Relevance of the Topic: Mains: Detailed question on scope, and challenges regarding AI use in the Defence sector.
AI and Defence Integration in India
- India is at the nascent stage of integration of AI with military technology. One such example is the Indrajal drone defence system.
- Institutional framework: India has launched an institutional framework for inducting AI with the military in 2022.
- Defence Artificial Intelligence council chaired by the Defence Minister of India to to provide necessary guidance and structural support.
- Defence AI Project Agency (DAIPA) has been created under the Chairmanship of Secretary Department of Defence Production (DDP) for enabling AI based processes in defence Organisations.
- Listing priorities: In 2022, the government published a list of 75 priority projects related to using AI for defence; these focused on data processing and analysis, cyber security, simulation and autonomous systems, particularly drones.
- AI embedded centers in armed forces: AI-application centres embedded in each of the three armed-service branches – at the Military College of Telecommunication Engineering, Mhow (Army), the INS Valsura (Navy) and Air Force Station Rajokri (Air Force).
Scope of AI in Defence sector
- Autonomous systems:
- Defence: AI driven autonomous systems can aid armed forces in difficult operations and prevent casualties. E.g., Indrajaal system on drone defence is based on an autonomous AI system; AI-enabled Robot Sentries.
- Offence: Can be used to conduct precision strikes and support armed forces in offence. E.g., AI-powered killer robots and Armed UAVs; AI-embedded guided missiles (determines target’s range and adjust flight patterns without human intervention).
- Surveillance: AI-embedded radars, satellites, software-identification systems can aid in geospatial analysis, detection of illegal or suspicious activities and alerting authorities. E.g., Indian Army uses facial recognition system ‘Project Seeker’ for monitoring, surveillance, and garrison security.
- Cyber-security: AI can be utilised to timely detect and launch a counter attack on cyber attack.
- Data Analysis: Defence data is complex like intelligence data, enemy movement, previous trends and strategy analysis can be done effectively with use of AI.
- Predictive maintenance: AI can be utilized for predicting the maintenance needs to prevent failure during crucial operations.
- Simulations and training: AI can generate multiple and complex hypothetical situations to train soldiers and operatives for unpredictable threats.
Risks and Challenges Associated:
- Security risks: AI based defence technologies are susceptible to hacking and cyber attacks leading to catastrophic results.
- Ethical questions: AI based decision making in defence can cause collateral damage creating questions of accountability in case of unintended harm.
- Interoperability issue: Integrating AI across diverse military platforms (aircraft, naval ships, ground vehicles) is complex. Existing systems might not be compatible, limiting its effectiveness.
- Bias and poor data quality: AI systems rely on data for training, and if the data is biased or incomplete, AI models can produce flawed decisions. E.g., biased training data could lead AI inappropriately identifying enemy targets based on incomplete intelligence.
- Legal issue: AI based operations lack the global consensus, as AI is not subjected to the Geneva convention, unlike traditional wars and conflicts.
Conclusion: AI in the military offers significant potential for enhancing capabilities, including autonomous systems and cybersecurity. However, it also faces challenges such as security risks, ethical concerns, and technical limitations. A balanced approach involving robust research, international cooperation, and ethical considerations will ensure that AI serves as a strategic asset for defense.