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Designing a conceptual framework for integrating explainable artificial intelligence into cognitive command and control systems: A Human-Centered DOODA-Based Framework
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Amin Amini *   , Mohsen Norouzi |
| Faculty of Artificial Intelligence and Cognitive Sciences, Imam Hossein University |
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Abstract: (10 Views) |
| The increasing complexity of operational environments and the growing adoption of Artificial Intelligence (AI) in Command and Control (C2) systems have intensified the need for transparency, trust, and cognitive alignment between human decision-makers and intelligent systems. Although Explainable Artificial Intelligence (XAI) has emerged as a promising approach for enhancing the transparency of AI-driven decision-making, a comprehensive evidence-based framework for integrating XAI into Cognitive Command and Control (C2) systems has not yet been established. This study aimed to develop a research-derived conceptual framework for integrating XAI into Cognitive C2 systems based on the DOODA cognitive decision cycle. A qualitative research design employing thematic analysis was adopted. Data were collected through semi-structured interviews and structured brainstorming sessions with experts in command and control, artificial intelligence, cognitive science, and intelligent decision-support systems. The data were analyzed following Braun and Clarke's thematic analysis approach, while the trustworthiness of the findings was ensured using Lincoln and Guba's criteria. The analysis identified five interrelated themes underlying the successful integration of XAI into Cognitive C2 systems: Situation Sensemaking, Planning and Decision-Making, Operational Execution, Cognitive Explainability, and Deployment Feasibility. These themes encompass operational, cognitive, and technological dimensions that were systematically mapped onto the stages of the DOODA cognitive cycle to construct the final conceptual framework. The proposed framework explains how XAI capabilities interact with human decision-makers throughout the cognitive decision process and demonstrates their contribution to enhanced situational awareness, improved decision quality, increased user trust, reduced cognitive workload, and greater operational effectiveness. The primary contribution of this study is the development of a research-derived conceptual framework grounded in empirical thematic evidence rather than solely theoretical assumptions. The proposed framework bridges the gap between the XAI and Cognitive C2 literature and provides practical guidance for designing, implementing, and evaluating next-generation intelligent decision-support systems operating in complex and dynamic environments. |
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| Keywords: Cognitive Command and Control, Decision Support, DOODA Loop, Explainable Artificial Intelligence (XAI), Human-Centered Design. |
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Full-Text [PDF 1631 kb]
(6 Downloads)
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Type of Study: Research |
Subject:
Artificial Intelligence
Received: 2026/06/26 | Accepted: 2026/10/5 | Published: 2026/10/11
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