Explainability With Observation Sharing in Long Collaboration Chains of Automated Systems-of-Systems

Abstract

Robotics enabled by AI and advanced software technologies are taking the world by storm. The advanced automation systems, systems-of-systems that power them, and their collaboration are complex and difficult to understand. Lacking knowledge about how they work can only improve our lives so much; in fact, it can hamper the interactions between systems, harm businesses, disrupt daily lives, and even endanger us. Increasing the observability and explainability of these systems helps us remain in control and leverage the technologies to improve our lives. This article introduces a blueprint architecture for long collaboration chains formed by systems-of-systems, provided by multiple companies, that can significantly improve the understanding of the processes and events taking place. We illustrate the vision with an automated supply chain scenario and utilizing example use cases of how different stakeholders can benefit from the enhanced observability and explainability within long collaboration chains.