In daily life, individuals often make decisions that are influenced by incomplete information or the decisions of other individuals. Decision in the presence of incomplete information are frequently characterized by low confidence and errors, and group decision-making tends to outperform individual decisions, capitalizing on the 'wisdom of crowds'. Recent advancements explore the integration of Brain-Computer Interface (BCI) technology as a support system to improve group decision-making. Such systems combine inputs from multiple users to improve the overall decision quality. However, these systems are susceptible to performance degradation due to factors such as mental fatigue and disengagement.
This research project builds upon our team's expertise in computational modelling for decision-making and BCI-based decision support systems by developing a symbiotic decision support system that merges human judgement and autonomous AI to improve group decision-making, particularly in time-sensitive, complex scenarios. The autonomous AI will act as an equitable partner to human team members while simultaneously monitoring human performance.
This project will serve as a catalyst for future research in Human-Machine Teams and Neurotechnology to boost productivity in both public and commercial sectors.
The PhD candidate will benefit from the research centre’s expertise in Computational Neuroscience, Neurotechnology and AI, and state-of-the-art facilities in neuroimaging and high-performance computing, paving the way for promising and exciting opportunities in a career in AI, big data analytics and computational social science. The candidate will also interact with leading national and international collaborators. In 2021, Ulster University was ranked 2nd in the UK for Ph.D. researcher satisfaction, 6th largest Computer Science and Informatics unit, and 7th for the level of world-leading or internationally excellent research and impact with respect to staff number