The Chief Justice of India may have cleared the air on India’s courts using artificial intelligence (AI) in their decision-making process, but some concerns remain. In a measured gesture, CJI SA Bobde clarified a statement he reportedly made a few weeks ago at an event, saying that using technologies such as AI could help deliver justice swiftly. The CJI had also said that such technologies would help streamline hearing of cases while enabling better court management. The statement made many experts raise concerns over the potential abuse of AI in the judicial decision-making processes — an issue that’s fodder for heated debates across the globe now — including former CJI RM Lodha, who at an event in Nagpur last week, expressed concerns over the use of AI in court proceedings.

Today, the explosive growth in machine learning and AI seems so enticing that almost everyone, from businesses to governments to savvy individuals, is tempted to try these emerging technologies in services and processes they deem fit and in requirement of some automatic processes. The abundant availability of tools — many half-baked — that claim to offer quick data-driven remedies to process woes makes matters even worse.

Bringing AI into judicial matters is a problem because it involves, among other things, the use of Big Data, which, as data scientists and rights activists have pointed out, reflect dark human biases. Using large amounts of historical data to assess what is right and wrong according to the law may seem interesting, but as a recent paper — The AI is now in session: The impact of digitalization on courts — by a team of Hungarian law experts showed, beyond the obvious ethical issues (such as human biases creeping into AI and resultant discrimination), there are economic issues also to be considered. If legal systems rush headlong into AI, it may not only end up sending the wrong people to jail, but also do so at a pace that’s dangerous and cannot be easily corrected. Machines, as things stand, now cannot exercise creative liberty while making decisions, since they rely on the data fed.

The writer is Deputy Editor with BusinessLine

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