In this project, I designed and developed interactive data visualizations and graphical user interfaces for a machine learning-based decision support system for condition-based maintenance. This system was used as a testing platform in two experiments with human participants.

I used this platform to conduct a controlled experiment with 24 participants to evaluate the impact of automation transparency and explainability on human decision-making performance, reliance, and trust. 

The results found no evidence to corroborate the common belief that presenting a rationale for an automated output will positively impact automation reliance and efficacy.