Context: 

• This article is based on an Editorial “Why the Indian Army is embracing AI” which was published in the Indian Express. The Indian Army has been deploying Artificial Intelligence (AI) surveillance systems along its borders with Pakistan and China which include high-resolution cameras, sensors, unmanned aerial vehicle (UAV) feeds, and radar feeds which shows a path toward adoption of AI in defence.  

Enhancing Border Security: AI-Powered Surveillance for Intrusion Detection and Target Classification

• Data Collection and Analysis: The data collected from these various sources is processed and analyzed using artificial intelligence technology.
• Aim: The primary goal of AI in Defence is to detect intrusions at the borders and classify potential targets for more effective border security.

Significance of AI in Defence: Revolutionising Warfare Strategies and Surveillance Capabilities

• Positioning in Intelligent Warfare: India aims to position itself at the forefront of intelligent warfare strategies, recognizing the importance of AI in defence and military applications, including border control, comprehensive surveillance, and AI-equipped drones.
• Data Management and Enhanced ISR (Intelligence, Surveillance, and Reconnaissance) Capabilities:
  • AI in defence can process vast amounts of military data, providing actionable intelligence.
  • Supports on-field warfighters with credible intelligence.
    • Example: Project Maven of the US for counter-insurgency operations.
  • AI in defence aids physical ISR in harsh terrains and weather conditions.
• Cybersecurity:
  • AI is used for both ISR activities and as a weapon system (offensive or defensive).
  • Trained AI systems are more efficient in identifying and responding to cyber threats.
  • To combat evolving and sophisticated cyber threats that surpass human capabilities.
• Game-Changer in Various Fields: 
  • By enhancing efficiency in military logistics and supply chain management.
  • By enhancing security by detecting intrusions & classifying targets.
  • AI-equipped drones excel in day and night reconnaissance missions. They also detect enemy drones, offering cost-effective threat mitigation.
  • Lethal Autonomous Weapon Systems (LAWS) autonomously detect, select, and engage hostile targets, multiplying force effectiveness while requiring minimal personnel.

The Challenges of Implementing AI in Defense Operations

• Budget Constraints: As per Delhi Policy Group, a security think tank, the Indian military allocates approximately US$50 million annually for AI in defence spending, while China invests more than 30 times.
• Over-Reliance on Surveillance Systems: Overreliance on even advanced surveillance systems may not be foolproof as observed in the recent surprise attack on Israel by Hamas. 
• Complexity of Counter-Terrorism: Counter-terrorism and counter-insurgency operations often involve complex and nuanced situations that AI systems do not interpret easily. 
• Misidentification of Targets: AI systems may make mistakes in identifying targets, potentially leading to unintended attacks on non-combatants or friendly forces.
  • Example: U.S. drone surveillance footage has misidentified civilians as terrorist targets in the August 2021 strike in Afghanistan.
• Data and Privacy: Balancing personal data protection with AI’s benefits poses challenges and trade-offs between privacy and prosperity.
• Ethical Dilemma: Whether AI systems should have the authority to autonomously select and engage targets without human intervention.

Way Forward: Key Strategies for Advancing AI in defence and Integration in Defense Operations

• Human Accountability: Defining the extent of human involvement and responsibility in AI-driven military operations is crucial. 
• Robust Hardware and Enabling Data Banks: Such a critical infrastructure availability is crucial for AI’s success in both civilian and military applications.
• Doctrinal Variations: The extent of AI system autonomy may vary among different military doctrines, but there is a general consensus that fully unpredictable autonomous systems may not be preferred in military operations.
• Collaboration: Establish processes and practices that facilitate collaboration with research labs, academia, startups, and the private sector. 

Conclusion:

• The Indian Army’s adoption of AI for border surveillance underscores the nation’s commitment to leveraging advanced technology in defence. While the challenges of implementation and ethical considerations persist, strategic collaboration and responsible human oversight are vital for the successful integration of AI in defence operations.

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