What Does Generative AI Mean for Scholarly Publishing?
Over the past 24 months, generative AI has become inescapable. As a tool that is capable of generating content, its implications for how scholarly research is conducted and for scholarly publishing and communication are potentially transformative. What is not yet clear is how transformative this impact will be, and which areas of scholarly communication may see more rapid and revolutionary change than others.
In a report published today, with funding from STM Solutions and six of its member organizations, we explore how key stakeholders—publishers, technology disruptors, librarians, and scholars—think generative AI will change their practices and processes. The consensus among the individuals with whom we spoke is that generative AI will enable efficiency gains across the publication process. As the report considers, certain aspects of scholarly publishing seem more likely than others to see significant change, leaving open the possibility that generative AI creates incremental change in some areas while disrupting others.
A Third Transformation? Generative AI and Scholarly Publishing is designed as a companion or addendum to the larger Second Digital Transformation of Scholarly Publishing report published in January 2024. To facilitate reading the two reports together, we decided to closely follow the original report’s internal structure. As such, today’s report addresses many of the same themes to provide analysis of the present landscape and recommendations to address key needs:
- Consolidation and competition within the scholarly publishing ecosystem
- Research integrity and establishing a trusted global public good
- Making meaning from the scholarly record
- Supporting new business models
Most of the people interviewed for this report see a future in which generative AI becomes embedded in workflows across the publication lifecycle, making positive contributions to existing goals, processes, and infrastructures for scholarly publishing. However, the path to this future depends on stakeholders taking action now to ensure that definitions around what constitutes ethical usage of generative AI is understood consistently across authors, readers, rights holders, publishers, and aggregators. Their strategic optimism about generative AI is predicated on finding ways to ensure trust and trustworthiness in scholarship. That will require cross-sector collaboration.
As we continue to work in this space, we look forward to working with publishers, universities, funders, libraries, and technology providers to understand the implications of generative AI on their strategy.