Changes and challenges of legal education in the era of generative artificial intelligence: Chinese experience
Vol 8, Issue 8, 2024
VIEWS - 212 (Abstract) 170 (PDF)
Abstract
Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.
Keywords
Full Text:
PDFReferences
Busch, P. A., & Henriksen, H. Z. (2018). Digital discretion: A systematic literature review of ICT and street-level discretion. Information Polity, 23(1), 3–28. https://doi.org/10.3233/ip-170050
Chen, R., & Wang, W. Y. (2024). Analysis of the Role Orientation of Judicial Artificial Intelligence and Human Judges. Journal of Chongqing University (Social Science Edition), 1–16.
Crawford, J., Cowling, M., & Allen, K. A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching and Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02
Choi, C. Q. (2023). Columbia Perspectives on ChatGPT. Available online: https://datascience.columbia.edu/news/2023/columbia-perspectives-on-chatgpt/ (accessed on 23 January 2024).
Chen, Z. Z., Shi, Y. W., & Wang, M. K. (2023). The realistic prospect of artificial intelligence promoting educational reform—an analysis of teachers’ coping strategies for ChatGPT. Journal of Guangxi Normal University (Philosophy and Social Sciences Edition), 16(4), 1–11.
Chen, J. Z., & Lyu, Y. Z. (2020). Research on Legal Methodology Focusing on Thinking Rules. Peking: Peking University Press.
Crompton, H., & Ren, G. H. (2023). The Era of ChatGPT: How to Innovate in Education. Available online: https://baijiahao.baidu.com/s?id=1759698185379105617&wfr=spider&for=pc (accessed on 6 March 2023).
Deshpande, A., Murahari, V., Rajpurohit, T., et al. (2023). Toxicity in ChatGPT: Analyzing persona-assigned language models. Findings of the Association for Computational Linguistics: EMNLP 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.88
Fan, W. (2020). The historical evolution and development of “judges must no refuse the referee”. Academia Bimestris, (06), 173–179.
Feng, Y. H. (2023). The application value, potential ethical risks, and governance pathways of ChatGPT in the field of education. Ideological and Theoretical Education, (04), 26–32.
Fang, S. S., & Tang, Q. Y. (2023). Smart but misled: a typological analysis of ChatGPT’s incorrect content generation. Journalism and Writing, (04), 31–42.
Foucault, M. (2012). Discipline and Punish. Shanghai: Shanghai Sanlian Publishing House.
Hua, L. C. (2021). What kind of education do undergraduate students in law schools need in the era of legal artificial intelligence—macro framework and micro solutions? Legal Education Research, 33(02), 90–116.
Katherine, R. K. (2013). Legal Education and Professional Skills: Myths and Misconceptions about Theory and Practice. McGeorge Law Review, 45(1), 7–50.
Li, Z. T. (2023). The Subversion and Resetting of the “Foundation” of Basic Education by ChatGPT/Generative Artificial Intelligence. Journal of East China Normal University (Educational Sciences Edition), 41(07), 47–55.
Luo, W. P., & Gao, Z. C. (2020). The Selection of Training Modes for Artificial Intelligence Rule of Law Talents. Shandong Social Sciences, (11), 97–102.
Linda J. S., Kathleen L. M., & Mark B. (1999). Does Automation Bias Decision-making? International Journal of Human-Computer Studies, (51), 991–1006.
Liu, M. F. (2022). Teaching Reform and Innovation of Law Courses Based on Artificial Intelligence Features. China Higher Education, (11), 53–55.
Liu, K. L. (2020). How to Consolidate the Foundation: How Should Legal Education Respond to the Era of Artificial Intelligence? Shandong Social Sciences, (11), 91–96.
Liu, Y. M., & Wang, C. L. (2023). Actively Responding to the Challenges of Generative Artificial Intelligence in Liberal Arts Education. Nanjing Journal of Social Sciences, (06), 119–128.
Omiye, J. A., Lester, J. C., Spichak, S., et al. (2023). Large language models propagate race-based medicine. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00939-z
Park, J. S., O’Brien, J., Cai, C. J., et al. (2023). Generative Agents: Interactive Simulacra of Human Behavior. In: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. https://doi.org/10.1145/3586183.3606763
Qian, Y. Y. (2018). Critical Thinking and Creative Thinking Education: Concepts and Practices. Research on Education Tsinghua University, (4), 1–16.
Ren, W. D. (2023). Legal Education Needs to Face and Respond to the Development of Generative artificial intelligence, Democracy and Legal Times. Available online: http://e.mzyfz.com/paper/2114/paper_56651_11677.html (accessed on 18 October 2023).
Shultz, M. M., & Zedeck, S. (2011). Predicting Lawyer Effectiveness: Broadening the Basis for Law School Admission Decisions. Law & Social Inquiry, 36(03), 620–661. https://doi.org/10.1111/j.1747-4469.2011.01245.x
She, S. S., & Zhu, Z. T. (2023). ChatGPT-like Products: Internal Mechanisms and Their Impact on Learning Evaluation. Distance Education in China, (4), 8–15.
Sang, J. T., & Yu, J. (2023). Exploring Future Trends and Challenges of AI from the Perspective of ChatGPT. Journal of Computer Research and Development, 60(6), 1191–1201.
Sun, L. H., & Shen, W. L. (2024). On the Destiny Community of Generative Artificial Intelligence in Education. Electrifying Education Research, 45(02), 20–26.
Skitka, L. J., Mosier, K., & Mark, D. (1999). Does Automation Bias Decision-making? International Journal of Human-Computer Studies, 51(5), 91–1006. https://doi.org/10.1006/ijhc.1999.0252
Skitka, L. J., Mosier, K., & Mark, D. (2011). Accountability and automation bias. International Journal of Human-Computer Studies, (52), 701–717. https://doi.org/10.1006/ijhc.1999.0349
Wang, T. E. (2023). The characteristics, educational significance, and responses to issues of ChatGPT. Ideological and Theoretical Education, (04), 19–25.
Wang, Y., Shen, W. X., & Long, W. Q., et al. (2022). The Cultivation of Compound Rule of Law Talents in the New Era (pen talk). Journal of Northwestern Polytechnical University (Social Sciences), (2), 106–123.
Wang, X. G., & Liu, J. (2023). On the construction of the experimental teaching system of digital law course. Chinese Journal of University Teaching, (12), 46–55.
Wu, N. Z., Chen, X. Z., & Feng, Y. (2023). From “disorder” to “order”: the shift of generative artificial intelligence applications in education and its generation mechanism. Journal of Distance Education, 41(06), 42–51.
Xiao, J. M., & Sun, Y. N. (2023). Problems and countermeasures in the cultivation of computational legal talents. Southeast Jurisprudence, (01), 1–16.
Yang, L. M. (2023). Development Logic and Construction Path of Digital Intelligence Based on Generative Artificial Intelligence Legal Services. Journal of Shenzhen University (Humanities & Social Sciences), 40(06), 111–120.
Zhou, H. Y., & Li, Y. Y. (2023). The Impact of ChatGPT on the Educational Ecology and Coping Strategies. Journal of Xinjiang Normal University (Philosophy and Social Sciences Edition), 44(04), 102–112.
Zhou, L., & Wang, F. (2023). Enlightenment of Generative Artificial Intelligence in Education: Letting Everyone Become Themselves. China Educational Technology, (05), 9–14.
Zhao, X. W., Dai, L., & Shen, S. S., et al. (2024). Designing Educational Prompts to Facilitate High-Consciousness Learning. Open Education Research, 30(01), 44–54.
Zhao, W. X., Zhou, K., & LI, J., et al. (2023). A survey of large language models. Available online: https://arxiv.org/abs/2303.18223 (accessed on 15 August 2023).
Zheng, L. Q., Gao, L., & Huang, Z. C. (2024). Can Conversational Robots Based on Generative Artificial Intelligence Technology Improve Online Collaborative Learning Performance? Research on Electrification Education, 45(03), 70–76+84.
Zhuo, T. Y., Huang, Y., Chen, C., & Xing, Z. (2023). Exploring AI Ethics of ChatGPT: A Diagnostic Analysis. Available online: https://arxiv.org/abs/2301.12867 (accessed on 15 August 2023).
Zhu, Y. X., & Yang, F. (2023). ChatGPT/Generative Artificial Intelligence and Educational Innovation: Opportunities, Challenges, and the Future. Journal of East China Normal University (Educational Sciences Edition), 41(07), 1–14.
Zhang, J. W. (2023). Educational Reflection on ChatGPT: The Educational Challenges and Ethical Limits of Otherness Technology. Research on Electrification Education, 44(09), 5–11+25.
Zhang, J. W., & Pan, L. Q. (2021). New Starting Points, New Concepts, and New Solutions for Legal Talent Cultivation in the Era of Artificial Intelligence. Legal Education Research, 32(01), 53–73.
Zhang, Y., Li, Z. F., & Qian, W. (2023). From ChatGPT to Human-Machine Collaboration in Knowledge Co-construction. Studies in Science of Science, (12), 2131–2137.
Zhang, W. X., Shen, T. J., & Sun, X. Y. (2023). From Disorder to Reorder: Changes in Information Order and Governance in the Context of Generative Artificial Intelligence. Journalism and Communication, (10), 41–51.
Zhang, Z. (2023). The Underlying Logic and Possible Paths of ChatGPT/Generative Artificial Intelligence Reshaping Education. Journal of East China Normal University (Educational Sciences Edition), 41(07), 131–142.
DOI: https://doi.org/10.24294/jipd.v8i8.5600
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Wenyu Wang, Zhilang Xu, Zichun Xu
License URL: https://creativecommons.org/licenses/by/4.0/
This site is licensed under a Creative Commons Attribution 4.0 International License.