Dr Janine Horn (UOL; offered as part of the HSOS LearningCentre's AI Month)

Artificial intelligence (AI) and, in particular, generative AI models have seen a significant increase in use in universities in recent years and have opened up growing application contexts. Nevertheless, legal categorisation and evaluation is still a major challenge for universities, as there was initially a lack of legal regulations. The understanding of the role of universities in this context was and still is often relatively diffuse. The European AI Act now provides legal guidelines that universities and teaching staff can and must follow.

The presentation will introduce the legal framework of the AI Act that is relevant for universities. It will address the regulations applicable to high-risk systems in the education sector and the other requirements of the AI Regulation.

The slide set for the presentation is available here.

Marieke Prien (HSOS, Offer as part of the AI month of the HSOS LearningCentre)

Objective, fair, based purely on facts - this is how we often imagine AI systems. However, AI often conceals prejudices, which we then refer to as "bias". Bias leads to discrimination and therefore has far-reaching ethical and legal consequences.

The development of bias-free AI is very important, but not that easy. The systematic distortions that form the basis of bias are often already present in the training data or are included in the programming. Bias is particularly difficult to detect and prevent in so-called black-box AI, whose mode of operation is not really visible from the outside.

This presentation is about how a bias arises, why black-box AI is still used and what approaches there are to solve the problem.

Youcan access the slides here, unfortunately we do not currently have a recording.

Dr Janine Horn (UOL)

Generative artificial intelligence is used by students to prepare credits and by teachers to create assignments. Copyright and data protection issues must be taken into account both when entering content and data into the system and when re-using the generated output.

The following questions will be addressed in the presentation: Which copyrights and personal rights must be observed when re-using content? What role does data protection play when accessing the system and inputting data? What are the implications of the AI Regulation for teachers and students as users of AI systems?

Click here for the slides and the lecture was recorded:

Dr Janine Horn (UOL)

The discussion surrounding the use of artificial intelligence (AI) in academic examinations is becoming increasingly important and is occupying universities and courts alike. Particularly in the case of unsupervised examinations such as Bachelor's, Master's, student research projects and seminar papers, there is a need for communication on what is permitted, a need for regulation regarding the labelling of adopted AI content and, if necessary, a need for adaptation regarding the content of the examination and the type of examination.

The presentation highlights the legal issues surrounding the use, discovery and proof of the use of generative AI in examinations and outlines a possible way of dealing with AI in examinations.

The slides can be found here and the event was recorded:

by Kira Baresel (UVec) + Susanne Schorer (UOL)

What does autonomy mean in connection with the use of AI in the context of examinations? How can university lecturers deal with it? In this session there will be a short input on the topic of autonomy. The focus will then be on sharing experiences and discussion.

The slides can be found here and the lecture was recorded:

by Kira Baresel (UVec)

Artificial intelligence (AI) brings new challenges for university teaching, especially with regard to examinations. Transparency is a top priority. The presentation shows that citing AI-generated content is not enough. But how can we ensure that students work responsibly and transparently with AI? How should you disclose the use of AI?

The slides of the lecture are available here, the recording of the lecture part (without discussion) is also available:

Susanne Schorer (UOL)

Due to the possibilities of AI, the problems of asynchronous examination formats such as bachelor theses & co. have once again come into focus, as the distinction between AI-generated content and content from examinees can no longer be reliably distinguished. Possibilities will be shown as to how these examination formats can be adapted for use with AI and how they should be further developed in order to be able to examine more securely in the future. This will be followed by a joint exchange of experiences and discussion.

To the lecture recording, the slide set and an accompanying text for the event.

Presentation by Sarah Becker, student at the Ruhr University Bochum.

Sarah Becker's presentation will focus on the perspective of students on the use of artificial intelligence (AI) in their studies. The presentation will focus on the consequences of a culture of mistrust towards AI in higher education and how this affects relationships between teachers and students. While more and more studies show that the actual use of AI has long been part of student practice, it is often institutionally taboo or viewed with suspicion. This tension creates uncertainty and leads to a loss of trust between teachers and students. The aim is for participants to develop new ideas and approaches for organising studies with AI and for the discussions to contribute to a better understanding of the opportunities and risks of using AI in studies. The second part of the event will focus on the exchange between students and lecturers. The aim is to discuss the opportunities and risks of using AI in studies and to share experiences and ideas.

Click here for the video of the lecture on YouTube.

Sylvia Feil (LUH), Ina Hoffmann (MHH) and Felix Schroeder (LUH)

Good teaching should promote the personal development of students and prepare them for their career entry. This increasingly requires the teaching of AI skills. In addition to the competences specified in the European AI regulation, there are numerous AI competence models - these deal with the reflected use of AI tools as well as the development and expansion of options for action with them. The presentation will introduce the reference model selected by the AI competences working group, including the associated categories.

How these AI competences can be integrated and promoted as learning objectives in teaching and learning scenarios will be discussed together. The different competence levels are important here - from being able to explain to being able to use and combine creatively. Methodologically, AI competences can thus be well integrated into didactic concepts and linked to the goal of good academic practice.

The slides can be found here and the lecture was recorded.

Lecture and discussion, Laura Fiegenbaum (Ostfalia) & Fritz Wilhelms (HAWK)

Text-generative AI tools can support academic writing in a variety of ways. The lecture will show the possibilities as well as the limits and risks of using AI. We will then discuss the following questions: What is the relationship between generative AI tools and the teaching of academic writing? Does the use of AI tools in teaching promote or prevent the acquisition of writing skills? How can AI-integrated writing didactics succeed? This event is aimed at lecturers who teach academic writing in interdisciplinary and/or subject-specific courses. All other interested parties are welcome.

Click here for the slides. The first part of the event was recorded. The subsequent discussion was not recorded.

Malte Heyen (UOS) and Tim Dernedde (UHi)