Investigating the role of artificial intelligence in the public policy cycle; Metasynthesis approach

Abstract

Artificial intelligence is a rapidly emerging and crucial technology that has significantly impacted various fields, including public policy. This qualitative research aims to identify the potential applications of artificial intelligence in the public sector policy-making process. It involves extracting 339 basic themes that align with the research goal, creating 33 organizing themes from these basic themes, and classifying these concepts into four overarching themes that cover the applications, methods, advantages, and challenges of artificial intelligence in the public policy cycle. Based on the research findings, one critical application of this technology in public policy-making is prioritizing issues based on society's actual needs and demands. It also aids in diagnosing issues and problems by recognizing patterns in big data, leading to the formulation of evidence-based policies. Additionally, using methods such as machine learning algorithms, neural networks, and natural language processing has advantages such as increased intelligence and dynamism in the policy formulation process. As a result, this technology can be more efficiently applied in the public policy cycle, allowing policymakers to play a more effective role. However, several challenges require further investigation, such as ethical issues in data usage, human resource gaps, management biases, and security challenges.

Keywords

• artificial intelligence
• public policy making
• policy-making cycle
• meta-synthesis