Envisioning the work of reconfiguring: A modeling perspective for designing adaptive human‐agent systems
Year: 2026
Type: article
Abstract: This paper discusses the perspective that managing the configuration of a network of human and software agents is a form of distributed work that should be explicitly considered when designing human‐agent systems. We describe a configuration of human and software agents as the organization of their roles and relationships that shape and constrain their joint activity while responding to a dynamic flow of events. The paper argues that design for safe and effective teamwork must consider how human and software roles together manage, change, and coordinate their collective configuration over time to respond to changing work demands. We illustrate this form of distributed work at multiple layers of abstraction of a human‐agent system, describing how maintaining goal alignment, tracking and managing interdependencies, synchronizing multi‐threaded activities, and managing the structural topology all involve deliberate and continuous effort. In the second half of the paper, we connect these ideas to modeling approaches for supporting conceptual design of human‐agent systems. The paper discusses how functional modeling of work can help designers first envision the coordinative structures necessary for adaptation before specifying the technical details of how individual tasks are executed (a whole‐to‐parts and coordination‐first approach). We illustrate a specific modeling framework, currently under development, that aims to facilitate the envisioning of the work of configuration management and help designers identify competencies and coordinative structures to support it. We provide an initial discussion of a three‐phase “bootstrapping” approach for using this framework in human‐agent system design. This paper contributes a new direction for explicitly modeling and designing for reconfiguration in human‐agent systems. Future work is needed to further develop the tooling and techniques, evaluate and validate their ability to inform human‐agent system design, and ultimately create more resilient human‐agent systems.
Source: AI Magazine
DOI: 10.1002/aaai.70085
Authors: Martijn IJtsma, Salvatore Hargis
Institution: The Ohio State University
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $2,400
Funder: National Science Foundation
OpenAlex ID: W7204454287