Open Access and AI - How to Safeguard Your Published Work in a Time of Unmitigated Co-option
Location
Online
Start Date
21-10-2025 10:00 AM
End Date
21-10-2025 10:20 AM
Description
The meteoric rise of generative artificial intelligence has exposed a precarious fault line within the open access movement: the unchecked appropriation of scholarly labor by proprietary AI systems. While open access was designed to democratize knowledge, it is now being exploited by tech corporations who ingest publicly funded research to power closed-source AI models, often without citation, attribution, or consent.
This dynamic disproportionately affects Black scholars, academics, and authors, whose work has long been under-cited, under-platformed, and devalued within traditional scholarly ecosystems. As AI models draw indiscriminately from the open web and academic repositories, the historical and ongoing unpaid intellectual labor of Black thinkers is absorbed into algorithmic systems that rarely, if ever, acknowledge their contributions, further replicating epistemic erasure in the digital age.
This presentation examines the ethical and political tensions that arise when open access is co-opted by AI, particularly as governments vacillate between funding public research and subsidizing private innovation. Drawing from global case studies and existing advocacy efforts, I explore licensing strategies, institutional safeguards, and collective actions that can help scholars, especially those whose labor has been historically exploited, retain agency over their work.
To defend research today means not only resisting government censorship, but also confronting the algorithmic commodification of public knowledge. It means demanding equity in who gets cited, who gets compensated, and who gets to remain visible in the archives of the future.
Open Access and AI - How to Safeguard Your Published Work in a Time of Unmitigated Co-option
Online
The meteoric rise of generative artificial intelligence has exposed a precarious fault line within the open access movement: the unchecked appropriation of scholarly labor by proprietary AI systems. While open access was designed to democratize knowledge, it is now being exploited by tech corporations who ingest publicly funded research to power closed-source AI models, often without citation, attribution, or consent.
This dynamic disproportionately affects Black scholars, academics, and authors, whose work has long been under-cited, under-platformed, and devalued within traditional scholarly ecosystems. As AI models draw indiscriminately from the open web and academic repositories, the historical and ongoing unpaid intellectual labor of Black thinkers is absorbed into algorithmic systems that rarely, if ever, acknowledge their contributions, further replicating epistemic erasure in the digital age.
This presentation examines the ethical and political tensions that arise when open access is co-opted by AI, particularly as governments vacillate between funding public research and subsidizing private innovation. Drawing from global case studies and existing advocacy efforts, I explore licensing strategies, institutional safeguards, and collective actions that can help scholars, especially those whose labor has been historically exploited, retain agency over their work.
To defend research today means not only resisting government censorship, but also confronting the algorithmic commodification of public knowledge. It means demanding equity in who gets cited, who gets compensated, and who gets to remain visible in the archives of the future.
