Mistaking digital progress for AI?

Nepal’s judiciary has embraced the digital age, evident in its adoption of online cause lists, scanned records, SMS notices, virtual hearings, and digital summons. However, this progress does not equate to entering the age of artificial intelligence (AI). Public discourse often conflates various technological advancements, treating online cause lists, scanned records, and AI as if they belong to the same stage of reform, which is inaccurate.

A scanned record is not automation, and a video hearing is not artificial intelligence. Similarly, a template that automatically fills in a reference number does not constitute machine learning. For a meaningful debate on technology and justice in Nepal, an honest assessment of the system's current standing is crucial. The movement towards digital systems has been gradual and often driven by necessity, with planned judicial reform beginning in 2004 and later guided by a Long-Term Information Technology Master Plan.

Digitalization involves making court information and services accessible through digital systems. Automation takes this further by enabling systems to perform repetitive tasks based on fixed rules, reducing manual effort but without cognitive abilities. AI, on the other hand, represents systems capable of analyzing records, assisting legal research, transcribing hearings, summarizing documents, translating materials, or identifying patterns under human supervision. In Nepal, these advanced AI capabilities are still largely in the realm of future possibilities rather than current operational realities.

Significant steps have been taken, including the Supreme Court's introduction of automated case management in 2023 to enhance transparency and reduce manual influence. Chief Justice Dr. Manoj Kumar Sharma's reform agenda actively promotes e-courts, virtual hearings, electronic case files, live proceedings, and audio-to-text systems. Feasibility studies on AI, blockchain, and machine learning are also underway, indicating a forward-looking approach, even as the practical implementation of AI remains a distant goal.