Enhancing the United States Counterterrorism Policy through Artificial Intelligence: A Comprehensive Analysis of Machine Learning Applications, Challenges, and Strategic Implications

Abstract

The upcoming implementation of the artificial intelligence (AI) technologies in counter terrorism activities is an innovation that seems to change the game in the national security strategy, providing an incredible potential in terms of threats detection, analysis, and response. This paper focuses on discussing the current capability and future prospects of AI-augmented counter terrorism policy in the United States, looking at applications of machine learning in the detection of online extremism as well as predictive analytics and automatic threat evaluation. In a broad survey of the empirical research and case studies, i discuss the efficiency of AI systems that consider terrorist actions, the ethical and privacy issues of automatic surveillance, and the strategic areas of concern that policymakers have to face. The discussion shows that although AI technologies can play a substantial role in the large-scale data analysis and pattern-recognition in regards to radicalization processes, its application leads to many civil liberties, bias in algorithms, and infringement of privacy and security concerns. The results indicate that to effectively implement AI in the policy of countering terrorism, highly structured forms of governance, multidisciplinary cooperation and regular assessment of technological strengths and weaknesses must also be considered.