경인행정학회

키워드

초록

본 연구는 인공지능을 비롯한 디지털 신기술이 우리 사회를 변화시키고 있는 이 시점에서 새롭게 등장한 자동적 책무성 체계하에서 발생할 수 있는 결과에 대한 책임 문제를 살펴보았다.
이를 위해 본 연구는 책무성 체계 분석틀을 활용하여 인공지능 기반 의사결정 시스템의 책무성 확보를 위한 역할책임(role responsibility), 설명책임(explanatory responsibility), 부담책임(liability)에 대해 살펴보았다. 역할책임에 대해서는 RASCI 모델을 활용하여 인공지능 기반 의사결정 시스템의 생명주기 별로 이해관계자 간 역할분담 방향을 제시하였다. 그리고 설명책임과 관련해서는 해당 시스템의 생명주기 별로 설명 가능성(explainability)을 고려한 이해관계자 간 책임 배분에 대해 살펴보았다. 마지막으로 부담책임은 인공지능 시스템의 복잡성이 초래한 책임 부담의 주요 이슈들에 대해 학자들의 논의를 중심으로 살펴보았다.
이러한 연구 결과를 바탕으로 외국의 인공지능 관련 법제화 동향과 함께 우리나라의 인공지능 관련 법령 및 가이드라인이 인공지능 기반 의사결정 시스템의 책무성 확보를 위해 어떤 한계를 보이고 있는지 분석하고, 향후 우리나라에서 인공지능 책무성 문제에 적절하게 대응하기 위해 고려하여야 할 사항을 정책적 제안으로 제시하였다.

This study examines the issue of accountability within emerging automated accountability frameworks at a time when artificial intelligence (AI) and other digital emerging technologies are fundamentally transforming society. To this end, the study employs an accountability framework to analyze three core dimensions of accountability in AI-based decision-making systems: role responsibility, explanatory responsibility, and liability.
With respect to role responsibility, the study applies the RASCI model to propose a systematic allocation of roles and responsibilities among stakeholders across the life cycle of AI-based decision-making systems. Regarding explanatory responsibility, it examines how accountability for explainability should be distributed among relevant actors at each stage of the system life cycle. Finally, in addressing liability, the study reviews major scholarly debates concerning the challenges of attributing and allocating responsibility arising from the complexity of AI systems.
Based on these analytical findings, the study evaluates recent trends in foreign AI-related legislation alongside South Korea’s AI-related laws and guidelines, identifying their limitations in ensuring accountability for AI-based decision-making systems. It concludes by offering policy recommendations on how South Korea should respond more effectively to emerging accountability challenges associated with artificial intelligence.

목차

Ⅰ. 서론
Ⅱ. AI와 책무성에 대한 이론적 논의
Ⅲ. AI 시스템의 책무성 확보를 위한 분석틀 및 책임 배분
Ⅳ. AI 시스템의 책무성 확보 방향
Ⅴ. 결론

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