Decision-making augmentation system for solving the problem of risk reduction

Abstract

The decision-making augmentation system for solving the problem under risk and uncertainty is demonstrated. This system helps decide on the most satisficing alternative for solving the problem of risk reduction. Satisficing alternative is an alternative that satisfies requirements for risk reduction and is sufficient for the decision-maker. The process of solving the problem is self-regulating, where the problem goal, initially set up as an uncertain “sufficient risk reduction”, should be clarified in the process of problem-solving to reflect the formation of the mental model, while the activity goal should be accordingly modified by adding corresponding objectives as criteria for success to reflect the formation of the level of motivation. This iterative process ultimately leads to the most satisficing solution to the problem. Given human limitations in computational capacity due to the size of working memory, the augmentation system supports computation on various levels, encompassing motivation, self-efficacy, and risk reduction. This system is implemented in ED2® mobile web apps, addressing both reactive and proactive risk reduction for present or future risk events, respectively.

Keywords: Decision-making, Problem-solving, Uncertainty, Risk Reduction, Goal Setting, Instrumental Rationality, Satisficing

DOI: 10.54941/ahfe1004738