There is no one-size-fits-all answer to this question, as the most effective way to use AI to identify terrorist threats will vary depending on the specific context and application. However, some potential ways to use AI for this purpose include using machine learning algorithms to automatically analyze large volumes of data (including text, images, and video) for patterns that may indicate terrorist activity; using natural language processing (NLP) to automatically extract information from unstructured text sources (such as social media posts) that could be useful for detecting and stopping terrorist attacks; and deploying automated systems that can monitor for and flag suspicious activity (such as unusual travel patterns or strange behavior) in real-time.
In general, the most successful AI-based systems for detecting and stopping terrorist threats will likely be those that are able to effectively combine multiple data sources and AI techniques. For example, a system that is able to automatically analyze both text and video data sources using NLP and machine learning may be more effective than one that only analyzes text. Similarly, a system that incorporates real-time monitoring of suspicious activity along with historical data analysis may be more effective than a system that only relies on one of these approaches.
References:
https://www.NCBI.NLM.NIH.gov/pubmed/29136358
https://link.springer.com/article/10.1007/s10458-017-9358-8
https://www.usna.edu/Users/cs/nswyllie/classes/ic221/s12/lec15.pdf
https://www.aclweb.org/anthology/D14-1181.pdfhttps://ieeexplore.ieee.org/document/7817328
https://www.researchgate.net/publication/321084073_The_counter-terrorism_role_of_artificial_intelligence_A_state_of_the_art_review