신뢰할 수 있는 AI를 위한 데이터 품질 요구사항
Ⅰ. 개요 ···············································································································1
Ⅱ. 국제 권고사항 및 표준화 동향 ··································································3
Ⅲ. 연구 및 산업 분야의 데이터 품질 평가 및 편향성 완화를 위한 수평적 이니셔티브 ·····································································································6
Ⅳ. 6대 산업 분야의 데이터 품질 요구사항
1) 교육 및 고용 ······················································································· 13
2) 법 집행 및 공공 부문 ···········································································16
3) 금융 ·······································································································19
4) 소셜 미디어 콘텐츠 조정 추천 시스템을 포함한 미디어 ··················20
5) 의료 및 헬스케어 ··················································································22
6) 산업 자동화 및 로봇 공학 ··································································25
Ⅴ. 향후 논의 내용 ·························································································29
Ⅵ. 결론 ·············································································································33
● 본 데이터산업 동향 이슈브리프 2023 년 제 9 호는 유럽위원회 (European Commission) 의 공동연구센터(JRC) 컨퍼런스 및 워크숍 보고서 「포용적이고 편향되지 않으며 신뢰할 수 있는 AI (DATA QUALITY REQUIREMENTS FOR INCLUSIVE, 를 위한 데이터 품질 요구사항 NON-BIASED AND TRUSTWORTHY AI)1)」를 요약‧정리하였음
● 2022 6 PSIS AI 년 월 개최된 워크숍은 포용적이고 편향되지 않으며 신뢰할 수 있는 AI를 위한 데이터 품질 요구사항에 초점을 맞춤
- 표준화 활동의 우선순위, 특정 기술(Particular technologies), 잠재적 표준화 로드맵 초안 작성을 주 내용으로 진행함
● 이를 바탕으로 본 보고서는 첫째, 데이터세트의 생성 및 데이터화부터 데이터 품질 요구사항, AI 시스템의 편향성 검사 및 완화까지 기존 표준과는 다른 새로운 표준의 필요성을 강조함
● 둘째, 6 AI 개의 특정 산업에서 모델의 데이터 품질 요구사항과 잠재적인 표준화 요구사항에 대해 논의함
한국데이터산업업진흥원
페이스북 데이터바우처 지원사업은 한국데이터산업진흥원과 공급기업, 수요기업으로 구성되어 있습니다. 그 중 오늘은 데이터를 제공하는 ‘공급기업‘에 대해 알려드리겠습니다. 데이터바우
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