Designing Computational Tools for Exploring Causal Relationships in Qualitative Data
A new system uses AI to visually map out why people think and act the way they do.
Deep Dive
Researchers have developed 'QualCausal', an AI-powered system designed to help social scientists and HCI researchers uncover cause-and-effect relationships in qualitative data like interviews. Current tools mostly just categorize data. Based on a study with 15 participants, the new system builds interactive visual networks of causal links. A feedback study found it reduced analytical burden but raised questions about fitting into established research practices. The work is conditionally accepted for CHI 2026.
Why It Matters
It could revolutionize how we understand human behavior by making complex social data easier to analyze.