7 Key Military Applications of Machine Learning
Machine learning is now a critical component in modern warfare systems. Let’s explore 7 key military applications of artificial intelligence today.
Machine learning has become a critical part of modern warfare, and a major point of interest for me, both as an Army veteran and data scientist. Compared with conventional systems, military systems equipped with ML/DL are capable of handling tremendously larger volumes of data more efficiently. Additionally, AI improves self-control, self-regulation, and self-actuation of combat systems due to its inherent computing and decision-making capabilities; a critical aspect to consider due to the nature of combat.
AI/ML is being deployed in almost every military application, and increased funding for research and development from military research agencies promises to drive adoption of AI-driven systems in the military sector even further.
For instance, the US Department of Defense’s (DoD) Defense Advanced Research Projects Agency (DARPA) is financing the development of a robotic submarine system, which is expected to be employed in applications ranging from detection of underwater mines to engagement in anti-submarine operations. Additionally, the US DoD overall spent 7.4 billion on artificial intelligence, Big Data, and cloud in the fiscal year 2017. The market size of military ML solutions is expected to reach 19 billion by 2025.
Here are seven major military applications where machine learning will prove its importance in the years to come.
1. Warfare Platforms
Defense forces from different countries across the globe are embedding AI into weapons and other systems used on land, naval, airborne, and space platforms.
Using AI in systems based on these platforms has enabled the development of efficient warfare systems, which are less reliant on human input. It has also led to increased synergy and enhanced performance of warfare systems while requiring less maintenance. AI is also expected to empower autonomous and high-speed weapons to carry out collaborative attacks.
2. Cybersecurity
Military systems are often vulnerable to cyber attacks, which can lead to loss of classified military information and damage to military systems. However, systems equipped with AI can autonomously protect networks, computers, programs, and data from any kind of unauthorized access.
In addition, AI-enabled web security systems can record the pattern of cyber attacks and develop counter-attack tools to tackle them.
3. Logistics & Transportation
AI is expected to play a crucial role in military logistics and transport. The effective transportation of goods, ammunition, armaments, and troops is an essential component of successful military operations.
Integrating AI with military transportation can lower transportation costs and reduce human operational efforts. It also enables military fleets to easily detect anomalies and quickly predict component failures. Recently, the US Army collaborated with IBM to use its Watson artificial intelligence platform to help pre-identify maintenance problems in Stryker combat vehicles.
4. Target Recognition
AI techniques are being developed to enhance the accuracy of target recognition in complex combat environments. These techniques allow defense forces to gain an in-depth understanding of potential operation areas by analyzing reports, documents, news feeds, and other forms of unstructured information. Additionally, AI in target recognition systems improves the ability of these systems to identify the position of their targets.
Capabilities of AI-enabled target recognition systems include probability-based forecasts of enemy behavior, aggregation of weather and environmental conditions, anticipation and flagging of potential supply line bottlenecks or vulnerabilities, assessments of mission approaches, and suggested mitigation strategies. Machine learning is also used to learn, track, and discover targets from the data obtained.
For example, DARPA’s Target Recognition and Adaption in Contested Environments (TRACE) program uses machine learning techniques to automatically locate and identify targets with the help of Synthetic-Aperture Radar (SAR) images.
5. Battlefield Healthcare
In war zones, AI can be integrated with Robotic Surgical Systems (RSS) and Robotic Ground Platforms (RGPs) to provide remote surgical support and evacuation activities. The US in particular is involved in the development of RSS, RGPs, and various other systems for battlefield healthcare. Under difficult conditions, systems equipped with AI can mine soldiers’ medical records and assist in complex diagnosis.
For instance, IBM’s Watson research team partnered with the US Veterans Administration to develop a clinical reasoning prototype known as the Electronic Medical Record Analyzer (EMRA). This preliminary technology is designed to use machine learning techniques to process patients’ electronic medical records and automatically identify and rank their most critical health problems.
6. Combat Simulation & Training
Simulation & training is a multidisciplinary field that pairs system engineering, software engineering, and computer science to construct computerized models that acquaint soldiers with the various combat systems deployed during military operations. The US is investing increasingly in the simulation & training applications.
The US Navy and Army have each been conducting warfare analysis, which has led to the initiation of several sensor simulation programs. The US Navy has enlisted such companies such as Leidos, SAIC, AECOM, and Orbital ATK to support their programs, while the US Army’s programs are supported by firms including SAIC, CACI, Torch Technologies, and Millennium Engineering.
7. Threat Monitoring & Situational Awareness
Threat monitoring & situational awareness rely heavily on Intelligence, Surveillance, and Reconnaissance (ISR) operations. ISR operations are used to acquire and process information to support a range of military activities.
Unmanned systems used to carry out ISR missions can either be remotely operated or sent on a pre-defined route. Equipping these systems with AI assists defense personnel in threat monitoring, thereby enhancing their situational awareness.
Unmanned aerial vehicles (UAVs) — also known as drones — with integrated AI can patrol border areas, identify potential threats, and transmit information about these threats to response teams. Using UAVs can thus strengthen the security of military bases, as well as increase the safety and efficacy of military personnel in battle or at remote locations.
Conclusion
The mass adoption of AI in military technology, both hardware and software, presents to us an incredible and frightening paradigm shift in modern warfare. It should be no surprise that the largest militaries in the world are focusing more on this technology than anything else, and the winner of this tech race will likely have more global leverage than the US had after developing the atom bomb.