Regulation & Copyrights: Do They Work for AI & Open Source?

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  Heavybit
  Heavybit

Emerging Questions in Global Regulation for AI and Open Source

The 46th President of the United States issued an executive order to prescribe “safe, secure, and trustworthy development and use of Artificial Intelligence.” About a year later, within days of taking office, the 47th President rescinded it. There remain disparate views across technology, regulation, and business on the future of AI, all the way up the chain to federal governments and prime ministers.

At the 2025 Paris AI Summit, leaders from the US and UK declined to sign the diplomatic declaration on “inclusive AI.” US representatives claimed the agreement was too restrictive. UK representatives claimed it was not restrictive enough. As nation-states increasingly regard AI development as a precious resource and a competitive advantage on the world stage, it’s unclear whether regulation can keep up with the pace of innovation. OpenUK CEO Amanda Brock explains how:

• World Leaders Don’t See Eye-to-Eye on AI Regulation: Western governments can’t agree on how much AI should be regulated, but do want to see accelerated competition against international competitors like China
• AI Governance May Come Through Tooling and Foundations: There are relatively new public and private initiatives to govern AI through tooling and foundations devoted to public good
• Regulation Always Seems to Lag Innovation: While different nations are at different levels of sophistication in thinking through concepts like data and open source, regulation itself may struggle to keep pace with fast-moving innovation in AI
• The Concept of IP Will Struggle to Stay Relevant: Intellectual property is seeming like an increasingly antiquated way to deal with technology that innovates at such a pace and is built on gobbling up copyrighted materials
• “Winning” Will Look Different When Innovation Outpaces Copyright: In the new world, the best way forward may be finding a way to compensate creators beyond the restrictions of a copyright

World Leaders Don’t See Eye-to-Eye on AI Regulation

“In Paris, the messaging around regulation, particularly from the US and China was that the bureaucracy that comes with the EU’s AI Act must stop,” says Brock. “There was a very definite sense across the summit of a vibrancy, a pro-innovation approach.”

“I think that the US Vice President was very clear that [the US doesn’t] want to see prescriptive regulation across the world, and I think that was very directed at the EU. The EU were focused on a code to explain how to comply with their cumbersome regulation and their conversation felt very old school and like they were watching from the sidelines.”

She suggests that the AI regulation should be more nuanced. “I think there is a sense that there'll be regulation to the extent, and only to the extent, it's needed. But the Vice President talked about their being a ‘new sheriff in town,’ who clearly does things very differently.”

Brock continues, “I personally happen to agree on the particular point that bureaucracy and regulation don't work here,” suggesting AI is a potential source of great innovation, of the sort that probably shouldn’t be stifled. “Whilst there may be a need for regulation in specific use case of AI and in particular across already-regulated sectors like mobile, healthcare, or finance, AI regulation in most countries on a more broad-brush basis will only exist in spaces where it’s absolutely necessary.”

More Resources on AI and Open Source Regulation:

• Article: The Power User's Guide to Open-Source Licenses
• Article: Understanding Business Models and Defensibility in Open Source
• Article: Emerging Legal Challenges for Open Source in the Age of AI

AI Governance May Come Through Tooling and Foundations

“A really interesting development is the launch of ROOST, a set of open-source tooling, which is all about automating governance in AI. The approach speaks directly to developers by creating governance through tooling, or ‘tools not rules,’ as they put it.”

“The initiative was launched by former Google CEO, Eric Schmidt, and META Chief Scientist of AI Yann LeCun, and includes a number of tools that have been donated by big techs at its launch.

Schmidt specifically clarified they were not talking about open weight models, but rather, open-source software when talking about ROOST tools. In the light of accusations about open washing in AI, they did this to be sure that there was no confusion around what they meant by the term open source in the context of ROOST.

Schmidt’s clarification was notable as it also aligned to a theme across the summit, the first global summit to really focus on open source, and this was that the term ‘open-source AI’ was really not used at all at the summit.

Open weights were discussed frequently, beginning to clarify what had previously and wrongly been referred to as “open-source AI” and making clear exactly what the component being mentioned was. “It’s quite possible we’ll see regulatory language evolve in the months to come to focus on open-weight AI rather than open source.”

“Interestingly, according to research from Tortoise and the Tortoise Index, France is number one in Europe in open-source AI. Research that OpenUK has conducted shows that France is by far growing fastest in open-source software in Europe while the UK remains Europe’s largest open-source contributor and number one in open source by far.”

“At some point, unless we have a shift in our policies in the UK, they'll catch up with us.” Brock suggests a definite shift in France, with significant support from President Macron leading to a number of pro-open-source policies alongside the setup of a foundation called Current AI, focused on public good AI, led by Martin Tisné.

Brock suggests that Current AI is about “building a public good, rather than open source. It has $500M in public/private funding at launch to focus on working out the data conundrum and the inputs and outputs that create AI. So there is a really interesting piece there where the French have absolutely grabbed what needs done with both hands. They're looking to get to $5 billion in five years. That's a huge foundation.”

Regulation Always Seems to Lag Innovation

Brock offers that data governance remains a core challenge in AI, particularly as some nations don’t have as well-developed an understanding of data and openness as the UK. “Forgive me for being blunt, but the UK has a much more sophisticated understanding of data and what ‘open data’ means than the US.” Suggesting that the differential between thinking about and regulating different data types may contribute to the confusion, she agrees with Tisné that a focus on data is essential to resolving the challenge.

“It's not an easy thing to fix. You've got a landscape or different forms of information in the input data used by AI: Numbers, words, music, imagery, and so on. All going in and out of the AI, each with different rights attached. And it depends on whether you’re looking at rights based on contracts, or at individuals' personal and privacy rights, or regulatory rights how these apply.”

“You might be looking at confidentiality and contracts, data privacy in a regulatory regime, or healthcare information that's never going to be public. Some of this information isn’t in the legal category of data.”

“You have to understand what kinds of information you are talking about and you have to understand the legal rights. When we talk about data in the context of AI, it is nothing like software, and the term ‘source’ as in open source, becomes a complete misnomer and confusing.”

“We shouldn't be talking about ‘open-source data,’ but open data, because there is no source in it.” Brock notes that intellectual property regimes around data are also different. “And when we look at information or content used to train AI it’s broader than both software and data in their legal meanings, differentiating ‘open data’ from ‘open-source software’ is a big conceptual shift that doesn’t fit with existing software licensing structures used by Wikipedia or Creative Commons.”

“We really need to look at this landscape of rights, apply it to the use cases and then understand what the data or information challenges are. I think that there's been a disconnect because the leadership in the area of open data is European, not American, and we've not managed to pull that group together with the AI context. I suspect that that is the next step: to sketch out that basic landscape and start to build understanding for people.”

We really need to look at this landscape of rights, apply it to the use cases and then understand what the data challenges are.” -Amanda Brock, CEO/OpenUK

The Concept of IP Will Struggle to Stay Relevant

Brock offers that a holistic, top-down approach to classifying an endless sea of data may be needed. “Thinking about the data used at scale, ‘inputs and outputs’ is probably the term we have to shift towards, which includes not only what we would traditionally define as ‘data.’ This is bigger.”

“It is going to be a bit alien to software engineers, because it has a different set of legal rights. Personally, I think our intellectual property regime is no longer fit for purpose. I think it's been heading that way for a long time and that the AI boost of the last couple of years has provided the final nail in its coffin.”

“In the case of the software industry, I’ve always believed that open source is actually a correction of the application of copyright to software. We had collaboration in software from the get-go, but then lawyers applied copyright to software, meaning licensing was required to be able to use another’s code.”

“This led to people building deep war chests of copyright, silos in usage, and of course meant copyrighted code became extremely valuable. Without that you wouldn't have a few big companies owning our digital infrastructure. Without this application of copyright we would all have been collaborating on software development.”

“Arguably this is the way it should’ve evolved. Had that happened, there would be no need for open source, but effectively, open source at its heart corrects that application of copyright and returns us to the pre-copyright days of collaborative creation of software and de facto standards.”

“I view the actions of the open-source movement as a correction of intellectual property’s mistakes.” Brock suggests that the current point in time, with friction regarding the use of publicly available copyrighted works for text and data mining, sees content publishers and intellectual property holders trying to apply old-world sensibilities that aren’t keeping up with modern innovation.

“Winning” Will Look Different When Innovation Outpaces Copyright

When it comes to training AI and text- and data mining, “What we're seeing from the European Commission is this concept of building a license to use with an opt-out and having a registry of people who've opted out that you have to check against. Despite any new tools, that is just not going to be workable in the long term.”

“It can never be more than a stopgap and even the EU admits this. You might try to go down that route because you don't know what to do but ultimately it’s avoidant. It’s no more than a sticking plaster that will ultimately fail. The real issues will have to be dealt with.”

“I think in the same way for software, we have to use licenses because we have places outside of the US that don't have public domain as a concept. So you need to have a license to use copyrighted code. You need to have a license because copyright applies. If we say that that was a mistake of history and you took copyright away, there would be no need for that license.”

“I think we will shift gradually towards that because the concept of building the infrastructure, even with smart tooling, that can manage that licensing regime is just unthinkable. It’s just never going to work and it's also going to be a massive inhibitor to innovation particularly when other countries that are more successful in AI are taking a different approach such as how the US approaches fair use.”

“When it comes to managing content usage as an AI input, I believe that the winner will be whichever regime works out a way to reward the creators of content that doesn't involve licensing and royalties but enables their future to be one where content creators survive by having different business and funding models that are not IP dependent for their content provision to continue.”