Artificial intelligence applied to lawyers’ appraisals

IF 0.7 Q2 LAW
Susana Almeida Lopes, Marta Aranha Conceição, João Francisco Santos, Madalena Duarte Ferreira, José Sintra, João Almeida Lopes
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引用次数: 0

Abstract

ABSTRACT This pilot study presents an innovative artificial intelligence (AI) model to predict lawyers’ appraisal ratings in a law firm. Methodology development was based on an 11-years database comprising multiple descriptors from 229 lawyers. The AI model builds upon law firms’ tournament, simulating lawyers’ career competition to predict performance rankings. Within a one-year lag, the accuracy of the model was approximately 88%. With two- and three-year lag times, the predictions show only a minor drop in performance. Benefits of this in-silico strategy involve decreasing the frequency of appraisals linked with considerable time and resource savings. By highlighting the most relevant performance predictors in the firm, practitioners may identify bias in appraisals and realign talent management with business strategy. This longitudinal study aims to pilot predictive research for AI models in talent management in law firms. Future research may lead to predictive models supporting talent strategies and practices.
人工智能在律师鉴定中的应用
摘要本试点研究提出了一种创新的人工智能(AI)模型来预测律师事务所的律师评估评级。方法的开发是基于一个11年的数据库,该数据库包含229名律师的多个描述符。人工智能模型建立在律师事务所锦标赛的基础上,模拟律师的职业竞争来预测绩效排名。在一年的滞后时间内,该模型的准确率约为88%。在滞后两年和三年的情况下,预测显示业绩只会略有下降。这种电子策略的好处包括减少评估频率,同时节省大量时间和资源。通过强调公司中最相关的绩效预测因素,从业者可以识别评估中的偏见,并将人才管理与商业战略重新调整。这项纵向研究旨在为律师事务所人才管理中的人工智能模型进行预测性研究。未来的研究可能会产生支持人才战略和实践的预测模型。
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CiteScore
0.70
自引率
0.00%
发文量
7
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