"Are We Undervaluing Open Access by Not Correctly Factoring in the Potentially Huge Impacts of Machine Learning? — An Academic Librarian’s View (I)"

Synopsis: I have recently adjusted my view to the position that the benefits of Machine learning techniques are more likely to be real and large. This is based on the recent incredible results of LLM (Large Language models) and about a year’s experimenting with some of the newly emerging tools based on such technologies.

If I am right about this, are we academic librarians systematically undervaluing Open Access by not taking this into account sufficiently when negotiating with publishers? Given that we control the purse strings, we are one of the most impactful parties (next to publishers and researchers) that will help decide how fast if at all the transition to an Open Access World occurs.


| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

Avatar photo

Author: Charles W. Bailey, Jr.

Charles W. Bailey, Jr.