Trust has been realised as one of the most important factors in management and organisational behaviour for all personal and business decision making as well as for efficiency and task performance. It is also found to be a critical factor driving human behaviour in human-machine interactions with automation systems in modern complex high-risk domains such as aviation, and the military command and control. This project aims to develop automatic, real-time, and implicit methods of assessing human-machine interactions and analysing multimodal and social behavioural features to provide dynamic measure of trust and to perform uncertainty-aware trust calibration. The research outcomes will help achieve some adaptive system response according to users’ current trust perception as a strategy to improve the user’s trust and the effectiveness of communication between the user and the system. This will help improve their overall system interaction experience, task performance, and decision making.
People: Fang Chen, Jianlong Zhou, Kun Yu, Dan Conway, Ahmad Khawaji, Yang Wang