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Copyright and AI, Part 1: How Does Copyright Apply to AI-Generated Works?

By Rafael, on 21 June 2024

Guest post by Christine Daoutis, UCL Copyright Support Officer. 

This the third blog post of the collaborative series between the UCL Office for Open Science and Scholarship and the UCL Copyright team. Here, we continue our exploration of important aspects of copyright and its implications for open research and scholarship.

An artist’s illustration of artificial intelligence (AI). This illustration depicts language models which generate text. It shows distorted text on a screen seen through a glass container. The visible text at the top reads, "How do large language models work?" The rest is partially obscured, but includes mentions of "neural networks" and "machine learning.

Photo by Google DeepMind.

In a previous post we introduced questions that arise when using and creating materials protected by copyright. What options are available to you if you want to reuse others’ work (e.g. articles, theses, images, film, code) in your research? And what do you need to consider before you share your own research with others? Issues around copyright protection, permissions, exceptions, licences, and ownership need to be examined when creating new works and including others’ materials. These questions are also relevant when we think about works that are created with the use of GenAI tools, such as ChatGPT. However, with the use of these technologies still being relatively new and the legal aspects being shaped as we speak, answers are not always straightforward.

GenAI Training Data: GenAI models are trained on a large number of materials, usually protected by copyright (unless copyright has expired or been waived). Does this mean AI companies are infringing copyright by using these materials? How would copyright exceptions and fair dealing/fair use apply in different countries? How would licence terms – including the terms of open licences – be respected? Answers will come both from legislation and codes of practice introduced by governments and regulatory bodies (such as the EU AI Act) and from the outcomes of court cases (see, for example, Getty Images vs Stability AI, the Authors’ Guild against OpenAI and Microsoft.

User Prompts: The prompts a user provides to the model (instructions, text, images) may also be protected. You should also consider whether the prompts you enter include any confidential/commercially sensitive information that should not be shared. Please see UCL’s IP policy for guidance on this.

A digital illustration depicts a serene-looking young woman with glowing skin and braids that resemble threads. Text overlay reads "Zarya of the Dawn," The background has shades of green, black and blue forming an ethereal environment.

Image Credit: Kris Kashtanova using Midjourney AI, Public domain, via Wikimedia Commons.

AI-Generated Work: Is the AI-generated work an original work protected by copyright? Is it a derivative of other original works, and therefore, possibly infringing? If it is protected, who owns the copyright? The answer to this will vary by case and jurisdiction. In the US, a court ruled that AI-generated images in a comic book were not protected, although the whole comic book and story were. In China, it was ruled that images generated with the use of GenAI tools would be protected, with the owner being the person who provided the prompts. The UK’s CDPA (9.3) states that ‘in the case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken’.

In short, GenAI raises questions about what constitutes an original work, what constitutes infringement, how copyright exceptions and fair dealing/fair use are applied, and how authorship is established. While these questions are still being shaped, here are three things you can do:

  1. Consider any limitations in using GenAI besides copyright (e.g., confidentiality, biases, publishers’ policies). See UCL’s Generative AI hub for guidance.
  2. Be transparent about how you use GenAI. See UCL Library guidance on acknowledging the use of AI and referencing AI.
  3. If you have any copyright-related questions on the use of GenAI, contact the copyright support service.

 While GenAI has opened up more questions than answers around copyright, it also offers an opportunity to think about copyright critically. Stay connected with us for Part 2 of this blog post, which will discuss how new technologies, including GenAI, are changing our understanding of copyright. We look forward to continuing this important conversation with you.

Get involved!

alt=""The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on X, formerly Twitter, LinkedIn, and join our mailing list to be part of the conversation!

 

 

How understanding copyright can help you as a researcher

By Rafael, on 4 April 2024

Guest post by Christine Daoutis, Copyright Support Officer

Welcome to the inaugural blog post of a collaborative series between the UCL Office for Open Science and Scholarship and the UCL Copyright team. In this series, we will explore important aspects of copyright and its implications for open research and scholarship.

Research ideas, projects, and their outcomes often involve using and producing materials that may be protected by copyright. Copyright protects a range of creative works, whether we are talking about a couple of notes in a notebook, a draft thesis chapter, the rough write-up of a data, a full monograph and the content of this very blog. While a basic knowledge of copyright is essential, particularly to stay within the law, there is much more to copyright than compliance. Understanding certain aspects of copyright can help you use copyright materials with more confidence, make use of your own rights and overall, enhance the openness of your research.

Two stick figures are facing each other. A large red copyright symbol is behind the first one. The first person is holding a document and says: ‘Ah, copyright! I have the right to copy!’. The second person is rubbing their chin and saying: ‘Err…’.

Image attribution: Patrick Hochstenbach, 2014. Available under https://creativecommons.org/licenses/by/4.0/

This first post in our series is dedicated to exploring common questions that arise during research projects. In future posts, we will explore some of these questions further, providing guidance, linking to new resources, and signposting relevant workshops. Copyright-related enquiries often arise in the following areas:

Reusing other people’s materials: How do you GET permission to reuse someone else’s images, figures, software, questionnaires, or research data? Do you always need permission? Is use for ‘non-commercial, research’ purposes always permitted, or are there other factors to consider? How do licenses work, and what can you do when a license does not cover your use? It’s easy to be overconfident when using others’ materials, for example, by assuming that images found on the internet can be reused without permission. It’s equally easy to be too cautious, ending up not making use of valuable resources for fear of infringing someone’s rights. Understanding permissions, licenses, and copyright exceptions – what may be within your rights to do as a user – can help you.

Disseminating your research throughout the research cycle: There are open access options for your publications and theses, supporting access to and often, reuse of your work. How do you license your work for reuse? What do the different licenses mean, and which one is most suitable? What about materials produced early on in your research: study preregistrations, research data, preprints? How can you make data FAIR through licensing? What do you need to consider when making software and other materials open source?

Is your work protected in the first place? Documents, images, video and other materials are usually protected by copyright. Facts are not. For a work to be protected it needs to be ‘original’. What does ‘original’ mean in this context? Are data protected by copyright? What other rights may apply to a work?

Who owns your research? We are raising questions about licensing and disseminating your research, but is it yours to license? What does the law say, and what is the default position for staff and students at UCL? How do contracts, including publisher copyright transfer agreements and data sharing agreements, affect how you can share your research?

‘Text and data mining’. Many research projects involve computational analysis of large amounts of data. This involves copying and processing materials protected by copyright, and often publishing the outcomes of this analysis. In which cases is this lawful? How do licences permit you to do, exactly, and what can you do under exceptions to copyright? How are your text and data mining activities limited if you are collaborating with others, across institutions and countries?

The use of AI. Speaking of accessing large amounts of data, what is the current situation on intellectual property and generative AI? What do you need to know about legal implications where use of AI is involved?

These questions are not here to overwhelm you but to highlight areas where we can offer you support, training, and opportunities for discussion. To know more:

Get involved!

alt=""The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on X, formerly Twitter, LinkedIn, and join our mailing list to be part of the conversation!