Human-Data Interaction, Exploration, and Visualization in the AI Era: Challenges and Opportunities
The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. In the AI era, data analysis increasingly involves large-scale, heterogeneous, and multimodal data that is predominantly unstructured, as well as foundation models such as LLMs and VLMs, which introduce additional uncertainty into analytical processes. These shifts expose persistent challenges for human-data interactive systems, including perceptually misaligned latency, scalability constraints, limitations of existing interaction and exploration paradigms, and growing uncertainty regarding the reliability and interpretabili...
| Authors | Jean-Daniel Fekete, Yifan Hu, Dominik Moritz et al. |
|---|---|
| Primary category | cs.DB |
| Published | 4 March 2026 |
| Last updated at source | 4 March 2026 |
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