The Role of AI-Based Intelligent Systems in Public Policy Formulation

Abstract

Existing public policies have failed to adequately solve complex public problems in society. To deal with the complexities of public problems, intelligent systems are required. The input and output of an intelligent system are similar to those of a conventional system, where correct input leads to correct output. The intelligent system can receive a public problem, prioritize it, and offer a solution for it. This is a qualitative, exploratory research with an applied objective. The data collection was conducted through fieldwork using semi-structured interviews. The research population included public policy experts and Artificial Intelligence (AI) experts. Snowball sampling was utilized, reaching theoretical saturation with a final sample size of 12 people. To assess the validity and reliability of this research, the opinions and guidelines of a group of experts were considered before, during, and after the coding process, and the necessary final adjustments were made. For the qualitative data analysis, the Thematic Analysis method and the Thematic Network tool, following the Attride-Stirling approach in six steps, were used. In this research, 4 global themes, 7 organizing themes, and 143 basic themes were extracted to determine the role of the intelligent system in public policy formulation. The results showed that intelligent systems must be used to formulate intelligent policies. By using the capabilities of AI, the intelligent system can perform the process of public problem identification, agenda setting, and offering the best solution intelligently. Consequently, the public policy formulation processes are presented more precisely, effectively, and with fewer negative side effects. The knowledge required by the intelligent system to perform these processes intelligently is supplied by the capabilities of the Expert System and the Learning System.