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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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AI-GENERATED CONTENT AND COPYRIGHT LAW: A COMPARATIVE ANALYSIS OF THE U.S.A. AND UZBEKISTAN

Authors: Abdusattorov Shokhjakhon Jurabek ugli;

AI-GENERATED CONTENT AND COPYRIGHT LAW: A COMPARATIVE ANALYSIS OF THE U.S.A. AND UZBEKISTAN

Abstract

This article examines the evolving challenges that artificial intelligence (AI) poses to traditional copyright frameworks, focusing specifically on AI-generated content. It begins by defining AI-generated works and exploring why these outputs disrupt long-standing legal principles, such as human authorship, originality, and creative expression. The article then conducts a comparative legal analysis between the United States and Uzbekistan—two jurisdictions with markedly different levels of technological development and legal infrastructure. In the U.S., copyright protection is explicitly reserved for human creators, as reinforced by recent case law and the U.S. Copyright Office’s guidance. Conversely, Uzbekistan's legal framework does not yet address AI-generated content, offering both challenges due to legal uncertainty and opportunities for progressive reform. The article highlights the lack of legal precedent in Uzbekistan and underscores the importance of establishing a coherent IP policy that balances innovation and legal protection. Through this comparative approach, the article aims to inform policymakers, scholars, and practitioners on how different jurisdictions can adapt or reform copyright law in response to AI advancements. It concludes by advocating for flexible, forward-looking legal strategies that accommodate technological change while upholding the fundamental principles of intellectual property.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green