基于国际标准的人工智能成熟度评估框架

IF 8 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Rubén Márquez , Moisés Rodriguez , Javier Verdugo , Francisco P. Romero , Mario Piattini
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引用次数: 0

摘要

在一个以技术整合为主导的时代,人工智能(AI)在各个领域都至关重要,推动了重大进步,并要求为其实施提供强有力的质量措施。本文介绍了一种新的人工智能成熟度评估框架,该框架是根据ISO(国际标准化组织)和IEC(国际电工委员会)提供的国际标准设计的,特别是ISO/IEC 33000系列过程评估标准。我们的框架旨在为人工智能系统开发人员提供一个结构化的工具,以持续改进他们的开发过程,从而提高人工智能应用程序的可靠性和有效性。为了证明我们提出的框架的适用性,我们通过汽车行业的案例研究对其进行了验证。具体来说,该框架被用于评估和增强一个人工智能项目,以开发一种机制,在车载设备的约束下,根据传感器数据确定车辆行为。我们的发现确定了关键的改进点,有助于工程应用中人工智能系统质量的迭代增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Artificial Intelligence maturity assessment framework based on international standards
In an era dominated by technological integration, Artificial Intelligence (AI) is pivotal across various sectors, driving significant advancements and demanding robust quality measures for its implementations. This paper introduces a novel AI maturity assessment framework designed in alignment with International Standards provided by ISO (International Organization for Standardization) and IEC (International Electrotechnical Commission), specifically with the ISO/IEC 33000 family of standards for process assessment. Our framework aims to provide AI system developers with a structured tool for continuous improvement of their development processes, thereby enhancing the reliability and efficacy of AI applications. To demonstrate the applicability of our proposed framework, we have validated it through a case study in the automotive sector. Specifically, the framework was employed to assess and enhance an AI project to develop a mechanism to determine vehicle behavior from sensor data within the constraints of onboard devices. Our findings identify key improvement points contributing to the iterative enhancement of AI system quality in engineering applications.
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来源期刊
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence 工程技术-工程:电子与电气
CiteScore
9.60
自引率
10.00%
发文量
505
审稿时长
68 days
期刊介绍: Artificial Intelligence (AI) is pivotal in driving the fourth industrial revolution, witnessing remarkable advancements across various machine learning methodologies. AI techniques have become indispensable tools for practicing engineers, enabling them to tackle previously insurmountable challenges. Engineering Applications of Artificial Intelligence serves as a global platform for the swift dissemination of research elucidating the practical application of AI methods across all engineering disciplines. Submitted papers are expected to present novel aspects of AI utilized in real-world engineering applications, validated using publicly available datasets to ensure the replicability of research outcomes. Join us in exploring the transformative potential of AI in engineering.
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