sector, taking into account recent developments at the European level – such as the AIA proposal – as well as the experience of countries that have issued principles and guidelines or even laws for the use of ML in the public sector. 

“For two reasons, this study is relevant not only for an audience which is interested in Estonian administrative law. First, the authors base their legal analysis primarily on EU law and provide a state of the art-analysis of the relevant secondary legislation. This makes the book a reference text for the European debate on public sector AI governance. Second, this study is part of a larger research project in which four specific use cases of public sector AI have been developed and tested. The practical insights gained in these projects have provided the authors with an excellent understanding of the opportunities and risks of the technology, which distinguishes this legal analysis from similar enterprises.” Excerpt from the foreword by Professor Thomas Wischmeyer (University of Bielefeld) 



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Editorial
Springer
Año de publicación
2023
Idioma
Inglés
ISBN 10 
303119666X
ISBN 13 
9783031196669
Encuadernación
Tapa dura
Número de páginas
260
Contacto del fabricante
no disponible
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9783031196690: Artificial Intelligence and Machine Learning Powered Public Service Delivery in Estonia: Opportunities and Legal Challenges: 2 (Data Science, Machine Intelligence, and Law)

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ISBN 10:  3031196694 ISBN 13:  9783031196690
Editorial: Springer, 2024
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