Affiliation:
1. School of Law, Henan University of Urban Construction , Pingdingshan , Henan, , China .
Abstract
Abstract
Legal judgment prediction is becoming a research hotspot in the legal field as an important artificial intelligence-assisted decision-making tool in legal case management, which is able to predict judgment results. In this paper, data from the 2018 China Law Research Cup competition is gathered, and the dataset is preprocessed in the context of international economic law. Then, a multi-task model for legal verdict prediction is proposed, and the training optimization and prediction of the model are designed using CNN, RNN, and LSTM as the semantic coding layer. The model proposed in this paper achieves a significant improvement of 8% and 6% in the accuracy of the model in the prediction of the charging task and the legal sentence task, respectively. In case outcome prediction, the accuracy of the model proposed in this paper is improved by 14.6% on average compared to the feature model-based modeling approach.
Reference18 articles.
1. Reiling, A. D. (2020). Courts and artificial intelligence. In IJCA (Vol. 11, p. 1).
2. Mokhtarian, E. (2018). The bot legal code: developing a legally compliant artificial intelligence. Vand. J. Ent. & Tech. L., 21, 145.
3. Ashley, K. D. (2017). Artificial intelligence and legal analytics: new tools for law practice in the digital age. Cambridge University Press.
4. Walters, E. (2018). The Model Rules of Autonomous Conduct: Ethical Responsibilities of Lawyers and Artificial Intelligence. Ga. St. UL Rev., 35, 1073.
5. Atkinson, K., Bench-Capon, T., & Bollegala, D. (2020). Explanation in AI and law: Past, present and future. Artificial Intelligence, 289, 103387.