Scaling Evidence Identification from Communication Process Data with AI

Jiangang Hao

Abstract

Communication process data contain rich evidence of communication and collaboration skills yet identifying that evidence manually is difficult to scale. Our findings show that AI can efficiently and reliably extract evidence from large volumes of communication data without introducing systematic subgroup inconsistencies. These results demonstrate the potential of AI to enable scalable, reliable, and equitable assessment of complex skills.