Categorization and eccentricity of AI risks: a comparative study of the global AI guidelines

Kai Jia () and Nan Zhang ()
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Kai Jia: University of Electronic Science and Technology of China
Nan Zhang: Tsinghua University

Electronic Markets, 2022, vol. 32, issue 1, No 5, 59-71

Abstract: Abstract Background Governments, enterprises, civil organizations, and academics are engaged to promote normative guidelines aimed at regulating the development and application of Artificial Intelligence (AI) in different fields such as judicial assistance, social governance, and business services. Aim Although more than 160 guidelines have been proposed globally, it remains uncertain whether they are sufficient to meet the governance challenges of AI. Given the absence of a holistic theoretical framework to analyze the potential risk of AI, it is difficult to determine what is overestimated and what is missing in the extant guidelines. Based on the classic theoretical model in the field of risk management, we developed a four-dimensional structure as a benchmark to analyze the risk of AI and its corresponding governance measures. The structure consists of four pairs of risks: specific-general, legal-ethical, individual-collective and generational-transgenerational. Method Using the framework, a comparative study of the extant guidelines is conducted by coding the 123 guidelines with 1023 articles. Result We find that the extant guidelines are eccentric, while collective risk and generational risk are largely underestimated by stakeholders. Based on this analysis, three gaps and conflicts are outlined for future improvements.

Keywords: Artificial Intelligence; Risk management; Categorization; Eccentricity; H83 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12525-021-00480-5

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