Lt. Gen. Jack Shanahan Media Briefing on AI-Related Initiatives within the Department of Defense

This post contains Lt Gen Shanahan’s opening statement from his Aug. 30, 2019 media roundtable.” For the full transcript, click here.

Well, I'm Lt. Gen. Jack Shanahan, the director of DOD's Joint AI Center, or the JAIC [Joint Artificial Intelligence Center].  I've been in this position since January, and before this, as many of you have heard in the room, I led Project Maven, the artificial intelligence, machine-learning pathfinder project under the Undersecretary of Defense for Intelligence.

And let me start with the JAIC's mission:  to accelerate DOD's adoption and integration of AI to achieve mission impact at scale.

Leadership in the military application of AI is critical to our national security.  The table stakes are high.  For that reason, I doubt I will ever be entirely satisfied that we're moving fast enough when it comes to DOD's adoption of AI  My sense of urgency remains palpable.

Yet, at the same time, it's important to acknowledge the myriad challenges that come with building and sustaining an AI-ready force across the Department, both in terms of people and weapon systems.

As a DOD AI and machine-learning pathfinder, Project Maven was always focused on building a product delivery pipeline.  The JAIC was designed from the beginning to be an AI center of excellence, expanding beyond product delivery to full AI capability delivery by adding other elements such as strategic engagement and policy, plans and analysis, intelligence and more with an operating model of centralized direction, a common foundation and decentralized development and experimentation.

I want you to know what we've accomplished since the JAIC was established a year ago.  At this time last year, the JAIC only had a handful of people, no money and no permanent spaces from which to operate, and we did not get the majority of our fiscal year '19 funding until the beginning of March this year.  We now have over 60 government employees, a real home, a healthy fiscal year '20 budget, and we are delivering some initial AI-enabled capabilities.

I am proud of our team's talent and diversity:  government civilians, active duty military, National Guard, Reservists, contractors, and, until their departure a couple of weeks ago, even two college summer interns.

We are seeing initial momentum across the department in terms of fielding AI-enabled capabilities.  You can see some evidence of this in the fiscal year '20 service and component budgets with even more investments expected in the fiscal year '21 FYDP [Future Years Defense Program] POM [Program Objective Memorandum].

Yet, we still have a long way to go to help bring pilots, prototypes and pitches across the technology valley of death to fielding and updating AI-enabled capabilities at speed and at scale.

It is difficult work, yet it is critically important work.  It's a multi-generational problem requiring a multi-generational solution.  It demands the right combination of tactical urgency and strategic patience.

We have to move beyond the hype where we don't view AI as another technology flash in the pan but instead focus on what it takes to weave AI into the very fabric of DOD.  And we'll know we have succeeded when you've gained irreversible momentum and AI has become ubiquitous.

I will briefly mention our ongoing and planned mission initiatives and can provide more details on each of them in the Q&A session that follows.

Our ongoing projects include predictive maintenance for the H-60 helicopter; humanitarian assistance and disaster relief, or HA/DR, with an initial emphasis on wildfires and flooding; cyber sense-making, focusing on event detection, user activity monitoring and network mapping; information operations; and intelligent business automation.

For fiscal year '20, our biggest project will be what we are calling AI for maneuver and fires, with individual lines of effort or product lines oriented on warfighting operations; for example, operations intelligence fusion, joint all-domain command and control, accelerated sensor-to-shooter timelines, autonomous and swarming systems, target development and operations center workflows.

We are also embarking with DIU [Defense Innovation Unit] and the services’ Surgeons General, as well as many others, on a warfighter health project, with several proposed lines of effort, to include health records analysis, medical imagery classification and PTSD [Post-Traumatic Stress Disorder] mitigation/suicide prevention.

Our other major effort, one that is instrumental to our AI center of excellence concept, is what we are calling the Joint Common Foundation, or JCF.  The JCF will be a platform that will provide access to data, tools, environments, libraries and to other certified platforms to enable software and AI engineers to rapidly develop, evaluate, test and deploy AI-enabled solutions to warfighters.

It is designed to lower the barriers of entry, democratize access to data, eliminate duplicative efforts and increase value added for the department.  This platform will reside on top of an enterprise cloud infrastructure.

I would now like to share a few of our biggest lesson learned -- lessons learned from over the past three years, my two years at Project Maven and not quite a year as the JAIC director.  These lessons learned are hardly unique to DOD.  For those of you who are following AI in the corporate world, these will all sound very familiar.

First, problem framing.  I cannot overstate the importance of a comprehensive, user-defined, data-driven workflow analysis to determine if AI is even the right solution to the problem.  If there are any AI silver bullets or AI easy buttons, I have not yet found them, though I am optimistic that the pace of technological change over the next year and beyond will yield better and faster ways to simplify the AI delivery pipeline.

Second, data is at the heart of every AI project.  We are addressing challenges related to data collection, data access, data quality, data ownership and control, intellectual property protections, and data-related policies and standards.  In short, we have to liberate data across the DOD.

Next, DOD's AI adoption capacity is limited by the pace of broader digital modernization.  Along with enterprise cloud, cyber and C3 [command, control and communications], AI is one of Chief Information Officer Dana Deasy's four digital modernization pillars.  These four pillars are going to converge in such a way that digital modernization and warfighting modernization become synonymous.

In terms of culture, in DOD, we need to match the rate of institutional change to the rate of change of commercial technology.  As I said earlier, this is a multi-generation commitment.
We have a lot of work ahead, to build a data-literate force across the department.  Within the JAIC, we are cultivating a leading AI workforce with the aim of attracting world-class AI talent through training, targeted recruitment and industry and academia engagement.

We face hard decisions ahead in the department about striking the right balance between adapting legacy systems, legacy data practices and legacy workflows to AI; in effect, bolting on cutting-edge technologies to old systems and accepting a certain level of sunk costs by divesting legacy systems to accelerate the development and fielding of AI-ready systems.

Finally, we are thinking deeply about the ethical, safe and lawful use of AI  At its core, we are in a contest for the character of the international order in the digital age.  Along with our allies and partners, we want to lead and ensure that that character reflects the values and interests of free and democratic societies.  I do not see China or Russia placing the same kind of emphasis in these areas.

To conclude, contrary to a lot of the hype prevalent today, we don't view AI as a magical solution, a specific thing to be sprinkled on top of any problem to yield miraculous results.  AI is an enabler, much more like electricity than a gadget, a widget or a weapons system.

AI's most valuable contributions will come from how we use it to make better and faster decisions.  This includes gaining a deeper understanding of how to optimize human-machine teaming.  We want AI to increase operational effectiveness, accelerate integration with autonomous systems, and enhance efficiency across the department.

This is less about any individual technology than it is about how we design, experiment with and deploy AI-enabled operating concepts to gain competitive advantage, from the tactical edge to the strategic level.  In some cases, perhaps only gaining a fleeting upper hand, a temporal advantage.  In others, achieving a sustained strategic advantage against a peer competitor.

And as we look to a future of informatized warfare, comprising algorithm against algorithm and widespread use of autonomous systems, we need to design operating concepts that harness AI, 5G, enterprise cloud, robotics and eventually quantum.  This critical path from a hardware-centric to an all-domain digital force will shape the department for decades to come.

And finally, I am optimistic that 2020 will be a breakout year for the department when it comes to fielding AI-enabled capabilities.

And with that, I'm ready to take the questions.