Artificial intelligence challenges: a comparative analysis of artificial intelligence strategies

Abstract

thus, it is a challenge to bring AI in the policy context because policymaking is inherently about multiple and conflicting goals. Adopting new technologies in the public sector demands tremendous focus on maximizing the public value, which is a complex compared to maximizing shareholders’ value. In addition, managers have very little knowledge of using AI in their operations. Therefore, countries worldwide face a new challenge in policy formulation to avoid the dark sides of AI and embrace the potential of its technological development for society and businesses. Thus, the purpose of this research is to use the theoretical framework to examine whether AI national strategies have covered the challenges of AI public policy, and to elucidate what is missing. The framework is composed of six dimensions before deploying any solution for public AI use: ethics, transparency and audit, accountability and legal issues, fairness and equity, misuse protection, digital divide, and data deficit. Based on the framework, a comparative study of countries is conducted. In conclusion, this study will discuss theoretical and practical implications for future research and practice.

Artificial Intelligence (AI) as a general-purpose technology will greatly impact various socio-economic elements and create new opportunities for continuous innovation. Nowadays, AI advancement has attracted both public and private sector organizations worldwide. While the private sector has made extensive progress in developing AI and digital transformation strategies, the public sector cannot directly adopt these practices. One could claim that most AI models are based on a single agent with single goals