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Automated copyright filters = a law ...

Englisch, Oliver.

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Automated copyright filters = a law and economics analysis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Automated copyright filters/ by Oliver Englisch.
Reminder of title:	a law and economics analysis /
Author:	Englisch, Oliver.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	x, 244 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Chapter 1. Introduction -- Chapter 2. Economic, Technical, and Legal Background -- Chapter 3. Impact of Automated Filtering on Right Holders' Profits and Availability of Works on Platform -- Chapter 4. Design of Automated Filtering to Approach Efficient Error Avoidance -- Chapter 5. Improving Right Holders' and Platforms' Incentives to Design Automated Filtering -- Chapter 6. Conclusion.
Contained By:	Springer Nature eBook
Subject:	Copyright. -
Online resource:	https://doi.org/10.1007/978-3-031-83161-4
ISBN:	9783031831614

Automated copyright filters = a law and economics analysis /
Englisch, Oliver.

Automated copyright filtersa law and economics analysis /[electronic resource] :by Oliver Englisch. - Cham :Springer Nature Switzerland :2025. - x, 244 p. :ill. (chiefly color), digital ;24 cm. - International law and economics,2364-186X. - International law and economics..

Chapter 1. Introduction -- Chapter 2. Economic, Technical, and Legal Background -- Chapter 3. Impact of Automated Filtering on Right Holders' Profits and Availability of Works on Platform -- Chapter 4. Design of Automated Filtering to Approach Efficient Error Avoidance -- Chapter 5. Improving Right Holders' and Platforms' Incentives to Design Automated Filtering -- Chapter 6. Conclusion.

The automated filtering of upload attempts to online platforms is one of the most contentious issues in the fields of copyright enforcement and platform regulation. Notwithstanding the impassioned debate, research from a law and economics perspective is scarce. This book presents the first comprehensive economic analysis of automated copyright filtering. The author develops an economic model of the competition between right holders and copyright-infringing uploaders on a platform. Furthermore, he applies insights from the economic literature on decision-making under uncertainty and incentive alignment to automated copyright filtering. The analysis disentangles complex relationships and challenges prevailing assumptions. It offers a novel perspective on the implications of automated filtering for the objectives of copyright policy, on the avoidance of erroneous filtering decisions, and on regulatory approaches to automated filtering. The author employs his findings to evaluate the current US and EU legal frameworks and proposes improvements. This book will appeal to researchers and policy makers interested in automated filtering, copyright enforcement, and platform regulation.

ISBN: 9783031831614

Standard No.: 10.1007/978-3-031-83161-4doiSubjects--Topical Terms:

601694
Copyright.

LC Class. No.: K1420.5

Dewey Class. No.: 346.0482

Automated copyright filters = a law and economics analysis /
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490 1 $a International law and economics, $x 2364-186X
505 0 $a Chapter 1. Introduction -- Chapter 2. Economic, Technical, and Legal Background -- Chapter 3. Impact of Automated Filtering on Right Holders' Profits and Availability of Works on Platform -- Chapter 4. Design of Automated Filtering to Approach Efficient Error Avoidance -- Chapter 5. Improving Right Holders' and Platforms' Incentives to Design Automated Filtering -- Chapter 6. Conclusion.
520 $a The automated filtering of upload attempts to online platforms is one of the most contentious issues in the fields of copyright enforcement and platform regulation. Notwithstanding the impassioned debate, research from a law and economics perspective is scarce. This book presents the first comprehensive economic analysis of automated copyright filtering. The author develops an economic model of the competition between right holders and copyright-infringing uploaders on a platform. Furthermore, he applies insights from the economic literature on decision-making under uncertainty and incentive alignment to automated copyright filtering. The analysis disentangles complex relationships and challenges prevailing assumptions. It offers a novel perspective on the implications of automated filtering for the objectives of copyright policy, on the avoidance of erroneous filtering decisions, and on regulatory approaches to automated filtering. The author employs his findings to evaluate the current US and EU legal frameworks and proposes improvements. This book will appeal to researchers and policy makers interested in automated filtering, copyright enforcement, and platform regulation.
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