Measuring the Influence of Characteristics on Decision-Making Scenarios: A Prototype

Abstract

Nowadays, the world is digitalized and data-driven, transforming decision-making as information is available to essentially any person at practically any time. A naive approach would at first propose that with a greater amount of information, i.e., a greater amount of data, a more educated choice can be reached. Rather, many decision scenarios reach a point today where individuals can no longer acquire and comprehend the vast volume of data on their own. As a corollary, people seek the assistance of algorithms and machines to make reasoned and informed decisions when confronted with difficult issues or problems. However, current research lacks a perspective that can recognize and empirically explore the complex multidimensional nature of the relationships between the defining characteristics of such scenarios. We bridge this void by investigating how the influence of these relationships affects human decision making and perception of an artificial intelligence/system. Specifically, we propose a web-based prototype to simulate decision-making scenarios in which it is possible to change certain characteristics (e.g., transparency, control) and analyze how the change affects the person’s decisions and perceptions (e.g., trust) toward the system.