We envision a new research direction in AI for health to foster a transformative human centric paradigm, in which an emerging collaborative relationship between computers and humans will be created based on the ever-increasing power of AI. The computers will no longer just be used as tools, but instead act actively as a co-worker to offer sound, clear and evidence-based solutions to support clinicians and patients in clinical decision making and enhance clinical outcome.
We are working on the intersection of machine learning and task planning with the goal of developing long-life autonomous systems that are robust and trusted. As these systems become more complex, they become more opaque to non-expert users. Our vision is to develop novel approaches to intelligent control that are capable of reacting robustly and safely in dynamic and challenging environments, explaining their behaviour, and working within mixed teams of humans and machines.
We are looking at how artificial intelligence techniques can be used to support the process of software engineering with the aim of creating systems that are robust, reliable and adaptable. We are also looking at the converse problem of how AI systems should be engineered, which is particularly important as AI technologies are becoming commonly deployed in critical situations.