정보처리학회지 (Korea Information Processing Society Review)

  • 제28권3호
  • /
  • Pages.45-55
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  • 2021
  • /
  • 1226-9182(pISSN)
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  • 2734-0376(eISSN)
한국정보처리학회 (Korea Information Processing Society)
권호 표지

인공지능 시스템의 신뢰성 확보를 위한 설명가능 인공지능 기술 동향

  • 발행 : 2021.09.30
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초록

키워드

참고문헌

  1. S. R. Islam, W. Eberle, S. Khaled, M. Ahmed, "Explainable Artificial Intelligence Approaches: A Survey," arXiv.2101.09429 v1, Jan. 2021.
  2. KISA GDPR 대응지원 센터, https://gdpr.kisa.or.kr.
  3. 신용우, "인공지능 관련 입법 현황 및 전망," 국회입법조사처, 2019년 12월
  4. Depart Innovation Board, "AI Principles: Recommendations on the Ethical Use of Artificial Intelligence by the Department of Defense," Oct. 2019.
  5. 양서연, "차별하는 인공지능: AI가 확산할 수 있는 은연 중 차별과 우려와 새로운 사회적 윤리의 필요성," pp. 28-34, 한국여성정책연구원 젠더리뷰 54호, 2019.
  6. M. V. Lent, W. Fisher, M. Mancuso, "An Explainable Artificial Intelligence System for Small-unit Tactical Behavior," pp. 25-29, 16th Proc. of Innovative Applications of Artificial Intelligence, July, 2004.
  7. P. J. Phillips, C. A. Hahn, P. C. Fontana, D. A. Broniatowski, M. A. Przybocki, "Four Principles of Explainable Artificial Intelligence," NIST Report, Draft NISTIR 8312, August 2020.
  8. A.B. Arrieta, N. Diaz-Rodriguez, J. D. Ser, A. Bennetot, S. Tabik, et. al., " Explainable Artificial Intelligence(XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsive AI," Information Fusion, Vol. 58, Dec. 2019.
  9. D. Gunning, D. W. Aha, "DARPA's Explainable Artificial Intelligence Program," AI Magazine, Vol. 40, No. 2, pp. 44-58, Summer 2019. https://doi.org/10.1609/aimag.v40i2.2850
  10. W. Samek, T. Wiegand, K.-R. Muller, "Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models," ITU Journal: ICT Discoveries, Special Issue No. 1, Oct. 2017.