Workshop on Generative Artificial Intelligence in Interactive Systems: Experiences from the Community
at the Mensch und Computer 2024
This workshop brings together the German HCI community from research and industry to gather experiences and perspectives on the use of generative Artificial Intelligence (GenAI). This workshop aims to draw on individual experiences using GenAI in different HCI research or industry projects. By collecting the expertise from different stakeholders, we will identify existing practices and success stories for integrating GenAI into the HCI research cycle. The goal is to highlight individual approaches and create a practical insights report. This report synthesizes the collective experiences and practical insights with detailed examples of personal best practices for the wider HCI community.
We welcome participants and contributions from the whole spectrum of the HCI community: Researchers, interaction designers, visual artists, product developers, etc., who might provide their experience on leveraging the GenAI potential. Participants are requested to submit a position paper, which, upon acceptance, will be published on the website and included in the Practical Insights Report. Many different use cases and innovative approaches in using GenAI have emerged that have changed how we currently conduct HCI research. This workshop aims to bring the community together to share experiences and best practices that can shape guidelines and new approaches of including tools like ChatGPT to research practices and interactive systems. One of the workshop's objectives is to create a practical insights report on different work practices and allow the exchange of alternative approaches and creative workarounds.
We invite position papers that address prompts such as:
- What are routines that you have built for using GenAI in your research process, and how does this change how you execute different tasks?
- Describe a specific application of generative AI that has strongly impacted a particular task within your research process.
Deadline for submitting your position paper or personal statement: 13 June 2024 (AoE)
You can submit your paper to https://www.conftool.com/muc2024/. The submission does not need to be anonymized. Each submission will be reviewed by the organisers and the selection will be made based on their relevance, quality, and ability to trigger discussion and coverage of diverse topics.
Notification date: 04 July 2024
Format: single-column ACM Master Article Submission Template, up to 2500 words excluding references. Accepted papers will be published in the GI Digital Library
Location and format: The workshop is a part of the Mensch und Computer '24 conference, which will take place at the at the Karlsruhe Institute of Technology in Karlsruhe, Germany.
Date: (full-day).
Registration: At least one author of each accepted submission must attend the workshop. All participants must register for the workshop and at least one conference day.
Generative Artificial Intelligence (GenAI) is establishing itself in academia and industry through accessible implementations like ChatGPT and Stable Diffusion. Subsequently, GenAI is changing the interaction paradigms between users and computers. Currently, many individual approaches exist to leverage these tools, creating various strategies and agendas for using them in HCI research. Thus, we expect this will change how researchers design and create interactive interfaces. This workshop facilitates a common understanding of GenAI concerning HCI in which participants will share and discuss their experiences using GenAI and Large Language Models (LLMs) in HCI research. In this workshop, the potential of GenAI for Human-Computer Interaction will be explored and discussed with the research community through position papers, research statements, and opinions, thereby creating comprehensive practical insights synthesizing collective experience and strategies with real-world examples.
| 9:00 – 9:15 | Opening of the workshop: welcome and introduction to workshop goals |
| 9:15 – 10:00 | Startup Talk and practical insights on generative AI |
| Coffee break | |
| 10:30 – 12:00 | Session I: Experience on using GenAI in HCI research and input for a practical insights report |
| Lunch | |
| 13:00 – 14:30 | Session II: Talks and Demos by Participants |
| Coffee break | |
| 15:00 – 16:30 | Session III: Outlook on future GenAI interactions |
| 16:30 – 17:00 | Wrap-up, Conclusion and Feedback |
| 17:00: End of the workshop | |
Anastasiya Zakreuskaya (ExSitu Inria and Université Paris-Saclay) anastasiya.zakreuskaya@inria.fr
Anastasiya Zakreuskaya is a researcher at ExSitu Inria and a Ph.D. candidate at the Université Paris-Saclay in France, where she investigates how new technologies change collaboration and work practices in hospitals. Before this position, she worked at the Machine Learning and Data Analytics Lab at the Friedrich-Alexander Universität Erlangen Nürnberg and completed a research visit at NYU Langone’s Healthcare Innovation Bridging Research, Informatics, and Design (HiBRID) Lab, gathering insights in how to build clinical applications that include new approaches like generative AI or automated workflows.
Tobias Münch (Münch Ges. für IT-Solutions mbH) to.muench@muench-its.de
Tobias Münch is the CTO of Münch Gesellschaft für IT-Solutions and a Ph.D. student at Chemnitz University of Technology. He has implemented various PWA solutions in the finance, veterinary medicine, and logistics sectors for ten years. In his past research, he has focused on the maintainability of the World Wide Web and the use of standards. He talked about the availability and privacy issues of the WebSpeech API at the ACM WebConf 2023. His current research focuses on conversational user interfaces in progressive web apps and how they can be implemented in the context of web engineering and LLM-based AI.
Henrik Detjen (Fraunhofer Institute for Digital Medicine MEVIS) henrik.detjen@mevis.fraunhofer.de
Henrik Detjen is a Human-Computer Interaction Scientist at the Fraunhofer Institute for Digital Medicine MEVIS. He has a background in cognitive science and HCI in the automotive domain. His current focus is on the human-centered design of automated and autonomous systems in the medical domain, e.g., visual programming tools that aid medical researchers designing ML workflows or patient interfaces that embody LLMs and other intelligent technologies.
Sven Mayer (LMU Munich) info@sven-mayer.com
Sven Mayer is an assistant professor of computer science at LMU Munich, Germany. His research sits at the intersection between Human-Computer Interaction and Artificial Intelligence, where he focuses on the next generation of computing systems. He uses artificial intelligence to design, build, and evaluate future human-centered interfaces. In particular, he envisions enabling humans to outperform their performance in collaboration with the machine. He focuses on areas such as augmented and virtual reality, mobile scenarios, and robotics.
Passant Elagroudy (German Centre for Artificial Intelligence (DFKI) and RPTU) passant.elagroudy@gmail.com
Passant Elagroudy is a post-doctoral researcher at the intersection of innovation, as she works at the German Centre for Artificial Intelligence (DFKI) and RPTU Kaiserslautern University, Germany. With a Ph.D. in Computer Science from the University of Stuttgart, her work focuses on creating technologies that enhance human cognition. She contributed to major European research projects to augment memories like RECALL and AMPLIFY. She is also from the management team coordinating Humane AI Net, one of the largest research and industrial consortia, advancing ethical AI solutions for everyday life.
Bastian Pfleging (TU Bergakademie Freiberg) bastian.pfleging@informatik.tu-freiberg.de
Bastian Pfleging is a professor for Ubiquitous Computing and Smart Systems at TU Bergakademie Freiberg, Germany. With a background in computer science, his expertise is in the fields of human-computer interaction, ubiquitous systems, multimodal interaction, natural user interfaces, and specifically automotive user interfaces. His research aims to understand how ubiquitous computing systems can support users with their tasks and activities while keeping the user in the loop and in control.
Fiona Draxler (University of Mannheim) fiona.draxler@uni-mannheim.de
Fiona Draxler is a postdoctoral researcher at the University of Mannheim, working at the intersection of human-computer interaction and social data science. Her research focuses on human-AI interaction in application domains such as LLM-supported writing, AI methods in survey research, and the auto-generation of learning material in technology-supported education.
Benjamin Weyers (University of Trier) weyers@uni-trier.de
Benjamin Weyers is a junior professor for Human-Computer Interaction at Trier University. His primary interests in research and teaching lie in the scientific development and investigation of interactive systems, specifically focusing on using virtual and augmented reality technology in everyday work contexts and environments. He is especially interested in the use of Petri net-based description concepts and graph transformation systems for modeling flexible and adaptable user interfaces, virtual reality, interactive data analysis and information visualization, collaborative and learning systems, and ambient intelligent systems.
Uwe Gruenefeld (University of Duisburg-Essen GenerIO.net) uwe.gruenefeld@uni-due.de
Uwe Gruenefeld is a postdoctoral researcher in Human-Computer Interaction at the University of Duisburg-Essen, Germany, and the co-founder of GenerIO.net. He works at the intersection of Mixed Reality and Artificial Intelligence. His research has focused on a range of topics, including the augmentation of human perception, usable security, cross-reality systems, and generative AI.
Waldemar Titov (Furtwangen University) waldemar.titov@hfu.eu
Waldemar Titov is a research scientist at the Furtwangen University. He conducts research in the fields of human-computer interaction, usability, and digitalization in mobility, focusing on non-motorized means of transport and public transport. In the research project SmartMMI, he and his team researched and tested the provision of relevant data for public transport journeys directly in the train window. This approach enables the provision of intelligent information on transparent mobile displays, which allows passengers to find out about their route and current developments on the window during the journey.
Jonas Auda (jonas.auda@uni-due.de) University of Duisburg-Essen and GenerIO.net
Jonas Auda is a postdoctoral researcher at the University of Duisburg-Essen and the co-founder of GenerIO.net, a startup dedicated to human-centered generative AI. He has obtained a Ph.D. in Human-Computer Interaction, focusing on exploring interactions within virtual realities. His research has utilized emerging technologies such as electrical muscle stimulation to actuate users, drones for autonomously delivering haptic feedback, and brain-computer interfaces employing EEG for interacting in VR. Presently, his work centers around human-centered generative deep learning, where he holds a leadership position at GenerIO, driving the development of intuitive and accessible AI solutions.
Wendy E. Mackay (ExSitu, INRIA, LRI, Université Paris-Saclay) wendy.mackay@inria.fr
Wendy E. Mackay is a Research Director, Classe Exceptionnelle (DR0), equivalent to a tenured full professor and a Professor Attaché at the Université Paris-Saclay. She received her Ph.D. from MIT and have served as Chair of ACM/SIGCHI, co-editor–in-chief of the journal IJHCS, was general chair of our flagship conference CHI’13, and received the ACM/SIGCHI Lifetime Achievement Award for Service. Her research group Ex)situ explores the limits of interaction and seek to create effective human-computer partnerships
Daniel Buschek (University of Bayreuth) daniel.buschek@uni-bayreuth.de
Daniel Buschek is a professor of Mobile Intelligent User Interfaces at the University of Bayreuth, Germany. His group works at the intersection of Human-Computer Interaction and AI, exploring interaction with models for text and images to shape the future of working with AI tools in a human-centered way.
Thomas Kosch (HU Berlin) thomas.kosch@hu-berlin.de
Thomas Kosch is a professor of the Human-Computer Interaction Group at the Humboldt University of Berlin. His research focuses on implicit AI-driven physiological interfaces, user sensing, and user state predictions for human augmentation and self-reflection. He integrates his research into the next generation of user interfaces, including extended reality and generative artificial intelligence. This includes conceptualizing, designing, and implementing unobtrusive user sensing and interaction. He is experienced in designing user studies, quantitative and qualitative methods, machine learning, and prototyping.