Generative AI for content discovery in academic publishing: A content provider’s perspective

Generative Artificial Intelligence (GAI) is reshaping the landscape of content discovery, access, and usage within the academic publishing ecosystem. This paper examines the complex relationships between content providers and GAI, focusing on the multifaceted roles that publishers play as consumers, developers, feeders, and influencers of GAI technologies. It explores the ethical considerations, policy developments, and principles guiding the use of GAI in academic publishing. The paper also analyzes the impact of GAI-assisted search on content discoverability, linkability, accessibility, and trackability. By auditing current GAI tools and discussing the dilemma of blocking GAI bots, the paper highlights the challenges and opportunities that GAI presents. Finally, it calls for collaborative efforts among stakeholders to promote ethical AI practices and introduces future directions, including the upcoming NISO Open Discovery Initiative survey on GAI.

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Publication Details

Journal
Information Services & Use
Published
2025-04-22
DOI
https://doi.org/10.1177/18758789251336075
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Generative AI for content discovery in academic publishing: A content provider’s perspective

Julie Zhu
Information Services & Use
Topic Modeling
article

Generative AI for content discovery in academic publishing: A content provider’s perspective

Julie Zhu
article en

Abstract

Generative Artificial Intelligence (GAI) is reshaping the landscape of content discovery, access, and usage within the academic publishing ecosystem. This paper examines the complex relationships between content providers and GAI, focusing on the multifaceted roles that publishers play as consumers, developers, feeders, and influencers of GAI technologies. It explores the ethical considerations, policy developments, and principles guiding the use of GAI in academic publishing. The paper also analyzes the impact of GAI-assisted search on content discoverability, linkability, accessibility, and trackability. By auditing current GAI tools and discussing the dilemma of blocking GAI bots, the paper highlights the challenges and opportunities that GAI presents. Finally, it calls for collaborative efforts among stakeholders to promote ethical AI practices and introduces future directions, including the upcoming NISO Open Discovery Initiative survey on GAI.

Information Services & UseVol. 45(1-2)
Institute of Electrical and Electronics Engineers (US)
Openalex Percentile: Top 96%
Topic Modeling
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