How to deal with generative AI in UNIGIS studies

Generative artificial intelligence (AI) systems offer a wide range of potential for studying and teaching, but also new challenges. Important questions about studying and using generative AI will be answered on this website. You should also take a look at our guideline to dealing with generative AI.

It is important to us that, despite or even with generative AI systems, you can manage your learning processes autonomously and secure your learning progress. Ultimately, the intellectual process and responsibility for the content produced must always remain with humans and must not be outsourced to a machine. Aleksandr Tiulkanov’s decision tree helps with this:

Flowchart generative AI

Based on Aleksandr Tiulkanov (2023): Is it safe to use ChatGPT for your task? Available online (© https://creativecommons.org/licenses/by/4.0/deed.de)

What exactly is generative artificial intelligence?

Generative artificial intelligence (AI) is a type of AI that is able to create content such as text, images, videos, audio or software code. Generative AI is based on sophisticated deep learning models that are trained with huge amounts of data in a so-called “self-supervised” approach. Patterns and relationships are identified and coded in a “self-learning” process. In a second step, the inference phase, this information is used to generate content that is similar to the learned patterns and relationships in response to a prompt.

The most important questions and answers

Here you will find questions and answers on the topic, which, in addition to the guidelines for dealing with generative AI, provide an initial orientation for the use of generative AI systems in UNIGIS studies. Please note that the available systems are constantly evolving and the situation is currently quite dynamic. It is therefore possible that this guide will also have to be adapted. Feel free to check back here, stay critical and use your common sense more than ever.

Status: 05.06.2025

In UNIGIS studies, unless the module lecturer explicitly prohibits the use of generative AI systems, the application of this technology is generally subject to your own responsible handling. Should generative AI be used, it must always be clearly indicated (see the section “How do I cite the use of generative AI correctly?”).

A separate section (“Is it allowed to use generative AI in the Master Thesis?”) refers to the use of generative AI in the Master Thesis, which is different.

Generative AI is particularly suitable for supporting the introduction to a new topic, providing an initial overview of relevant aspects, or offering initial ideas. However, the deeper and more specific a question is, the more problematic the generative process step (the “inference phase”) becomes when using generative AI; during this step a new output (such as text, images, etc.) is created by combining individual components from the trained dataset. The deeper your understanding of the thematic area, the better your capabilities to accurately verify the validity of the results.

But keep in mind: Whenever you do not fully understand the results or cannot reliably assess their accuracy, generative AI is not an appropriate tool!

The use of generative AI tools for creating texts, figures, or code, as well as for proofreading and style improvement is strictly regulated in a Master Thesis. Please read carefully the guidelines and If you have further questions, do not hesitate to consult the supervisor of your Master Thesis.

If you are using AI systems such as ChatGPT, Microsoft Copilot, Gemini, Claude or similar tools for the assignment submissions, you must disclose this in a transparent and appropriate manner. Please keep the following points in mind:

1. Disclosure Statement on the use of generative AI

The use of generative AI must be disclosed in a “Disclosure Statement on the Use of Generative AI” at the end of the solution document of your assignments, and should contain the following information:

  • The name of the software used, including the version number and date (if known)
  • A clear description of which sections of the text or stages of the work were supported, influenced, or generated by the AI tool.

Example of such a disclosure statement:
Disclosure Statement on the Use of Generative AI:
In developing the solution to the assignment, the author used Claude.ai (Claude Sonnet v4 by Anthropic) to gain a better understanding of the concept of the “Travelling Salesman Problem (TSP)” and to explore example applications. The implementation of the TSP for the application case formulated in the assignment was carried out independently. The author takes full responsibility for the content of this work.

2. Citation Requirement for Adopted Content

If generated content – such as texts or figures – from AI tools is used directly or with slight modifications in your work, a proper MLA citation style is required.

Example:
“Which hotel is closest to the Department of Geoinformatics Z_GIS in Salzburg?” Prompt. ChatGPT, GPT-4.5, OpenAI, May 26, 2025, chatgpt.com.

3. Use of Generative AI in Programming Tasks

When generative AI is used for coding assignments, it must be disclosed not only in the “Disclosure Statement on the Use of Generative AI”, but also directly in the code. All code sections that were not entirely written independently or were only slightly modified must be clearly marked, for example, with appropriate comments.

Here is an example of such a comment in a Python script:
# This code section was generated with the assistance of ChatGPT (GPT-4.5, May 2025).
# Prompt: “Write a Python script to convert WGS84 coordinates to UTM”
# Output partially adopted and modified.

Please note that you remain fully responsible for the accuracy and academic integrity of your work in all cases!

The use of generative AI to create assessment-relevant content without proper indication is considered as academic misconduct. This is equivalent to plagiarism and may result in a negative grade or, in the worst case, even exclusion from your studies.

Further Resources

Guidelines

Guidelines for the use of generative AI in UNIGIS studies