AI Gunpowder in Military Barrel

Artificial Intelligence (AI) is becoming a critical part of modern warfare. Compared with conventional systems, military systems equipped with AI are capable of handling 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.

AI is deployed in almost every military application, and increased research and development funding from military research agencies to develop new and advanced 
applications of artificial intelligence is projected to drive the increased adoption of AI-driven systems in the military sector.


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 USD 7.4 billion on artificial intelligence, Big Data, and cloud in the fiscal year 2017, while China is 
betting on AI to enhance its defense capabilities and is expected to become the world Leader in this field by 2030.

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.
Also 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.
Moreover, 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.