“Victory Adorns the Crown of Most Versatile”. Mankind has witnessed many great battles and wars, planned and fought by great strategists and warriors, leading to the rise and fall of empires or change of world order. Several lessons drawn from past wars by military commanders, scholars and strategists have been proven, amended or refuted in the subsequent ones eventually leading to the emergence of Principles of War. Few of these principles unsurprisingly have stood the test of time and have commonly been emphasized by all the military pundits from Chanakya to Clausewitz. Maintaining supremacy of force before entering a conflict is one such principle. Developing and employing technological advancements in war dynamics to maintain the supremacy of force differentiates the victorious from the vanquished.
The examples range from the victory of Saracen forces over the Western Crusaders in the battle of Hattin in AD 1187 to the victory of Azerbaijani forces in Nagorno-Karabakh, from Alexander’s conquests to the victory of the allied forces in World War II, from the occupation of Central Asia and China by Ghengis Khan in AD 1227 to establishment of European colonies post-industrialization era and the list goes on and on. After the World Wars and the power struggle throughout the twentieth century, the world order was established in favour of the technologically advanced forces however, in the last three decades there have been prodigious technological advancements in the field of Artificial Intelligence (AI), Machine Learning, Big Data and Robotics, and its application to the military domain has a potential of making a paradigm shift in contemporary warfare (covert or overt) spanning into psychological, physical and cognitive domains. This essay focuses on understanding the infinite capabilities of AI in emergent warfighting and explores the future roadmap for possible applications relevant to India.
Emerging Warfare and AI
AI has the potential to emulate human intelligence and associated capabilities like perception, planning, problem-solving, reasoning, and learning to improve upon these skills further. Better-trained AI algorithms have displayed remarkable potential in social intelligence and creativity. AI has already outweighed human efficacy in big data analytics, pattern recognition, evaluation, prediction and automation applications. Another application of AI is Machine Learning (ML) wherein machines can learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data. AI systems can get progressively better through ML. Robotics is the conception, design, manufacturing and operation of intelligent machines called robots to undertake jobs assigned by humans. AI and ML together with Robotics create an advanced machine capable of executing a set of actions once automated by human control with precision and what’s more impressive is its capability of getting better at these actions.
Just like the changing facets of technology, the face of war is also ever-changing and even unpredictable at times. Till recently many pundits had predicted that large-scale conventional wars between states involving ground invasion of one state by another is a thing of the past and that future wars would be short, ambiguous and indecisive, fought in a complex environment greatly affected by non-military interactions such as media, perception of international community and business interests emerging from intertwined nature of modern economics. While the former has been proven otherwise by the ongoing Russia-Ukraine conflict which is bordering between a multi-state direct conflict and a special military operation by one state to defend the interests of another, the latter holds good and has been validated in several conflicts. The future wars or conflicts would not be limited to the soldiers on the battlefield in one realm but would encompass men and machines operated manually or autonomously engaged directly or indirectly in space, land, sea surface and sub-surface. It would involve strategies executed and entrenched to achieve supremacy through economic, political and psychological effects including coercion, subversion, and disruption of command structure in a politico-military-economic system. Cyberspace warfare is characterized by the use of computer technology for accessing, monitoring and incapacitating of opponent’s military, economic and civil infrastructure assets, research and development facilities and command and control networks Information Warfare is characterized by perception management and psychological operations through propaganda and information management in all forms of media would form an integral part of future conflicts. Fighting such a war would demand seamless theatrical Network Centric Operations (NCOs), Command, Control, Communication, Computer, Intelligence, Surveillance and Reconnaissance (C4ISR) Operations and employment of all available technological means for achieving supremacy in Cyber warfare and Information warfare.
AI the captivating pursuit of computer-aided machines to match human intelligence and capabilities, albeit with greater speed and precision seems to be just the right answer to all the challenges posed by future warfare. It appears promising in achieving the classic Clausewitzian Trinity of warfare viz. enhancing combat capabilities, reducing losses to own forces and gaining public opinion. AI holds vital promises for all key components in the tactical level of multi-dimensional warfare with its key applications as data analytics for intelligence gathering and predictive assessment, cyberspace dominance, economic belligerence, C4ISR and NCOs, autonomous detection-acquisition-classification and engagement of targets, deployment of autonomous unmanned platform for specific missions, predictive maintenance and efficient war logistics to name a few. Considering this potential of AI, it is natural to explore the applications of AI in the military domain and how it is relevant to India.
AI Applications in the Military Domain
Threat monitoring, Battlefield Awareness and Predicting Enemy Course of Actions
ISR (Intelligence, Surveillance, and Reconnaissance) operations are crucial for threat monitoring, situational analysis and predicting enemy Course of Action (CoA). Using AI, data gathered from assets dedicatedly deployed for intelligence or from social media and the internet may be processed to identify relevant information and gather intelligence. Unmanned systems dispatched along predetermined paths may be employed for surveillance and reconnaissance. Neural network-enabled fusion and analysis of multidimensional data inputs like imagery, weather, terrain, enemy positions, force composition, movement patterns etc. would lead to better Battlefield Awareness. The available data about the enemy may be trended, correlated and processed to extract information like statistical characters of the enemy, disposal and deployment of military assets, geo-political dynamics etc. and may be used to undertake predictive analysis to forecast enemy course of action. AI’s already proven efficiency in the fields of image recognition, recommendation systems, prediction systems, anomaly detection and language translation would be significantly useful in this application.
AI for Network Centric Operations (AINCO)
Superior C4ISR through effective NCOs would be the deciding factor in the multidimensional conflicts of the future. For this, the Combat Management Systems would be required to have intra and inter-platform networking, integration and fusion of sensors and communication systems to create a Common Operating Picture and a Decision Support System (DSS) which would enable the Command-and-Control hierarchy to undertake effective threat evaluation, identification of hostile intent and deployment of weapons with enhanced precision and reduced latency. Such a Combat Management System would require extensive application of AI and efficient ML algorithms trained over a large data set generated in numerous military exercises and operations.
Strategic Decision Support Systems
Victories in battles are mostly attained through tactical moves by the commanders based on insights, training, exercises, doctrines and experiences. AI’s efficiency in the collection and processing of data from multiple sources in quick time is irrefutable. Unlike humans, it is also immune to external factors like the stress of the situation, weather, emotions and prejudices. For efficient Multi-Criteria decision-making tasks, AI-based DSS trained over statistics from past battles, decisions of great commanders, scientific calculations of force levels, data from regular military exercises and situational intelligence seem to be the obvious choice. This would complement human capability, lessen response time and may even be employed to suggest pseudorandom yet efficient tactical manoeuvres in battles to achieve an element of surprise. The combination of humans’ ethical understanding and AI’s quick analytical abilities can be a game changer in Strategic Decision Making.
Electronic Warfare
Battlefield dominance largely depends on achieving EW supremacy. With the heavily interleaved civilian and military application of the RF spectrum, the application of EW measures is not limited to the battlefield but also in ISR missions and politico-strategic applications. Integrating AI into EW systems has promising applications in improving intelligence through analysis of voluminous data available on the RF spectrum, accurate classification of signals, fingerprinting of enemy sensors, decryption of intercepted communication especially where the translation is required, developing a clear picture of the EW environment, identification and labelling of friend, foe and neutral forces and identification of enemy HVUs or Command Centers through the interaction of various units or nodes. Completely unmanned AI-powered automated EW decision-support system, capable of independently identifying and selecting targets such as radio stations, communication systems, radars, satellites, and other facilities, and deciding how to suppress them and what countermeasures to use may be deployed at strategic locations on land, in open seas or space.
Unmanned Operations
The use of unmanned systems especially Unmanned Aerial Vehicles (UAVs) has proven to be extremely effective in the conflicts of the past decade. Building upon that, the development of autonomous unmanned physical systems has taken centre stage. AI has the potential to increase the speed, persistence, reach and endurance of unmanned systems in the air, on the ground, underwater and in space. It can enhance coordination in both human-machine teams and between multiple unmanned systems. AI-enabled autonomous systems could also allow for a broader range of missions in denied and hostile environments, like surveillance, detection, classification, protection of own forces, sacrificial missions, precise targeted killing, explosive neutralization etc. all while minimizing the risk to military personnel. In naval scenarios, deployments of Unmanned Underwater Vehicles (UUVs) equipped with SONARs along with or independent of conventional surface or sub-surface groups can be explored for sub-surface surveillance of territorial waters or choke points. Monitoring and recording of signatures of all ships and submarines by the UUVs during peacetime and using it for the classification of enemy signatures during the conflict using AI is yet another promising application. Cooperative and collective data relaying, processing and analysis supported by cloud intelligence employed for enemy detection, defensive systems activation and weapon delivery mechanisms also have greater potential in the underwater domain. In the domain of air operations, this concept is already in the deployment phase in the form of what is known as embedded autonomous Swarming Drones. For the border security forces, AI-powered systems could be the tireless omnipresent security sentry with reduced human involvement and risk. Volatile or sensitive borders requiring a high state of readiness, especially on a vast landmass, harsh terrain, severe weather, and inaccessible locations may be equipped with sensors like gravity gradiometers, motion sensors, infra-red sensors, hyper-spectral imagery sensors, surveillance radars etc. which are integrated with automated systems capable of analysing the data, identifying the threat and executing the appropriate response out of the available pre-defined options. Even the mundane, time-consuming, high risk and repetitive nature jobs like patrolling can be offloaded to AI-powered robots.
Autonomous Weapon Systems
While the use of AI for deployment of autonomous weapons and even the use of autonomous weapons itself is legally controversial and morally questionable but still the potential of AI in this application is unquestionably immense. Loitering Munitions commanded by an AI-based Decision System with or without a man in the loop can be deployed in a designated area to find, identify and engage enemy assets with a reaction time better than any other possible means. UUVs can find a similar application in sub-surface warfare especially near choke points or in enemy harbours. AI-based systems can also pioneer the conversion usage of civil shipping for Grey Zone Operations (GZOs) using retrofitted modular silos interfaced with autonomous control systems and data linked with military satellites. This can also increase the reach and magnitude of firepower of surface combatant groups and also act as a contingency measure in case of loss of warships.
Information and Cyber Warfare
Sun Zu’s principle of war about making the enemy believe what is contrary to reality may not have been envisioned for the present era but it couldn’t have been more relevant than in today’s context. Controlling the narrative of war, manipulating the information available to the enemy and managing the perception of the global community is the key to determining the outcome of any future conflict. Relying on human capabilities alone to achieve this is a losing strategy. Various specific requirement-based applications powered by AI could be used for perception management through controlled narrative in media, especially on social media. Targeted propaganda and psychological operations to incite civil unrest, proxy war, insurrection or discontent could be achieved by managing the information available to the masses. Cyber Warfare is a complete realm in itself with potential ranging from completely determining the result of a conflict to having its manifestation on the battlefield. This domain is very dynamic and progressive with new technological advancements happening in quick succession but the use of AI in this domain is a singular constant in all emerging technologies. AI-enabled tools can be employed for anomaly detection in network activity for timely deployment of defensive measures and for developing offensive capability more comprehensively and dynamically. The cyberattack means disabling economic structure, industrial networks or power infrastructure, misleading military systems, generating social unrest through misinformation using deepfakes etc. can force the enemy into submission without even engaging on the physical battlefield. On the battlefield, cyber-attacks can be employed for infiltrating, disrupting or even obtaining control of enemy military networks employed for sensor data exchange, logistics management or weapon control. Such an attack carried out pre-emptively can severely deter the tactical ability and will of the enemy to engage in a conflict.
Training and Induction
Various Military training simulation software have been in use for some time now especially for training the soldiers on the weapons and sensors and for conducting war games. However, the involvement of AI in this could increase its efficiency multifold as the scenario would evolve based on the progress of the personnel during training. The war games would become more intense as the inclusion of multi-dimensional inputs would become feasible. The use of AI for the promotion of job opportunities in defence forces, identification of volunteers, streamlining of selection and training process and human resource management as prevalent in the contemporary industry is yet another promising prospect.
Logistics Management
Big data analysis has had a revolutionary impact on the business models of contemporary industry and defense logistics stands to benefit from this development. The AI algorithms being employed for consumer pattern analysis, demand forecast, resource management/ optimization, inventory management, warehousing, accounting and automated initiation of procurement action based on pre-defined criteria can be tailored for defence applications to ensure optimal inventory levels sans exorbitant carrying cost.
Predictive Maintenance
Predicting when equipment will fail can not only prevent the impact of failure on the overall mission but also prevent the failure itself by undertaking preventive maintenance. AI-powered algorithms fed with embedded sensor data, documentation, performance data and equipment history can aid predictive maintenance, minimise breakdowns and avoid unnecessary periodic routines.
Global Perspective
The potential of AI and Robotics to trigger a new Revolution in Military Affairs (RMA) has been recognized globally and it is directly proportional to the capability of contemporary industry to develop autonomous systems. At present, there are no truly autonomous systems in use but several systems like UAVs, UUVs, Drones, Loitring Munition etc. developed primarily by NATO, Russia and China are using AI, ML or robotics in one form or another. Globally, a significant amount of R&D is being done on autonomous systems. Russia has highlighted its intention to pursue AI development vigorously to maintain the global balance of military power by developing AI-based robots, anti-drone systems, border protection systems and EW systems. It is believed that the Russian EW system Krasukha employs AI to identify the high-value units or command centres based on the pattern of communication between various nodes. China is giving huge impetus to AI-enabled autonomous systems which is evident from its ambitious project for the development of an AI-enabled cruise missile system. High-level support for R&D in robotics and unmanned systems has led to a myriad of institutes cropping up within China’s Defence Industry. In the hopes of winning the AI battle, the Department of Defense of the United States of America in Feb 2022 established the Chief Digital and Artificial Intelligence Office (CDAO) which is responsible for the adoption of data, analytics and AI to generate decision advantages from the boardroom to the battlefield. It integrates the Joint Artificial Intelligence Center (JAIC), Defense Digital Services (DDS), the Chief Data Officer and the enterprise platform Advana into one organization. With a well-structured organization, a healthy budget and a clear future roadmap the US already has AI-based projects deployed in the field like Project Maven, some projects in the testing or improvement stage like DARPA’s Squad X Experimentation program and several other projects in the development stage. The F-35’s Autonomic Logistics Information System by USAF is already an example to emulate in military logistics. The US has invested heavily in the development of Precision-Guided Munitions, Stealth Weapons, Intelligence, Surveillance and Reconnaissance (ISR) systems, robotics, autonomous systems, human-machine collaboration, and cyber and electronic Warfare.
Indian Perspective
India has traditionally been the importer of defence technology due to higher impetus on basic infrastructure building for social causes and less budget allocation for research and development on military technology. In the last few years, there has been a great thrust on Indigenous manufacturing and some focus on research and development as well, but AI tech and its applications in the defence sector are still at a very nascent stage. India’s current AI industry is estimated to be only about 180 million dollars annually. Notwithstanding, the importance of AI has not gone unnoticed and important initiatives have been taken like the appointment of the Defence Artificial Intelligence Council (DAIC) as the apex body, the formation of the Artificial Intelligence Task Force and the allocation of a dedicated budget of 1200 crores for five years for AI-based projects. With the initiative from Hindustan Aeronautics Limited (HAL) and Bharat Electronics Limited (BEL), a ‘not for profit’ company ‘Innovations for Defence Excellence’ (IDEX) was formed to work with AI incubators, designated Centre of Research Excellence (CORE) and International Centres of Transformational AI (ICTAI). The Department of Defense production constituted a task force in Feb 2018 to study the use of AI in Defense Applications and tasked it with flagship projects namely AINCO, Family of Robots and Center for AI and Robotics (CAIR). CAIR has been working closely with the Armed Forces on projects like Multi Agent Robotics Framework (MARF), Snake, Legged Robot, Wall Climber, and Unmanned Ground Vehicles and has also developed the Network Traffic Analysis (NETRA) system. Some other uses of AI and other niche technologies in armed forces are Project Beehive by the Corps of Electronics and Mechanical Engineers (EME) for predictive maintenance, use of Natural Language Processing for repairs and Virtual Assistant for data entry and recording. Indian Naval Maintenance Authority (INSMA) has a similar AI-based application for preventive maintenance deployed in its recently launched Unified Maintenance Module (UM2).
Challenges
India, in its present position, is striving for economic development to provide human security and a better quality of life to its people. Therefore, the budget allocation for the defence sector is not usually very generous. The technology development in the defence sector is also marred by bureaucratic prevarication, risk averseness, changing qualitative requirements, occasional corruption charges, political intervention, and improper planning. All these challenges would naturally be encountered in the development of AI-based military technology. Additionally, some AI domain-specific challenges are miniscule access to actionable data, strong data network, reliable repository and lack of regulations for data, availability of resident subject experts, low industrial participation and extortionate cost of imported technology. The contribution of leading Indian IT companies in the development of AI and ML has been insignificant despite their competence in the design and implementation of cutting-edge software applications.
Way Ahead
Considering the initiative and need-driven diversified emergence of AI utilisation for military applications in India and the lack of robust organizational structure and generous budget allocation thus far, the Indian Armed Forces need a bottom-up approach in the immediate future for bridging capability and resource gaps and preparation of a framework for the development of the necessary application to keep pace with potential adversaries. In consonance with Niti Aayog’s recommendations, Integrated HQs MoD and respective commands should have dedicated directorates with sanctioned manpower to implement sustainable AI and ML solutions through collaboration with stakeholders at optimum prices within defined timelines. Dedicated panels with members from armed forces, PSUs, R&D Organizations, academia and industry should be formed and tasked with the generation of awareness and academic interest in students, identifying potential and integration of selected ideas and human resources in manufacturing facilities. Building in-house expertise to have a better understanding of AI and its applications also needs immediate attention and accordingly, the course curriculum of premier defence institutes like INA, NDA, MCEME and other specialist training schools should be revised.
In the medium term, India needs to implement sustainable measures for the indigenous development of AI technology for defence applications. The starting point would be the identification of mission-specific military systems meriting the focus of AI investments, curtailing the imports to encourage indigenous development and enriching the understanding of the design philosophy and algorithms of AI-embedded military systems. The next step would be to gradually impregnate the startups, MSMEs and R&D organisations with small-scale projects and monitor them closely through dedicated central coordinating bodies like DAIC and IDEX. Once optimal know-how and competence are achieved within the country, dedicated projects may be assigned to DRDO, CAIR, Weapons and Electronics Systems Engineering Establishment (WESEE), PSUs and selected industries. To increase the deliverability of these projects, avoid procedural delays and have better control over the Budget and Delivery Schedule, a dedicated organizational structure with a streamlined chain of command, the reduced bureaucracy of non-specialist civil servants, insulation from political intervention and apex-level supervision would be required. The first of these could be projects like integrating AI capability with available indigenous robotic unmanned vehicle technology like Daksha, Muntra and Adamya and Integration of AI with indigenously developed Command and Control systems like CMS by WESEE which is already integrated with several battlefield/ maritime sensors. These projects could be accelerated and improved by harnessing the advantages of Collaboration with world leaders in AI/ ML technology with due caution towards preventing disclosure of equipment data to external agencies.
In the long term, the approach has to be top-driven, structured, well planned and sustained. Towards this the government should begin with the introduction of AI and ML-specific courses in IITs, NITs and Centres of Educational Excellence for the creation of the technical workforce, guided expertise building and generation of credible data. The young human resource available in the country which presently is the second largest after China, works for India’s advantage in this aspect. Government-driven generous funding for research and projects by start-ups, MSMEs and academic institutions with clear statements of requirements and well-defined timelines, further supported by venture capitalists in the private sector would be the next requisite initiative. The government and the armed forces should become stakeholders in the development of AI technology rather than merely being the buyers or users. Towards this deputation of suitable government officers to research labs with good career prospects, encouraging the officers with expertise in the domain and opening avenues for lateral entry of personnel with expertise would be required. The government also needs to ensure that the research facilities have access to quality data which is essential for developing AI and ML capabilities. To ensure this, necessary legislation, MoUs with data handling organisations, optimum transparency and collaboration with international allies would be required. Once significant progress is made in indigenous technology, alliance with international partners on equal terms and export of technology would make the progress sustainable and profitable.
Conclusion
The Balance of power since world wars has always tilted in favour of nations with superior economic, military, industrial and technical leverage. In modern warfare, superiority will be achieved with military strength complemented by a strong economy, immense industrial capacity and deeper diplomatic outreach, ability for collection and accurate processing of multisensory diverse data to facilitate threat perception and decision making under dynamic multiple threat environments, Synthesis of mission-specific intelligence regarding strength and weaknesses of the enemy and subsequent rapid response mechanism and prediction of the future course of action by the enemy, Reduction in human casualties by use of unmanned systems including localized swarms for accurate reconnaissance, precision targeting and strike and post-strike damage assessments for assured destruction/ effects — at minimum cost, Dominance in information and cyber warfare, perception management, psychological operations and economic warfare, Automated maintenance/repair to reduce downtime of equipment and Maintenance of optimum operational logistics.
The application of AI and robotics to military objectives for national security promises all this and much more. India with vast and relatively young human resources which has already made a name for itself in computer programming and corporate leadership has a bright future in the swift development of AI capabilities. The ball has been set rolling in the right direction with Government think tanks, Niti Ayog, DAIC and IDEX synergizing for building of robust ecosystem at the national level and with the launching of the Naval Innovation and Indigenisation Organisation (NIIO), Naval Technology Acceleration Council (N-TAC) and Technology Development Acceleration Council (TDAC) in the Indian Navy. Now needed is continued focus on maintaining sustained efforts for developing the AI and robotics capabilities for military applications to achieve not only self-reliance but also global dominance in this field.
Title image courtesy: Indian Navy
Disclaimer: The views and opinions expressed by the author do not necessarily reflect the views of the Government of India and Defence Research and Studies
