Humans and Their Relation to Ill-Defined Systems
Using a taxonomy of systems proposed by Ashby this paper examines the various species of ill-defined systems which may occur in man-machine interaction. A distinction is made between objectively ill-defined systems and effectively ill-defined systems. Various properties of humans as information processors are examined, and it is claimed that humans turn almost all systems, whether initially well-defined or objectively ill-defined into effectively ill-defined systems. It is suggested that while conscious decision making is particularly ill-suited to controlling ill-defined systems, sheer practice frequently enables humans to control them through skills which are not understood even by their owner.
KeywordsState Vector Transition Matrix Human Relation Information Processor System State Vector
Unable to display preview. Download preview PDF.
- Gaines, B., 1976, On the complexity of causal models, IEEE Trans. Sys., Man & Cyb., SMC-6:56.Google Scholar
- Hopf-Weichel, R., Lucciani, L., Saleh, J., and Freedy, A., 1979, Aircraft emergency decisions: cognitive and situational variables, Perceptronics PATR 1065–79–7.Google Scholar
- Kahneman, D., and Tversky, A., 1973, Belief in the law of small numbers, Psychol. Bull., 76:105.Google Scholar
- Kelley, C., 1968, “Manual and Automatic Control,” Wiley, N.Y.Google Scholar
- McRuer, D., Hoffman, L., Jex, H., Moore, G., Phatak, A., Weir, D., and Wolkovitch, J., 1968, New approaches to human-pilot/vehicle dynamic analysis, AFFDL-TR-67–150, Wright-Patterson A.F.B.Google Scholar
- Moray, N., 1980a, Human information processing and supervisory control, M.I.T. Man-Machine System Laboratory Report.Google Scholar
- Moray, N., 1980b, The use of information transmission as nonparametric correlation in the analysis of complex behaviour, M.I.T. Man-Machine System Laboratory Report.Google Scholar
- Rouse, W., 1980, “Systems Engineering Models of Himian-Machine Interaction,” North-Holland-Elsevier, New York.Google Scholar
- Simon, H., 1962, The structure of complexity Proc. Amer. Philos. Soc., 106:467.Google Scholar