As artificially intelligent agents become integrated into various sectors, they require
an analysis of their capacity to make moral decisions and of the influence of human
supervision on their performance. This study investigates the impact of textual feature
explanations on human supervision and the trust in a semi-autonomous firefighting
robot named Brutus, which operates in a morally complex environment. Grounded in
the field of Explainable AI (XAI), which seeks to render AI decisions transparent, this
research compares textual and visual explanations’ effectiveness in conveying situational
sensitivity during a simulated rescue operation. Through a detailed experimental setup
using the MATRX software to simulate a burning office building, participants’ trust
and understanding were assessed based on their interaction with Brutus using either
textual or visual explanations. This study contributes to the broader discourse on
AI ethics and the optimization of human-agent teaming in high-stakes scenarios. The
findings suggest that textual explanations can enhance human supervision and trust,
fostering greater engagement and satisfaction compared to visual explanations.