Based on the outcomes of the 38th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2024), the paper titled “ELSI discussions in building the Japanese Tort-case Dataset,” co-authored by Prof. Sumida Mihoko (Graduate School of Law, Hitotsubashi University), Associate Prof. Hiroaki Yamada (Tokyo University of Science), and Mr. Ryutaro Ohara (Nakamura, Tsunoda & Matsumoto), has been published in the Proceedings of the Annual Conference of JSAI (2024). The authors developed the Japanese Tort-case Dataset (JTD) for legal judgment prediction, an important area of AI application research in the legal field. This paper reports on the issues considered during the dataset construction process and aims to deepen the discussion on dataset construction and sharing. The authors point out that, since JTD contains legal data, various social issues need to be considered during its construction, including the appropriateness of using computers for judicial predictions and the potential biases inherent in the dataset. Furthermore, they note that discussions on promoting open data provision of court judgments in Japan are still ongoing and that the foundation for sharing datasets like JTD with other researchers has to be established. This presentation received the 2024 National Conference on Artificial Intelligence Excellence Award (Organised Session Oral Presentation Category).

https://www.jstage.jst.go.jp/article/pjsai/JSAI2024/0/JSAI2024_3K1OS2a02/_article/-char/ja/