The Intelligence Game is Changing. Are We Ready?

By Cynthia Saddy

Cynthia Saddy is a former senior executive with the Central Intelligence Agency, where she held numerous leadership positions including the Directorate of Operation’s Chief Technology Officer (Acting and Deputy), Senior Advisor to In-Q-Tel, Chief of Staff to the Director of Operations, and as a two time Division Chief of Operations responsible for leading large-scale HUMINT and technical programs across multiple geographic regions.

By EunJoo “EJ” Alam

EunJoo “EJ” Alam is a retired senior national security executive with over 30 years of government service. She has led clandestine operations, tradecraft, counterintelligence, information security, and intelligence collection efforts for the CIA. Her senior assignments include three-time field commander in the former Soviet Union, East Asia, and South Asia; Chief of Operations for Iran Mission Center, Deputy Department Chief in East Asia Pacific Mission Center, and Executive Assistant to the Deputy Director for Operations.

By Kelli Holden

Kelli Holden retired as a senior Central Intelligence Agency (CIA) executive with over 28 years of experience in intelligence operations. Concluding her career as Counterintelligence Chief of Operations for CIA, she served in numerous field command and Washington-based leadership positions driving complex HUMINT and technical programs across geographic regions, including high threat and high counterintelligence environments.

EXPERT PERSPECTIVE — As retirees of the Clandestine Service at the CIA, we worked for decades in the shadows around the world, at ease in that space where we quietly served. Recently, we found ourselves in an uncomfortable public space, compelled to be vocal on social media regarding data and the need for the U.S. government to embrace commercially sourced intelligence, CSINT, as a foundational and critical component of national security.  

Data is ubiquitous, dynamic, and has the potential to inform analysis and decision-making on issues ranging from climate change to terrorism to critical national infrastructure, and everything in between. CSINT is a complement to HUMINT (human intelligence) and other national technical means of collection, not a substitute. CSINT plus these other collection tools is the equation for success in gaining strategic advantage. 

CSINT is not OSINT (open source intelligence). Whereas OSINT is a reference to any information that can be legally gathered from free, public sources, CSINT is data that is produced by people throughout the world and is collected and sold by a variety of firms to others to make informed decisions.  Examples of CSINT include; pharmaceutical sales in the era of Covid, vehicle telematics data, geospatial insights, weather trends, and website cookies that inform retailer strategies for targeting consumers for advertisements based on their internet browsing history. 

And yes, we see the irony of HUMINT-ers extolling the virtues of CSINT – a new INT. 

We are in the midst of the fourth industrial revolution. And data – that data that we, as citizens, generate on a daily basis – is the commodity of value. We would liken it to the value of oil and oil’s role in the third industrial revolution, but oil is a finite resource and data is not. In fact, commercial data is growing at an exponential rate through our daily personal and professional interactions. Many businesses leverage this data to improve their bottom lines and grow their businesses. Likewise, some governments are exploiting commercially sourced data to achieve their objectives as well.

Take the People’s Republic of China (PRC) for example. Open source articles document the investments the PRC continues to make to build data centers and develop their artificial intelligence (AI) and machine learning (ML) models to allow them to more quickly derive value from data. The PRC government put into place laws that require Chinese companies, even when operating outside of China, to funnel data they collect by virtue of doing business, back to Chinese data centers. A new law in the PRC also requires foreign firms doing business in China to turn over their data to the PRC government. The PRC is concurrently locking down data from its citizens as a defensive measure.

The PRC has a data strategy to attempt to win supremacy in the fourth industrial revolution. The key components to their strategy are a wide variety of commercially sourced data, AI/ML models and computing power that speed the time from data to value/insights. The quality of the AI/ML models and the speed of compute power are critical components of this daisy chain, but the data is arguably the most critical.

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This paradigm does not cease to exist at the gates of intelligence agencies. We believe that commercially sourced data is a cornerstone to the future of intelligence. CSINT is the radical innovation that will launch intelligence services and businesses alike ahead of their adversaries, leapfrogging in essence, the status quo to establish a new order. Classified data sets and information that is clandestinely acquired, remain extremely valuable and cannot be replaced. CSINT does not seek to replace classified data; it seeks to enhance and complement it.

The paradigm of valuing classified data above all else is archaic and must be modernized in order to adapt to the data-driven world. If the US government continues to value classified data at the expense of embracing commercially sourced data, we run the risk of the United States losing ground to its adversaries. 

And that begs the question, what is the USG’s Data Strategy? While that is not readily clear, what is clear is that there is a big role for CSINT to play.

There is no rules-based order on the playing field of the fourth industrial revolution when it comes to data. In our techno-democracy, there is a lot of concern around privacy – and appropriately so. This complicates the development of a national data strategy akin to the PRC model.  While many grapple with how to optimize commercially sourced data and balance privacy concerns, we would propose that the United States and likeminded techno-democracies impose our values in defining how data will be utilized in the future.

If we cede the playing field to our adversaries to define the rules, rest assured they will not meet our democratic values. We must lean into this difficult conversation, find common cause with our likeminded techno-democratic partners, and create a framework that balances creating value from commercially sourced data on one hand and privacy concerns on the other.   

It is time for the U.S. to embrace commercially sourced data, modernize our laws to allow for the effective storing and computing of data, and invest in AI and ML tools and models to derive value at scale and at speed of mission. It is time for the U.S. to embrace CSINT.

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