There is a lack of a single architecture specification that addresses the needs of trusted and secure Artificial Intelligence systems with humans in the loop, such as human-centered manufacturing systems at the core of the evolution towards Industry 5.0. To realize this, we propose an architecture that integrates forecasts, Explainable Artificial Intelligence, supports collecting users' feedback, and uses Active Learning and Simulated Reality to enhance forecasts and provide decision-making recommendations. The architecture security is addressed as a general concern. We align the proposed architecture with the Big Data Value Association Reference Architecture Model. We tailor it for the domain of demand forecasting and validate it on a real-world case study.

翻译：缺乏单一的架构规格,无法满足受信任和安全的人工智能系统的需求,在循环中与人打交道,例如以人为中心的制造系统,这是向工业5.0发展的核心。为了实现这一点,我们提议了一个将预测、可解释的人工智能、支持收集用户反馈、利用积极学习和模拟现实来改进预测和提供决策建议相结合的架构。 架构安全作为一个普遍问题处理。我们把拟议的架构与大数据价值协会参考建筑模型相协调。我们根据需求预测领域进行调整,并在现实世界案例研究中加以验证。