Epistemological role of human reasoning in data-informed decision-making

Abstract

Visual analytics was introduced in 2004 as a “grand challenge” to build an interdisciplinary “science of analytical reasoning facilitated by interactive visual interfaces”. The goal of visual analytics was to develop ways of interactively visualizing data, information, and computational analysis methods that augment human expertise in analysis and decision-making. In this paper, we examine the role of human reasoning in data analysis and decision-making, focusing on issues of expertise and objectivity in interpreting data for purposes of decision-making. We do this by integrating the visual analytics perspective with Decision Intelligence, a cognitive framework that emphasizes the connection between computational data analyses, predictive models, actions that can be taken, and predicted outcomes of those actions. Because Decision Intelligence models factors of operational capabilities and stakeholder beliefs, it necessarily extends objective data analytics to include intuitive aspects of expert decision-making such as human judgment, values, and ethics. By combining these two perspectives we believe that researchers will be better able to generate actionable decisions that ideally effectively utilize human expertise, while eliminating bias. This paper aims to provide a framework of how Decision Intelligence leverages visual analytics tools and human reasoning to support the decision-making process.