Explainable Artificial Intelligence (XAI) is a topic receiving close review and increasing interest 
across different fields. Crucial to explainability is understanding of cause-effect relationships which in 
complex intelligent systems are anything but clear. Lack of ability to present the rationale behind a 
decision making process inevitably mines trust and introduces uncertainty with respect to 
accountability of consequences. 

The proposed research program will focus on the creation of a theoretical and applied framework to 
support the creation of systems to help people interpret the reasoning behind decisions made by AI 
systems. The project will entail design, implementation, and testing of visualization interfaces 
connecting to and integrating with explainable intelligent systems designed by partners. 

This project places itself across three different fields: visual analytics, human-computer interaction, 
and artificial intelligence. 

Hub relevance: Autonomous Systems
informatics-phd-projects-2022-23