Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

The Role of Confidence in Government in Acceptance Intention towards Artificial Intelligence

인공지능 수용의도에서 정부신뢰의 역할

  • Hwang, SeoI (HK Research, Humanities Research Institute, Chung-Ang University) ;
  • Nam, YoungJa (HK Research, Humanities Research Institute, Chung-Ang University)
  • 황서이 (중앙대학교 인문콘텐츠연구소) ;
  • 남영자 (중앙대학교 인문콘텐츠연구소)
  • Received : 2020.07.07
  • Accepted : 2020.08.20
  • Published : 2020.08.28
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study is to discuss implications for government policy aimed at increasing public's intention to accept AI. Knowledge regarding AI and feelings regarding AI were found to influence acceptance to intention towards AI. Hierarchical regression analysis was then conducted to explore the moderation effect of confidence in government on knowledge and feelings regarding AI. Results showed that as advanced knowledge regarding AI has a positive influence on acceptance intention towards AI and negative feelings regarding AI has a negative influence on acceptance intention towards AI. Feelings regarding AI had the highest impact on acceptance intention towards AI, followed by confidence in government and knowledge regarding AI. Results also revealed that a high level of confidence in government regulations was associated with greater acceptance intention towards AI and a low level of confidence in government regulations acceptance intention towards AI was more influenced by feelings regarding AI than by knowledge regarding AI. Furthermore, religion had a significant influence on acceptance intention towards AI, which provides one insightful direction for future research.

본 연구는 인공지능 수용의도를 증가시킬 수 있는 정책적 시사점을 제시하고자 하였다. 이를 위해 인공지능에 대한 지식수준과 감정적 요인이 인공지능 수용의도에 미치는 영향을 확인하였고, 이에 대한 영향을 정부신뢰가 조절하는지 검증하고자 위계적 회귀분석을 활용하였다. 연구결과는 다음과 같다. 첫째, 인공지능에 대한 지식수준이 높을수록 수용의도가 증가하였고, 인공지능에 대한 감정이 부정적으로 형성될수록 인공지능의 수용의도가 감소하였다. 그리고 수용의도에 미치는 영향은 인공지능에 대한 감정, 정부신뢰, 지식 순으로 나타났다. 둘째, 규제에 대한 정부신뢰가 높을수록 수용의도가 증가하였으며, 규제에 대한 정부신뢰가 낮은 집단일수록 인공지능에 대한 감정이 수용의도에 미치는 영향이 더 큰 것으로 나타났다. 한편, 인구통계학적 요인 중 종교가 인공지능 수용의도에 유의미한 영향을 미치는 것으로 나타나 후속연구에 대한 필요성을 제안하였다. 이 연구는 전반적인 인공지능에 대한 지식과 감정, 그리고 규제에 대한 정부신뢰라는 변인을 통해 인공지능에 대한 인식과 판단을 실증 분석하여 인공지능 연구를 위한 기초자료를 제공하는데 의의가 있다.

Keywords

References

  1. Y. D. Yun, Y. W. Yang & H. S. Lim. (2016). A SNS Data-driven Comparative Analysis on Changes of Attitudes toward Artificial Intelligence. Journal of Digital Convergence, 14(2), 173-182. DOI : 10.14400/JDC.2016.14.12.173
  2. S. I. Hwang & M. K. Kim. (2019). An Analysis of Artificial Intelligence_related Studies' Trends in Korea Focused on Topic Modeling and Semantic Network Analysis. Journal of Digital Contents Society, 20(9), 1847-1855. DOI : 10.9728/dcs.2019.20.9.1847
  3. S. Y. Kin, S. O. Choi & D. G. Kim. (2010). Searching for Determinants for Acceptance of New Science Technology and Policy Implication. The Korea Association for Policy Studies, 19(1), 211-244. UCI : G704-000110.2010.19.1.006
  4. J. S. Wang & H. J. Lee. (2011). Multi-dimensionality of Perceptions on Science Technology and Its Determinants: The Case of Public Perceptions on Genetically Modified Food. Journal of Governmental Studies, 17(1), 145-185. UCI : G704-000703.2011.17.1.005
  5. J. S. Wang. (2012). Origins of Risk Conflicts on Science Technology: Knowledge or Feeling?. The Korea Association for Policy Studies, 21(1), 219-251. UCI : G704-000110.2012.21.1.006
  6. M. C. Lee, J. A. An & Y. M. Kim. (2018). The Effects on Perceived Risk, Confidence in the Government, and the Acceptance of Nuclear Power Caused by Knowledge to Nuclear Power : Focused on Local Residents Nearby Hanbit Nuclear Power Plant. Practical Science Forum of Advertising & Public Relations, 11(3), 54-74. DOI : 10.21331/jprapr.2018.11.3.003
  7. M. Siegrist & G. Cvetkovich. (2000). Perception of Hazards: The Role of Social Trust and Knowledge. Risk Analysis, 20(5), 713-719. DOI : 10.1111/0272-4332.205064
  8. I. J. Mauro & S. M. McLachlan. (2008). Farmer Knowledge and Risk analysis: Post release Evaluation of Herbicide-Tolerant Canola in Western Canada. Risk Analysis, 28(2), 463-476. DOI: 10.1007/s11356-009-0177-6
  9. P. Slovic, M. Finucane, E. Peters, & D. G. MacGregor. (2004). Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality. Risk analysis, 24(2), 311-322. DOI : 10.1111/j.0272-4332.2004.00433.x
  10. E. Townsend, D. D. Clarke & B. Travis. (2004). Effects of Context and Feelings on Perceptions of Genetically Modified Food. Risk Analysis, 24(5), 1369-1384. DOI : 10.1111/j.0272-4332.2004.00532.x
  11. J. S. Wang. (2019). Policy Participations, Government Trust and Policy Acceptance: The Case of Nuclear Policy. The Korea Public Administration Journal, 28(1), 33-60. DOI : 10.22897/kipajn.2019.28.1.002
  12. T. C. Earle & M. Siegrist. (2006). Morality Information, Performance Information, and the Distinction Between Trust and Confidence. Journal of Applied Social Psychology, 36(2), 383-416. DOI : 10.1111/j.0021-9029.2006.00012.x
  13. M. Siegrist, H. Gutscher & T. C. Earle. (2008). Perception of risk: the influence of general trust, and general confidence. Journal of Risk Research, 8(2), 145-156. DOI : 10.1080/1366987032000105315
  14. K. Min. (2009). The Impact of Local Residents' Rurality on Policy Acceptance: A Case of Ropeway Establishment in Mt. Halla. Korean Governance Review, 16(3), 53-70. DOI : 10.17089/kgr.2009.16.3.003
  15. T. J. Kim, J. E. Lee & Y. S. Jung. (2007). TA Study on the Social Risk Comparison for Various Power Systems. The Korea Spatial Planning Review, 55, 41-58. DOI : 10.15793/kspr.2007.55.4.003
  16. G. F. Loewenstein, E. U. Weber, C. K. Hsee & N. Welch,. (2001). Risk as Feeling. Psychological Bulletin, 127, 267-286. DOI: 10.1037/0033-2909.127.2.267
  17. M. Y. Oh, J .M. Choi & H. S. Kim. (2008). Stigma Effect of Technology with Risk : the Impact of Stigma on Nuclear Power on the Perception and Acceptance of Products based on Radiation Technology. Korean Journal of Journalism & Communication Studies, 52(1), 467-501. UCI : G704-000203.2008.52.1.015
  18. C. H. Park & S. Y. Kim. (2015). The Role of Knowledge in Acceptance of Nuclear Power: A Focus on Objective and Subjective Knowledge. Korean Journal of Public Administration, 53(3), 117-150. UCI : G704-000826.2015.53.3.006
  19. J. W. Mok. (2017). Moderating Effect of Knowledge Level on the Risk and Acceptance Relationship: The Case of Korean Nuclear Policy. The Korea Association for Policy Studies, 26(2), 419-448. UCI : 410.ECN.0102.2018.300.000590489
  20. A. Knight. (2007). Do Worldviews Matter? Post-materialist, Environmental, and Scientific Technological Worldviews and Support for Agricultural Biotechnology Applications. Journal of Risk Research, 10(8), 1047-1063. DOI : 10.1080/13669870701603004
  21. A. Spence & E. Townsend. (2006). Examining Consumer Behavior Toward Genetically Modified Food in Britain. Risk Analysis, 25(3), 657-670. DOI: 10.1111/j.1539-6924.2006.00777.x
  22. Y. G. Kim, J. K. Kim & I. H. Choi. (2015). A Study on Obtaining the Public Acceptance of Nuclear Power for Conflict Resolution. The Study on Exploratory Comparison of Conflict in Conflict Theory, 13(2), 41-76. DOI : 10.16958/drsr.2015.13.2.41
  23. J. S. Wang & S. Y. Kim. (2017). Changes in Nuclear Energy and Trust: Influence of Trust in Objects and Attributes. Journal of Governmental Studies, 23(1), 193-222. DOI : 10.19067/jgs.2017.23.1.193
  24. J. B. Chung & H. K. Kim. (2009). Competition, Economic Benefits, Trust, and Risk Perception in Siting a Potentially Hazardous Facility. Landscape and Urban Planning , 91(1), 8-16. DOI : 10.1016/j.landurbplan.2008.11.005
  25. J. E. Lee, Y. P. Kim & Y. S. Jung. (2007). Analyzing the Decision Factor of the Social Acceptance in te Various Power Systems. The Korea Public Administration Journal, 16(2), 189-217. UCI : G704-000428.2007.16.2.003
  26. D. A. Scheufele. E. A. Corley, T. J. Shin, K. E. Dalrymple & S. S. Ho. (2009). Religious Beliefs and Public Attitudes Toward Nano-technology in Europe and the United States. Nature Nano-technology, 4(2), 91-94. DOI: 10.1038/nnano.2008.361