Reorganizing the DoD to Deter China and Win in the Ukraine – A Road Map for Congress

This article previously appeared in Defense News. It was co-written with Joe Felter, and Pete Newell.

Today, the U.S. is supporting a proxy war with Russia while simultaneously attempting to deter a China cross-strait invasion of Taiwan. Both are wakeup calls that victory and deterrence in modern war will be determined by a state’s ability to both use traditional weapons systems and simultaneously rapidly acquire, deploy, and integrate commercial technologies (drones, satellites, targeting software, et al) into operations at every level.

Ukraine’s military is not burdened with the DoD’s 65-year-old acquisition process and 20th-century operational concepts. It is learning and adapting on the fly. China has made the leap to a “whole of nation” approach. This has allowed the Peoples Liberation Army (PLA) to integrate private capital and commercial technology and use them as a force multiplier to dominate the South China Sea and prepare for a cross-strait invasion of Taiwan.

The DoD has not done either of these. It is currently organized and oriented to execute traditional weapons systems and operational concepts with its traditional vendors and research centers but is woefully unprepared to integrate commercial technologies and private capital at scale.

Copying SecDef Ash Carter’s 2015 strategy, China has been engaged in Civil/Military Fusion employing a whole of government coordinated effort to harness these disruptive commercial technologies for its national security needs. To fuel the development of technologies critical for defense, China has tapped into $900 billion of private capital in Civil/Military Guidance (Investment) Funds and has taken public state owned enterprises to fund their new shipyards, aircraft, and avionics.  Worse, China will learn from and apply the lessons from Russia’s failures in the Ukraine at an ever increasing pace.

But unlike America’s arch strategic rival, the US to date has been unwilling and unable to adapt and adopt new models of systems and operational concepts at the speed of our adversaries. These include attritable systems, autonomous systems, swarms, and other emerging new defense platforms threaten legacy systems, incumbent vendors, organizations, and cultures. (Until today, the U.S. effort was still-born with its half-hearted support of its own Defense Innovation Unit and history of lost capabilities like those that were inherent the US Army’s Rapid Equipping Force.)

Viewing the DoD budget as a zero-sum game has turned the major defense primes and K-street lobbyists into saboteurs for DoD organizational innovation that threaten their business models. Using private capital could be a force multiplier by adding 100’s of billions of dollars outside the DoD budget. Today, private capital is disincented to participate in national security and incentives are aligned to ensure the U.S. military is organized and configured to fight and win the wars of the last century.  The U.S. is on a collision course to experience catastrophic failure in a future conflict because of it. Only Congress can alter this equation.

For the U.S. to deter and prevail against China the DoD must create both a strategy and a redesigned organization to embrace those untapped external resources – private capital and commercial innovation. Currently the DoD lacks a coherent plan and an organization with the budget and authority to do so.

A reorganized and refocused DoD could acquire traditional weapons systems while simultaneously rapidly acquiring, deploying, and integrating commercial technologies. It would create a national industrial policy that incentivizes the development of 21st-century shipyards, drone and satellite factories and a new industrial base along the lines of the CHIPS and Innovation and Competition acts.

Congress must act to identify and implement changes within the DoD needed to optimize its organization and structure. These include:

  1. Create a new defense ecosystem that uses the external commercial innovation ecosystem and private capital as a force multiplier. Leverage the expertise of prime contractors as integrators of advanced technology and complex systems, refocus Federally Funded Research and Development Centers (FFRDCs) on areas not covered by commercial tech (kinetics, energetics, nuclear and hypersonics).
  2. Reorganize DoD Research and Engineering. Allocate its budget and resources equally between traditional sources of innovation and new commercial sources of innovation and capital. Split the OSD R&E organization in half. Keep the current organization focused on the status quo. Create a peer organization – the Under Secretary of Defense for Commercial Innovation and Private Capital.
  3. Scale up the new Office of Strategic Capital (OSC) and the Defense Innovation Unit (DIU) to be the lead agencies in this new organization. Give them the budget and authority to do so and provide the services the means to do the same.
  4. Reorganize DoD Acquisition and Sustainment. Allocate its budget and resources equally between traditional sources of production and the creation of new from 21st-century arsenals – new shipyards, drone manufacturers, etc. – that can make 1,000s of low-cost, attritable systems.
  5. Coordinate with Allies. Expand the National Security Innovation Base (NSIB) to an Allied Security Innovation Base. Source commercial technology from allies.

Why Is It Up To Congress?

National power is ephemeral. Nations decline when they lose allies, economic power, interest in global affairs, experience internal/civil conflicts, or miss disruptive technology transitions and new operational concepts.

The case can be made that all of these have or are happening to the U.S.

There is historical precedent for Congressional action to ensure the DoD is organized to fight and win our wars. The 1986 Goldwater/Nichols Act laid the foundation for conducting coordinated and effective joint operations by reorganizing the roles of the military services, and the Joint Chiefs, and creating the Joint Staff and the combatant commands. US Congress must take Ukraine and China’s dominance in the South China Sea as call for action and immediately establish a commission to determine what reforms and changes are needed to ensure the U.S. can fight and win our future wars.

While parts of the DoD understand we’re in a crisis to deter, or if that fails, win a war in the South China Sea, the DoD as a whole shows little urgency and misses a crucial point: China will not defer solving the Taiwan issue on our schedule. Russia will not defer its future plans for aggression to meet our dates.  We need to act now.

We fail to do so at our peril and the peril of all those who depend on U.S. security to survive.

Playing With Fire – ChatGPT

The world is very different now. For man holds in his mortal hands the power to abolish all forms of human poverty and all forms of human life.

John F. Kennedy

Humans have mastered lots of things that have transformed our lives, created our civilizations, and might ultimately kill us all. This year we’ve invented one more.

Artificial Intelligence has been the technology right around the corner for at least 50 years. Last year a set of specific AI apps caught everyone’s attention as AI finally crossed from the era of niche applications to the delivery of transformative and useful tools – Dall-E for creating images from text prompts, Github Copilot as a pair programming assistant, AlphaFold to calculate the shape of proteins, and ChatGPT 3.5 as an intelligent chatbot. These applications were seen as the beginning of what most assumed would be domain-specific tools. Most people (including me) believed that the next versions of these and other AI applications and tools would be incremental improvements.

We were very, very wrong.

This year with the introduction of ChatGPT-4 we may have seen the invention of something with the equivalent impact on society of explosives, mass communication, computers, recombinant DNA/CRISPR and nuclear weapons – all rolled into one application. If you haven’t played with ChatGPT-4, stop and spend a few minutes to do so here. Seriously.

At first blush ChatGPT is an extremely smart conversationalist (and homework writer and test taker). However, this the first time ever that a software program has become human-competitive at multiple general tasks. (Look at the links and realize there’s no going back.) This level of performance was completely unexpected. Even by its creators.

In addition to its outstanding performance on what it was designed to do, what has surprised researchers about ChatGPT is its emergent behaviors. That’s a fancy term that means “we didn’t build it to do that and have no idea how it knows how to do that.” These are behaviors that weren’t present in the small AI models that came before but are now appearing in large models like GPT-4. (Researchers believe this tipping point is result of the complex interactions between the neural network architecture and the massive amounts of training data it has been exposed to – essentially everything that was on the Internet as of September 2021.)

(Another troubling potential of ChatGPT is its ability to manipulate people into beliefs that aren’t true. While ChatGPT “sounds really smart,” at times it simply makes up things and it can convince you of something even when the facts aren’t correct. We’ve seen this effect in social media when it was people who were manipulating beliefs. We can’t predict where an AI with emergent behaviors may decide to take these conservations.)

But that’s not all.

Opening Pandora’s Box
Until now ChatGPT was confined to a chat box that a user interacted with. But OpenAI (the company that developed ChatGPT) is letting ChatGPT reach out and interact with other applications through an API (an Application Programming Interface.)  On the business side that turns the product from an incredibly powerful application into an even more incredibly powerful platform that other software developers can plug into and build upon.

By exposing ChatGPT to a wider range of input and feedback through an API, developers and users are almost guaranteed to uncover new capabilities or applications for the model that were not initially anticipated. (The notion of an app being able to request more data and write code itself to do that is a bit sobering. This will almost certainly lead to even more new unexpected and emergent behaviors.) Some of these applications will create new industries and new jobs. Some will obsolete existing industries and jobs. And much like the invention of fire, explosives, mass communication, computing, recombinant DNA/CRISPR and nuclear weapons, the actual consequences are unknown.

Should you care? Should you worry?
First, you should definitely care.

Over the last 50 years I’ve been lucky enough to have been present at the creation of the first microprocessors, the first personal computers, and the first enterprise web applications. I’ve lived through the revolutions in telecom, life sciences, social media, etc., and watched as new industries, markets and customers created literally overnight. With ChatGPT I might be seeing one more.

One of the problems about disruptive technology is that disruption doesn’t come with a memo. History is replete with journalists writing about it and not recognizing it (e.g. the NY Times putting the invention of the transistor on page 46) or others not understanding what they were seeing (e.g. Xerox executives ignoring the invention of the modern personal computer with a graphical user interface and networking in their own Palo Alto Research Center). Most people have stared into the face of massive disruption and failed to recognize it because to them, it looked like a toy.

Others look at the same technology and recognize at that instant the world will no longer be the same (e.g. Steve Jobs at Xerox). It might be a toy today, but they grasp what inevitably will happen when that technology scales, gets further refined and has tens of thousands of creative people building applications on top of it – they realize right then that the world has changed.

It’s likely we are seeing this here. Some will get ChatGPT’s importance instantly. Others will not.

Perhaps We Should Take A Deep Breath And Think About This?
A few people are concerned about the consequences of ChatGPT and other AGI-like applications and believe we are about to cross the Rubicon – a point of no return. They’ve suggested a 6-month moratorium on training AI systems more powerful than ChatGPT-4. Others find that idea laughable.

There is a long history of scientists concerned about what they’ve unleashed. In the U.S. scientists who worked on the development of the atomic bomb proposed civilian control of nuclear weapons. Post WWII in 1946 the U.S. government seriously considered international control over the development of nuclear weapons. And until recently most nations agreed to a treaty on the nonproliferation of nuclear weapons.

In 1974, molecular biologists were alarmed when they realized that newly discovered genetic editing tools (recombinant DNA technology) could put tumor-causing genes inside of E. Coli bacteria. There was concern that without any recognition of biohazards and without agreed-upon best practices for biosafety, there was a real danger of accidentally creating and unleashing something with dire consequences. They asked for a voluntary moratorium on recombinant DNA experiments until they could agree on best practices in labs. In 1975, the U.S. National Academy of Science sponsored what is known as the Asilomar Conference. Here biologists came up with guidelines for lab safety containment levels depending on the type of experiments, as well as a list of prohibited experiments (cloning things that could be harmful to humans, plants and animals).

Until recently these rules have kept most biological lab accidents under control.

Nuclear weapons and genetic engineering had advocates for unlimited experimentation and unfettered controls. “Let the science go where it will.”  Yet even these minimal controls have kept the world safe for 75 years from potential catastrophes.

Goldman Sachs economists predict that 300 million jobs could be affected by the latest wave of AI. Other economists are just realizing the ripple effect that this technology will have. Simultaneously, new startups are forming, and venture capital is already pouring money into the field at an outstanding rate that will only accelerate the impact of this generation of AI. Intellectual property lawyers are already arguing who owns the data these AI models are built on. Governments and military organizations are coming to grips with the impact that this technology will have across Diplomatic, Information, Military and Economic spheres.

Now that the genie is out of the bottle, it’s not unreasonable to ask that AI researchers take 6 months and follow the model that other thoughtful and concerned scientists did in the past. (Stanford took down its version of ChatGPT over safety concerns.) Guidelines for use of this tech should be drawn up, perhaps paralleling the ones for genetic editing experiments – with Risk Assessments for the type of experiments and Biosafety Containment Levels that match the risk.

Unlike moratoriums of atomic weapons and genetic engineering that were driven by the concern of research scientists without a profit motive, the continued expansion and funding of generative AI is driven by for-profit companies and venture capital.

Welcome to our brave new world.

Lessons Learned

  • Pay attention and hang on
  • We’re in for a bumpy ride
  • We need an Asilomar Conference for AI
  • For-profit companies and VC’s are interested in accelerating the pace