We’re delighted to invite you to a seminar by STAI CDT alumni, Dr Fabrizio Russo and chaired by Dr Odinaldo Rodrigues. Part of the UKRI Centre for Doctoral Training (CDT) in Safe and Trusted Artificial Intelligence (STAI) seminar series.
Causal Discovery for Trustworthy Artificial Intelligence
Artificial Intelligence (AI) is increasingly deployed in high-stakes domains such as healthcare, finance, and public policy, where decisions have far-reaching societal consequences. Ensuring trust in these systems requires moving beyond opaque, pattern-driven predictions to methods that are both effective and interpretable, while aligning with expert knowledge. Causal discovery, which uncovers cause-and-effect relationships from data and represents them as graphs, plays a central role in achieving these goals as a foundation for trustworthy AI.
This talk will introduce the methodologies that I proposed in my thesis, specifically: Contestable Neural Networks, Shapley-PC and Argumentative Causal Discovery. Together, these contributions firmly position causal discovery as a cornerstone for trustworthy AI. By aligning data-driven insights with expert input, improving reliability, and ensuring transparency, this work lays a solid foundation for AI decision-making in high-stakes domains.