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Understanding the Extent of Automation and Process Transparency Appropriate for Public Services: AI in Chinese Local Governments
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Author(s): Yi Long (Shanghai University of Political Science and Law, China)and J. Ramon Gil-Garcia (University at Albany, State University of New York, Albany, USA & Universidad de las Americas Puebla, Cholula, Mexico)
Copyright: 2023
Volume: 19
Issue: 1
Pages: 20
Source title:
International Journal of Electronic Government Research (IJEGR)
Editor(s)-in-Chief: Nripendra P. Rana (Qatar University, Qatar)
DOI: 10.4018/IJEGR.322550
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Abstract
Many countries are exploring the potential of artificial intelligence (AI) to improve their operations and services, and China is no exception. However, not all AI techniques or automation approaches are suitable for every government service or process since transparency and accountability are paramount in the public sector. In this context, automation via expert systems (ES) is still a vital complement or even an alternative to AI techniques, because they can be more easily audited for potential biases. This paper analyzes the smart examination and approval (SEA) process use in China and explores how different forms of automation could be better options for certain services or specific processes within services, considering their level of transparency as an important characteristic. Based on these results, the authors argue that governments could consider hybrid approaches combining, for example, machine learning, for verification processes, and ES, which are more easily auditable, to make final decisions on individual cases. They also propose a classification of services by considering the extent of automation and process transparency needed. The classification considers a hybrid approach such as SEA, but also include other alternatives such as the exclusive use of AI techniques, as well as traditional online delivery and face-to-face procedures.
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