인공지능 증거의 심리방법

• 영문명: Examination of AI-Generated Evidence
• 발행기관: 한국민사소송법학회
• 저자명: 전원열(Wonyol Jon)
• 간행물 정보: 『민사소송』제28권 제3호, 55~94쪽, 전체 40쪽
• 주제분류: 법학 > 법학
• 파일형태: PDF
• 발행일자: 2024.10.31

국문 초록

The era of artificial intelligence has arrived, sparking discussions on how AI can be utilized in litigation processes. However, there has been relatively little discussion about how to evaluate and examine evidence generated by AI when it is submitted in court. This paper begins by examining how different jurisdictions address the admissibility and weight of evidence, as a foundation for studying the examination of AI-generated evidence. It argues that rejecting AI evidence at the admissibility stage is unreasonable. Furthermore, after considering the unique characteristics of AI-generated evidence, this paper explores the possibility of subjecting such evidence to cross-examination. Following a discussion of the Daubert standard, which applies to general scientific evidence, the paper focuses on and analyzes key issues—such as error rates, data size, and the “black box” nature of AI—that may arise when applying the standard to AI evidence.

목차

Ⅰ. 서론

Ⅱ. 증거로서의 자격과 가치

Ⅲ. AI 증거의 개념과 반대신문권

Ⅳ. AI 증거의 심리방법

Ⅴ. 결론

키워드

인공지능 증거능력 반대신문 도버트 기준 데이터 사이즈 블랙박스 artificial intelligence admissibility cross examination Daubert standard size of data black box