Automated Copyright Filters
Description
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.
More details
Other editions
Additional editions
Person
Oliver Englisch is a law clerk at the Hanseatic Higher Regional Court, Germany, and a lecturer at the Hamburg University of Technology, Germany. He studied law with a focus on the economic analysis of law at the University of Kassel, Germany, the University of Amsterdam, the Netherlands, and the University of Hamburg. He was a member of the DFG Graduate School "The Economics of the Internationalisation of the Law" at the University of Hamburg and a visiting researcher at the University of Oxford, UK. His research interests include the economic analysis of platform regulation, intellectual property law, and competition law.
Content
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.