Hyun-kyoung Song, Seongjin Ahn, Journal of Internet Computing and Services, Vol. 24, No. 3, pp. 27-41, Jun. 2023
10.7472/jksii.2023.24.3.27, Full Text:
Keywords: AI robot, artificial intelligence robot, AI robot risk, AI robot risk prevention, AI robot risk measurement indicators, AI robot measurement indicators

Abstract

As the era of AI robots such as emotional humanoids approaches, there are unpredictable risks such as robot discrimination remarks and medical accidents, but related research is very insufficient. This paper proposes a risk measurement index for AI robots that is essential for safe robot industrialization. Since the risk of AI robots is a high-level study that must predict artificial intelligence and robot problems, 30 experts, including AI and robot developers and professors and researchers in related fields, were surveyed twice using Delphi techniques. Through two statistical analyses, four risk types, 11 items, and 37 measurement indicators were derived that secured content validity and reliability. If the measurement indicators proposed in this study are checked by using them in fields such as test evaluation, certification, and education of AI robots, humans and AI robots will be able to live a safe life together. It is hoped that the measurement index of this study will become a cornerstone and be actively used in AI robot policies and research in various fields such as the government, industry, education, medical care, and home so that AI robots can be used safely.

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