• Journal of Korea Entertainment Industry Association
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• v.15 no.6
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• pp.93-103
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• 2021

The purpose of this study is to explore changes in future sports by introducing baseball robot umpire. The study was conducted using qualitative research methods, and participants selected five baseball fans who were interested in baseball. The results of the study are as follows. First, baseball fans expressed displeasure with the frequent misjudgment in Korean Professional Baseball game, and doubted the fairness of the umpire's judgment. And repeated misjudgment of professional baseball has contributed to the decline in viewing and viewing of baseball. Second, baseball fans were positive about the introduction of robot umpire as a way to reduce bad calls in baseball games, and considered the accuracy, consistency, and recordability of robot umpire to complement their limitations. Third, the application of baseball robot umpire will serve as a basis for strengthening the fairness and efficiency of baseball games, which will positively change the image of sports. As a result, the introduction of robot umpire in baseball games could exert desirable influence on people and contribute to restoring the ethics of sports and strengthening fairness.

• Journal of The Korean Association of Information Education
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• v.26 no.4
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• pp.273-284
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• 2022

The goal of this paper is to propose the use of machine learning platforms in education to train learners to recognize data biases. Learners can cultivate the ability to recognize when learners deal with AI data and systems when they want to prevent damage caused by data bias. Specifically, this paper presents a method of data bias education using MachineLearningforKids, focusing on the case of AI baseball referee. Learners take the steps of selecting a specific topic, reviewing prior research, inputting biased/unbiased data on a machine learning platform, composing test data, comparing the results of machine learning, and present implications. Learners can learn that AI data bias should be minimized and the impact of data collection and selection on society. This learning method has the significance of promoting the ease of problem-based self-directed learning, the possibility of combining with coding education, and the combination of humanities and social topics with artificial intelligence literacy.