Pakistan's judiciary boosts case throughput 6.3% with custom GPT-4 tool

The buried detail is methodological: Sultan Mehmood is an economist, not a computer scientist or legal technologist, and the study was run through the New Economic School. That framing matters because it means the evaluation criteria prioritized systemic throughput and institutional capacity over the narrower benchmarks AI labs typically use to assess legal reasoning quality.

This story is largely disconnected from recent activity in our archive, which has no prior coverage of judicial AI deployments or LLM adoption in South Asian public institutions. It belongs to a slower-moving thread about AI in under-resourced government systems, a space where evidence of actual deployment outcomes is still sparse. Most coverage in this area has been speculative or cautionary, so a peer-reviewed trial with a measurable resolution metric is notable precisely because it is rare. The Pakistan case also sidesteps the liability and due-process debates that dominate Western judicial AI discussions, which reflects a different set of institutional constraints rather than a more permissive attitude toward risk.

Watch whether the Pakistan judiciary publishes case-level data or a replication dataset in the next 12 months. Without that, independent researchers cannot verify whether judgment quality held across case types or only in the lower-complexity matters most likely to resolve quickly anyway.