Artificial intelligence and machine learning powered public service delivery in Estonia : opportunities and legal challenges / Martin Ebers, Paloma Krõõt Tupay.
Ebers, Martin, 1970- author.; Tupay, Paloma Krõõt, author.
2023
JF1525.A8
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Title
Artificial intelligence and machine learning powered public service delivery in Estonia : opportunities and legal challenges / Martin Ebers, Paloma Krõõt Tupay.
Author
Ebers, Martin, 1970- author.
ISBN
9783031196676 (electronic bk.)
3031196678 (electronic bk.)
9783031196669
303119666X
DOI
https://doi.org/10.1007/978-3-031-19667-6
Published
Cham : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (xxi, 237 pages).
Item Number
10.1007/978-3-031-19667-6 doi
Call Number
JF1525.A8
Dewey Decimal Classification
352.3/802854678
Summary
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) .
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 25, 2023).
Added Author
Tupay, Paloma Krõõt, author.
Series
Data science, machine intelligence, and law ; volume 2. 2730-5902
Available in Other Form
Print version: 9783031196669
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1. Introduction
2. The Promise and Perils of AI and ML in Public Administration
3.The Regulatory Framework in Overview
4. Privacy Issues: Processing Personal Data, Monitoring, and Profiling Citizens
5. Delegation of Administrative Powers to AI Systems
6. Due Process, Fair Trial, Transparency, and Explainability
7. Fairness and Equal Treatment
8. Safety and Security
9. Accountability and Liability
10. Intellectual Property Rights and Data Ownership
11. Final Conclusions and Recommendations.

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