Explainable AI for Human Supervision over Firefighting Robots
How Do Textual and Visual Explanations Affect Human Supervision and Trust in the Robot?
B.C. Pietroianu (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M.L. Tielman – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
R.S. Verhagen – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
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.