In a significant step towards enhancing the integration of artificial intelligence (AI) in vital sectors, the AI4REALNET consortium has published a foundational document outlining its strategy to apply AI across critical infrastructures, including power, transportation, and air traffic management. This report aims to redefine the interaction between human operators and AI systems, focusing on both operational effectiveness and ethical considerations.

The document presents two primary outcomes: the formal specification of domain-specific use cases (UCs) and the creation of an interdisciplinary conceptual framework. These use cases simulate real-world scenarios, allowing human operators to leverage innovative AI solutions, backed by a comprehensive set of quantitative and qualitative key performance indicators (KPIs).

Key use cases include:

• Power Grid Management: AI tools designed to aid operators in managing electrical congestion and optimizing workflow.
• Railway Operations: Systems that automate train re-scheduling to reduce delays.
• Air Traffic Control: AI applications that assist in effective airspace management and workload distribution among controllers.

The consortium’s approach is notable for its emphasis on interdisciplinary collaboration, integrating insights from social sciences, ethics, and engineering to foster trustworthy AI systems. The use of the Assessment List for Trustworthy Artificial Intelligence (ALTAI) as a self-assessment tool underscores a commitment to ethical standards in safety-critical environments.

As the AI4REALNET project advances, it aims not only to improve operational frameworks within these sectors but also to influence the broader conversation on responsible AI practices throughout Europe and beyond. The full report detailing these initiatives can be accessed here.