Commentary: Data, AI, and the Future of U.S. Counterterrorism: Building an Action Plan.

• Author: Rassler, Don

The United States has collected petabytes of data relevant to counterterrorism and the study of terrorism over the past 20 years. (1) The amalgamation and analysis of data led the United States to Usama bin Ladin's hideout in Abbottabad, Pakistan. Innovations in how the United States processed and fused information and made data actionable has also been one of the most important and game-changing achievements of the United States' two-decade long war on terrorism. (2) Indeed, the tactical and operational counterterrorism successes that the United States and its partners have accomplished since 9/11 is a story intimately tied to how analysts and practitioners have exploited data to better understand and degrade terror networks.

The United States has shifted its strategic emphasis and focus to address the rise of, and threats posed by, China and Russia, a transition that is needed and overdue. Yet, despite the United States' desire to put terrorism in the rear or side view mirror, terrorism is not going away anytime soon. The threats posed by transnational groups like al-Qa'ida and the Islamic State, key militant Iranian proxies, and other networks--to include a diverse mix of domestic extremists in the United States--will evolve and continue to manifest in one dangerous form or another. There is also a real risk, due to the enduring nature of the terrorism threat, that the manner of America's terrorism pivot could end up complicating the United States' ability to maintain its near-peer focus. This is because while the United States has moved on to other priorities, core U.S. terror adversaries have not, and they like to disrupt and spoil. Indeed, as Brian Michael Jenkins has noted in this publication, "Events, not plans or preferences, will determine how much the United States will be able to shift or not shift resources away from counterterrorism and toward near peer competition." (3)

Much is riding on how the United States balances and manages these two national security priorities--counterterrorism and nearpeer competition--in practice, as in the years and decades ahead the United States is going to need to be able to deal with both challenges and do so simultaneously, and well. It needs to get better at both.

Data, and what the United States does with data, will be a central part of that future. The United States recognizes that data is a strategic asset (a) and that data science-informed approaches and artifcial intelligence (AI)--like electricity--"holds the secrets

Don Rassler is an Assistant Professor in the Department of Social Sciences and Director of Strategic Initiatives at the Combating Terrorism Center (CTC) at the U.S. Military Academy. His research interests are focused on how terrorist groups innovate and use technology; counterterrorism performance and the evolution of counterterrorism practices and strategy; and understanding the changing dynamics of militancy in select countries in Asia. Twitter: @DonRassler

The views expressed in this article are the author's and do not necessarily reffect those of the Combating Terrorism Center, United States Military Academy, Department of Defense, or U.S. Government. which will reorganize the life of the world." (4) (b) For the past several years, the United States has been making big moves to adjust, adapt to, and prepare for the coming AI-driven future, and to position itself to lead. One only needs to look at the mix of national-level to agency-specific AI strategy documents and plans, (5) hefty financial investments (c) and organizational adaptations made to drive and scale AI initiatives, (6) and the testing and operational application of machine learning (ML)/AI approaches (7) to see that the large, 'sea tanker-like bureaucracy' of the U.S. government is in the process of making an important strategic pivot. (d)

A high-level overview of recent changes that have taken place within the Department of Defense (DoD) is instructive. (e) Since 2018, for example, the DoD has released its artifcial intelligence strategy (2018), digital modernization strategy (2019), and data strategy (2020). In 2018, the Defense Advanced Research Project Agency (DARPA) announced a "multi-year investment of more than $2 billion in new and existing programs called the 'AI Next' campaign" with emphasis placed on key areas. (8) In 2018, these efforts and investments were given added organizational structure and form through the creation of the DoD's Joint Artificial Intelligence Center (JAIC), an entity established to be the focal point for carrying out DoD's AI Strategy. (9) That same year, U.S. Special Operations Command (SOCOM) made a similar organizational move through the establishment of its Command Data Ofce, designed "to oversee ... workforce transformation, as well as provide a node for industry outreach, data governance, and application of a data-focused perspective to capability development decision-making processes." (f) The Defense Innovation Unit has been active in "pursuing a number of AI projects to optimize business processes in the DoD" as well. (10)

The JAIC, SOCOM, and the National Media Exploitation Center (NMEC) have also played critical roles in operationalizing 'big data' through AI and ML approaches. (11) When it comes to counterterrorism, a seminal example is Project Maven, a "pathfinder effort" to employ AI and ML "in the fight against ISIS, al-Qaeda, and their geographically dispersed proxies." (12) As noted by the scholar Richard Shultz and SOCOM Commander General Richard Clarke, Project Maven's initial objective was "to automate the processing, exploitation, and dissemination of massive amounts of full-motion video collected by intelligence, surveillance, and reconnaissance (ISR) assets." (13) This was achieved through the utilization of "specially trained algorithms," which "could search for, identify, and categorize objects of interest in massive volumes of data and fag items of interest." (14)

These moves are important signs of momentum and advancement. The data and AI strategy documents and plans that the U.S. government has released provide the broad framework for how it intends, or hopes, to move forward in the data and AI arena. And that has been complemented by vision offered by seasoned practitioners like former head of the Defense Intelligence Agency Lieutenant General (Ret) Robert Ashley for where these changes should, or are likely, to lead. For example, according to Ashley, in the future "Leveraging data from captured enemy material, applying machine learning and computer vision against petabytes of publicly available information, embracing open-source intelligence and open architectures should be a routine part of every military operation going forward." (15) But as the United States looks forward and works through how to 'right size' counterterrorism, (16) it also needs a more defned plan for how it intends to utilize, integrate, and more fully leverage the petabytes of terror and counterterrorism data it has collected, collated, and created over the past 20 years. Those vast quantities of data are an incredible resource--a strategic asset that if leveraged in smart and strategic ways will help the United States to continue to learn and transfer knowledge across generations, track future terror developments, identify new counterterrorism opportunities, and gain analytical efficiencies.

There are two primary reasons why such a new terrorism and counterterrorism data action plan is needed and should be developed and resourced. Like other domains, counterterrorism is evolving into a means of geopolitical infuence that states, including the United States and its near-peer rivals, have been competitively using to develop relationships and to secure defense-related access and placement. And while counterterrorism assistance to foreign partners usually revolves around hardware, training, and financial assistance, the parties that will evolve and lead the counterterrorism field over the next decade are those actors who possess the 'best' data and who are able to make most effective use of that data. General (Ret) Joseph Votel, the former commander of U.S. Central Command, highlighted this point in a recent interview in this publication: "I do think the future will be dominated by those who understand it [data] the best, whether it is through publicly available information sources, managing large data, or whether it is the ability to see and understand what is happening in areas so that it preserves our decision space and informs our policy choices." (17)

A new terrorism and counterterrorism data action plan is also needed for efficiencies' sake. For if the United States wants to focus less on terrorism and more on China and other strategic competitors, it needs to find areas where efficiencies can be gained in the processing, analysis, and use of terrorism-related data through deeper focus on data science-informed approaches and investment in and broader experimentation and adoption of ML and AI. This article is designed to help shape the conversation of how this can be done.

The piece starts by unpacking in greater detail why such a new terrorism and counterterrorism data action plan is needed. The article is then organized around five recommended focus areas (in addition to other priorities) that deserve attention and emphasis as part of that plan. There is a need to: 1) reinvest in and advance core terrorism data, 2) strategically leverage captured material, 3) better develop and utilize counterterrorism data, 4) practice data alchemy, and 5) automate basic and other analytical tasks, and augment data. To ground those discussions, each section contains practical examples that demonstrate how specific categories, or types, of data could be better leveraged in relation to the five "need" areas, and how diferent approaches could be used to extract more utility from existing data sources.

While this article discusses various...