Mind the Ownership Gap? Copyright in AI-generated Language Data

Authors

  • Pawel Kamocki IDS Mannheim, Germany
  • Toby Bond Bird & Bird, London, UK
  • Krister Lindén University of Helsinki, Finland
  • Thomas Margoni KU Leuven, Belgium
  • Aleksei Kelli University of Tartu, Estonia
  • Andrius Puksas Vytautas Magnus University, Lithuania

DOI:

https://doi.org/10.3384/ecp210008

Abstract

For language scientists, a prima facie advantage of AI-generated data over human-created content is that AI outputs are generally regarded as free from copyright. This contribution addresses this issue in some detail.

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Published

2024-07-09

Issue

Selected papers from the CLARIN Annual Conference 2023

Section

Contents

License

Copyright (c) 2024 Pawel Kamocki, Toby Bond, Krister Lindén, Thomas Margoni, Aleksei Kelli, Andrius Puksas

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.