Copyright and Artificial Intelligence

Whenever content is involved, copyright comes into the discussion. And when we talk about the Artificial Intelligence, we are talking about systems that absorb petabytes of content to meet their educational needs. So, copyright issues are at the forefront of the discussion.

Copyright usually only becomes an issue when there is a perception that someone or something is successful – because copyright holders lose potential control or revenue.

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For decades, “robot reading” has been a part of our digital lives. Think of search engines crawling billions of pages to index them. These robots read far more content than any human could ever read.

But it was only when Artificial Intelligence began to learn from this content and, more importantly, produce content that seemed successful that the rules derived from the Statute of Queen Anne of 1710 came into effect.

Artificial Intelligence relies heavily on the data it consumes, but under EU law, its access should be carefully regulated. The 2019 EU Directive on Copyright in the Digital Single Market (DCDSM ) sets the framework for text and data mining (TDM). Article 3 of the Directive allows TDM only for scientific research, while Article 4 allows it more broadly — provided that the rights holder does not explicitly protect their rights.

With the Artificial Intelligence Act passed in 2024 and referring to these provisions, there are a number of questions about the future of AI models. One of the key concerns is the possibility of a data winter, a scenario where AI models face limited access to the data they need to evolve and improve.

This brings us to a fundamental concept in Artificial Intelligence, Garbage In, Garbage Out.

AI models are only as good as the data they are trained on. If access to high-quality datasets is restricted by strict copyright rules, AI systems will end up being trained on lower-quality data.

Poor quality data will lead to unreliable, biased, or completely inaccurate Artificial Intelligence results.

Restricting access due to copyright concerns risks leading AI into a “data winter” where innovation will freeze, limited by the garbage that feeds the system.

A data winter will not only stifle technological progress, but will also widen the gap between countries that impose stricter copyright policies and those that adopt more flexible rules.

Ultimately, Europe's competitiveness in Artificial Intelligence depends on whether it can provide an environment where Artificial Intelligence can access the data it needs without unnecessary restrictions.

However, access to diverse data is also important from a cultural perspective: if AI is trained primarily on Anglo-Saxon or non-European content, it naturally reflects these cultures in its results.

This could mean that European creativity will be increasingly marginalized, with content produced by Artificial Intelligence lacking cultural relevance and not reflecting Europe's diversity.

Artificial Intelligence should be a tool that enhances the diversity of human expression, not one that homogenizes it.

From the perspective of producing creative artificial intelligence.

The assumption that creative works, such as films, video games or books, are automatically protected by copyright may not apply to content generated by artificial intelligence.

Traditional protection of creative expression depends on human authorship, while creative elements, such as artificial intelligence-generated backgrounds in video games or films, could be freely copied by others.

This uncertainty could lead to increased pressure from creative industries to amend copyright law, pushing for greater levels of protection for AI-generated content that is currently not protected.

If such changes occur, we could end up with limited access to knowledge, stifling creativity and innovation.

The future path requires a careful balancing act:

We need copyright laws that protect human creativity and work without hindering access to the data that Artificial Intelligence and society need to innovate and thrive.

By avoiding a data winter and ensuring that AI systems have access to diverse, quality data, we can harness the potential of AI to advance the creative industries, rather than allowing outdated copyright regulations to slow progress.

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