Live
- LS polls: Union Minister Bhagwanth Khuba, Dingaleshwara seer, Priyanka Jarkiholi file nominations in K'taka
- Amid show of strength, Congress’ Praniti Shinde files nomination from Solapur
- Tamil Nadu Police gives clean report to Isha Foundation in missing volunteers case
- Home Minister Amit Shah to address public meeting in Goa on April 24
- Gurgaon Open: M Dharma fires 67 for two-shot lead on penultimate day
- Sharad Pawar made many attempts to finish Shiv Sena, claims Maha minister
- Former England opener Raman Subba Row dies aged 92
- IPL 2024: Impact player rule is affecting the progress of half all-rounders, says Zaheer Khan
- ‘Teppa samudram’ review: Entertains with twists and turns
- ‘Market Mahalakshmi’ review: Blends humour and heartfelt moments
New AI system beats humans at predicting court outcomes
Scientists have developed a new artificial intelligence system that can predict court decisions better than legal scholars, even with less information. Researchers, including those from The Stanford Centre for Legal Informatics, used the US Supreme Court Database - which contains information on cases dating back to 1791 Using this, they built an algorithm for predicting any justice\'s vote at any
Washington: Scientists have developed a new artificial intelligence system that can predict court decisions better than legal scholars, even with less information. Researchers, including those from The Stanford Centre for Legal Informatics, used the US Supreme Court Database - which contains information on cases dating back to 1791 Using this, they built an algorithm for predicting any justice's vote at any time. Researchers drew on 16 features of each vote, including the justice, the term, the issue, and the court of origin.
They also added other factors, such as whether oral arguments were heard. For each year from 1816 to 2015, the team created a machine-learning statistical model. It looked at all prior years and found associations between case features and decision outcomes. Decision outcomes included whether the court reversed a lower court's decision and how each justice voted. The model then looked at the features of each case for that year and predicted decision outcomes.
