My recent research projects employed rigorous literature and empirical and statistical examinations of automation transparency as a design principle. Automation transparency is a design principle consistently presented in the literature as a means to improve human performance with automated and autonomous systems, including Artificial Intelligence and Machine Learning. However, I have demonstrated little evidence that automation transparency is a generalizable principle. I am passionate about researching means to make Artificial Intelligence transparent and explainable to its users.
I designed, developed, and evaluated interactive data visualizations and graphical user interfaces for a machine learning-based decision support system for condition-based maintenance.
Meta-analysis of Automation Transparency
I conducted a meta-analysis of automation transparency to estimate the observed effects of transparency conditions/manipulations on human performance with greater statistical power than any one study offered.
Designing Visual Guides for Casual Listeners of Live Orchestral Music
We employed human-centred design techniques in iteration to improve the live classical music experience for casual listeners.