About methods of support for management decision-making under conditions of significant uncertainty

Abstract

Attempts to improve the quality of managerial decisions by introducing modern advances in information technology in various areas of public administration (socio-humanitarian, strategic, foreign policy, etc.) do not give the desired effect, comparable to the effect of their implementation in the manufacturing sector. The solution to this problem requires qualitatively new approaches to the issues of information and analytical support for decision-making in conditions of significant uncertainty. This article highlights the difficulties of predictive management of social processes based on direct computer modeling of social systems, considers the disadvantages of expert decision support methods used in practice, and proposes new technologies for applying expert knowledge and competencies based on the use of computer modeling and research. Current approaches to working with experts can be described as methods of coordinating the opinions of a group of experts based on their personal views (models) on the issue under discussion. Our experience has shown that creating a common integrated model by a group of experts gives a much better result. While the traditional approach can be called "group" intelligence, the new approach is called "collective" intelligence. In addition, methods of decision support using artificial intelligence systems are currently being intensively developed. We propose to begin work on the creation of "hybrid" intelligence with the integration of these approaches to obtain a synergistic effect.