With the proliferation of the Large Language Model (LLM), the concept of World Models (WM) has recently attracted a great deal of attention in the AI research community, especially in the context of AI agents. It is arguably evolving into an essential foundation for building AI agent systems. A WM is intended to help the agent predict the future evolution of environmental states or help the agent fill in missing information so that it can plan its actions and behave safely. The safety property of WM plays a key role in their effective use in critical applications. In this work, we review and analyze the impacts of the current state-of-the-art in WM technology from the point of view of trustworthiness and safety based on a comprehensive survey and the fields of application envisaged. We provide an in-depth analysis of state-of-the-art WMs and derive technical research challenges and their impact in order to call on the research community to collaborate on improving the safety and trustworthiness of WM.

本研究针对当前世界模型（WM）技术在安全性和可信度方面的不足进行分析，强调了其在构建AI代理系统中的重要性。通过深入审查当前技术和应用领域，本文揭示了技术研究挑战，并呼吁研究界合作提升WM的安全性和可信度。研究表明，WM的安全属性对其在关键应用中的有效使用至关重要。

世界模型：安全视角