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The Urgency of the Moment for Congress on AI and National Security

The Urgency of the Moment for Congress on AI and National Security
(Editor’s Note: This article is the fifth and final article in a series first published by our friends at Just Security that is dives into the foundational barriers to the broad integration of AI in [...] More

A Roadmap for AI in the IC

A Roadmap for AI in the IC
A Roadmap for AI in the Intelligence Community(Editor’s Note: This article was first published by our friends at Just Security and is the fourth in a series that is diving into the foundational [...] More
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More from Corin Stone

AI and the IC: The Tangled Web of Budget and Acquisition

AI and the IC: The Tangled Web of Budget and Acquisition

Corin Stone, Washington College of Law

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Corin Stone is a Scholar-in-Residence and Adjunct Professor at the Washington College of Law.  Stone is on leave from the Office of the Director of National Intelligence (ODNI) where, until August 2020, she served as the Deputy Director of National Intelligence for Strategy & Engagement, leading Intelligence Community (IC) initiatives on artificial intelligence, among other key responsibilities. From 2014-2017, Ms. Stone served as the Executive Director of the National Security Agency (NSA).

(Editor’s Note: This article was first published by our friends at Just Security and is the third in a series that is diving into the foundational barriers to the broad integration of AI in the IC – culture, budget, acquisition, risk, and oversight.)

OPINION — As I have written earlier, there is widespread bipartisan support for radically improving the nation’s ability to take advantage of artificial intelligence (AI). For the Intelligence Community (IC), that means using AI to more quickly, easily, and accurately analyze increasing volumes of data to produce critical foreign intelligence that can warn of and help defuse national security threats, among other things. To do that, the IC will have to partner closely with the private sector, where significant AI development occurs. But despite the billions of dollars that may ultimately flow toward this goal, there are basic hurdles the IC still must overcome to successfully transition and integrate AI into the community at speed and scale.

Among the top hurdles are the U.S. government’s slow, inflexible, and complex budget and acquisition processes. The IC’s rigid budget process follows the standard three-year cycle for the government, which means it takes years to incorporate a new program and requires confident forecasting of the future. Once a program overcomes the necessary hurdles to be included in a budget, it must follow a complex sequence of regulations to issue and manage a contract for the actual goods or services needed. These budget and acquisition processes are often considered separately as they are distinct, but I treat them together because they are closely related and inextricably intertwined in terms of the government’s purchasing of technology.

Importantly, these processes were not intended to obstruct progress; they were designed to ensure cautious and responsible spending, and for good reason. Congress, with its power of the purse, and the Office of Management and Budget (OMB), as the executive branch’s chief budget authority, have the solemn duty to ensure wise and careful use of taxpayer dollars. And their roles in this regard are vital to the U.S. government’s ability to function.

Unfortunately, despite the best of intentions, as noted by some in Congress itself, the budget process has become so “cumbersome, frustrating, and ineffective” that it has weakened the power of the purse and Congress’ capacity to govern. And when complicated acquisition processes are layered on top of the budget process, the result is a spider web of confusion and difficulty for anyone trying to navigate them.

The Need for Speed … and Flexibility and Simplicity

As currently constructed, government budget and acquisition processes cause numerous inefficiencies for the purchase of AI capabilities, negatively impacting three critical areas in particular: speed, flexibility, and simplicity. When it comes to speed and flexibility, the following difficulties jump out:

  • The executive branch has a methodical and deliberate three-year budget cycle that calls for defined and steady requirements at the beginning of the cycle. Changing the requirements at any point along the way is difficult and time-consuming.
  • The IC’s budgeting processes require that IC spending fit into a series of discrete sequential steps, represented by budget categories like research, development, procurement, or sustainment. Funds are not quickly or easily spent across these categories.
  • Most appropriations expire at the end of each fiscal year, which means programs must develop early on, and precisely execute, detailed spending plans or lose the unspent funds at the end of one year.
  • Government agencies expend significant time creating detailed Statements of Work (SOWs) that describe contract requirements. Standard contract vehicles do not support evolving requirements, and companies are evaluated over the life of the contract based on strict compliance with the original SOW created years earlier.

These rules make sense in the abstract and result from well-intentioned attempts to buy down the risk of loss or failure and promote accountability and transparency. They require the customer to know with clarity and certainty the solution it seeks in advance of investment and they narrowly limit the customer’s ability to change the plan or hastily implement it. These rules are not unreasonably problematic for the purchase of items like satellites or airplanes, the requirements for which probably should not and will not significantly change over the course of many years.

However, because AI technology is still maturing and the capabilities themselves are always adapting, developing, and adding new functionality, the rules above have become major obstacles to the quick integration of AI across the IC. First, AI requirements defined with specificity years in advance of acquisition – whether in the budget or in a statement of work – are obsolete by the time the technology is delivered. Second, as AI evolves there is often not a clear delineation between research, development, procurement, and sustainment of the technology – it continuously flows back and forth across these categories in very compressed timelines. Third, it is difficult to predict the timing of AI breakthroughs, related new requirements, and funding impacts, so money might not be spent as quickly as expected and could be lost at the end of the fiscal year. Taken together, these processes are inefficient and disruptive, cause confusion and delay, and discourage engagement from small businesses, which have neither the time nor the resources to wait years to complete a contract or to navigate laborious, uncertain processes.

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Artificial Intelligence in the IC: Culture is Critical

Corin Stone is a Scholar-in-Residence and Adjunct Professor at the Washington College of Law.  Stone is on leave from the Office of the Director of National Intelligence (ODNI) where, until August 2020, she served as the Deputy Director of National Intelligence for Strategy & Engagement, leading Intelligence Community (IC) initiatives on artificial intelligence, among other key responsibilities. From 2014-2017, Ms. Stone served as the Executive Director of the National Security Agency (NSA).

(Editor’s Note: This article was first published by our friends at Just Security and is the second in a series that is diving into the foundational barriers to the broad integration of AI in the IC – culture, budget, acquisition, risk, and oversight.)

OPINION — Several weeks ago, I wrote an article praising the widespread, bipartisan support for the U.S. Innovation and Competition Act (USICA), which would dramatically expand federal government support for U.S. technological growth and innovation in the face of the global AI race.

In that article, I argued that for the Intelligence Community (IC) to take advantage of AI in this supportive environment, it must overcome several critical implementation challenges, and quickly. In particular, the IC must more rapidly and nimbly navigate U.S. government budget and acquisition processes, create a simple but effective risk assessment framework, and work with congressional overseers to streamline engagement and improve the partnership between Congress and the IC. Each of these areas is in dire need of radical re-imagining, without which any one of them could be the Achilles’ heel for AI in the IC. I will address each of these in my next few articles.

To successfully tackle any of these specific tasks, though, the IC must at the same time prioritize an issue much more intangible and nebulous – its own culture. Culture is the ethos of an organization – the beliefs, behaviors, values, and characteristics of a group that are learned and shared over many years. In the IC, there are several predominant cultures, all of which flow from the mission of the IC – protecting the women and men on the front lines, defending U.S. national security, and delivering insights to policymakers at the speed of decision. This mission is a powerful and unifying force that naturally leads to important IC values and behaviors.

IC Culture Today

Intelligence operations – uncovering foreign secrets and protecting assets, for example – are inherently risky; they very often put people in harm’s way. If there is a leak of information related to an operation – if the people involved, or the location or target of an operation, are exposed – not only might the mission fail to collect the desired information, but someone’s life could also be in jeopardy. The extreme consequences of leaks are well understood, thanks to notorious spies like Robert Hanssen and inside leakers like Edward Snowden. But significant damage can also flow from what seem like merely small mistakes. If someone fails to make a connection between relevant information or forgets to check a database of known terrorists, for example, the results can be just as disastrous. Thus, the IC’s high-stakes operations drive an enormous emphasis on security, preparation, and tradecraft, all of which help mitigate operational risk.

This same spirit manifests in “enabling” activities, like budget, acquisition, or human resources, through a focus on certainty of action and predictability of results. Enabling activities – by some considered a negative term but one in which I take pride as a life-long enabler – are somewhat removed from the “pointy end of the spear” but are no less critical to the ultimate success of the mission. Proper funding and resources, the right capabilities, skilled officers, legal approval, and the many other support activities are integral to successful operations.

In the field, risks are unavoidable – operators cannot choose inaction to avoid those risks. Given that risks are inherent in what they do, they must accept the reality that risks are inevitable, and they must learn to manage those risks to get the huge payoff of successful operations. So, the focus is not on risk avoidance, it is on risk management – what level of risk is acceptable for what level of intelligence gain?

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Artificial Intelligence and the Intelligence Community

This article was first published by our friends at JustSecurity.

Corin R. Stone is a Scholar-in-Residence and Adjunct Professor at the Washington College of Law. She is on leave from the ODNI where, until August 2020, she served as the Deputy Director of National Intelligence for Strategy & Engagement, leading Intelligence Community initiatives on artificial intelligence, the 21st Century workforce, and acquisition agility; overseeing the Intelligence Advanced Research Projects Activity; creating IC-wide innovation and net assessment organizations; re-imagining data and information management for the digital age; establishing IC policy and strategy; and overseeing engagement with Congress and the public. 

OPINION — Congress wants to pour hundreds of billions (yes with a B) of dollars into the federal government to increase the nation’s competitiveness in emerging technology and, in particular, to accelerate the development of artificial intelligence (AI) technologies that are vital to protecting our national security. The bipartisan support shown for the U.S. Innovation and Competition Act (USICA) – the bill that provides these funds –  is a noteworthy and important step in ensuring the United States is resilient and competitive in the 21st century. And that kind of money is nothing to sneeze at. But can the federal government manage to spend it?

Thanks to China’s aggressive, whole-of-nation approach to emerging technology and the ubiquity of AI technologies that adversaries big and small are now poised to exploit, there is a sudden urgency around AI and national security. In addition to the USICA, the National Security Commission on AI has produced sixteen chapters of recommendations over the last three years (along with several quarterly, interim, and special topic reports) and several prominent think tanks have produced their own reports on AI and national security.  While there are open questions about ethics and proper implementation that must be addressed, there is no question that the United States must figure out how to address them and quickly take advantage of AI to continue to be a leader on the world stage.

The USICA, a $200 billion proposal, dramatically expands federal government support for technological growth and innovation and strengthens U.S. national competitiveness. It proposes new incentive programs and increased research and development funding in areas like AI and microelectronics, as well as the creation of new offices and increased public investment, lending, and trade abroad to support key technology focus areas and to counter China’s influence. The USICA is an important measure to protect and promote U.S. research and innovation and to drive national strategic advantage on the global stage.

However, having spent the last 20 years in the U.S. government, 15 of them in the Intelligence Community (IC), I believe that without a visible, concerted effort to revisit current budget, acquisition, risk, and oversight frameworks – led by the Director of National Intelligence (DNI) and IC leadership – the IC will not be able to effectively identify, develop, and incorporate in real-time the technological advances needed to keep its competitive edge, regardless of how much USICA money comes its way.

AI systems have the potential to transform how the IC makes sense of the world, rapidly and at scale. To discover secrets and provide policymakers with exquisite intelligence and insights at mission speed, the IC must be able to quickly and accurately sort through vast amounts of data to find patterns, uncover connections, understand relevance, and draw conclusions in real-time. Without the advantages that evolving AI will continue bring, the IC will quickly be outmatched by the nation’s formidable adversaries.

But, as we have seen before, money is necessary but not sufficient. In the immediate aftermath of the September 11, 2001 attacks, Congress threw a great deal of money at the counterterrorism problem, much of it aimed at helping the IC “connect the dots.” This goal included a steady focus on sharing information across agency lines with those who needed it so that the IC would never again fail to discover or understand information it already had in its holdings. However, the IC quickly realized that money alone could not solve that problem. Among other things, the IC had to tackle foundational issues involving cultural resistance and inconsistent, complex authorities.  The IC has come a long way on information sharing 20 years after 9/11, but it still has more work to do.

Similarly, when it comes to the IC being able to take advantage of significant advances in AI, the jury is still out. To take full advantage of what AI has to offer, the IC will have to work closely with the private sector, where much of the emerging technology is being developed.  Unfortunately, when it comes to that kind of partnership, the IC’s track record is mediocre, at best. Time and again we have seen that the national security community – including in particular the Department of Defense (DOD) and the IC – has serious, basic hurdles to clear if it is to partner smartly with the private sector to harness innovation and emerging technology like AI. Existing budget and acquisition processes are laborious, complex, and slow; the IC neither sufficiently understands nor accepts risks associated with AI technologies; and congressional oversight processes compound these issues. Moreover, within the national security community the cultural barrier to trying new things persists, despite the fact that there is jaw-dropping innovation and creativity in pockets.

DOD has started tackling some – but not all – of these issues. It has recently piloted new approaches to software procurement, received important legislative flexibilities to deal with acquisition bottlenecks, and driven the need for innovation and emerging technologies from the most senior levels of the Department. This is an encouraging start.

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