[论文解读] When Industry meets Trustworthy AI: A Systematic Review of AI for Industry 5.0

Eduardo Vyhmeister, Gabriel G. Castañé|arXiv (Cornell University)|Mar 5, 2024

Digital Transformation in Industry被引用 6

一句话总结

本文对工业4.0中的可信人工智能进行了系统性文献综述，并探索走向工业5.0的路径，强调趋势、差距和治理需求。

ABSTRACT

Industry is at the forefront of adopting new technologies, and the process followed by the adoption has a significant impact on the economy and society. In this work, we focus on analysing the current paradigm in which industry evolves, making it more sustainable and Trustworthy. In Industry 5.0, Artificial Intelligence (AI), among other technology enablers, is used to build services from a sustainable, human-centric and resilient perspective. It is crucial to understand those aspects that can bring AI to industry, respecting Trustworthy principles by collecting information to define how it is incorporated in the early stages, its impact, and the trends observed in the field. In addition, to understand the challenges and gaps in the transition from Industry 4.0 to Industry 5.0, a general perspective on the industry's readiness for new technologies is described. This provides practitioners with novel opportunities to be explored in pursuit of the adoption of Trustworthy AI in the sector.

研究动机与目标

• 了解工业领域中以人为本的人工智能技术和可信人工智能的趋势与现状。
• 识别在工业4.0使能因素及其AI应用中被优先考虑的可信AI要求。
• 绘制工业4.0使能因素与AI应用之间的关系，以指导工业5.0的采用。
• 突出将可信人工智能整合到工业5.0中的挑战、差距和机会。

提出的方法

• 对可信人工智能与工业4.0/5.0相关的同行评审文章进行系统综述。
• 以 PICOC（Population, Intervention, Comparison, Outcomes, Context）为基础界定研究问题和映射方法。
• 根据表3和表4对AI应用方法和可信AI要求进行分类。
• 对与以人为本的AI、治理和工业环境中的安全相关主题进行定性综合。
• 以文献计量学为基础，识别文献中的趋势和差距。

实验结果

研究问题

• RQ1 RQ1: What Trustworthy AI requirements are prioritized in Industry 4.0 technological enablers and their AI applications, and how can they be promoted?
• RQ2 RQ2: What are the current trends in the relationship between Industry 4.0 enablers and AI applications?
• RQ3 RQ3: What innovative approaches can facilitate the integration of Trustworthy AI into Industry 4.0 to transition to Industry 5.0?

主要发现

• Trustworthy AI is framed around seven pillars including human agency, transparency, privacy, accountability, and environmental well-being.
• AI applications in industry cover process planning, quality control, predictive maintenance, logistics, robotics, and process control/optimization.
• Industry 5.0 emphasizes human-centric, sustainable, and resilient production with emphasis on data sharing, digital twins, and reconfigurability.
• There are identified governance and regulatory considerations, such as the AI Act and GDPR-related data governance requirements, shaping AI adoption in industry.
• Gaps exist in mapping specific Trustworthy AI requirements to concrete Industry 4.0 enablers and practical transition steps to Industry 5.0.