The information contained in this guide is intended to help staff and students understand how to stay copyright-compliant in the course of their work and studies at the University of Liverpool.
Please be aware that any third-party materials used by staff and students in teaching and learning and their associated systems and communication channels such as Canvas, must adhere to copyright law. The University holds the Copyright Licensing Agency's HE Licence. The CLA makes it easy for us to use other's work in our own teaching, private research and study. It has a mandate from publishers, authors and visual artists to offer collective licences on their behalf. The CLA HE Licence is intended to broaden and enrich the student learning experience, by allowing HEIs to provide wider access to copyright materials than would otherwise be possible. In parallel, it enables publishers, authors and visual artists to be remunerated for the use of their work.
Find out more in the CLA User Guidelines (PDF).
It is important to note that it is not intended that these (or any linked pages) should provide definitive legal opinion on copyright.
If you are unable to find the information you are looking for, please feel free to contact your Liaison Librarian or the Licensing Manager licenses@liverpool.ac.uk with your particular query.
For assistance with the recording and reporting procedure and initial queries about the Licence, please contact the appropriate Liaison Librarian.
For further enquiries about copyright and licensing, please contact the Licensing Manager.
If any person becomes aware that any defamatory, inaccurate or copyright infringing material is included within Canvas or any other reason why it would be expedient for the University to remove materials whilst an investigation is undertaken by the Head of Department, they must contact the University Computing Services Department immediately.
Generative AI is evolving rapidly and, as debate continues around its role within teaching, learning and assessment and research, the issue of ownership and of the laws of copyright in particular raise important concerns. Challenging questions arise which don’t have totally clear answers at the moment.
Court cases that are currently underway will, in time, resolve many of these questions and if we in education want to engage with the transformative changes that Generative AI brings, we may have to live with a bit of risk and uncertainty until then and take steps to mitigate that risk.
Understanding the legal aspects of how copyright operates in the context of Generative AI is central to supporting staff and students to become more Generative AI literate and to mitigate the risks.
Staff and students need to be aware of the intellectual property concerns that might arise when using Generative AI tools. These are outlined by the National Centre for AI: ‘An introduction to copyright law and practice in education, and the concerns arising in the context of GenerativeAI’
The following advice is based upon the above guidelines.
UK law states that unless a work is licensed, out of copyright, or used under a specific exception, making copies of it will be infringement.
A key question that arises is whether Generative AI is in fact copying the input that it uses to train its models. This, in turn, leads to further questions:
Cases that are currently being litigated in the US and the UK will, eventually, clarify whether copying is taking place.
This will obviously help those in education who are navigating the Generative AI revolution. An understanding of the technology, as well as the risks of copyright infringement, can in the meantime provide a pathway forward for those involved in teaching, learning and research.
Generative AI creates text, images, music, speech, code or video/materials based on learning from existing available content that is likely to be owned by someone and copyright protected. Where the Generative AI tool is able to provide the necessary assurance about the provenance of its output, then the risk of infringement of others’ rights can be greatly reduced. This both enables the lecturer to credit the appropriate source and will ensure that the learning materials produced can more confidently be used as an asset by the university going forward.
Without that certainty, the risk of infringement of the rights of others can undermine the entire process as well as diminish the value of learning materials as assets of the institution.
Currently educators who want to use Generative AI for teaching, learning and research are required to deal directly with the tool providers and agree to whatever terms and conditions are in the individual contracts.
Part of the solution to the question of copyright infringement involves AI vendors reassuring their users by promising legal support in the face of future legal threats. These indemnity clauses act like an insurance policy, designed to reassure users that it’s safe to use the technology for commercial (and presumably education) purposes.
However, it is clear that there are limits on the indemnification being offered.
There is an argument that educational use of Generative AI requires different terms and conditions. There is a call for agreements to provide assurances on the provenance of training data used. This transparency would then enable academics to uphold an acknowledgement-based approach. Such education agreements would also need to clarify how outputs created from content that academic staff submit to Generative AI tools can be acknowledged and protected.
Without Generative AI special educational agreements, innovation in teaching and learning may be constrained. Meanwhile, institutions need to continue to support academics, students and researchers to understand what they can and can’t do with third party licensed materials when using Generative AI tools.
Good practice then is to review the terms and conditions of the contract that is being entered into with the Generative AI tool provider to see if there is an indemnification clause in the contract and to understand what that covers.
In the world before Generative AI became widespread, academic practice largely dealt with the ownership rights of others by:
As part of what we can call Generative AI literacy those using licences need to understand what they are permitted to do as licensees and adhere to those terms and conditions.
Details of the licences the university holds can be found at [INSERT LINK TO THE LICENCES].
Clarifying for those in education whether these licensed materials can be used with Generative AI tools would be beneficial.
It remains to be seen how any alleged breaches can be enforced should a publisher contend that Generative AI tools are being used to circumvent or expand the licensed use in ways that were not anticipated when such licences were agreed.
In education using the existing exceptions to copyright law is also put forward as part of the solution. One exception that is pivotal to Generative AI is s.29A of the Copyright, Designs and Patents Act (CDPA) – Text and Data Mining (TDM). This allows researchers to make copies of any copyright material for the purpose of “computational analysis” subject to certain restrictions.
The UK government aims to promote an innovative AI industry in the UK by enabling the mining of information within the existing protections of copyright and IP law.
To achieve this, in late 2023 the UK Intellectual Property Office (IPO) brought together representatives from AI companies, as well as arts and news organisations, to produce guidance and a “code of practice” on how the mining of text and data for AI models could be authorised.
As of February 2024, it is reported that this “code of practice” is delayed because of failure to reach agreement on a set of rules. The consequent uncertainty effects all of those who could benefit from this exception including those in education and research.
The copyright exceptions in the CDPA including TDM remain relevant to how AI is used. However, the uncertainty about an agreement on a new AI copyright code of practice is damaging to education particularly which requires assurances about the sources and accuracy of teaching and research materials.
Those in education require certainty about the source and accuracy of materials used in teaching and research.
Clearly a more comprehensive review and study of emerging and developing legislation is called for. In particular, how will this legislation govern and regulate the use of Generative AI in UK education?
Hopefully, the government, rights holders and AI providers can progress the ‘code of practice’.
If you are inputting data into a Generative AI tool:
Be aware of the following when relying on outputs generated by AI tools:
