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