Transition From Scenario-Based to Outcome-Based Engineering in SE4AI

Abstract

As intelligent systems become increasingly integrated into our daily lives, it has become evident that there is a mismatch between traditional systems engineering (SE) practices and the nature of intelligent systems. In this article, we posit that the current SE practices need to change their hyperfocus on scenario-based engineering to a process that is more focused on engineering outcomes in the presence of changing environment. To help enabling such transition, we incorporate closed systems precepts from systems theory into formal SE practices. The concept of closed systems is based on the idea that a system is an entity that is bounded by a physical or conceptual boundary and is isolated from its environment. Closed systems are self-contained and self-regulating, and their behavior can be predicted and controlled based on the system's internal rules and mechanisms. In our previous paper, we formalized different types of closed systems and explored how SE practices can utilize these types for various applications. However, there is a need to transition from theorizing about these types of closure to implementing them in SE processes. In this article, we will demonstrate how closed system precepts can be applied to SE practices using a simple example of an intelligent system. We will explore different aspects of applying closed system formalization from our previous effort, including how to define a system's boundary when there is an intelligent property, how to perform problem formulation, and how to address a system's causal dependencies, in order to build a more scalable and well-scoped system.