How ‘open’ is generative AI really? Not very
Financial TimesThe Open Source Initiative is attempting to draft a definition of open source AI. But this will not stop tech companies adding restrictions to AI models they refer to as open.
The Open Source Initiative is attempting to draft a definition of open source AI. But this will not stop tech companies adding restrictions to AI models they refer to as open.
Few inventions in history have been as important for human civilisation and as poorly understood as the internet. It developed not as a centrally planned system, but as a patchwork of devices and networks connected by makeshift interfaces. Decentralisation makes it possible to run such a complex system. But every so often comes a chilling reminder that the whole edifice is uncomfortably precarious.
On the face of it, open-source AI promises a future where anyone can take part in the technology’s development. That could accelerate innovation, boost transparency, and give users greater control over systems that could soon reshape many aspects of our lives. But what even is it? What makes an AI model open source, and what disqualifies it?
Civil society and academics are joining together to defend AI openness and transparency. Mozilla and the Center for Democracy & Technology (CDT), along with members of civil society and academia, have united to underscore the importance of openness and transparency in AI. Nearly 50 signatories sent a letter to Secretary Gina Raimondo in response to the U.S. Commerce Department’s request for comment on openness in AI models.
Leading in-memory database vendor Redis is switching to a dual-license approach, imposing far more restrictive terms. It is not the first time Redis has rewritten its terms. Back in 2018 it adjusted the license on some of its modules in ways which upset a quite a few open source luminaries.
Open source AI, where the source code is publicly available for use, modification, and distribution, encourages innovation by allowing developers to build upon existing algorithms and models. In contrast, closed-source AI restricts the source code to private use, with only the owning company having the ability to make changes.
“OSI and the Open Policy Alliance commend CISA for engaging with the open source software community and appreciate the opportunity to participate in this week’s Open Source Security Summit. Including less represented, small open source non-profits into the discussion will facilitate workable, practical policies and practices, building upon the strength of the collaborative model of Open Source,” said Deb Bryant, US Policy Director, Open Source Initiative.
In December 2023, the authors of this blog, David Edelsohn and Ofer Hermoni, had an enriching opportunity to attend a thought-provoking session at the AI.Dev event, titled “Towards the Definition of Open Source AI,” moderated by the insightful Mer Joyce and Ruth Suehle. The authors and other AI and open-source professionals joined together to create an initial proposal for the definition of Open Source AI.
The interest in data technologies goes hand in hand with the exponential growth happening right now in the artificial intelligence (AI), machine learning (ML) and deep learning (DL) space, said Stefano Maffulli, executive director of the Open Source Initiative, which worked with OpenLogic by Perforce on the report.
DOSP involves initially releasing software under a proprietary license, followed by a planned transition to an open source license.
Cloud and AI are the most important technologies today, and both have outstripped open source licenses. It’s time for a new open source definition.
