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

ABSTRACT

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.

KEYWORDS:

• Decision support systems
• analytics
• collaborative decision models
• decision support
• cognition and reasoning

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.