Designing Human-AI System for Legal Research: A Case Study of Precedent Search in Chinese Law
Fuente:
arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866910909036756992 |
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| author | Guan, Jiarui Zou, Ruishi Zhang, Jiajun Xin, Kimpan He, Bingsu Zhang, Zhuhe Ye, Chen |
| author_facet | Guan, Jiarui Zou, Ruishi Zhang, Jiajun Xin, Kimpan He, Bingsu Zhang, Zhuhe Ye, Chen |
| contents | Recent advancements in AI technology have seen researchers and industry professionals actively exploring the application of AI tools in legal workflows. Despite this prevailing trend, legal practitioners found that AI tools had limited effectiveness in supporting everyday tasks, which can be partly attributed to their design. Typically, AI legal tools only offer end-to-end interaction: practitioners can only manipulate the input and output but have no control over the intermediate steps, raising concerns about AI tools' performance and ethical use. To design an effective AI legal tool, as a first step, we explore users' needs with one specific use case: precedent search. Through a qualitative study with five legal practitioners, we uncovered the precedent search workflow, the challenges they face using current systems, and their concerns and expectations regarding AI tools. We conclude our exploration with an initial prototype to reflect the design implications derived from our findings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08235 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Designing Human-AI System for Legal Research: A Case Study of Precedent Search in Chinese Law Guan, Jiarui Zou, Ruishi Zhang, Jiajun Xin, Kimpan He, Bingsu Zhang, Zhuhe Ye, Chen Human-Computer Interaction Recent advancements in AI technology have seen researchers and industry professionals actively exploring the application of AI tools in legal workflows. Despite this prevailing trend, legal practitioners found that AI tools had limited effectiveness in supporting everyday tasks, which can be partly attributed to their design. Typically, AI legal tools only offer end-to-end interaction: practitioners can only manipulate the input and output but have no control over the intermediate steps, raising concerns about AI tools' performance and ethical use. To design an effective AI legal tool, as a first step, we explore users' needs with one specific use case: precedent search. Through a qualitative study with five legal practitioners, we uncovered the precedent search workflow, the challenges they face using current systems, and their concerns and expectations regarding AI tools. We conclude our exploration with an initial prototype to reflect the design implications derived from our findings. |
| title | Designing Human-AI System for Legal Research: A Case Study of Precedent Search in Chinese Law |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2504.08235 |