Modeling the Effects of Machine Rigidities on Joint Work Strategies

Abstract

One of the challenges in designing resilient human-machine systems is that machine capabilities are inherently rigid. A resilient joint cognitive system can anticipate and adapt to changing work demands effectively, but limitations of machines can make this adaptation constrained and less fluid. By identifying and accommodating for these rigidities in the design of human-machine system architectures, developers can build human-machine systems that support multiple contexts. This paper proposes a work-modeling approach for analyzing joint human-machine work strategies, focusing on identifying interdependencies that would support opportunistic adaptation and reduce the risk of machine rigidity leading to brittle failures of a human-machine system. The approach is applied to a case study in space operations to demonstrate how interdependencies can be identified and evaluated. The results of this analysis provide early insight into how team adaptation and machine limitations can be systematically accounted for in system architecture design.