This hybrid workshop brings together researchers from the interdisciplinary FWF/DFG-funded project AniVision (2022–2026), archivists, and film scholars to explore AI-supported approaches to animation history. Short presentations introduce machine-learning assisted methods for identifying animation techniques, metadata exploration, visualization, and selected case studies. A hands-on session invites participants to test the AniVision tools, discuss their potential for film-historical research, and provide feedback, followed by an outlook method to identify semantic content of animated films in Central Europe.

The ARI5E workshop bridges research and industry practice: participants gain a compact overview of the state of the art in AI-driven humanoid robotics and the project's core objectives.

Demos illustrate concrete application scenarios for manufacturing. Interactive group work invites participants to explore deployment potentials, safety and economic considerations, and societal acceptance — generating tangible impulses for technology transfer into SMEs.

How can digital tools, AI, and local knowledge uncover rural industrial heritage? The project Industrie im Dorf (GFF NÖ, 2025-2028) brings together citizen scientists from four Lower Austrian communities. Through hands-on activities, participants explore historical records, objects, places, and memories using AI-assisted research, digital modelling, and oral history. The workshop reflects on how human-centered AI and participatory approaches can support heritage research while valuing local knowledge and experience.

This workshop brings together researchers from the FFG-funded flagship project FairAI (2024-2026) with interested colleagues to discuss ethical considerations and learnings from the project. Furthermore, we aim to provide a first preview into the FairAI handbook that is currently under development. In project FairAI a large consortium of leading players in Austria developed innovative solutions that promote sustainability and trustworthiness of AI and in particular addressed fairness, robustness, accountability, and transparency in the development of AI solutions. The project took a co-development approach to realize real-world AI-driven use cases. We defined research modules in which industry partners provided use cases and worked together with research institutions to implement new solutions. In this workshop company partners will present their learnings from the project during the respective use cases, especially regarding ethical questions.

Different Brilliant showcases outstanding theses that bring new perspectives to media and design. The selected finalists present their research questions, methodological approaches, processes, and key outcomes. Moving beyond traditional methods, the presentations highlight a broad spectrum of approaches, including practice-led research, research-through-design, artistic research, experimental methods, and mixed-methods approaches. The workshop creates a space for peer exchange and methodological inspiration. By bringing together diverse disciplines and research practices, Different Brilliant demonstrates that methodological diversity can open up new ways of understanding media, design, technology, and creative practice.