标题： FST.ai 2.0：面向奥运会和残奥会跆拳道公平、快速和包容性决策的可解释人工智能生态系统 显示英文标题

标题： FST.ai 2.0: An Explainable AI Ecosystem for Fair, Fast, and Inclusive Decision-Making in Olympic and Paralympic Taekwondo

摘要： 公平、透明和可解释的决策仍然是奥林匹克和残奥会格斗运动中的一个关键挑战。 本文介绍了 \emph{FST.ai 2.0}，一个可解释的人工智能生态系统，旨在实时支持跆拳道比赛和训练中的裁判、教练和运动员。 该系统集成了 {基于姿态的动作识别}使用图卷积网络（GCNs），{认识不确定性建模}通过credal集，以及 {可解释性叠加}用于视觉决策支持。 一组 {交互式仪表板}使得人在AI协作中进行裁判评估、运动员表现分析和残疾人跆拳道分类。 除了自动评分外，FST.ai~2.0 还在世界跆拳道生态系统内集成了裁判培训、公平性监控和政策级分析模块。 在竞赛数据上的实验验证表明，AI辅助决策具有 {决策评审时间减少85%}和{93％审稿人信任}。 因此，该框架建立了一个透明且可扩展的流程，用于值得信赖的数据驱动的裁判和运动员评估。 通过弥合实时感知、可解释推理和治理意识设计， FST.ai~2.0 代表了在体育领域实现公平、负责和与人类一致的AI的一个步骤。 显示英文摘要

摘要： 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.