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http://dx.doi.org/10.14400/JDC.2022.20.2.269

A Data Analysis and Visualization of AI Ethics -Focusing on the interactive AI service 'Lee Luda'-  

Lee, Su-Ryeon (Department of Information Security, Seoul Women's University)
Choi, Eun-Jung (Department of Information Security, Seoul Women's University)
Publication Information
Journal of Digital Convergence / v.20, no.2, 2022 , pp. 269-275 More about this Journal
Abstract
As artificial intelligence services targeting humans increase, social demands are increasing that artificial intelligence should also be made on an ethical basis. Following this trend, the government and businesses are preparing policies and norms related to artificial intelligence ethics. In order to establish reasonable policies and norms, the first step is to understand the public's perceptions. In this paper, social data and news comments were collected and analyzed to understand the public's perception related to artificial intelligence and ethics. Interest analysis, emotional analysis, and discourse analysis were performed and visualized on the collected datasets. As a result of the analysis, interest in "artificial intelligence ethics" and "artificial intelligence" favorability showed an inversely proportional correlation. As a result of discourse analysis, the biggest issue was "personal information leakage," and it also showed a discourse on contamination and deflection of learning data and whether computer-made artificial intelligence should be given a legal personality. This study can be used as data to grasp the public's perception when preparing artificial intelligence ethical norms and policies.
Keywords
AI; Artificial Intelligence; AI ethics; BERT; CONCOR analysis;
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Times Cited By KSCI : 4  (Citation Analysis)
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1 D. G. Kim & S. Y. Shin. (2021). Comparing the Results of Big-Data with Questionnaire Survey. Journal of the Korea Institute of Information and Communication Engineering, 20(11), 2027-2032 DOI : 10.6109/jkiice.2016.20.11.2027   DOI
2 Y. H Ko & C. S Leem. (2021). The Influence of AI Technology Acceptance and Ethical Awareness towards Intention to Use. Journal of Digital Convergence, 19(3), 217-225 DOI : 10.14400/JDC.2021.19.3.217   DOI
3 G. S. Kim & Y. J. Shin. (2021). A Cross-Sectional Study of Artificial Intelligence Ethics Awareness - Preparation for Climate Change Education Using Artificial Intelligence -. Jounral of Energy and Climate Change Education (JECCE), 11(1), 27-36 DOI : 10.22368/ksecce.2021.11.1.27   DOI
4 G. S. Choe, Y. G. Ham & S. H. Kim. (2013) Bigdata Visualization. KSCI Review, 21(1), 33-43
5 Personal Information Protection Commission, (2021). Case of corrective action for violation of the Personal Information Protection Act. no 2021-007-072
6 K. H. Kim. (2021). Current Status and Implications of Artificial Intelligence (AI) Introduction by Major Industries. Jincheon : KISDI
7 K. S. Kwang. (2021. 03). The problem left by the chatbot "Iruda" in our society: Mounting a human rights manual on artificial intelligence. Culture and science, 105, 183-198.
8 Ministry of Science and ICT. (2021.05.13.). The government has come up with a reliable AI realization strategy centered on people. https://www.korea.kr/news/policyNewsView.do?newsId=148887381
9 NAVER. (2021.02). AI ethical rules. https://www.navercorp.com/value/aiCodeEthics
10 W. Y. Lee. (2011). Seoul National University Law. The Law Research Institute Seoul National University, 52(4), 125-168 UCI : G704-002133.2011.52.4.003
11 Y, H. Kim. (2020. Oct). Understanding and application of social network analysis technology. KIPA Research Forum, 34, 58-68
12 Friendly, M. (2008). A brief history of data visualization. In Handbook of data visualization (pp. 15-56). Springer, Berlin, Heidelberg. DOI : 10.1007/978-3-540-33037-0_2   DOI
13 Veale. M. & Borgesius. F. Z. (2021). Demystifying the Draft EU Artificial Intelligence Act-Analysing the good, the bad, and the unclear elements of the proposed approach. Computer Law Review International, 22(4), 97-112. DOI : 10.9785/cri-2021-220402   DOI
14 Borgatti, S.P., Everett, M.G. and Freeman, L.C. (2002). Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies.
15 J. H. Park. (2021). An Analysis of Perception on Law and Policy regarding the 4th Industrial Revolution. Korean Journal of Law & Society, 66, 175-204 DOI : 10.33446/KJLS.56.3   DOI
16 J. H. Lee, J. M. Moon & Y. S. Jang. (2017). Analysis of 2018 PyeongChang Olympic keywords using social network big data analysis. Korean Journal of Sport Management, 22(6), 73-89 DOI : 10.31308/KSSM.22.6.5   DOI
17 W. G. Kang, E. S. Ko, H. R. Lee & J. N. Kim. (2018). A Study of the Consumer Major Perception of Packaging Using Big Data Analysis -Focusing on Text Mining and Semantic Network Analysis-. Journal of the Korea Convergence Society. 9(4). 15-22 DOI : 10.15207/JKCS.2018.9.4.015   DOI
18 J. S. Lee. (2013). A Study on Visualizing Method and Expression of Information Design for Big Data. Journal of Basic Design & Art, 14(3), 259-269 UCI : G704-001069.2013.14.3.026
19 J. Devlin, M. W. Chand, K. Lee, K. Toutanova. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.