Implementing Artificial Intelligence in Indian Army – A Spinning Exercise
Artificial Intelligence (AI) is shaping and changing all industries across the world. Global spending on AI touched $118 billion in 2022 and is projected to surpass $300 billion in 2026. Although we are still at the ‘Narrow AI’ stage, where AI can outperform a human in only a narrowly defined and structured task, it still has enormous utility and potential. Similar to other industries, the power of AI has led to militaries around the world increasingly integrating AI into warfighting systems. AI is currently being incorporated into command and control, intelligence, surveillance, logistics, healthcare, information warfare, cyber warfare, training and simulation, autonomous systems, and lethal autonomous weapons.
The Indian Army also needs to work towards harnessing the potential of AI. On July 11, the Indian Defence Minister, Rajnath Singh, launched 75 newly developed AI technologies during the first-ever ‘AI in Defence’ (AIDef) symposium and exhibition organised by the Ministry of Defence in New Delhi. Speaking on the occasion, Mr Rajnath had said, “Timely infusion of technologies like AI and Big Data in the defence sector is of utmost importance so that we are not left behind the technological curve and are able to take maximum advantage of technology for our services. AI is undoubtedly a force multiplier, but its adoption has many challenges that the Indian Army must overcome to fully utilize its potential. This brief will look at some of the key requirements and recommend steps to be taken by the Indian Army to harness the power of AI effectively.
Key Requirements for Effective Application of AI
Artificial Intelligence (AI) is a broad field that involves the creation of intelligent machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. There are several different approaches to creating AI systems, but the most common method is through the use of machine learning algorithms. Machine learning is a type of AI that involves training a computer program on a large dataset, allowing the program to learn from the data and make predictions or decisions based on that knowledge.
Some of the critical requirements for the effective application of AI:
Data – Quality data is the most essential requirement, as AI algorithms require large amounts of high-quality data to train on. ChatGPT, the AI chatbot that has taken the world by storm, was fed some 300 billion words systematically scraped from the internet. In military applications, this data would need to be obtained from various sources and would have to be cleansed, transformed, and aggregated to ensure that it is suitable for use. The data must also be specific to the operating environment, e.g., data for a desert region will not be relevant when creating an algorithm for high-altitude areas and do we have the mechanism to check the sensitivity of the Data.
Interoperability – AI systems need to be able to exchange data and work seamlessly with other systems in order to be useful in military contexts. This may require the development of common data standards, Application Programming Interfaces, or other interoperability solutions. In addition, the three services will need to be fully networked with each other to ensure interoperability.
Computing power – AI algorithms require significant computing power to process and analyze large amounts of data. This may involve the use of high-performance computing systems, cloud computing, or other advanced computational resources. An added complication is that a large amount of data will have to be processed at the edge (at or near the user). Therefore, sufficient computing power will have to be made available for making decisions in a contested battlespace environment.
Security – AI systems used in the military need to be secure and protected against cyber threats and attacks. The adversary could use AI to probe for weaknesses in our systems and corrupt the integrity of the data on which our AI systems depend. This will require implementing measures such as encryption, firewalls, and secure data storage using AI solutions.
Ethics and Responsibility – The use of AI in the military raises ethical and legal concerns, particularly regarding the level of autonomy that can be granted to AI systems. There is a need to formulate and adopt strict ethical guidelines while ensuring that the implementation of AI does not get unduly delayed due to these considerations, and we fall behind our adversaries.
Expertise – Developing and applying AI will require a multidisciplinary team with expertise in areas such as AI, computer science, data science, cybersecurity, ethics, and military operations. Some of this expertise may not be available in-house in the military, and civilian talent may have to be imported.
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