An Initial Scholarly AI Taxonomy – Adam Hyde, John Chodacki and Paul Shannon. April 11, 2023. https://doi.org/10.54900/6p6re-xyj61
“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.

The above is the first pass at a taxonomy. To flesh out these further, we have provided examples to illustrate each category further. We thoroughly recognise that some of the examples below, when further examined, may be miscategorized. Further, we recognise that some examples could be illustrations of several of these categories at play at once and don’t sit easily within just one of the items listed. We also acknowledge that the categories themselves will need thorough discussion and revision going forward. However, we hope that this initial taxonomy can play a role in helping the community understand what AI could mean for publishing processes…”