This page is a derivative of a Generative AI and Library Skills guide by UCL. © 2024 by UCL - Library Skills. It has been used under CC BY-NC-SA 4.0 
Image by John Conde from Pixabay Accessed 11.04.2025
The prompts you have created yourself and provide as inputs to the tool may be protected by copyright, as long as they are original, i.e. your own intellectual creation. Examples include a series of short prompts you provide as instructions to create and refine an image; and articles, thesis extracts or essays you have written yourself.
Even if the prompt is your own intellectual property you should be aware that prompts you provide may be used to train the tool and reproduced in future outputs. Whether and how different tools do this varies and should be set out in their terms and conditions. They may state that they will not use your data, provide this as an opt-in or have a default licence for reusing the data, offering an opt-out. Licences to the tool to reuse your inputs and outputs can be very broad. Read the terms and conditions and if necessary, opt out of your data being reused, particularly if there are data protection concerns or confidentiality agreements. Please note that inputting commercially sensitive information that could, for example, lead to a patent would be considered as disclosure and restrict further exploitation. The University of Derby IP policies for staff and students also advises on this.
Generative AI has immense potential to support research when used in an open, critical, ethical, transparent and informed way. Training datasets that consist of high quality research should help increase the accuracy of the models and reduce biases. For a more extensive discussion, please see the Knowledge Rights 21 Principles on Artificial Intelligence, Science and Research.
Scholarly research that is published open access or shared in open access and research data repositories could be used to train AI under the licensing terms that apply. If text and data mining or other copyright exceptions apply, subscription articles, monographs and book chapters may also be used as training data as long as the provider has lawful access. This raises attribution issues and copyright issues, for example if the outputs reproduce substantial content from the originals or create derivatives.
A number of publishers now have, or are negotiating, agreements with AI providers licensing the reuse of their publications. While it has been assumed that publishers, traditionally being the copyright owners of journal articles, can license these works without the consent of their authors, it can also be argued that such use is not covered by previous agreements and permission should be sought separately.
Publishers may now ask you to agree to your article, monograph or book chapter to be used as part of training datasets. Such agreements should address:
The purpose and nature of the reuse. What is covered by current licensing agreements with AI providers? For example, your work could be used to improve the accuracy of the tools or to develop new tools. How could this be achieved?
Control over new uses in the future.
Accurate attribution. If parts of your publication is to be reproduced in Gen AI outputs, how will you be attributed?
Royalties (in the case of books).
You should be able to ask your editor for more information before you make a decision.
A comprehensive discussion of issues related to GenAI and academic publishing is available on the Kluwer copyright blog:
Trapova, Alina (2024). 'Report on a roundtable on academic publishing and genAI deals – GenAI and copyright series at the Institute of Brand and Innovation Law', Kluwer Copyright blog, 18 December. Available at: https://copyrightblog.kluweriplaw.com/2024/12/18/report-on-a-roundtable-on-academic-publishing-and-genai-deals-genai-and-copyright-series-at-the-institute-of-brand-and-innovation-law/ (Accessed 18 December 2024).
