Guest Post – ODI Survey on AI and Web-Scale Discovery
NISO’s Open Discovery Initiative (ODI) survey reflects the positive and negative expectations of generative AI in web-scale discovery tools.
Guest Post — Who Controls Knowledge in the Age of AI? Part 2, Recommendations for Stakeholders
The MIT Press surveyed book authors on attitudes towards LLM training practices. In Part 2 of this 2 part post, we discuss recommendations for stakeholders to avoid unintended harms and preserve core scientific and academic values.
Guest Post — Who Controls Knowledge in the Age of AI? Part 1
The MIT Press surveyed book authors on attitudes towards LLM training practices. In Part 1 of this 2 part post, we discuss the results: authors are not opposed to generative AI per se, but they are strongly opposed to unregulated, extractive practices and worry about the long-term impacts of unbridled generative AI development on the scholarly and scientific enterprise.
Guest Post — Beyond Access: Untangling Copyright Confusion in Asian Open Access Journals
In Asia, open access adoption is accelerating, yet the legal and structural underpinnings of this openness remain fragile, with significant licensing and copyright confusion.
Confused and Ambivalent: Scholarly Authors and Creative Commons Licenses
An AAAS survey reveals authors’ concerns and confusion regarding open licensing of their work.
Ask The Chefs — New Court Decisions Issued in Cases Addressing AI Training and Copyright
We asked the Chefs for their thoughts on two important court decisions on the legality of using copyrighted materials for AI training.
A Tumultuous Week at the Library of Congress
Changes in Library of Congress leadership could have profound impacts on copyright and intellectual freedom.
Innovation, Governance, and Public Trust: The US Office of Management and Budget (OMB) Issues Guidance on AI
We are expecting the US Government’s AI Action Plan to be issued over the summer. In the meantime, we may glean some of the administration’s views by looking at recently issued information from the Office of Management and Budget (OMB).
We Could Use a Model Licensing Framework for Scholarly Content Use in AI Tools
Model licenses simplified library licenses in the 2000s. The same approach can streamline licensing scholarly content for AI training today.
Copyright’s Big Win in the First Decided US Artificial Intelligence Case
The first AI training case has been decided in the US in favor of the copyright holder.
AI Rights Reservation: Human Readable is Machine Readable — An Interview with Haralambos (“Babis”) Marmanis
“Rights reservation language, whether in plain English, included in terms, or coded into, e.g., metadata, is “machine readable.” It is a choice by an AI developer to not read “human readable” rights reservation language.”
AI and Content — The 2024 Trend that Wasn’t and the Related Opportunity that Exists
As a result of EU law and other factors, rights holders are reserving their AI rights. This material is available for AI training/licensing.
A Dissonance of Ideals: Openness, Copyright, and AI
Robert Harington attempts to reveal inherent conflicts in our drive to be as open as possible, authors’ need to understand their rights, and a library’s mandate to provide their patrons with the enhanced discovery that comes with AI’s large language models (LLMs).
Guest Post: Supply Chain of Writing Fools
While Aretha Franklin’s “Chain of Fools” referred to betrayal of trust in love, when it comes to AI use of our work, writers feel betrayed by those who should be protecting our intellectual and creative property.
Lessons Learned from a Fair Use Defeat
Several weeks ago, the Internet Archive lost its appeal of the lawsuit brought by a group of publishers opposed to its controlled digital lending programs. Roger Schonfeld examines what can be learned from this fair use defeat.