Artificial Intelligence (AI) is expected to play a key role in 6G networks including optimising system management, operation, and evolution. This requires systematic lifecycle management of AI models, ensuring their impact on services and stakeholders is continuously monitored. While current 6G initiatives introduce AI, they often fall short in addressing end-to-end intelligence and crucial aspects like trust, transparency, privacy, and verifiability. Trustworthy AI is vital, especially for critical infrastructures like 6G. This paper introduces the REASON approach for holistically addressing AI's native integration and trustworthiness in future 6G networks. The approach comprises AI Orchestration (AIO) for model lifecycle management, Cognition (COG) for performance evaluation and explanation, and AI Monitoring (AIM) for tracking and feedback. Digital Twin (DT) technology is leveraged to facilitate real-time monitoring and scenario testing, which are essential for AIO, COG, and AIM. We demonstrate this approach through an AI-enabled xAPP use case, leveraging a DT platform to validate, explain, and deploy trustworthy AI models.

翻译：人工智能（AI）预计将在6G网络中发挥关键作用，包括优化系统管理、运营与演进。这需要对AI模型进行系统化的全生命周期管理，确保其服务影响与利益相关方影响得到持续监控。尽管当前6G研究已引入AI技术，但在实现端到端智能化及解决信任、透明度、隐私与可验证性等关键维度方面仍存在不足。可信AI对6G等关键基础设施尤为重要。本文提出REASON方法，以整体性视角解决未来6G网络中AI的原生集成与可信性问题。该方法包含三个核心模块：负责模型生命周期管理的AI编排（AIO）、执行性能评估与可解释性分析的认知模块（COG），以及实现追踪与反馈的AI监控（AIM）。研究通过数字孪生（DT）技术实现实时监控与场景测试，为AIO、COG和AIM提供支撑。我们通过AI增强型xAPP应用案例，借助DT平台验证、解释并部署可信AI模型，展示了该方法的有效性。