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26 November 2020

King's expertise in causal reasoning furthering research in Trusted Autonomous Systems

Researchers in King’s Software Systems Group and Trusted Autonomous Systems hub are furthering contribution towards the UKRI Trustworthy Autonomous Systems hub by honing a focus on causal reasoning.


Led by the University of Edinburgh and together with other academic and external project partners, King’s research will contribute towards the Governance and Regulation Research Node of the UKRI Trustworthy Autonomous Systems (TAS) hub.

King’s is bringing an expertise in causal reasoning and the applications of causal reasoning to the complex interactions between human, institutional and technical factors. King’s research leads pillar 2 of the TAS Governance and Regulation Research Node, which provides a novel modelling framework and tools to help regulators and developers consider chains of causal factors leading to unexpected or undesired outcomes in autonomous systems.

Dr Hana Chockler, Reader in Computer Science at King’s Department of Informatics, is leading the research from King’s. Commenting on the impact that this research will have, she said:

The main impact of the research in pillar 2 of the project is envisioned to be introducing structural causal reasoning to the legal domain and policy making. Measurable and computable responsibility for different outcomes of complex interactions will provide a basis for more informed decisions that affect governance and will allow the regulators to predict the effect of changes.

Dr Hana Chockler

This project is part of the UKRI Trustworthy Autonomous Systems (TAS) programme, funded through the UKRI Strategic Priorities Fund and delivered by the Engineering and Physical Sciences Research Council (EPSRC). The TAS programme brings together research communities and key stakeholders to drive forward cross-disciplinary, fundamental research to ensure that autonomous systems are safe, reliable, resilient, ethical and trusted.

In this story

Hana Chockler

Reader in Computer Science