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The Influence of AI in the Media Workforce: How Companies Use an Array of Legal Remedies

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  • Díaz-Noci, Javier
  • Peña-Fernández, Simón

    (University of the Basque Country (UPV/EHU))

  • Meso-Ayerdi, Koldobika
  • Larrondo-Ureta, Ainara

Abstract

The emergence of ChatGPT and other related artificial intelligence systems has posed many questions upon the impact that such tools could have on some jobs, including media workers. Serious legal concerns have arisen regarding the learning practices of AI-related companies such as OpenAI and Google. These concerns involve crawling and extracting presumably unauthorized copyright works from news repositories, whose rightholders are often media companies. In this article, we aim to categorize the newsroom practices and routines affected by artificial intelligence. We also explore copyright-law related issues, including AI-assisted reporting, its impact on journalists and the media workforce, SEO and commercial strategies, as well as training and blocking AI engines. The legal solutions applied to solve those questions are also addressed, including technical solutions, fair use guidelines and legal solutions (litigation, legislative reform, and negotiation). Our conclusion is twofold: first, in the unequal fight against artificial intelligence systems, a utilitarian and entrepreneurial conception of intellectual property is enforced; and second, the position of journalists as authors is weakening.

Suggested Citation

  • Díaz-Noci, Javier & Peña-Fernández, Simón & Meso-Ayerdi, Koldobika & Larrondo-Ureta, Ainara, 2024. "The Influence of AI in the Media Workforce: How Companies Use an Array of Legal Remedies," SocArXiv 2xmjw_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:2xmjw_v1
    DOI: 10.31219/osf.io/2xmjw_v1
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    References listed on IDEAS

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    1. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    2. Brenden M. Lake & Marco Baroni, 2023. "Human-like systematic generalization through a meta-learning neural network," Nature, Nature, vol. 623(7985), pages 115-121, November.
    3. Xiang Hui & Oren Reshef & Luofeng Zhou, 2023. "The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market," CESifo Working Paper Series 10601, CESifo.
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