With the recent advances in machine learning, especially deep learning, we have witnessed increasing applications of AI in various domains. The past few years have seen a growing interest towards more explainable machine learning systems.
At HKUST VisLab, we focus on human-centered approaches to make AI explainable, interactive, and trusworthy. In critical domains such as finance, security, and healthcare, explanability allows us to make more reliable decisions powered by the collaboration of machine- and human-intelligence. Interactivity makes the exploration, creation, and customization of AI at ease. With XAI, it is easier to build trustworthy AI solutions: we trust its performance, know when and where it is possible to fail, and can decide whether the AI solution meets our needs.