The successful candidate will join a team of talented research associates and investigators to work on an innovative EPSRC/UKRI funded project THuMP: Trust in Human-Machine Partnerships. This post is focussed particularly on data visualisation and interface development for explainable AI (XAI). THuMP is a multi-disciplinary project, with the ambitious goal of advancing the state-of-the-art in trustworthy human-AI decision-support systems.
THuMP will address the technical challenges involved in creating Explainable AI (XAI) systems, with a focus on Visualization for Explainable Planning and Argumentation, so that people using the system can better understand the rationale behind and trust suggestions made by an AI system. This project is conducted in collaboration with three project partners: Schlumberger and Save the Children, which provide use cases for the project, and a law firm who will cooperate in considering legal implications of enhancing machines with transparency and the ability to explain.
The candidate will be responsible for conducting research around the interfaces to support explainability in the context of decision making in human-machine partnerships. Tasks will involve: building an interaction infrastructure for the project; developing a prototype interface for communicating with users; designing new visual layouts for systems and designing and conducting experiments with human subjects based on the use cases co-created with the project partners.