Identifying and prioritizing the obstacles and challenges of data-driven governance from the perspective of applying artificial intelligence and data-based technologies in the public sector

The public sector is facing diverse and complex challenges in the current era. Solving these challenges, which are often related to the development of communication and data, will not be possible except by benefiting from the capacities created by these technologies and realizing data-driven governance. Artificial intelligence technology is one of the revolutionary technologies in the current era that can be used to improve the quality of governance. In order to apply this technology, it is necessary to first consider possible obstacles and challenges in a conscious way. Therefore, in the current research, after a systematic review of the literature, 16 obstacles and challenges of using artificial intelligence in the public sector have been identified and prioritized using the fuzzy simple weighting method(FSAW). According to the findings, "access to data and its quality" have been identified as the most important obstacle, and "ignoring public and social considerations" as the most important challenge. Finally, the identified cases are placed in 6 economic, social, political, managerial, technological and ethical categories, and policy recommendations are proposed according to each category and relevant stakeholders.