RESETTING THE COMPASS OF INDIA-CHINA RELATIONS
The recent visit of Chinese Foreign Minister to India marked a significant attempt at recalibrating relations after four years of turbulence at the Line of Actual Control (LAC). While the visit highlighted a willingness to normalise ties, it also underscored the structural complexities that continue to define India-China relations.
Key Outcomes of the Visit
Resumption of Engagements: Both sides agreed to restart border trade at select points, direct flights, and pilgrimages such as Kailash Mansarovar yatra, reflecting a cautious restoration of people-to-people and commercial exchanges.
Economic Cooperation: Discussions were held on easing restrictions related to fertilizers, rare earths, and machinery, though concerns over Chinese FDI scrutiny in India remain unresolved.
Boundary Question: Understanding to expedite negotiations under the framework of the 2005 Political Parameters and Guiding Principles, signalling a revival of structured dialogue mechanisms.
Symbolic Signals: The meetings with India’s top leadership conveyed political intent to stabilise relations despite recent tensions.
Strategic Issues in Focus
Lingering Border Disputes: Despite the quiet border, the legacy of Galwan and Chinese transgressions has left deep mistrust that cannot be erased quickly.
Economic Asymmetry: India’s concerns about its large trade deficit with China and over-dependence on Chinese critical imports remain unresolved.
Third-Party Dynamics: China’s continued support to Pakistan, extension of the Belt and Road Initiative (BRI) into Afghanistan, and role in regional geopolitics cast a shadow on bilateral ties.
Geopolitical Competition: India’s growing alignment with the U.S. and Indo-Pacific partners contrasts with China’s strategic partnerships with Pakistan and Taliban-led Afghanistan.
Navigating the Path Ahead
Sustained Border Stability: Peace and tranquillity at the LAC must be institutionalised through confidence-building measures and transparent communication channels.
Balanced Economic Engagement: While cooperation in trade and technology is essential, India needs to reduce critical dependence and strengthen domestic resilience.
Regional Balancing: India must deepen its presence in South Asia and the Indian Ocean to counterbalance China’s regional inroads.
Strategic Autonomy: Engagement with China should be pursued without compromising India’s partnerships with the U.S. and Quad, ensuring a multi-vector foreign policy.
Conclusion
The visit marks a thaw in ties but not a resolution of core divergences. For India, managing the duality of cooperation and competition with China will remain a defining challenge of its foreign policy. A cautious, calibrated approach that blends dialogue with strategic preparedness is key to ensuring that engagement does not translate into vulnerability.
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AI IN INDIAN JUDICIARY: EFFICIENCY WITH SAFEGUARDS
The Indian judiciary faces a pressing backlog of over five crore cases, making efficiency-enhancing technologies attractive. Artificial Intelligence (AI) is being tested for tasks such as transcription, translation, and legal research. However, its use in adjudication raises ethical, legal, and structural concerns that demand a balanced framework.
Background
Kerala High Court (2024) issued the first formal guidelines on AI use in district judiciary, setting a precedent for cautious adoption.
Globally, courts in countries like the U.K., Singapore, and Canada have experimented with AI-assisted processes, but most rely on human oversight.
In India, the eCourts Project seeks to digitise judicial processes, and AI is emerging as the next logical step in this transition.
Promise and Perils of AI in Judiciary
Opportunities
Speed and Efficiency: Automated translation, transcription, and research reduce procedural delays.
Accessibility: AI-powered translation tools can make judgments available in multiple languages, improving inclusivity.
Data Management: AI can help analyse case backlogs, identify systemic bottlenecks, and streamline filing processes.
Cost-effectiveness: Reduces reliance on human resources for repetitive tasks.
Challenges
Accuracy Risks: Instances of mistranslation, hallucination, and fabricated references undermine credibility.
Erosion of Judicial Nuance: AI may oversimplify adjudication into rule-based outputs, ignoring context, equity, and precedents.
Bias and Opacity: AI systems learn from available data, which may perpetuate existing biases or deliver opaque outcomes.
Data Security Concerns: Handling of sensitive court data raises risks of privacy breaches and misuse.
Infrastructure Gaps: Reliable digital infrastructure and trained personnel are prerequisites that remain unevenly available across courts.
Way Forward
Strengthening AI Literacy
Training judges, lawyers, and staff in both utility and limitations of AI.
Judicial academies should include modules on ethics, algorithmic bias, and risk assessment.
Clear Usage Guidelines
Define permissible AI use in translation, research, and drafting.
Ensure litigants’ right to know when AI tools are deployed in their cases.
Allow litigants to opt out of AI-enabled adjudication if concerns about safeguards exist.
Robust Procurement Frameworks
Develop uniform standards for evaluating AI tools based on transparency, explainability, and accountability.
Mandate pre-deployment audits to ensure that AI adoption addresses specific judicial needs.
Dedicated Technology Offices
Create specialised units within the judiciary (as envisaged in eCourts Phase III) to oversee AI adoption, vendor compliance, and technical assessments.
Encourage collaboration between technologists, legal scholars, and ethicists.
Human Oversight as Non-Negotiable
Retain final decision-making with judges, ensuring AI remains an assistive tool, not a replacement.
Establish review mechanisms to vet AI-generated content before integration into official processes.
Conclusion
AI offers transformative potential to modernise the judiciary, but unchecked use may compromise fairness, privacy, and judicial independence. Adoption must be guided by ethical frameworks, transparency standards, and strong human oversight. Ultimately, the goal of AI in the judiciary is not just efficiency, but to strengthen public trust and uphold the constitutional promise of justice.
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