AI, plagiarism and text recycling: Information resources for academic authors

Handout for the solution session “AI, plagiarism and text recycling: Information resources for academic authors”. Open Science Conference, Hamburg, 8–9 October 2025 © Aysa Ekanger. https://doi.org/10.5281/zenodo.17591349, CC BY 4.0. Tasks Choose one of the following tasks. On the other side of this sheet you can find some information resources that may be useful. Task about text recycling and AI Develop a flowchart or FAQ list on behalf of a journal (that allows generative recycling) to address the following scenario: An author needs to include a method description from their previous publication into a manuscript that presents new research results. Can the author reuse the method description verbatim or do they need to paraphrase it? If the former, do they need to do it as a quotation (with quotation marks around each reused sentence) or can they incorporate the reused text into the new manuscript seamlessly, without quotation marks? If the latter, can they do it with the help of an AI tool? Consider including the following points in the flowchart/FAQ list. (Alternatively, you can simply discuss one or more of these points, without constructing a flowchart.) - Establish that this is generative recycling: the new manuscript presents new insight, and is not a duplicate publication (you decide whether you want to use the terms from the Text Recycling Project) - Does the author have reuse rights for the previous publication? Is there a difference between the following scenarios: o author has retained full copyright (article may or may not be under a CC license) o publisher has copyright, but the article is under a CC BY license o publisher has copyright (author retains only moral rights), all rights reserved - How to indicate text recycling in the manuscript - How to indicate use of AI in the manuscript – what information needs to be included? - In case of AI use, remind the author that they are responsible for the accuracy of the output Task about plagiarism of ideas and AI The Living guidelines on the responsible use of generative AI in research mention the following uses of AI as substantial, but allowed types of uses: “interpreting data analysis, carrying out a literature review, identifying research gaps, formulating research aims, developing hypotheses, etc” (p. 8). Plagiarism of expressions (text copied from previously published works) is easy to detect with plagiarism screening tools – but it is more challenging for such tools to detect plagiarism of ideas. Which of the specified AI uses above can cause plagiarism of ideas? (Think also of possible uses under “etc” that might do so.) When resorting to such types of AI use, is it possible for an academic author to ensure that their manuscript does not contain plagiarism of ideas? If so, how? If not, what measures can the author take to diminish a possible violation of research ethics? Handout for the solution session “AI, plagiarism and text recycling: Information resources for academic authors”. Open Science Conference, Hamburg, 8–9 October 2025 Supporting material for the tasks Text recycling “Text Recycling is the reuse of textual material (prose, visuals, or equations) in a new document where (1) the material in the new document is identical to that of the source (or substantively equivalent in both form and content), (2) the material is not presented in the new document as a quotation (via quotation marks or block indentation), and (3) at least one author of the new document is also an author of the prior document.” (Text Recycling Research Project (n.d.). What is Text Recycling? Licensed under CC BY 4.0.) Four types of text recycling (see Hall, S., Moskovitz, C., and Pemberton, M. 2021. Understanding Text Recycling: A Guide for Researchers. Text Recycling Research Project): - Developmental recycling: unpublished material (e.g. conference presentation) recycled in e.g. article - Generative recycling: excerpts from published material recycled in a new work with a substantive new intellectual contribution - Adaptive publication: recycling a published work for a new audience or in a new genre - Duplicate publication: recycling a published work for the same audience/genre Recycle verbatim or paraphrase? Sometimes verbatim copying is preferable: “altering the wording of recycled passages can confuse readers as to whether the method (or research question, research site, etc.) is actually different from the author’s previous work or is just being described using different words.” (Hall et al. 2021, p. 34). GenAI use (From European Commission (2025). Living guidelines on the responsible use of generative AI in research. V2. CC BY 4.0) «Researchers, to be transparent, detail which generative AI tools have been used substantially* in their research processes. When generative AI meaningfully shapes results, researchers transparently note its use in the methods section (or equivalent) responsibly evaluating the extent of the contribution. References to the tool could include the name, version, date, etc. and how it was used and affected the research process. If relevant, researchers make the input (prompts) and output available, in line with open science principles.» (p. 7-8) * “In this case, for example, using generative AI as a basic author support tool is not a substantial use. However, interpreting data analysis, carrying out a literature review, identifying research gaps, formulating research aims, developing hypotheses, etc. could have a substantial impact.” (p. 8) «Researchers remain mindful that generated or uploaded input (text, data, prompts, images, etc.) could be used for other purposes, such as the training of AI models. Therefore, they protect unpublished or sensitive work (such as their own or others’ unpublished work) by taking care not to upload it into an external AI system unless there are assurances that the data will not be re-used, e.g., to train future language models» (p. 8) «Researchers pay attention to the potential for plagiarism (text, code, images, etc.) when using outputs from generative AI. Researchers respect others’ authorship and cite their work where appropriate. The output of a generative AI (such as a large language model) may be based on someone else’s results and require proper recognition and citation» (p. 8) The Creative Commons Attribution condition «You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.» - “appropriate credit — If supplied, you must provide the name of the creator and attribution parties, a copyright notice, a license notice, a disclaimer notice, and a link to the material. CC licenses prior to Version 4.0 also require you to provide the title of the material if supplied, and may have other slight differences.” Handout for the solution session “AI, plagiarism and text recycling: Information resources for academic authors”. Open Science Conference, Hamburg, 8–9 October 2025 © Aysa Ekanger. https://doi.org/10.5281/zenodo.17591349, CC BY 4.0. Additional tasks The first two pages of this document can be printed out as one sheet, for workshop participants to use as a handout. The digital document used during the solution session at the Open Science Conference 2025 in Hamburg also contained the following additional tasks. Task about plagiarism of expressions and plagiarism of ideas On behalf of a journal, help an author to avoid plagiarism of expressions (text copied from previously published works) and plagiarism of ideas when using generative AI in the preparation of their manuscript. Should the author be responsible for running a plagiarism check on the manuscript? Does the journal need information about the type of screening tool used? Task about journal policies Set up a minimum list of issues related to AI use, plagiarism and text recycling that a journal must inform prospective authors about in its author guidelines or general journal policies. E.g., statements about specific types of text recycling or AI use, clear explanation of plagiarism and ways to avoid it, any statements about intellectual property rights.