AI in the Context of Complex Intelligent Systems: Engineering Management Consequences

Abstract

As artificial intelligence (AI) is increasingly integrated into the context of complex products and systems (CoPS), making complex systems more intelligent, this article explores the consequences and implications for engineering management in emerging complex intelligent systems (CoIS). Based on five engineering management aspects, including design objectives, system boundaries, architecting and modeling, predictability and emergence, and learning and adaptation, a case study representing future CoIS illustrates how these five aspects, as well as their relationship to criticality and generativity, emerge as AI becomes an integrated part of the system. The findings imply that a future combined perspective on allowing generativity and maintaining or enhancing criticality is necessary, and notably, the results suggest that the understanding of system integrators and CoPS management partly fundamentally alters and partly is complemented with the emergence of CoIS. CoIS puts learning and adaptation characteristics in the foreground, i.e., CoIS are associated with increasingly generative design objectives, fluid system boundaries, new architecting and modeling approaches, and challenges predictability. The notion of bounded generativity is suggested to emphasize the combination of generativity and criticality as a direction for transforming engineering management in CoPS contexts and demands new approaches for designing future CoIS and safeguard its important societal functions.

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