New Research Report From Ithaka S+R: “A Third Transformation? Generative AI and Scholarly Publishing”

The report linked below was published today by Ithaka S+R.

It was written by:

• Tracy Bergstrom
• Dylan Ruediger

Title

A Third Transformation? Generative AI and Scholarly Publishing

Source

Ithaka S+R

DOI:10.18665/sr.321519

Introduction

In January 2024, Ithaka S+R published “The Second Digital Transformation of Scholarly Publishing” on the state of the scholarly publishing industry as it navigated “the second digital transformation” and assessed shared infrastructure needs in light of ongoing change in the structures, workflows, incentives, and outputs in the industry.^[1] That report was based on interviews conducted in the first half of 2023 and included brief references to generative AI, which was just beginning to make its presence felt in academia and society. Since then, 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.

Generative AI has already established a foothold in the industry: recent estimates suggest that perhaps one percent of the scholarly literature produced in 2023 shows signs of having been created in part with the assistance of a large language model (LLM).^[2] Major publishers and content aggregators have rapidly developed and released AI-enhanced search and discovery tools and, less visibly, are experimenting with its potential use in back-end processes. The stage seems set for exponential growth in its use across the research and publication lifecycle.

What is not yet clear is how disruptive this growth will be. To this end, we interviewed 12 leaders in stakeholder communities ranging from large publishers and technology disruptors to academic librarians and scholars. The consensus among the individuals with whom we spoke is that generative AI will enable efficiency gains across the publication process. Writing, reviewing, editing, and discovery will all become easier and faster. Both scholarly publishing and scientific discovery in turn will likely accelerate as a result of AI-enhanced research methods. From that shared premise, two distinct categories of change emerged from our interviews. In the first and most commonly described future, the efficiency gains made publishing function better but did not fundamentally alter its dynamics or purpose. In the second, much hazier scenario, generative AI created a transformative wave that could dwarf the impacts of either the first or second digital transformations.

These two scenarios are neither mutually exclusive, nor are they the only possible futures for generative AI.^[3] If generative AI proves to be genuinely transformative, it will presumably also create significant efficiency gains. As detailed below, 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. Still, the scenarios are useful heuristic aids and were repeatedly used by our interviewees to frame their remarks and as indicators of their general disposition towards the technology itself. The strategic implications of generative AI for the publishing sector looks different from an incrementalist perspective than from a disruptive one, and even more complex if these different types of implications occur together.

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(31 pages; PDF.)

Filed under: Companies (Publishers/Vendors), Interviews, News, Publishing