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Enhancing decisions
Edited by Erwin Rausch
Introduction
[29] Milkman et al. (2008) noted in the knowledge-based economy, a knowledge worker's primary deliverable is a good decision. The ability of organizations, corporations and entities to contemplate, evaluate and implement quality decisions is dependent upon a multitude of intrinsic and extrinsic factors. While the management of extrinsic variables may be more difficult to control, the identification and management of human variables such as emotion and logic are pivotal in the effort to increase the quality of decisions and decision-making processes. Researchers have recently focused attention on the impact of some of the human emotion variables on decision making. [18] Hilary and Hui (2008) found that both individuals and organizations exhibiting a high degree of religiosity display lower levels of risk exposure in decision making. Similarly, [13] Fernando and Jackson (2006) noted that in the individuals studied, outcomes of difficult decisions, both good and bad, were in some way attributable to a religious, spiritual or value characteristic.
One of the most fascinating dichotomies in contemporary thought surrounding decision-making is the apparent conflict between the roles of emotion and rationality. [38] Stanovich and West (2000) divided cognitive functions between those that were faster, effortless, implicit and emotional as compared to those that were slower, conscious, explicit and logical. The authors believed better decisions could be derived by shifting decision-makers from intuitive and emotional thinking to logical and rational thinking. Moreover, the authors concluded replacing intuition with more intensive data collection and analytical processes enabled the decision-maker to construct linear models to produce relevant predictors. The suggestion here is that human beings will make better decisions if we transform our cognitive functions to resemble those of an emotion-free microprocessor.
There is an alternate research process proceeding in artificial intelligence to inject learned emotions into microprocessor driven decision-making. IBM is developing a cognitive computing processor to emulate the patterns of human thinking ([3] Bai, 2008). Additionally, the MIT Artificial Intelligence Laboratory has developed an artificially intelligent machine that has defined elements of sensory and emotional systems ([44] Velasquez, 1998). The computerized platform is capable of modeling six different emotions for decision-making: anger, fear, distress/sadness, joy/happiness, disgust and surprise. Velasquez's premise based upon previous work ([10] Damasio, 1994) is that intuition and...