Abstract：While renovating the operational scenario of legal service to a new stage, generative artificial intelligence also has a structural impact on legal professions both “instrumentally” and “conceptually”, forcing legal practitioners to face the transformation of professional roles and job attributes. From a functionalist perspective, it is no longer acceptable that we limit our stances and means to existing institutional systems and professional logic when probing into the status and role of generative AI in legal service. On the contrary, investigators ought to go beyond traditional and professional perspectives and “instrumental” positions, to understand the complex dynamics and uncertainties of the digital development of legal service, and to comprehensively examine the technical mechanism, industry feasibility and empowerment modes of generative AI’s application in legal service, and on the basis of which, to analyze the “de-skilling” phenomenon within legal professions that may be triggered by the “instrumental theory” psychology, and further explore generative AI’s role in reshaping the basic connotation, operational paradigm, group composition, market supply relationship, and other aspects of legal services. However, when examining the relationship between law and technology from a macroscopic view, it is obvious that generative AI remains far from completely replacing the legal profession group, as some fundamental issues inherent in its derivative logic and the inherent tension between AI technology and the inherent attributes of law have not yet been resolved. Empowering legal services with generative AI requires reconciling the attribute tension between the legal profession and intelligent technology at the national, professional, market, and technological levels, and paying attention to potential risks.
杨立民. 基于生成式人工智能法律服务的数智化发展逻辑与建构路径[J]. 《深圳大学学报》（人文社科版）, 2023, 40(6): 111-120.
YANG Li-min. The Development Logic and Construction Path of Digital Intelligence in Legal Services Based on the Artificial Intelligence Generated Content. , 2023, 40(6): 111-120.
2023, Vol. 40 
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