New Article: “An Initial Scholarly AI Taxonomy”

The article linked to below was published today by Upstream, a Force11 publication.

It was written by Adam Hyde (Coko Foundation), John Chodhacki (University of California Curation Center (UC3) at California Digital Library), and Paul Shannon.

DOI: 10.54900/6p6re-xyj61

From the Article:

Although advances in artificial intelligence (AI) have been unfolding for over decades, the progress in the last six months has come faster than anyone expected. The public release of ChatGPT in November 2022, in particular, has opened up new possibilities and heightened awareness of AI’s potential role in various aspects of our work and life.

It follows that in the context of the publishing industry, AI also holds the promise of transforming multiple facets of the publishing process². In this blog post, we begin the development of a rough taxonomy for understanding how and where AI can and/or should play a role in a publisher’s workflow.

We intend to iterate on this taxonomy (for now, we will use the working title ‘Scholarly AI Taxonomy’).

Scholarly AI Taxonomy

To kickstart discussions on AI’s potential impact on publishing workflows, we present our initial categorization of the “Scholarly AI Taxonomy.” This taxonomy outlines seven key roles that AI could potentially play in a scholarly publishing workflow:

1. Extract: Identify and isolate specific entities or data points within the content.
2. Validate: Verify the accuracy and reliability of the information.
3. Generate: Produce new content or ideas, such as text or images.
4. Analyse: Examine patterns, relationships, or trends within the information.
5. Reformat: Modify and adjust information to fit specific formats or presentation styles.
6. Discover: Search for and locate relevant information or connections.
7. Translate: Convert information from one language or form to another.

Direct to Full Text Article (2041 words)

Filed under: Data Files, Digital Collections, Interactive Tools, Libraries, News, Publishing