人工智能技术司法决策推理对制造业供应链合同履行的影响:基于进化博弈方法的仿真分析

G. Zhao, H. Shi, J.F. Wang
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引用次数: 1

摘要

当今世界以技术为中心,它不仅对人类生活产生了全面影响,而且对制造企业也产生了影响。许多公司已经以强大的计算机、应用程序或软件的形式接受了人工智能(AI),这些计算机、应用程序或软件可以筛选求职者,在机器即将发生故障时发出警报,并阅读法律合同。然而,人工智能的迅速扩张及其在法律环境(如公司的合同履行)中的应用是司法方面的一个重大挑战。因此,本文建立了法院选择使用人工智能(AI)技术时制造供应商是否履行合同的进化博弈模型。考虑到制造商人工智能策略选择的复杂性,该方法构建了多主体参与下制造商契约执行行为的仿真分析模型。通过改变不同的影响因素,研究不同法院引导和监管策略对绿色产品生产行为的演化规律,可以模拟所选择的因素对双方(制造商和法院)所选择的策略的影响。结果表明,法院和制造商选择是否使用人工智能技术策略是基于错误率的降低,通过多主体建模的计算实现。
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The influence of artificial intelligence technology judicial decision reasoning on contract performance in manufacturing supply chain: A simulation analysis using Evolutionary Game approach
Today's world revolves around technology, which has a total impact not only on human life but also on manufacturing companies. Many companies have embraced artificial intelligence (AI) in the form of powerful computers, applications, or software that can screen job applicants, alert when a machine is about to break down, and read legal contracts. However, the rapid expansion of AI and its use in legal settings, such as contract performance, in a company is a major challenge on the judicial side. This article, thus, establishes an evolutionary game model of whether manufacturing suppliers are performing contracts or not when the court chooses to use artificial intelligence (AI) technology. Considering the complexity of choosing manufacturers' AI strategy, the method constructs a simulation analysis model of manufacturers' contract enforcement behaviour with the participation of several subjects. We can simulate the influence of the factors selected on the strategy chosen by both parties (manufacturers and court) by changing the different influence factors and studying the evolutionary law of different court guidance and regulation strategies on the production behaviour of green products. The results show that the choice of the court and manufacturers to use the AI technology strategy or not is based on the rate of error reduction, through the computational implementation of multi-subject modelling.
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