Thesis Title
Enhancing the Reviewability of Automated Decision-making systems Under Australia’s Judicial Review Framework: “The Answer to the Machine is in the Machine”

Research Description
Rhyle’s primary research interests lie at the intersection of public law, data science and automated decision-making. His PhD research seeks to understand how machine learning systems might be made safe for use in administrative decision-making. He particularly focuses on exploring how emerging machine learning techniques, including those arising from the Fairness, Accountability and Transparency (FAccT) scholarship, might be used to inform the future development of administrative law doctrine.

Assoc Prof Anna Huggins, Queensland University of Technology
Prof Nicolas Suzor, Queensland University of Technology
Prof Kylie Pappalardo, Queensland University of Technology