One response has come from the Open Source Initiative — which laid out the definition of open-source software more than 20 years ago. This week, it produced a near-final definition that could help to shape how the field develops.
Open-source AI is everywhere right now. The problem is, no one agrees on what it actually is. Now we may finally have an answer. The Open Source Initiative (OSI), the self-appointed arbiters of what it means to be open source, has released a new definition, which it hopes will help lawmakers develop regulations to protect consumers from AI risks.
For the past two years, the Open Source Initiative (OSI) has been working on developing a definition for Open Source AI that the industry can use to determine which models are actually considered open, and it has a new draft of the definition to share as it nears the final release in October.
The Open Source Initiative (OSI), the organization widely seen as responsible for arbitrating openness standards, published the latest version of its definition of open-source AI on Thursday. The document comes after months of consulting with various developers, academics, and other concerned parties on a roadshow of workshops around the world.
Many generative AI models claim to be open source when they really aren’t. One Cornell paper describes the confusion around AI model restrictions as “open washing.” The US government is scratching its head, weighing the risks of open LLMs. Adding to the murkiness is the many lawsuits over alleged copyright infringement by AI model owners still working their way through various courts.
AI can’t exist without open source, but the top AI vendors are unwilling to commit to open-sourcing their programs and data sets. To complicate matters further, defining open-source AI is a messy issue that has yet to be settled.
The National Telecommunications and Information Administration (NTIA) issued a report supporting open-source and open models to promote innovation in AI, while emphasizing the need for vigilant risk monitoring.
While there is not yet a consensus on the definition of what constitutes “open source AI”, the Open Source Initiative, which maintains the “Open Source Definition” and a list of approved OSS licenses, has been “driving a multi-stakeholder process to define an ‘Open Source AI’”.
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AI uses both code and data, and this combination continues to be a challenge for open source, said experts at the United Nations OSPOs for Good Conference.
The cries to “ban open source” first surfaced last autumn—partly a response to Meta and others’ “opening” large language models (LLMs). Lobbyists bandied the phrase around political rallies and across policy circles. Yet many critics could not explain what open source means in any context and were unfamiliar with the Open Source Definition (OSD). Not knowing or understanding the technical details did not appear to be a barrier to sharing a negative opinion.
As per the current draft, an Open Source AI system should grant freedoms to use the system for any purpose without seeking permission; to allow others to study how the system works and inspect its components; and to modify and share the system for any purpose.
