[4H3-GS-11d] AIと社会：テキスト解析

[4H3-GS-11d-05] Probabilistic inference of Bayesian Network for evidence in trial process

Concept of issue identification process support system for child maltreatment cases

〇Kota Takaoka¹, Yoichi Motomura¹, Ken Sato², Yoshiaki Nishigai³ (1. AIST AIRC, 2. NII, 3. Chiba University)

Keywords:Bayesian Network, Probabilistici Inference, Trial process

In order to make a legal decision, identifying issues is important in judicial proceedings. However, it is sometimes very difficult to find the issues which should be in an argument because the way of their investigation and judgement process is different in each of the cases. To solve the problem, this study aims to clarify the concept of issue identification process support based on data and build a demo of the system. As a use-case, we employ child abuse cases for the system and deploy the artificial intelligence which enables to conduct probabilistic causal inference by Bayesian Network to support their judgement. Then, we discuss the concept of the future issue of this identification process support system, including the question whether this can be applied in trial process with advanced Bayesian Network from the perspectives of each case, user and manager position.