Build competency aware and assuring machine learning systems

机器学习（ML）的最新发展使ML模型具有极高的预测精度。然而，为了在复杂环境中支持人机合作决策，除了准确性之外，机器学习系统必须具有能力意识和可靠性，同时具有探索性。该项目旨在开发新技术，使机器学习系统具备识别自身能力、证明其能力和决策的能力、探索未知情况并充分利用现有专业知识来处理未知情况的能力。该项目的预期结果将使机器学习系统在广泛的应用中成为人类决策者的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.