임무공학(ME)에 기반한 AI 무인체계 개발 방법론: 설명가능성 및 통제가능성의 핵심 기능 분석 중심으로

김진우¹^{, *} ; 양정규²

1해군 대령/해군대학 해양전략·전력학처장/컴퓨터공학 박사·국제정치학 박사
2해군 중령/해군대학 획득관리 교관/조선해양공학 박사과정 수료

A Study on Mission Engineering-based Development Methodology for AI Unmanned Systems: Focusing on Explainability and Controllability

Jinwoo Kim¹^{, *} ; Jungkyu Yang²

1CAPT, ROK Navy/Director of Maritime Strategy & Military Force Studies, ROK Naval War College/Ph.D. in computer science & engineering, Ph.D. in international political science
2CDR, ROK Navy/Instructor on Defense Acquisition, ROK Naval War College/Ph.D. Candidate, Dept. of Naval Architecture and Ocean Engineering, Inha University

Correspondence to: ^*Jinwoo Kim Dept. of Naval Strategy and Force Planning, Republic of Korea Naval War College 271, Jaun-ro, Yuseong-gu, Daejeon, 34059, Republic of Korea Tel: +82-42-975-2420 E-mail: pkm311@gmail.com

초록

인공지능(AI) 기반 무인체계는 다양한 임무에서 전력승수로 활용될 잠재력이 크지만, 단순한 성능 충족만으로는 불확실한 전장에서 운용 신뢰성을 확보하기 어렵다. 본 연구는 이러한 한계를 보완하기 위해 설명가능성과 통제가능성을 핵심 요인으로 설정하고, 이를 임무공학(mission engineering) 절차에 통합하는 개념적 틀을 제시하였다. 또한 임무 단계별 적용과 위험 수준별 요구, 소요-기술-체계 연계, 지속적 인증 개념을 논의함으로써 기술 효율성과 작전 신뢰성의 균형을 위한 정책적 시사점을 도출하였다.

Abstract

AI-enabled unmanned systems possess strong potential as force multipliers, but performance metrics alone cannot ensure reliability in contested environments. This study frames explainability and controllability as core determinants and embeds them within the Mission Engineering process. By addressing risk-differentiated requirements, system–technology integration, and continuous certification, it offers policy insights for balancing technological efficiency with operational trustworthiness.

Keywords:

AI-enabled Unmanned Systems, Mission Engineering, Explainability, Controllability, Trustworthiness, Continuous Certification

키워드:

AI 기반 무인체계, 임무공학, 설명가능성, 통제가능성, 신뢰성, 지속적 인증

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