Systems Group at ACM CHI 2025
Najda Geisler and Benjamin Hättasch presented two position papers at workshops of the ACM CHI Conference in Yokohama
2025/04/30
Nadja Geisler & Carsten Binnig: XAI meets Data-Centric AI: The Need to Explain Data Processing
Human-Centered Explainable AI (HCXAI) Workshop 2025
Data preprocessing is an essential part of any AI system, as indicated by the current trend of data-centric AI. However, until now, explainability efforts have almost exclusively focused on models. Choices in preprocessing, such as handling missing data, outliers, scaling, and class balancing, and their effects are currently not part of the explanations. If we continue this way, we are left with only a partial understanding of the model’s outputs. This transparency deficit creates risks for accountability, fairness, model performance, and more. We argue why we need full pipeline transparency and, as part of that, data preprocessing explainability, even in an age of AutoML and foundational models.
Benjamin Hättasch & Carsten Binnig: Databases: From Data Storage Towards Partners for Information Access and Discovery
AutomationXP25: Hybrid Automation Experiences Workshop 2025
In the paper, we argue that research on future data systems should incorporate factors of human computer interaction, and that automation is needed to allow users to deal with the ever-growing amount of data, but many (simple) approaches, such as the usage of LLMs, are insufficient. Instead, we propose building systems that leverage structured data and user interaction, and automate some tasks while still leaving the users in control through carefully designed means of interaction. Based on three case studies, we outline directions and principles for future research.
