Menschzentrierte künstliche Intelligenz
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Research Disciplines
The rapid development of artificial intelligence (AI) in recent years has brought enormous opportunities but has also posed new risks. AI research has so far focused primarily on the development of systems that are intended to solve increasingly complex tasks with the greatest possible accuracy. As a result, the decisions and actions of such systems are becoming increasingly difficult to comprehend. HCAI is a doctoral research and education program run jointly by the University of Applied Sciences Upper Austria and Johannes Kepler University Linz. The program is funded by the Austrian Science Fund (FWF). It aims to put people and their needs at the center of AI research. Methods are being developed to make artificial intelligence more understandable, tran sparent and fair for humans on the one hand, and to support the interaction between humans and AI systems on the other hand. The doctoral students working in this program receive interdisciplinary training and work at the forefront of research and development of a new generation of human-centric AI technology.
| Title | Year(s) | DOI / Link |
|---|---|---|
| The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias | 2024 | 10.1007/978-3-031-56066-8_33 |
| Measuring Bias in Search Results Through Retrieval List Comparison | 2024 |
No additional funding sources recorded.
Research Fields
| Moral reasoning in a digital age: blaming artificial intelligence for incorrect high-risk decisionsCurrent Psychology | 2024 | 10.1007/s12144-024-06658-2 |
| The Changing Nature of Human-AI Relations: A Scoping Review on Terminology and Evolvement in the Scientific LiteratureInternational Journal of Human–Computer Interaction | 2025 | 10.1080/10447318.2025.2482742 |
| Transitioning to a Commercial Dashboarding System: Socio-Technical Observations and Opportunities.IEEE transactions on visualization and computer graphics | 2024 | 10.1109/tvcg.2023.3326525 |
| Marjorie: Visualizing Type 1 Diabetes Data to Support Pattern Exploration.IEEE transactions on visualization and computer graphics | 2024 | 10.1109/tvcg.2023.3326936 |
| Loops: Leveraging Provenance and Visualization to Support Exploratory Data Analysis in NotebooksIEEE Transactions on Visualization and Computer Graphics | 2024 | 10.1109/tvcg.2024.3456186 |
| D-Tour: Semi-Automatic Generation of Interactive Guided Tours for Visualization Dashboard OnboardingIEEE Transactions on Visualization and Computer Graphics | 2024 | 10.1109/tvcg.2024.3456347 |
| Iguanodon: A Code-Breaking Game for Improving Visualization Construction LiteracyIEEE Transactions on Visualization and Computer Graphics | 2024 | 10.1109/tvcg.2024.3468948 |
| A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios | 2024 | 10.1145/3640457.3688138 |
| Reassuring, Misleading, Debunking: Comparing Effects of XAI Methods on Human DecisionsACM Transactions on Interactive Intelligent Systems | 2024 | 10.1145/3665647 |
| Peer or Steer: A Pilot Study Exploring Human-AI Collaboration in Creative FieldsProceedings of the ACM on Human-Computer Interaction | 2025 | 10.1145/3757643 |
| Framing 'Collaboration': How Human-Human Principles Translate into Human-AI Realities | 2026 | 10.1145/3772318.3791746 |
| CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter spaceJournal of Cheminformatics | 2024 | 10.1186/s13321-024-00840-1 |
| molIEreVIS: exploring and interpreting the evidence behind drug repurposing predictions.Frontiers in bioinformatics | 2026 | 10.3389/fbinf.2026.1756459 |
| Visual Fingerprints for LLM Generation Comparison | 2026 | 10.48550/arxiv.2605.06054 |
| Audio, Lyrics, Videoclips, Interactions? An Analysis of Uni- and Multi-modal Music Retrieval Systems in Terms of Accuracy and Beyond-accuracy Aspects | 2026 | — |
| The Changing Nature of Human-AI Relations: A Scoping Review on Terminology and Evolvement in the Scientific LiteratureInternational Journal of Human-Computer Interaction | 2025 | — |
| Psychology-informed Information Access Systems Workshop | 2024 | — |
| AI Creativity in the Light of Autonomy; In: Artificial Intelligence, Co-Creation and Creativity | 2024 | Link |
| Designing Through Dialogue: Interaction Patterns in AI-Assisted UI Prototyping | 2026 | — |
| A Hybrid Cooperative Approach for Symbolic Regression- (Accepted) | 2024 | — |
| Peer or Steer: A Pilot Study Exploring Human-AI Collaboration in Creative FieldsProceedings of the ACM on Human-Computer Interaction (PACMHCI) | 2025 | — |
| AI Creativity in The Light of Autonomy; In: Artificial Intelligence, Co-Creation and Creativity: The New Frontier for Innovation | 2024 | — |
| Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models | 2024 | — |
| Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training | 2024 | — |
| Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems | 2026 | — |
| Personalized Complementarity in Human-AI Collaboration | 2024 | — |
| Single-Branch Architectures for Recommendation | 2025 | — |
| Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters | 2024 | Link |