Complexity: Learning to Muddle Through
Document Type
Article
Publication Date
9-2012
Abstract
The articles in this special issue are placed in the context of the literature of general systems theory. The focus is on the complexity (or requisite variety) of complex work domains and the implications for control. Following the insights of Ashby’s law of requisite variety, it is concluded that classical hierarchical or servomechanism-type control systems are inadequate as a basis for dealing with the unanticipated variability endemic to complex work domains. Alternative types of control (e.g., self-organizing systems) and alternative images of cognition are suggested as a theoretical context for modeling performance in complex work domains.
Repository Citation
Flach, J. M.
(2012). Complexity: Learning to Muddle Through. Cognition, Technology & Work, 14 (3), 187-197.
https://corescholar.libraries.wright.edu/psychology/275
DOI
10.1007/s10111-011-0201-8
