How AI is Changing The Landscape of Modern Warfare 

Militaries worldwide are integrating artificial intelligence and machine learning into their military weapons systems, fundamentally changing how nations wage war. From tanks with crews, planes with pilots, ships with sailors, and spacecraft orbiting the planet, today’s fighting forces are increasing investment in unmanned AI and ML-based combat systems for land, air, sea and space. These new assets expand situational awareness and can make decisions with little or no human intervention.

“The changes brought about by artificial intelligence will be unprecedented and distinctive in the history of humankind.” 

– Koichiro Takagi, visiting fellow with Hudson Institute’s Japan Chair

In 1935, Alan Turing, the brilliant UK computer scientist, cryptanalyst, mathematician and theoretical biologist, coined the term artificial intelligence (AI). Turing defined AI as a computer that can mimic human responses under specific conditions. 

The original “Turing Test” required three terminals. Each is physically separated from the other two. One terminal is operated by a computer, while the other two are operated by humans. During the test, one of the humans functions as the questioner, while the second human and the computer function as respondents. 

The questioner interrogates the respondents within a specific subject area, using a specified format and context. After a preset length of time or the number of questions, the questioner is then asked to decide which respondent is human and which is a computer.

Eighty-eight years later, AI has evolved to the point where it is transforming how nations prepare for and fight wars. It’s still early days, but autonomous systems with little or no human control are already being deployed on the battlefield, in the air, and at sea. 

Digital Autonomy is The Future of Military Assets

Autonomy is hardly new. The US Department of Defense (DoD) has been developing pilotless aircraft for more than five decades. It leads the world in AI research, has the largest annual military budget, and deploys a range of autonomous military assets.

The DoD Department of Advanced Research Programs Agency (DARPA) envisions a future where machines execute human-programmed rules from human-curated data sets. These future AI machines will not be “tools” but will function as “colleagues” through human-machine symbiosis. 

DARPA has a diverse and growing portfolio of fundamental and applied R&D AI programs. It aims to reshape the future of AI technology, where machines serve as trusted, collaborative partners with humans to solve problems critical to national security.

Other large nations, including China, Russia, and India, have significant military budgets and are investing in AI and ML capabilities with the intention of becoming world leaders in the coming years. China has the second-largest military budget behind the US. It plans to accelerate defense innovations by bridging China’s civilian research and commercial sectors.

This strategy was first articulated at the 20^th National Congress of the Chinese Communist Party (CCP) in October 2018. Premier Xi Jinping announced China was accelerating the pace of investment to elevate the People’s Liberation Army (PLA) to a world-class military force. Fast forward to 2023, and the progress the PLA has made in autonomous, unmanned weapons systems has been significant. 

China not only intends to seize the initiative to become a “global AI leader” but will deploy AI-based military assets on the battlefield, which has implications for international and regional security. For example, China’s military has swarms of connected drones that can coordinate and collaborate in an attack on targets with minimal human involvement.

China is exploiting AI to advance both economic competitiveness and military capabilities. It is conducting autonomous operations with various unmanned systems and weapons. For example, in August and September 2022, China sent unarmed drones to two islands belonging to Taiwan that are close to China’s southern coast. The drones targeted a garrison of Taiwanese soldiers stationed on one of the islands. In addition, the PLA launched pilotless drones that entered the airspace south of Taiwan’s Air Defense Identification Zone. China increased the number of sorties to 70 in December 2022. 

Not only does China plan to become the world’s leading AI power by 2030, but Beijing has turned to a military-civil fusion strategy to achieve it. This approach has enabled the country to speed up defense innovations by eliminating barriers between China’s civilian research and commercial sectors and its military and defense industrial sectors. 

The results are striking. China already produces the most AI scientists, and the country hosts the first nine of the world’s top 10 institutions publishing AI-related papers. Moreover, Chinese companies such as Tencent Holdings, Alibaba Group Holdings, and Huawei Technologies are reportedly among the top 10 Chinese firms conducting AI research. Also, China’s PLA reportedly aims to use AI to process information from many sources, including a network of unmanned systems and undersea sensors surrounding China. 

Setting a Course For AI Warfare

AI represents a generational shift in the capabilities of military assets that are being deployed worldwide. The top three military budgets in the world are the US, China, and Russia. They are all well-advanced in developing and deploying AI-enhanced military systems. 

Other countries with strong economies, such as India, Japan, and South Korea, are also ramping up investments in AI defense systems, but on a much smaller scale. For example, Japan allocates only ¥160 billion of the government’s annual ¥4 trillion science and technology budget for defense-related programs.

This shift is paving the way for AI-enabled warfare to become the dominant form of warfare in the not-too-distant future. First, military budgets must expand to gather and analyze the increasing volume of data generated on battlefields, at sea, in the air and in space. The capacity to analyze and process large amounts of data faster than an adversary will become critical.

Not only can AI systems digest, categorize, and analyze more data than human analysts, they can find correlations in the data that humans cannot detect. AI systems can process data from intelligence, surveillance, and reconnaissance sensors by sifting through massive troves of texts, images and audio, unburdening analysts from doing the work.

The Internet of Military Things

Crucial to an AI and ML future of managing military systems is the evolution of the Internet of Military Things (IoMT) and the Internet of Battlefield Things (IoBT). These systems use a cloud and edge architecture, alongside a network of hardened devices, including biometrics, environmental sensors, wearable devices, IoT devices, vehicles, robots, UAVs, munitions, armor, weapons, and other platforms and equipment that can sense and learn. 

IoMT and IoBT are robust military applications that produce massive amounts of data capable of connecting ships, planes, tanks, drones, soldiers, and operating bases in a network to improve situational awareness, measure and manage risk and reduce response time. Soldiers wear sensing and computing devices embedded in their combat suits, helmets, weapons systems, and other equipment. The devices can acquire static and dynamic biometrics such as face, iris, periocular space, fingerprints, heart rate, gait, gestures, and facial expressions.

The Four Categories of IoMT and IoBT Devices:

• Data-carrying devices: These devices are attached to a physical thing that indirectly connects it to a larger communication network.
• Data-capturing devices: These are reader/writer devices capable of interacting with physical things.
• Sensing and actuating devices: These devices can detect and measure information related to the surrounding environment and convert it to a digital electronic signal or a physical operation.
• General devices: A device with processing and communication capabilities that can exchange information with the larger network. Source

Researchers say one key element necessary for healthy IoMT and IoBT systems is the edge architecture that uses biometrics, environmental sensors, and other connected devices to send and receive data quickly. This system allows military personnel to respond quickly to dangerous situations on the battlefield. 

Challenges Ahead for Military Systems

The United States has the largest annual defense budget in the world and outspends second-place China by nearly $500 billion. The US figure is equal to the military budgets of the next ten countries combined. However, much of the US spending is tied to legacy programs, which represent the lion’s share of the budget. Today, the US maintains and improves these existing systems and integrates them with AI. However, only a minority is dedicated to programs designed with AI from the start. 

Top 10 military budgets in 2022 ranked by country

1 United States of America $800,672,200,000

2 The People’s Republic of China $293,351,866,359

3 India $76,598,031,181

4 United Kingdom $68,366,440,552

5 Russia $65,907,705,047

6 France $56,646,996,216

7 Germany $56,017,029,328

8 Saudi Arabia $55,564,266,667

9 Japan $54,123,551,702

10 South Korea $50,226,948,867

Source: Axios 

Today, US chip manufacturing accounts for about 10% of the world’s total production because it lacks onshore facilities to make the most advanced chips with geometries of 7 and 5 nanometers (nm). So instead, the US depends on Taiwan and South Korea to produce their most sophisticated designs.

The domestic production gaps are problematic from a national security perspective. China is the primary US strategic challenger and is building a world-class military industrial base that includes investing in semiconductor technology. The US vulnerability is particularly acute concerning the most advanced chips currently in production, which are essential for creating and applying AI. These cutting-edge AI chips are tens to thousands of times faster than conventional CPUs in developing AI algorithms. Moreover, state-of-the-art AI chips are in demand because they are cost-effective and quick to build and deploy.

The most advanced AI systems require semiconductor chips not currently manufacturable in the US. Taiwan Semiconductor Manufacturing Co. (TSMC) is building a fab in Arizona, which will operate at the 5 nm node. It is expected to be online in 2024. However, by then, the state-of-the-art geometry will likely be 3 nm chips and will be made in Taiwan.

The Limitations of AI 

China’s growing military power can be attributed in part to AI. But AI will not change the essence of armed conflict and the methods of waging war. AI is an enabler, not a weapon. Its function in military equipment is to improve the performance, speed, and efficiency of the equipment, systems, and platforms. AI can speed up war, but it cannot change its fundamental essence.

The broad deployment of AI-based systems still faces some serious challenges. First and foremost, a massive volume of high-quality data is required to train AI algorithms and enable machine learning. Second, war-related data is sensitive and not easy to access. And third, it is challenging to code some elements of warfare into quantitative machine-readable data. 

When AI algorithms run at flash speeds, it is very challenging for other military hardware to keep up. Ensuring the hardware can keep pace with AI programs requires ultra-high-speed communication and comprehensive data-link networks. As a result, the PLA still needs to enhance the interconnectedness among its units and organs, develop next-generation communications technology, and establish reliable and secure data links. 

These requirements echo China’s prioritization of 5G, blockchain, and quantum computing. Second, radical advances and improvements in basic physics and machinery engineering should optimize the performance of the original hardware. However, scientists still find it challenging to understand the behavior of AI. Armed forces take these issues very seriously and will be cautious in deploying AI-based systems if they cannot ensure battlefield reliability.

The Future is Now

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