This chapter provides an in-depth examination of the current use of artificial intelligence (AI) in military training applications, with a specific focus on the importance of explainability in these systems. The chapter begins by introducing the concept of AI in military training and discussing the challenges that come with building complex and efficient systems that can explain their decision-making processes. The chapter emphasizes the significance of explainability in military training applications, explaining how it enhances trust, transparency, and accountability. Furthermore, the chapter discusses the use of explainable AI in military simulations and presents a case study that demonstrates how it can be used to improve military training simulations and enhance decision-making in real-life scenarios.
Top1. Introduction
As figure 1.0, illustrates, the Artificial Intelligence encompasses several elements viz., machine learning (Mankodiya, Obaidat, Gupta, & Tanwar, 2021; S. Saeed, Abdullah, Jhanjhi, Naqvi, & Humayun, 2020; Umer), cognitive computing (Ettazi & Nassar, 2023; Mi, Quan, Shi, & Wang, 2022; Muhammad & Shamim Hossain, 2023; Usmani et al., 2020; Wu, Liu, & Wang, 2022), deep learning (Gaur, Arora, & Jhanjhi, 2022; Suri et al., 2023), neural networks (Humayun, Sujatha, Almuayqil, & Jhanjhi, 2022; Joshi, Walambe, & Kotecha, 2021; Kohlbrenner et al., 2020; Seo, Oh, & Oh, 2020) and Natural Language Processing (Ko, David Jeong, & Lee, 2023; Liddy, 2001; F. Wang, Gu, Bai, & Bian, 2023; YU, 2023).
A country's position on the global stage is largely influenced by its military potential. In recent times, Artificial Intelligence (AI) (Gaur, Arora, et al., 2022; Hanif et al., 2022) has been increasingly utilized in military training, facilitating simulations, decision support systems, and autonomous vehicles (Bistron & Piotrowski, 2021). However, the lack of transparency and accountability in AI decision-making has raised concerns (Mahmood et al., 2021). This is especially worrisome when such decisions have the potential to drastically alter lives. As a result, Explainable AI (XAI) has emerged (Srivastava et al., 2022), which aims to create AI systems that can be understood and interpreted by humans. In the realm of military training, XAI is of utmost importance as it can aid soldiers and commanders in making well-informed decisions and enhance the effectiveness and safety of military operations (Montasari, 2023b). XAI can provide insights into the factors considered by AI systems when making decisions (Adadi & Berrada, 2018), enabling military personnel to trust the outputs of these systems.
The assessment of military capability involves multiple factors, including structure, readiness, sustainability, and modernization (Luo & Zhou, 2021). Modernization, which encompasses technical advancements, weapon systems, and equipment contributing to overall military capability (W. Wang, Liu, Lin, Chen, & Yang, 2020). The implementation of XAI in military training presents several challenges, such as designing AI models that maintain both accuracy and transparency (Yu, 2023). Military operations are complex and constantly changing, making it difficult to explain how an AI system is making decisions in real-time (Vijayalakshmi et al., 2021). Despite these obstacles, significant progress has been made in XAI for military training (Demertzis et al., 2023). Researchers have developed techniques that use visualizations to explain an AI system's decision-making process, including data processing, pattern recognition, and prediction (Mahmood et al., 2021). In addition, the development of XAI models (Gaur, Jhanjhi, Bakshi, & Gupta, 2022; Luo & Zhou, 2021) that can be retrained using new data has resulted in more accurate and transparent AI systems. Ultimately, XAI is a vital advancement in ensuring the effectiveness and safety of military operations. Despite ongoing challenges, continued advancements in XAI techniques and models will lead to more trustworthy and transparent AI systems (Srivastava et al., 2022; Taj & Zaman, 2022).