In recent years, artificial intelligence has developed rapidly. In data analysis tasks, collaboration between AI and humans has become increasingly important for problems that cannot be directly solved by AI alone. In this talk, we discuss the collaboration between humans and AI through the visual interface from two aspects: the validation of AI models, which opens the “black box” of artificial intelligence to provide “explainability”, and utilizing AI to recommend interactive behaviors for visual exploration. Firstly, AI is still a “black box” for humans. Understanding the correctness of AI behavior and exploring scenarios and possible reasons for AI failure is the core of our first work. We applied our interactive AI detection method in an autonomous driving visual detection model. To further open the “black box” of AI, we explore the different parameters and layers of neural networks through visualization and attribution methods and investigate the interpretability of the model in open-domain natural language conversation. Secondly, Large Language Model (LLMs) provides the ability to interpret various forms of data, offering the potential to support intelligent visual analytics. We introduced a new framework LEVA: LLM-Enhanced Visual Analytics. It provides intelligent insight suggestions when interacting with the exploration and summarizes the story of the exploration. Through the above cases, we discuss various key points of human-AI collaboration and summarize the effectiveness that intelligent human-AI interaction needs to achieve.



Dr. Siming Chen is an Associate Professor at the School of Data Science, Fudan University. He leads the Fudan Visualization Lab (FDUVIS). Before this, he was a Research Scientist at Fraunhofer Institute IAIS (Intelligent Analysis and Information Systems) and a Postdoc Researcher at the University of Bonn in Germany. He received his Ph.D. in computer science at the School of EECS, Peking University, and received his BS degree in computer science at Fudan University. His research interests are visualization and visual analytics, with an emphasis on human-AI collaboration, social media visual analytics, and spatial-temporal visual analytics. He has published more than 100 papers, more than 30 of which are in top conferences and journals, including IEEE VIS, IEEE TVCG, ACM CHI, ACM UIST, etc. He served as multiple organizing chairs, associate editors, and program committees of several international journals and conferences. He was awarded 10+ best paper/poster awards and honorable mentioned awards in multiple conferences, including EuroVA, ChinaVis, AGILE, and IEEE VIS Poster, and won multiple IEEE VAST Challenge Excellent Awards. For more information, please visit



University of Vienna - HS2 Währinger Straße 29