Uncertainty estimation and the uncertaintyprobability shift under information load

Abstract

The human organism functions as a decider in a variety of systems, particularly at the level of groups and organizations. Because of the importance of the human's decisions to the performance of these systems, it is desirable to understand how human decision makers respond to the uncertainty and handle the information within them. Three experiments are reported which deal with the human's response to uncertainty in decisions varying in objective uncertainty as measured by the information theoretic metric, H. Results confirm earlier findings that mean uncertainty estimates increase linearly with H from 0.2 to 2.8 bits where a discontinuity in the function occurs. The location of this discontinuity is shown to change with information processing load and to be as high as 3.8 bits under low load conditions. Uncertainty estimation proves to be rather robust under conditions of reduced supports for estimation, such as the elimination of anchors (sample stimuli). Finally, a shift also from uncertainty to probability estimation occurs at the discontinuity in the function and this shift is shown to be dependent on information processing load.

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