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| Format: | Recurso digital |
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Zenodo
2023
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| Online Access: | https://doi.org/10.5281/zenodo.18397334 |
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Table of Contents:
- Explainable artificial intelligence (XAI) is becoming increasingly crucial in intelligence analysis as it addresses key ethical, legal, and security concerns such as transparency, accountability, and trust. This paper presents a systematic review of the literature on XAI in intelligence analysis and sheds light on the challenges and limitations of AI in this field. It also details the current state of XAI and various techniques used to make AI systems more explainable. The study evaluates existing research on XAI for intelligence analysis, identifies areas for future research, and discusses the implications of the results. Notably, the systematic review of academic and professional literature was conducted using several databases such as Google Scholar, IEEE Xplore, ACM Digital Library, and Scopus. It was limited to articles published between 2019-2023. The results emphasize the significance of a multidisciplinary approach to the development and application of XAI in intelligence analysis.