Role of AI in Judiciary 

• Courtroom efficiency: AI tools assist in voice to text conversion, smart scheduling, case prioritization etc. aiding reduce backlogs and delays.
  • E.g. ASR-SHRUTI (voice-to-text dictation for orders and judgments)
• Legal Research and Documentation: Analyzing vast databases of legal precedents, identifying relevant statutes, and summarizing complex judgments.
  • E.g. Supreme Court Portal for Assistance in Court Efficiency (SUPACE) or Saransh for judgement summaries 
• Language Accessibility: AI-driven Multilingual Translation tools breaking the English-language barrier for litigants in regional languages and helps Democratization of Justice.
  • E.g. SUVAS (Supreme Court Vidhik Anuvaad Software)
• Predictive Analytics: Can indicate likely case outcomes, encourage out-of-court settlements and reduce court burden. 

Challenges 

• Algorithmic Bias: AI trained on historical data may reinforce biases related to caste, gender, or community.
  • It can violate Articles 14 (Equality) and 21 (Right to Fair procedure)
• “Black Box” Problem: Opaque AI algorithms make it hard to understand logic behind outputs, undermining transparency.
• Risk of "Hallucinations": Generative AI can produce fictitious judgments posing risk to judicial integrity.
• Security & Privacy: Use of AI involves sensitive legal data, raising risks of cybersecurity breaches and misuse.
• Others: Judicial responsibility may be compromised by over-reliance on technology, digital divide.