2 min read
Called the Xiao Zhi 3.0 or Little Wisdom, the justice AI has already assisted a trial of 10 people that failed to repay bank loans
We have all heard about AI tools assisting humans with their assignments and office work, but courts in China have taken things a step ahead. A local court in the city of Hangzhou, China has started using an AI judge assistant program to provide instant justice.
Named the Xiao Zhi 3.0 or Little Wisdom, the AI tool first assisted in a trial of over 10 people that were unable to repay their bank loans.
The new AI tool makes the Chinese justice system a lot faster since it can deal with all small and daily life cases.
Solving this recent court case with over 10 people would have taken around 10 different court sessions and weeks worth of time. Xiao Zhi on the other hand resolved all ten cases together and delivered a decision in just over 30 minutes.
Courts are known to have a bunch of repetitive statements such as court procedure announcements, Xiao Zhi has also overtaken that job and announces the court procedure during hearings.
Xiao Zhi also collects case information by listening to testimonies, analyzes case materials and even verifies them through its database and intelligence.
Currently, the Xiao Zhi is mostly being used in financial disputes, but similar AI tools are being used in other Chinese courts for settling traffic disputes.
Shitong Qiao, professor of law at Duke Law School, speaking about AI said that “I can see the temptation for Chinese courts to adopt AI even in criminal cases. One of the challenges for Chinese criminal justice is to ensure uniformity. They want to make sure that across different regions of China, the penalties are consistent with one another.”
Zhiyu Li, an assistant professor in law and policy at Durham University however has other beliefs, he says that “While judges and prosecutors have the liberty to ignore or reject these suggestions for criminal punishments, we don’t know if it may nonetheless sway their decision-making unconsciously due to cognitive biases”.
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