Analytics, bias, and evidence: the quest for rational decision making

Evidence-based decision making seems both desirable and rational. New analytical tools for investigating 'big data' promise to provide additional unbiased evidence. Concurrently, technological advances for improving decision making reopen issues related to facts, biases, and beliefs. For m...

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Bibliographic Details
Published in:Journal of decision systems 2019-01, Vol.28 (2), p.120-137
Main Authors: Power, Daniel J., Cyphert, Dale, Roth, Roberta M.
Format: Article
Language:English
Subjects:
analytics
Cognition
cognition and reasoning
collaborative decision models
Decision analysis
Decision making
decision support
Decision support systems
Mathematical analysis
Social factors
System effectiveness
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Summary:Evidence-based decision making seems both desirable and rational. New analytical tools for investigating 'big data' promise to provide additional unbiased evidence. Concurrently, technological advances for improving decision making reopen issues related to facts, biases, and beliefs. For many years, decision support systems and technologies have had the goal of enhancing the effectiveness of human decision-making processes, fostering rational thinking, and avoiding biases and errors. Recently, cognitive neuroscience research has highlighted issues of implicit cognition, physiological and naturalistic processes, and the impact of social cues as elements of human thought. Decision support builders and data scientists must consider a broader range of issues, including issues of knowledge and belief, social factors, and technical capabilities when developing cognitive, analytical, and decision support systems.
ISSN:1246-0125
2116-7052
DOI:10.1080/12460125.2019.1623534