Digital Sovereignty and Software Engineering for the IoT-laden, AI/ML-driven Era

TL;DR

This paper discusses the challenges and responsibilities in software engineering to preserve digital sovereignty in IoT and AI/ML-driven systems, emphasizing design and operational considerations for future resilient solutions.

Contribution

It provides a perspective on digital sovereignty challenges and responsibilities in the context of IoT and AI/ML, highlighting design and operational issues.

Findings

Identifies key challenges in maintaining digital sovereignty in IoT/AI systems.

Highlights responsibilities at design and operation stages for software engineers.

Emphasizes the importance of preserving digital sovereignty for future IoT solutions.

Abstract

Today's software engineering already needs to deal with challenges originating from the multidisciplinarity that is required to realize IoT products: Many variants consist of sensor/actuator-powered systems that already today use AI/ML systems to better cope with the unstructuredness of their intended operational design domain (ODD), while, at the same time, such systems need to be monitored, diagnosed, maintained, and evolved using cloud-powered dashboards and data analytics pipelines that process, aggregate, and analyze countless data points preferably in real-time. This position paper discusses selected aspects related to Digital Sovereignty from a software engineering's perspective for the IoT-laden, AI/ML-driven era: While we can undeniably expect more and more benefits from such solutions, a specific light shall be shed in particular on challenges and responsibilities at design- and operation-time that, at minimum, prepare for and enable or, even better, preserve and extend digital sovereignty from a software engineering's perspective.