Automated Copyright Filters: A Law and Economics Analysis » książka
Automated Copyright Filters: A Law and Economics Analysis
ISBN-13: 9783031831607 / Angielski / Twarda / 2025 / 232 str.
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.
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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