Date of Award
2025
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Committee Chair
Vineetha Menon
Committee Member
Jacob Hauenstein
Committee Member
Bryan Mesmer
Research Advisor
Vineetha Menon
Subject(s)
Artificial intelligence, Augmented reality, Human-computer interaction, Explainable AI (XAI)
Abstract
Artificial Intelligence (AI) is increasingly deployed in high-stakes environments where success depends on more than computational accuracy; it also requires alignment with human perception and attention. Traditional explainable AI (XAI) methods provide static, post-hoc justifications that are poorly suited to time-critical decision cycles. This thesis investigates whether perceptually aligned, real-time explanations in Augmented Reality (AR) can enhance performance, workload balance, and trust within the Observe–Orient–Decide–Act (OODA) loop. A custom AR search-and-rescue simulation tested three conditions: no assistance, static overlays, and perceptually aligned explanations using adaptive cues such as occlusion-aware tethers and urgency-based visuals. The results show that any explanation improved results compared to no support, with perceptually aligned explanations producing the strongest gains: accelerating rescue performance, improving attentional alignment, reducing cognitive inefficiencies and fostering calibrated trust without distraction. These findings advance an OODA-centric framework for XAI and demonstrate that explanations can serve as active perceptual supports rather than passive rationalizations. The work contributes design principles for AR-enabled XAI systems that integrate objective, subjective, and physiological evidence to improve human performance in mission-critical contexts.
Recommended Citation
Wright, Dylan, "Augmenting attention : an OODA-centric framework for explainable AI in AR human-AI teaming applications" (2025). Theses. 790.
https://louis.uah.edu/uah-theses/790