论文标题
信念的动力：不断监视和可视化复杂系统
The dynamics of belief: continuously monitoring and visualising complex systems
论文作者
论文摘要
人工智能在人类背景下的兴起使对自动化系统的新需求是透明且可解释的。我们研究了一些与此类责任感相关的拟人化思想和原则，以开发一个理论框架，以思考复杂人类环境中的数字系统以及解释其行为的问题。从结构上讲，系统由模块化和层次组件制成，我们使用模式和模式过渡的概念在新的系统模型中抽象。模式是系统的独立组件，具有自己的目标，监视数据和算法。模式的行为，包括其向其他模式的过渡，由根据其目标和算法来解释每个模式监视数据的函数。我们展示了这些信念功能如何通过将其评估视为高维几何空间中的轨迹来帮助解释系统行为。这些想法是通过抽象和具体的简单复合物在数学上正式化的。我们提供三种技术：设计启发式方法的框架，基于模式的一般系统理论以及几何可视化，并将它们应用于三种类型的以人为中心的系统中。
The rise of AI in human contexts places new demands on automated systems to be transparent and explainable. We examine some anthropomorphic ideas and principles relevant to such accountablity in order to develop a theoretical framework for thinking about digital systems in complex human contexts and the problem of explaining their behaviour. Structurally, systems are made of modular and hierachical components, which we abstract in a new system model using notions of modes and mode transitions. A mode is an independent component of the system with its own objectives, monitoring data, and algorithms. The behaviour of a mode, including its transitions to other modes, is determined by functions that interpret each mode's monitoring data in the light of its objectives and algorithms. We show how these belief functions can help explain system behaviour by visualising their evaluation as trajectories in higher-dimensional geometric spaces. These ideas are formalised mathematically by abstract and concrete simplicial complexes. We offer three techniques: a framework for design heuristics, a general system theory based on modes, and a geometric visualisation, and apply them in three types of human-centred systems.
