The Korea Advanced Institute of Science and Technology (KAIST, President Kwang-Hyung Lee) announced on the thirtieth that it should establish a brand new course called ‘Generative Artificial Intelligence (AI) and Legal Tech’ for undergraduate students starting in the autumn semester of 2024.
Through this course, students will find out about computational law, legal AI systems, large language model theory, legal issues in generative AI, and AI ethics.
Particularly, we’ll deeply discuss the most important legal and ethical issues related to generative AI. Computational law refers to a super-convergence field that mixes basic academic disciplines similar to mathematics, statistics, brain science, and cognitive science with cutting-edge artificial intelligence technologies similar to large language models (LLMs) and law.
This course may also cover legal tech development methodologies similar to automatic legal document evaluation, judgment prediction, legal visualization simulation, and Legal-RAG augmented legal search generation technology. KAIST expects that this course will help predict and prepare for a way the AI industry and legal services will change in the long run.
With a view to enhance expertise, KAIST has appointed Lim Young-ik, the top of Intellicon Research Institute, as an adjunct professor on the Graduate School of Arts and Sciences. Lim has been researching legal AI and computational law theory for the past 10 years and has won the World Legal AI Competition for 2 consecutive years. Professor Jeon Woo-jeong, who’s the top professor of the lecture with Lim, is a scholar who deals with AI governance, mental property rights, digital assets, and contract law.
Professor Jeon Woo-jeong said, “This course provides academic theories on generative AI and legal convergence and methodology for developing next-generation legal tech systems.” He added, “It features a futurological approach to legal and ethical issues related to generative AI, similar to copyright of works created by AI, AI’s handling of non-public information, responsibility for AI decisions, AI regulation, explainability, the black box problem, and transparency obligations.”
Reporter Park Soo-bin sbin08@aitimes.com
