Artificial intelligence is a concept that seems tailor-made for the intelligence community. The ability to sort through massive amounts of data, seeking out patterns large and small, anomalies that warrant further investigation, that's what intelligence analysts do already. Imagine what they could achieve when augmented by AI? Dean Souleles, chief technology advisor for the Office of the Director of National Intelligence, said on Agency in Focus – Intelligence Community that the IC is working now to lay the foundation for adopting AI. "You cannot build a house without a solid foundation. The foundation of AI is data and computational technology," Souleles said. "The intelligence community has spent much of the last decade on a program we call ICITE, the information technology enterprise of the IC. And that's been about modernizing the technology infrastructure. And that is about getting cloud technology throughout the community, making basic computational capability available to our technologists just as it is in the private sector. But that's not good enough, because the new era of computation requires sophisticated kinds of computing. We talk about GPUs, graphical processing units, or tensor processing units (TPUs), or neuromorphic chips or field programmable gate arrays, or any of the wide variety of things that are the specialized computation that enable AI computation. And we need to make the investments in those things."

Artificial intelligence is a concept that seems tailor-made for the intelligence community. The ability to sort through massive amounts of data, seeking out patterns large and small, anomalies that warrant further investigation, that's what intelligence analysts do already. Imagine what they could achieve when augmented by AI? Dean Souleles, chief technology advisor for the Office of the Director of National Intelligence, said on Agency in Focus – Intelligence Community that the IC is working now to lay the foundation for adopting AI. "You cannot build a house without a solid foundation. The foundation of AI is data and computational technology," Souleles said. "The intelligence community has spent much of the last decade on a program we call ICITE, the information technology enterprise of the IC. And that's been about modernizing the technology infrastructure. And that is about getting cloud technology throughout the community, making basic computational capability available to our technologists just as it is in the private sector. But that's not good enough, because the new era of computation requires sophisticated kinds of computing. We talk about GPUs, graphical processing units, or tensor processing units (TPUs), or neuromorphic chips or field programmable gate arrays, or any of the wide variety of things that are the specialized computation that enable AI computation. And we need to make the investments in those things."

AI and machine learning are all the rage across a range of technology and industrial sectors. Now, the U.S. military is gauging the prospects for leveraging machine learning and other tools in autonomous weapons via emerging human-machine interfaces. In describing the latest version of the Pentagon's "offset strategy," senior U.S. defense officials have in recent months highlighted the military's desire to leverage AI to develop autonomous weapons. That, Robert Work, deputy U.S. defense secretary, noted in a recent address, "is going to lead to a new era of human-machine collaboration and combat teaming. Added Work: "Collaboration is using the tactical acuity of a computer to help a human make better decisions and human-machine combat teaming is using manned and unmanned platforms." DoD's "offset strategy" refers to a blueprint designed to maintain technological superiority.

The investigation of the terrorist attack is a time-critical task. The investigators have a limited time window to diagnose the organizational background of the terrorists, to run down and arrest the wire-pullers, and to take an action to prevent or eradicate the terrorist attack. The intuitive interface to visualize the intelligence data set stimulates the investigators' experience and knowledge, and aids them in decision-making for an immediately effective action. This paper presents a computational method to analyze the intelligence data set on the collective actions of the perpetrators of the attack, and to visualize it into the form of a social network diagram which predicts the positions where the wire-pullers conceals themselves.