Remember #ccsignals - creative commons first approach for an answer to AI? It was met with a lot of backlash.
Here is a blogpost by #CreativeCommons which sounds very different:
https://creativecommons.org/2026/04/23/update-on-cc-signals-what-changed-and-why/
Integrating Choices in Open Standards: CC Signals and the RSL Standard
https://creativecommons.org/2025/12/10/integrating-choices-in-open-standards/
How could #datastewards deal #AIbots? #CCSignals might show a way towards a new social contract in the era of #AI.
Get a brief intro and share your thoughts in our #coffeelecture on 2 Dec, 13:30 - 14:00, online via Zoom:
https://www.lib4ri.ch/coffee-lecture-series
New preprint on arXiv: “Who Owns the Knowledge? Copyright, GenAI, and the Future of Academic Publishing”. I discuss CC Signals, recent court cases, and argue that training GenAI on scholarly outputs should not be treated as a fair use exception.
https://doi.org/10.48550/arXiv.2511.21755
#GenerativeAI #Copyright #AcademicPublishing #OpenScience #ScholComm #AIpolicy #LLM #FairUse #CreativeCommons #CCSignals
The integration of generative artificial intelligence (GenAI) and large language models (LLMs) into scientific research and higher education presents a paradigm shift, offering revolutionizing opportunities while simultaneously raising profound ethical, legal, and regulatory questions. This study examines the complex intersection of AI and science, with a specific focus on the challenges posed to copyright law and the principles of open science. The author argues that current regulatory frameworks in key jurisdictions like the United States, China, the European Union, and the United Kingdom, while aiming to foster innovation, contain significant gaps, particularly concerning the use of copyrighted works and open science outputs for AI training. Widely adopted licensing mechanisms, such as Creative Commons, fail to adequately address the nuances of AI training, and the pervasive lack of attribution within AI systems fundamentally challenges established notions of originality. While current doctrine treats AI training as potentially fair use, this paper argues such mechanisms are inadequate and that copyright holders should retain explicit opt-out rights regardless of fair use doctrine. Instead, the author advocates for upholding authors' rights to refuse the use of their works for AI training and proposes that universities assume a leading role in shaping responsible AI governance. The conclusion is that a harmonized international legislative effort is urgently needed to ensure transparency, protect intellectual property, and prevent the emergence of an oligopolistic market structure that could prioritize commercial profit over scientific integrity and equitable knowledge production. This is a substantially expanded and revised version of a work originally presented at the 20th International Conference on Scientometrics & Informetrics (Kochetkov, 2025).
“CC signals are designed to sustain the commons in the age of AI,” said Anna Tumadóttir, CEO, Creative Commons. “Just as the CC licenses helped build the open web, we believe CC signals will help shape an open AI ecosystem grounded in reciprocity.”
CC Signals © 2025 by Creative Commons is licensed under CC BY 4.0 Creative Commons (CC) today announces the public kickoff of the CC signals project, a new preference signals framework designed to increase reciprocity and sustain a creative commons in the age of AI. The development of CC signals represents a major step forward…
I had the opportunity to join the Human Intelligence Institute podcast hosted by Ned Hayes and Kira Cleveland. Hear me wax on and off about open content in a world with #AI — or what I like to call ✨sparkling intelligence✨ https://www.humanintelligence.news/p/human-intelligence-nate-angell
We also talked about efforts to mark content for authorship, provenance, and use like @creativecommons #CCSignals, the developing ISO standard International Standard Content Code #ISCC, and the Coalition for Content Provenance and Authenticity #C2PA.
Human Content provenance, Creative Commons, ISCC, CP2A and more
@lfa it sounds like people can express they DON'T want their works to be used in Al training via #AIPreferences , and that #CCSignal is for people that do want their work to be used in specific ways.
A great many people already post their work to the public domain, or creative commons: #AllRightsReversed , #CopyLeft or via similar licenses.
If #AiPreferences already supports the #NoAI preference then it makes sense to me to offer content creators #CcSignals for more fine tune control.
Johnny Than
Thomas Gerdes
Lib4RI
Dmitry Kochetkov
iRights.info
Karen Keiller 🥌 📚
Nate Angell
MathiasTCK
Jeroen Bosman