Designing for effective collaboration between humans and intelligent machines requires reasoning about the human-machine system as a whole—to uncover how their activities are interdependent and to develop system architectures that support coordination for resilient, joint performance. In dynamic, high-consequence domains such as aviation, space operations, and disaster response, successful coordination is about synchronizing interdependent work processes of humans and machines with each other and with physical processes in the work environment. Considering work dynamics and synchrony early in design can help ensure that mechanisms for coordination are designed intentionally. However, while descriptive models of human-machine interaction dynamics exist, there is a lack of tooling for designers to explore how the dynamic behavior of human-machine systems is affected by early design decisions.

This talk discusses Work Models that Compute (WMC), a computational work modeling framework that helps designers analyze dynamics and synchrony of human-machine systems early in design. By integrating functional modeling, work analysis, and graph theory, WMC makes explicit the relationships between human cognitive functions and machine algorithms, highlighting critical dependencies and coordination demands.

Dr. IJtsmaI will present two case studies, one in disaster robotics and one in air traffic management, to illustrate how computational work models can serve as exploratory tools for envisioning and shaping more effective human–machine systems.