AI-Driven Contribution Evaluation and Conflict Resolution: A Framework & Design for Group Workload Investigation
Researchers have developed a novel framework and design for an AI-enhanced tool aimed at investigating group workload disputes. This system organizes diverse artifacts like code submissions, communications, and peer assessments into three dimensions with nine benchmarks. It uses objective measures, the Gini index for inequality, and a Large Language Model to analyze data and provide transparent advisory judgments, addressing a gap in current conflict resolution tools. AI
IMPACT This framework could improve fairness in team evaluations by providing objective, AI-driven insights into workload distribution and conflict.