DOI QR코드

DOI QR Code

An Analysis of Gender Differences in Primary, Middle and High School Students' Artificial Intelligence Ethics Awareness

초·중·고등학생의 인공지능 윤리의식의 성차 분석

  • Received : 2021.03.23
  • Accepted : 2021.04.26
  • Published : 2021.04.30

Abstract

The purpose of this study is to analyze the gender differences of elementary, junior high, and high school students in the artificial intelligence ethics awareness (hereinafter referred to as AIEA). This is a study to investigate whether there is a gender difference in the AIEA, and if so, when the gender difference will occur. This study was conducted with 198 elementary school students (98 female students, 100 male students), 265 middle school students (166 female students, 99 male students), and 114 high school students (58 female students and 56 male students) in I Metropolitan City. The results are as follows: First, a gender difference in the AIEA between all boys and girls was confirmed. Second, the gender difference in the AIEA tended to be solidified as the school age increased from elementary school to middle school and high school. Third, female students at all stages of elementary school, junior high school, and high school are not yet very reliable in artificial intelligence, and there is a greater concern about non-discrimination than boys. It turns out that they have a negative position on permission to enter the territory. Fourth, the interaction effects of school age and gender have been identified in 'stability and reliability,' and in 'permit and limit' categories. Taken together, these results show that an educational strategy that approaches the gender equality perspective of the educational program is necessary so that there will be no gender difference in the AIEA during artificial intelligence education activities.

이 연구의 목적은 인공지능 윤리의식에 대한 초등학교, 중학교, 고등학교 학생들의 성차를 분석하는 것이다. 과연 인공지능 윤리의식에 성차가 존재하는지, 존재한다면 언제부터 성차가 발생하는지를 알아보기 위한 연구이다. 본 연구는 I 광역시 초등학생 198명(여학생 98명, 남학생 100명), 중학생 265명(여학생 166명, 남학생 99명), 고등학생 114명(여학생 58명, 남학생 56명)을 대상으로 실시하였다. 본 연구 결과는 다음과 같다. 첫째, 전체 남학생과 여학생 사이의 인공지능 윤리의식의 성차가 확인되었다. 둘째, 인공지능 윤리의식의 성차는 초등학교에서 중학교, 고등학교로 학령이 높아질수록 확고해지는 경향이 있었다. 셋째, 초등학생, 중학생, 고등학생 모든 단계에서 여학생은 아직 인공지능에 대한 신뢰성이 그리 높지 않고, 차별 금지에 대한 우려가 남학생에 비해 크며, 예술 등의 분야에서 인공지능의 인간 영역에의 진입 허용에 대해 부정적인 입장을 가지고 있는 것으로 파악되었다. 넷째, 학령과 성별의 상호 작용 효과는 안정성 및 신뢰성, 그리고 허용과 한계 범주에서 확인되었다. 이러한 결과들을 종합해 볼 때, 인공지능 교육 활동시 인공지능 윤리의식에 성차가 생기지 않도록 교육 프로그램을 양성 평등적으로 접근하는 교육적 방안이 필요하다고 할 수 있다.

Keywords

References

  1. Bang, J. M. (2021). The transition of regulatory governance on AI algorithms - Focused on US algorithmic regulations and AI ethical principles. Public Law, 49(3), 375-406. https://doi.org/10.38176/PublicLaw.2021.02.49.3.375
  2. Barrat, J. (2013). Our final invention: Artificial intelligence and the end of the human era. New York, NY: Thomas Dunne Books/St Martin's Press.
  3. Barton, A. C. (1998). Feminist science education. Teachers College Press.
  4. Byun, S. Y. (2019). A study on the ethics certification program based on the morality types of AI robots. Journal of Ethics, 126, 73-90.
  5. Byun, S. Y. (2020). A study on the necessity of AI ethics education. The Journal of Korea elementary education, 31(3), 153-164.
  6. Heo, E. S., Lee, Y. H., & Shin, J. W. (2020). Why ethics is: A landscape of modern AI ethics debate, Its features and limitations. Human Beings, Environment and Their Future, 24, 165-209.
  7. Ji, H. A. (2020). A study on the application of roboethics to moral education (Doctoral Dissertation). Seoul National University.
  8. Kim. D. H. (2016). Forming and indicating a christian theological discourse on AI. Theological Studies, 68, 35-60.
  9. Kim, G. S., & Shin, Y. J. (2021). Study on the development of test for artificial intelligence ethical awareness. Journal of The Korean Association of Artificial Intelligence Education, 2(1), 1-19. https://doi.org/10.52618/aied.2021.2.1.1
  10. Kim, H. G., & Kim, Y. S. (2020). Meta-analysis of gender difference in performance on the information subtest of the Korean-Wechsler intelligence scale. The Korean Journal of Rehabilitation Psychology, 27(4), 151-163. https://doi.org/10.35734/KARP.2020.27.4.009
  11. Kim, J. H. (2010). Are women more sensitive than men to the risk of cyber victimizations?: Health communication perspective. Health Communication Research, 2(2), 155-180.
  12. Kim, J. M. (2020). Artificial intelligence algorithm regulation status, recent trends, and legal implications - Focusing on the issue of artificial intelligence bias. The Digital Ethics, 4(2), 27-42.
  13. Kim, M. J. (2017). The necessity of artificial intelligence ethics and trends in Korea and abroad. Journal of The Korean Institute of Communication Sciences, 34(10), 45-54.
  14. Kline, R. (2010). Cybernetics, automata studies, and the Dartmouth conference on artificial intelligence. IEEE Annals of the History of Computing, 33(4), 5-16. https://doi.org/10.1109/MAHC.2010.44
  15. Kurzweil, R. (2005). The singularity is near. New York, NY: Viking.
  16. Lee, A. R., Lee, Y. J., & Yang, H. I. (2014). The effects of cyber bullying and bullied experience on upper elementary students' aggression and verbal aggression. Korea Journal of Counseling, 15(6), 2437-2450. https://doi.org/10.15703/kjc.15.6.201412.2437
  17. Lee, C. S., & Lee, H. J. (2019). Expectations and anxieties affecting attitudes toward artificial intelligence revolution. Journal of the Korea Contents Association, 19(9), 37-46.
  18. Lee, E. J., & Lee, K. H. (2011). A study on the factors influencing gender differences changes of Korean students in PISA mathematics assessment. Journal of Educational Research in Mathematics, 21(4), 313-326.
  19. Lee, J. W. (2019). Can we impose responsibilities on artificial intelligence? To seek accountability- oriented ethics for artificial intelligence. Korean Journal for the Philosophy of Science, 22(2), 70-104.
  20. Lee, K. S., & Park, I. Y. (2015). Characteristics on gender difference of Korean students in TIMSS mathematics assessment. The Journal of Curriculum and Evaluation, 18(1), 155-183. https://doi.org/10.29221/jce.2015.18.1.155
  21. Ministry of Education [MOE]. (2020). Educational policy directions and key tasks in the age of artificial intelligence. Press Release, Nov., 20. 2020,
  22. Ministry of Science and ICT [MSIT]. (2020). Human-centered ethical standards for artificial intelligence. Press Release, Dec., 23. 2020,
  23. Organisation for Economic Co-operation and Development [OECD]. (2019). Trends shaping education 2019. Paris: OECD Publishing, DOI: 10.1787/trends_edu-2019-en.
  24. Oh, T. W. (2020). EU policy for AI ethics from white paper on artificial intelligence. The Digital Ethics, 4(1), 22-31.
  25. Park, A. C., & Woo, C. Y. (2008). The relationship among high school students' attachment for their parents and peers depending on gender, self-identity, and career decision-making levels. The Korean Journal of Educational Psychology, 22(1), 69-85.
  26. Park, C. J., Dong, H. K., & Shin, Y. J. (2007). An analysis of preferences for science and the role gender differences plays in determining preferences for It amongst elementary school students. Journal of Korean Elementary Science Education, 26(2), 216-225.
  27. Park, J. Y. (2018). Trend analysis of artificial intelligence technology using patent information. Journal of the Korea society of computer and information, 23(4), 9-16. https://doi.org/10.9708/JKSCI.2018.23.04.009
  28. Song, M. Y., Im, H. J., Rim, H. M., Park, H. Y., & Ku, J. O. (2015). Educational factors influencing the gender difference in PISA. The journal of Educational Studies, 46(4), 99-122. https://doi.org/10.15854/jes.2015.12.46.4.99
  29. Sung, S. J. (1999). Cyberface and gender difference ideology. Journal of Women Studies, 10, 101-116.
  30. Yoo, E. H. (2018). Online privacy, technologies, and perceived risk. The Journal of Social Science, 25(2), 82-100. https://doi.org/10.46415/jss.2018.06.25.2.82
  31. Yoon, S. H. (2016). The shaping and changes of scientific discourses: Focusing on the discourses on sex/gender differences in neuroscience (Doctoral Dissertation). Seoul National University.
  32. Yun, S. J. (2020). The allegory of AI and empathy in the movie Her. The Journal of Image and Cultural Contents, 19, 213-236. https://doi.org/10.24174/jicc.2020.02.19.213