JOURNAL ARTICLE

Protection of non-original objects generated by artificial intelligence: the Ukrainian copyright law approach.

  • Published In: International Journal of Law & Information Technology, 2024, v. 32, n. 1. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Bulat, Nataliia 3 of 3

Abstract

The article analyzes the approach of the Law of Ukraine "On Copyright and Related Rights" (LU CRR) of 1 December 2022 to non-original objects generated by computer programmes, including artificial intelligence (AI). It explains that Ukrainian copyright law distinguishes between original works created by natural persons using computer technologies, which receive standard copyright protection, and non-original objects generated without direct creative participation, which are protected by sui generis rights—a special category of intellectual property rights with a shorter duration and exclusion of moral rights. The article discusses the interpretation of "without direct participation," linking it to the absence of human creative decisions expressed in the object, and emphasizes that non-original objects must differ from existing similar objects to qualify for protection. It also addresses the assignment of sui generis rights, proposing that these rights should primarily belong to legitimate users of the computer programme unless otherwise agreed, and suggests legislative improvements to clarify protection scope and rights ownership.

Additional Information

  • Source:International Journal of Law & Information Technology. 2024/03, Vol. 32, Issue 1, p1
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2024
  • ISSN:09670769
  • DOI:10.1093/ijlit/eaae010
  • Accession Number:178300030
  • Copyright Statement:Copyright of International Journal of Law & Information Technology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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