FST.ai 2.0用AI实时辅助跆拳道判罚，提升公平性与透明度。
FST.ai 2.0: An Explainable AI Ecosystem for Fair, Fast, and Inclusive Decision-Making in Olympic and Paralympic Taekwondo
- 基于图卷积网络的姿势动作识别，结合可信度建模实现可解释判断。
- 决策审查时间减少85%，裁判对AI决策信任度达93%。
- 适合裁判培训、赛事公平监控及残奥跆拳道分级参考。
公平、透明且可解释的决策在奥运会和残奥会格斗项目中仍面临重大挑战。本文提出FST.ai 2.0，一个面向跆拳道比赛与训练的可解释AI生态，支持裁判、教练与运动员实时决策。系统融合基于姿态的动作识别（采用图卷积网络），通过置信集建模认知不确定性，并提供可视化可解释性叠加。交互式仪表板支持人机协同，涵盖裁判评估、运动员表现分析与残奥跆拳道分级。除自动计分外，系统还集成裁判培训、公平性监测与政策级分析模块，嵌入世界跆拳道体系。在真实赛事数据上的实验表明，决策审查时间减少85%，裁判对AI辅助决策的信任度达93%。该框架构建了可信赖、数据驱动的裁判与评估流水线，实现了感知、解释与治理设计的融合，推动体育中公平、负责且以人为本的AI发展。
原文摘要 · Abstract (English)
Fair, transparent, and explainable decision-making remains a critical challenge in Olympic and Paralympic combat sports. This paper presents \emph{FST.ai 2.0}, an explainable AI ecosystem designed to support referees, coaches, and athletes in real time during Taekwondo competitions and training. The system integrates {pose-based action recognition} using graph convolutional networks (GCNs), {epistemic uncertainty modeling} through credal sets, and {explainability overlays} for visual decision support. A set of {interactive dashboards} enables human--AI collaboration in referee evaluation, athlete performance analysis, and Para-Taekwondo classification. Beyond automated scoring, FST.ai~2.0 incorporates modules for referee training, fairness monitoring, and policy-level analytics within the World Taekwondo ecosystem. Experimental validation on competition data demonstrates an {85\% reduction in decision review time} and {93\% referee trust} in AI-assisted decisions. The framework thus establishes a transparent and extensible pipeline for trustworthy, data-driven officiating and athlete assessment. By bridging real-time perception, explainable inference, and governance-aware design, FST.ai~2.0 represents a step toward equitable, accountable, and human-aligned AI in sports.
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