A Conceptual Framework for AI-based Decision Systems in Critical Infrastructures
Milad Leyli-Abadi, Ricardo J. Bessa, Jan Viebahn, Daniel Boos, Clark Borst, Alberto Castagna, Ricardo Chavarriaga, Mohamed Hassouna, Bruno Lemetayer, Giulia Leto, Antoine Marot, Maroua Meddeb, Manuel Meyer, Viola Schiaffonati, Manuel Schneider, Toni Waefler
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The interaction between humans and AI in safety-critical systems presents a unique set of challenges that remain partially addressed by existing frameworks. These challenges stem from the complex interplay of requirements for transparency, trust, and explainability, coupled with the necessity for robust and safe decision-making. A framework that holistically integrates human and AI capabilities while addressing these concerns is notably required, bridging the critical gaps in designing, deploying, and maintaining safe and effective systems. This paper proposes a holistic conceptual framework for critical infrastructures by adopting an interdisciplinary approach. It integrates traditionally distinct fields such as mathematics, decision theory, computer science, philosophy, psychology, and cognitive engineering and draws on specialized engineering domains, particularly energy, mobility, and aeronautics. The flexibility in its adoption is also demonstrated through its instantiation on an already existing framework.