Will copyright law enable or inhibit generative AI?

As artificial intelligence (AI) moves beyond performing simple tasks to creating original content, it blurs the lines between humans and machines. In doing so, it challenges a core tenet of many traditional intellectual property (IP) frameworks: only works created by humans are protected by copyright laws.

The development and training of AI models also raise another important copyright issue: whether the use of third-party content in that exercise might infringe on the copyright of that content.

Emerging use cases around generative AI are disrupting traditional views of creativity, authorship and ownership and pushing the boundaries of copyright law. As the world catches up with innovation, the resulting legal ambiguity impacts all sides of the AI equation – developers, content creators and copyright owners.

To create content, generative AI learns from processing vast amounts of information. This training process can involve using copyright-protected content, raising a critical question: does training generative AI models constitute copyright infringement, exposing developers to related claims?

If so, is new legislation needed to address this issue in a manner that does not unreasonably impede innovation but still respects the rights of creators?

These questions have led some jurisdictions to consider amendments to existing text and data mining exemptions and/or fair use/fair dealing exceptions to cover the training of generative AI. Such exemptions permit certain activities that would otherwise constitute copyright infringement.

Other jurisdictions are still awaiting guidance, creating a drastically uneven regulatory landscape that will continue for some time. But, no matter where they stand, legislators need to consider this issue to incentivise innovation while protecting content creators' rights.

Looking past the legal uncertainty at traditional means of creativity, humans constantly learn as we receive and process information. Typically, things we create are inextricably linked to what we have learned from others and our experiences. One could argue that AI is no different in that it learns from the underlying datasets to produce something new.

Copyright law is a key means by which innovation and creation are rewarded – and thus enabled – raising the stakes for courts and intellectual property authorities to define copyright ownership in the context of generative AI.

Depending on where you are in the world, the definition of copyright varies, a significant legal consideration in its own right. But virtually everywhere, copyright requires meaningful human contribution.

Generative AI, which often involves little human input, shatters the mould of this traditional framework. It calls into question whether AI-generated content can be protected by copyright in the first place and, if so, then who owns this copyright?

Is it the developer of the AI model who arguably enabled the 'creative' process? Is it the owner of the AI model? Or is the person who considered and input the prompts that allowed the AI tool to generate the content? Of course, this depends on whether there was sufficient human contribution to justify copyright protection in the first place.

Currently, most generative AI tools provide that users own the content they generate in their terms of use. However, if the content is not copyright-protected in the first place, then the terms of use can't change that position. There is less clarity around who is responsible if AI-generated content infringes someone else's copyright in a protected work.

To answer these questions requires courts and intellectual property authorities to challenge the scope of traditional copyright law in relation to generative AI, which could lead to changes to existing legislation covering ownership of computer-generated content.

Eventually, it is possible that copyright law will need to be further reimagined and redefined to account for the possibility of recognizing a machine as its own entity with independent authority and the ability to own and protect content, though this does not appear to be on the horizon in the short term. In this more progressive scenario, it is unclear where liability would rest for negative consequences (including copyright infringement) caused by generative AI outputs.

Technology moves quickly, while the winds of legal change blow slowly. Eventually, the world will see laws introduced and pressure-tested in the courts to address copyright issues relating to generative AI, as well as the myriad other issues that surround AI-related developments.

Legal uncertainty associated with new technologies always creates risk, requiring new approaches to emerging issues that strike a balance between existing rights and innovation.

By way of a somewhat recent example, the internet also broke the norms and bounds of copyright law, requiring new legislation and judicial guidance on issues such as the protection of online content, legal responsibility for uploading and downloading content, ownership of user-generated content and the liability of online intermediaries like hosts and ISPs.

With AI too, the world will soon see legal developments that look to consider the interests of all stakeholders, including AI developers, owners and users and those who own copyright in the content needed to train these tools. These developments will also ideally provide clarity on who might own the intellectual property rights in AI-generated content.

But, while regulation catches up to innovation, only for innovation to inevitably race ahead again, those developing and using AI should be vigilant in managing their activities to safeguard against intellectual property-related risks.

These steps should include having insight and transparency into AI-related activities, objectively assessing the risks associated with AI-related activities, keeping abreast of legal and regulatory developments and ensuring that internal policies and training are aligned with emerging laws and guidance.