Cognitive modeling for understanding interactions between people and decision support tools in complex and uncertain environments: A study protocol

Abstract

Background Recent advances in Computational Intelligence Tools and the escalating need for decision-making in the face of complex and uncertain phenomena like pandemics, climate change, and geopolitics necessitate understanding the interaction between these tools and human behavior. It is crucial to efficiently utilize the decision-makers cognitive resources in addressing specific problems. Methods The main goal of this present protocol is to describe the effect that CITs (Computational Intelligence Tools) have on decisions made during complex and uncertain situations. It is an exploratory study with a mixed methodology. Solomon’s group experiment design includes a narrative analysis of cognitive features such as integrative complexity (IC), cognitive flexibility (CF), and fluid intelligence (FI). Additionally, measures of neural activity (NA), physiological measures (PM), and eye-tracking data (ET) will be collected during the experimental session to examine the marginal impact of these processes on decision outcomes (DO) and their relation to CIT capabilities. To achieve this objective, 120 undergraduate and graduate students involved in decision-making will participate as subjects. The approximate duration of the study will be 2 years. Strict adherence to the relevant ethical considerations will be maintained during the performance of the experimental tasks. Discussion The study will provide valuable information on CITs’ effect on decision-making under complex and uncertain contexts. This will help to better understand the link between technology and human behavior, which has important implications. CIT designers can use future results and at the same time, it will be possible to understand cognitive, behavioral, physiological processes, and even the subjective assessment of individuals when they use technological tools to solve a problem.