Research output per year
Research output per year
PhD student in Explainable AI for Black Box Autonomous Agents.
My research explores how we might begin to understand and explain the policies of black box autonomous agents, whose internal mechanisms and representations may be very different from our own, with a particular view to revealing the biases and flaws in their decision-making. Critical to this question are the putative trade-off between comprehensibility and performance of machine learning models, and the thorny relationship between correlation and causation in observed data whose generative origins are unknown.
Research output: Contribution to conference › Conference Paper › peer-review
Research output: Contribution to conference › Conference Paper › peer-review
Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)