Can AI assistants reduce India's judicial backlog?
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Can AI Assistants Help Reduce India’s Judicial Backlog? #
India’s judiciary faces a monumental challenge - an overwhelming backlog of over 50 million pending cases. This staggering number not only affects individuals awaiting justice but also has far-reaching implications for the country’s economic growth and societal stability. In recent years, Artificial Intelligence (AI) has emerged as a potential solution to address this critical issue. Long-context Large Language Models excel in summarizing large documents, similar to ones typically found in legal proceedings. Digital copies of the proceedings in a lawsuit can be fed into an AI tool that allows the judges to get a summary of the key points of contention based on which they can quickly make a decision.
The Current State of AI in Indian Judiciary #
The Indian judiciary is on the path to digitization, with great strides being made to modernize the governance systems such as :
- SUPACE (Supreme Court Portal for Assistance in Court’s Efficiency): This AI tool aids judges in legal research and tracks case progress.
- SUVAS (Supreme Court Vidhik Anuvaad Software): Designed to translate judicial orders and rulings, easing the task of language translation.
- National Judicial Data Grid (NJDG): Provides case management and legal research support.
These initiatives demonstrate the judiciary’s openness to leveraging technology for improving efficiency. Integrating artificial intelligence agents such as finetuned GPT’s on top of these systems will allow judges to summarize cases within seconds rather than the typical hours spent on reading the proceedings. Furthermore, using techniques such as Retrieval Augmented Generation in conjunction with these models, judges can also get answers to targeted questions by querying external data, such as databases, knowledge bases, and web pages of the current arguments, past proceedings, and historical precedents. These can further aid in increasing the throughput of the judiciary system.
How AI Can Address the Backlog #
AI assistants have the potential to significantly reduce India’s judicial backlog in several ways:
Case Management: AI can automate case prioritization, categorization, and scheduling, streamlining the administrative process.
Legal Research: AI tools can analyze vast volumes of legal documents, suggest relevant statutes, and predict applicable precedents, saving valuable time for legal professionals.
Language Translation: Integrating with tools like SUVAS, AI can break down language barriers, making the legal system more accessible to India’s diverse population.
Document Processing: AI can summarize lengthy legal documents, extract key information, and assist in preliminary legal research.
Decision Support: While not replacing human judgment, AI can provide data-driven insights to support judicial decision-making.
Real-World Applications #
While widespread information on the use of AI in the courtroom is not directly available due to lack of provisions for mandatory reporting of the use of AI, there are a few notable cases that have captured the public attention. This indicates an the overall willingness by the judiciary system to adopt AI, and also indicates in limited measure, the value provided by adoption of such a system in day-to-day functions of the court
- In Jaswinder Singh v. State of Punjab, the judge consulted ChatGPT for insights on bail laws in cases involving cruelty.
- The Manipur High Court used ChatGPT for research in a service matter case (Md Zakir Hussain v. State of Manipur).
These instances highlight AI’s potential as a supplementary tool in judicial proceedings.
Challenges and Considerations #
While the integration of AI in the judiciary shows promise, several challenges need to be addressed:
Ethical Concerns: Ensuring AI tools remain unbiased and transparent in their operations is crucial. LLMs powering these AI systems need to be open to independent audits and security researchers with appropriate authorization, so that security vulnerabilities can be quickly identified and mitigated.
Data Quality: The effectiveness of AI models depends heavily on well-curated, high-quality data. Fortunately the digitizing effort in the Judiciary system, and the success of contemorary digital peers such as ADHAAR and UPI, etc demonstrate India’s prowess in gathering , standardizing and safeguarding large stores of personal data.
Privacy Issues: Handling sensitive legal information requires robust data protection measures. One must look towards privacy preserving approaches in AI in order to ensure a safe rollout of this technology
Infrastructure: Adequate technological infrastructure is needed across all levels of the judiciary, this will involve setting up national datacenters for hosting judiciary AI, and increased internet penetration to rural courts and panchayats in order to enable them to access said infrastructure.
The Way Forward #
AI provides a unique opportunity for developing countries to fast-track the modernization of their economies and governance systems in an increasingly globalizing world. The Indian government has shown commitment to AI development by allocating ₹5,000 crore for AI Computing Power and ₹2,000 crore to support AI startups. By onboarding government agencies to AI frameworks, the benefits are twofold
It allows these agencies to use AI to shortcut the developmental gaps in maturity and optimization of their governance systems and processes, by using systems that are inherently based on the codified knowledge of the developed nations.
It would foster the growth of indigenous AI companies, which would start initially in the market of tailoring state-of-the-art open-sourced AI models to solve uniquely Indian problems, and eventually grow to become leaders at a global stage by building and bringing to market new research, business ideas and revenues as these companies mature.
While AI might not be able to reduce all causes of delays in justice, leveraging AI is akin to hiring a superhero as a secretary to the judicial machinery.