UGC Approved Journal no 63975(19)
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ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 2 | February 2026

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Published in:

Volume 10 Issue 12
December-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2312786


Registration ID:
547423

Page Number

h691-h709

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Title

Explainable AI in National Security: Enhancing Trust and Accountability

Authors

Abstract

AI applications in national security have become one of the key drivers of modern defense and law enforcement because they improve operation efficiency, decision-making, and threat identification. However, this has led to new questions as to the responsibility and explainability of these decisions by AI-based systems in sensitive or high-risk environments. Thus, this article discusses how explainable AI (XAI) can mitigate such issues in various applications of national security. XAI means AI systems that can explain all of their decision-making processes and actions clearly, coherently, and as comprehensively as possible for a human operator. In national security, where decisions that can have significant consequences are made, XAI makes AI processes accurate, explainable, and defensible. The article specifically explains how XAI can enhance trust and accountability in various national security domains such as intelligence analysis, threat assessment, autonomous systems, and cybersecurity. Through the information XAI provides about how it arrived at its conclusions, human operators and stakeholders can review, affirm, or question the actions of AI-driven decisions, reducing the chances of making wrong, biased, or incorrect decisions or causing negative consequences. Additionally, the integration of XAI in national security makes people trust the surmises made by artificial intelligence because such decisions strictly correlate with legal, ethical, and practical requirements. The article also discusses some technical and practical concerns with the application of XAI in national security, which includes the issue of balancing between explainability and security, as well as the application requirements in the form of trainings for the defense and law enforcement agencies. Lastly, the article presents targeted suggestions for how to apply XAI to Neuro-Symbolic Computing (NSC), particularly to build a common mission between the producers of AI technologies, the lawmakers, and security agencies to guarantee that big and sophisticated AI systems are not just highly useful and effective but also (and no less so) open, responsible, and compliant with justice and human rights.

Key Words

Artificial Intelligence, National security, AI in Defense, AI in Law enforcement, Ethical AI, Defense Operations, Defense Technology, AI Risk management

Cite This Article

"Explainable AI in National Security: Enhancing Trust and Accountability", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.h691-h709, December-2023, Available :http://www.jetir.org/papers/JETIR2312786.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Explainable AI in National Security: Enhancing Trust and Accountability", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. pph691-h709, December-2023, Available at : http://www.jetir.org/papers/JETIR2312786.pdf

Publication Details

Published Paper ID: JETIR2312786
Registration ID: 547423
Published In: Volume 10 | Issue 12 | Year December-2023
DOI (Digital Object Identifier):
Page No: h691-h709
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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