Any material from generative AI included (either directly or in edited form) in an assignment as if it were one’s own work, without disclosure or indication, is considered plagiarism. Such an offence will be treated on an equal footing with other forms of plagiarism (opens in a new tab).
As a general principle, the reader must be able to ascertain how generative AI has contributed to the final product.
If you have used generative AI in your assignment in a way that is not described below, you must always clearly explain why and how generative AI has been used at a relevant point in the assignment (e.g. method sections, footnotes, index, etc.). If in doubt, you can always include prompts (or prompts and answers) as appendices.
- The prompt is the text or instruction you enter into generative AI tools to achieve the desired response. It can be a simple prompt of, say, one line, or an advanced prompt that describes in detail what response the chatbot should generate.
The prompt also sets the tone and direction of the conversation with the chatbot, which can ensure that the chatbot delivers relevant responses. The method of constructing prompts is called prompt engineering.
Here are some examples of how to make it clear to the reader or reviewer of your work that you have used generative AI:
In academic contexts, generative AI is not perceived as an authoritative source. It is therefore not recommended to use generative AI to generate finished text for academic assignments, unless the assignment requires it (e.g. assignments dealing with generative AI or prompt engineering).
If you nevertheless insert text generated by generative AI into your assignment, it must be clearly declared:
- If you insert passages generated by generative AI directly into the assignment, they must be cited as a citation, and you must cite that generative AI on the list of references.
Note: this also applies if you have used AI-generated notes that are included in the assignment.
Read more about citation of generative AI here (in Danish). - If you insert passages in which you have paraphrased generative AI output, or if you insert passages in which generative AI has paraphrased the original text, you must cite generative AI.
Read more about citation of generative AI here (in Danish).
Explain at a relevant point the assignment (e.g. method sections, footnotes, indexes, etc.) how generative AI has helped organise chapters and sections or other elements of the assignment.
Your programme may require additional documentation.
Describe at a relevant point in the assignment (e.g. method sections, footnotes, indexes, etc.) how generative AI has condensed large data sets. Use source references to document which original data has been summarised.
Your programme may require additional documentation.
At a relevant point in the assignment (e.g. method sections, footnotes, indexes, etc.), include a description of the analyses and interpretations that generative AI has performed, and how they are included in your assignment. Use source references to document which data has been analysed and/or interpreted.
Your programme may require additional documentation.
Describe at a relevant point in the assignment (e.g. method sections, footnotes, indexes, etc.), how generative AI was used to support your assignment, e.g. by identifying relevant sources, literature and materials.
Include examples of search strings and criteria you have used with generative AI.
Describe at a relevant point in the assignment (e.g. method sections, footnotes, indexes, etc.) that generative AI has been used for proofreading (grammar, spelling and punctuation).
If generative AI is used to contribute to the linguistic presentation of your assignment (e.g. the correct use of terminology, wording, linguistic adjustments, feedback on language, translation, etc.), this must be explained at a relevant point in the assignment.
Little by little, an increasing number of existing software programs, such as Microsoft Office 365, Adobe Photoshop, etc. are gaining generative AI functionality, and completely new programs have been developed and are being developed based on the technology, which specialises in images, video, transcription work, data processing, etc.
SDU has made a number of generative AI tools available. SDU does not prohibit the use of any programs, but you are responsible for complying with the security guidelines.
Here are examples of tools that SDU makes available:
Copilot
Your SDU Microsoft Office account gives you access to Microsoft's Copilot (external page opens in a new tab).
Copilot is built on the same language model as ChatGPT combined with Microsoft’s Bing search engine. Find more information here: Copilot chat (external page opens in a new tab).
Scite.ai
The library provides access to the literature search and AI tool Scite.ai through the A-Z Database List (external page opens in a new tab). Access is available for SDU students and staff, as well as employees at the university hospitals in Region South and at OUH. Read more about Scite.ai in the library's AI guide (external page opens in a new tab).
Transcriber
SDU has access to the transcription tool "Transcriber" (external page opens in a new tab) via UCloud, which is secure and free for students. This solution uses the language model Whisper from OpenAI to create transcriptions from voice or video recordings. Uploading files here is secured in relation to GDPR, as files will be stored on SDU's own server. Files of type mp3, .mp4, .m4a, .wav, .mpeg, and .mpg can be used. If you need help getting started, please contact the SDU eScience Center at support@escience.sdu.dk.
What are chatbots and generative AI
Generative AI is a type of artificial intelligence that is designed to generate new content elements, such as text, code, images, music, videos, etc. (Stanford University, Nature, 2016).
Chatbots are computer programs based on generative AI – colloquially referred to as ‘generative language models’ or simply ‘artificial intelligence’.
A chatbot’s output is based on a series of statistical analyses based on probability calculations. Due to the advanced structure, computing power and large data sets of the language model, it can produce very precise, contextual output in the form of text, images, sound, video, tables, code, etc.
Generative chatbots come in many varieties and are offered by many different companies. Among the most widely used general chatbots are Copilot, ChatGPT, Gemini, Claude and Mistrall.
There are also a number of chatbots on the market that are trained on a more specialised and limited material, such as research papers, and trained for more focused tasks (including literature search and data processing).