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Regulating Artificial Intelligence

Overview of attention for book
Cover of 'Regulating Artificial Intelligence'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Artificial Intelligence as a Challenge for Law and Regulation
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    Chapter 2 Artificial Intelligence and the Fundamental Right to Data Protection: Opening the Door for Technological Innovation and Innovative Protection
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    Chapter 3 Artificial Intelligence and Autonomy: Self-Determination in the Age of Automated Systems
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    Chapter 4 Artificial Intelligence and Transparency: Opening the Black Box
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    Chapter 5 Artificial Intelligence and Discrimination: Discriminating Against Discriminatory Systems
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    Chapter 6 Artificial Intelligence and Legal Personality: Introducing “Teilrechtsfähigkeit”: A Partial Legal Status Made in Germany
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    Chapter 7 Artificial Intelligence and Social Media
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    Chapter 8 Artificial Intelligence and Legal Tech: Challenges to the Rule of Law
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    Chapter 9 Artificial Intelligence and Administrative Decisions Under Uncertainty
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    Chapter 10 Artificial Intelligence and Law Enforcement
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    Chapter 11 Artificial Intelligence and the Financial Markets: Business as Usual?
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    Chapter 12 Artificial Intelligence and Public Governance: Normative Guidelines for Artificial Intelligence in Government and Public Administration
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    Chapter 13 Artificial Intelligence and Taxation: Risk Management in Fully Automated Taxation Procedures
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    Chapter 14 Artificial Intelligence and Healthcare: Products and Procedures
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    Chapter 15 Artificial Intelligence in Healthcare: Doctors, Patients and Liabilities
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    Chapter 16 Artificial Intelligence and Competition Law
Attention for Chapter 10: Artificial Intelligence and Law Enforcement
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1 tweeter

Citations

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Readers on

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80 Mendeley
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Chapter title
Artificial Intelligence and Law Enforcement
Chapter number 10
Book title
Regulating Artificial Intelligence
Published by
Springer, Cham, November 2019
DOI 10.1007/978-3-030-32361-5_10
Book ISBNs
978-3-03-032360-8, 978-3-03-032361-5
Authors

Timo Rademacher

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 16%
Student > Master 11 14%
Researcher 9 11%
Professor > Associate Professor 4 5%
Student > Doctoral Student 2 3%
Other 11 14%
Unknown 30 38%
Readers by discipline Count As %
Social Sciences 20 25%
Computer Science 11 14%
Business, Management and Accounting 6 8%
Engineering 3 4%
Arts and Humanities 2 3%
Other 8 10%
Unknown 30 38%