AI And Evolution Of Warfare – OpEd
Artificial intelligence (AI) is altering our ways of life and statecraft. Warfare is no exception to this evolution. As military forces around the world are looking for cutting-edge technologies to make themselves more war-efficient in waging wars, new opportunities and challenges are emerging in this domain. Enhancing warfighting capabilities is not the only driver behind developing AI technologies for military applications, it is also opening new avenues of conflict management by providing complex simulated results with great accuracy.
This unprecedented potential of AI in warfare demands a closer examination of some use cases and examples of how different states and defense industry players are exploring and adapting AI to change the orientation of modern warfare. This change is not limited to military hardware alone. Due to the limited scope of this op-ed, only AI’s fusion in various aspects of aerial warfare has been discussed.
Air power is paramount for any military force and AI is ushering changes in this domain which hitherto were unthinkable. Spectrum warfare is the key to getting air dominance but it is a very complex, expensive, and technically daunting affair due to the ever-changing situation in air combat. Identifying and isolating enemy aircraft electromagnetic signatures has always been a primary goal for any air force or Air Defense System (ADS) guarding any sensitive installation on the ground.
AI can help locate the unique signature of a radio or radar signal that’s emitted by a particular aircraft within the entire electromagnetic spectrum. Once this signature is known and the aircraft’s exact location is traced, its signal, and communication can be jammed or its location can be passed to ADS to neutralize the threat by shooting down the aircraft. Apart from aircraft, AI can also help in accurately identifying strategic threats like ballistic missiles and can help identify missiles based on their specific electromagnetic signature apart from calculating their trajectory.
With this information, a Ballistic Missile Defense (BDM) system can direct countermeasures into the atmosphere to neutralize incoming ballistic missiles. AI’s use for ADS/BDM is experimental phases mostly. In 2020, Naval Post Graduate School, located in California, USA initiated a project to study the use of AI in a time-sensitive ADS/BDM environment. Specifically, this project studied current and future AI applications to the AMD kill chain with a Model-Based Systems Engineering (MBSE) approach. Following this approach, the ADS/BDM kill chain was established by allocating time to the various kill chain functions and decisions, based on the response time left after the early detection of an aerial/ballistic missile threat.
In such a complex and time-bound situation, efficiency in the decision-making cycle during a military conflict is critical and can alter the outcome of the war. This leads to a prudent question; how does AI affect this decision-making cycle to put military commanders in an advantageous position during a conflict?
Decision-making is a function of timely and precise analysis of data gathered by a military command center or base through a network of interconnected nodes of ground-based sensors, satellites, airborne radars, computers, communication devices, and personnel spread across the theatre of war. Before analysis, this data must be collected, stored, cleaned, and sorted. Then it is fed into an AI modeling system where specialized algorithms run complex simulations and permutations to conduct a war gaming level exercise within minutes to assist the commanders in seeing a more precise larger picture of the battlefield from tactical, operational, and strategic lenses and also present actionable insights based on data. Based on these insights, new operational planning with enhanced accuracy becomes possible. Ongoing operations can be reoriented based on constant monitoring of the battlefield through an AI-based real-time situational awareness model.
Another major application of AI in aerial warfare enabling UAS and drone swarms for Intelligence, Surveillance, Reconnaissance (ISR), and ground strike roles. UAS can operate independently and can perform ISR without human intervention. Drone Swarm is an interlinked group of UAS each carrying small payloads, each drone can independently communicate with any other drone in the swarm to coordinate their actions to achieve a common goal which can be both ISR and strike. In the case of a single UAS, AI can also help control autonomous weapons systems that can select and engage targets based on predefined rules of engagement.
The above discussion leaves no doubt that the integration of AI in air defense platforms is dependent on data mining and sensor fusion. This is the primary challenge for any military force looking to seek AI-based wartime solutions to enhance decision-making efficiency and effectiveness. Without a secure and fast communication network and world-class data mining and cleaning services in war theatre leveraging AI will remain a distinct dream.
If we look at the geopolitics of AI for military use, India launched its first national strategy for AI in June 2018 at roughly the same time that an AI task force convened by the government delivered defense-specific recommendations. Those included the creation, effective in 2019, of a high-level Defense AI Council and a Defense AI Project Agency. In 2021, the Indian Army demonstrated an AI-enabled swarm of 75 aerial drones and used AI for intelligence, and surveillance operations. Responding to Indian steps, PAF despite its limited resources, established “The Centre of Computing and Artificial Intelligence” in 2018.
AI is changing warfare by making time-sensitive decision-making accurate and early. Such decisions, based on well-trained AI algorithms generated by well-prepared data gathered by well-connected secure networks give tactical, operational, and strategic advantage to military commanders in a war theatre. Currently, the use of AI is limited in aerial warfare in defensive capabilities like ADSs/BDMs while drone swarms have become a reality not only in the world but also in the region. This is an encouraging sign that PAF is also developing its novel AI-based solutions in this emerging domain to ensure maintaining technical competitiveness and operational effectiveness.
