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Recommender Systems: Legal and Ethical Issues

Overview of attention for book
Cover of 'Recommender Systems: Legal and Ethical Issues'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction: Understanding and Regulating AI-Powered Recommender Systems
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    Chapter 2 Recommender Systems and Discrimination
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    Chapter 3 From Algorithmic Transparency to Algorithmic Choice: European Perspectives on Recommender Systems and Platform Regulation
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    Chapter 4 Black Hole Instead of Black Box?: The Double Opaqueness of Recommender Systems on Gaming Platforms and Its Legal Implications
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    Chapter 5 Digital Labor as a Structural Fairness Issue in Recommender Systems
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    Chapter 6 Recommender Systems, Manipulation and Private Autonomy: How European Civil Law Regulates and Should Regulate Recommender Systems for the Benefit of Private Autonomy
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    Chapter 7 Reasoning with Recommender Systems? Practical Reasoning, Digital Nudging, and Autonomy
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    Chapter 8 Recommending Ourselves to Death: Values in the Age of Algorithms
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    Chapter 9 Ethical and Legal Analysis of Machine Learning Based Systems: A Scenario Analysis of a Food Recommender System
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    Chapter 10 Factors Influencing Trust and Use of Recommendation AI: A Case Study of Diet Improvement AI in Japan
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    Chapter 11 Ethics of E-Learning Recommender Systems: Epistemic Positioning and Ideological Orientation
Attention for Chapter 9: Ethical and Legal Analysis of Machine Learning Based Systems: A Scenario Analysis of a Food Recommender System
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Readers on

mendeley
5 Mendeley
Summary
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Chapter title
Ethical and Legal Analysis of Machine Learning Based Systems: A Scenario Analysis of a Food Recommender System
Chapter number 9
Book title
Recommender Systems: Legal and Ethical Issues
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-34804-4_9
Book ISBNs
978-3-03-134803-7, 978-3-03-134804-4
Authors

Levina, Olga, Mattern, Saskia

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 20%
Student > Ph. D. Student 1 20%
Lecturer 1 20%
Student > Doctoral Student 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 1 20%
Business, Management and Accounting 1 20%
Computer Science 1 20%
Unknown 2 40%

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