Build competency aware and assuring machine learning systems

在机器学习(ML)的最新发展中，ML模型具有极高的预测精度。然而，为了支持人机伙伴关系在复杂环境中的决策，除了精确度之外，ML系统必须具有能力意识和可靠性，同时还必须具有探索性。该项目旨在开发新的技术，使ML系统能够识别自己的能力，证明其能力和决策的合理性，探索未知的情况，并充分利用现有的专业知识处理未知的问题。该项目的预期结果将使ML系统成为人类决策者在广泛应用中真正智能和可靠的机器合作伙伴。

Recent development in machine learning (ML) has seen ML models with extremely high prediction accuracy. However, to support human-machine partnership in decision-making in complex environments, beyond accuracy, it is essential for ML systems to be competency aware and reliable, and at the same time be exploratory. This project aims to develop novel techniques to equip a ML system with the ability to identify own competency, to justify its competency and decisions, to explore unknown situations and fully utilise existing expertise to deal with unknowns. The expected outcomes of the project will enable ML systems to become truely intelligent and reliable machine partners for human decision makers in a wide range of applications.