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GCRI · 인공지능과 자율 시스템

혁신과 실용 기술

Technology relevant to artificial intelligence and data and compute: what it can do, the constraints it faces and its consequences for people and institutions.

01순서

일이 일어나는 순서.

  1. 01초안출처 인용, 표시 부착
  2. 02근거 점검모든 값의 출처 추적
  3. 03독립 검토신고된 이해충돌
  4. 04판한계와 함께 공표됨
  5. 05정정조용한 수정이 아닌 새 버전
02접근 방식

Evaluate before adopting.

  1. 01

    Need

    Which problem does the technology address, and for whom?

  2. 02

    증거

    What has been demonstrated, under what conditions, and what remains untested?

  3. 03

    Constraints

    Cost, skills, infrastructure, data and governance requirements.

  4. 04

    Consequences

    Effects on safety, rights, equity and the environment.

03Technologies under assessment

What could change AI practice, and what it still has to show.

기술What it could changeWhat remains to be shown
Automated red teamingBroader coverage of failure modesCoverage of novel failures; evaluator reliability
Interpretability methodsUnderstanding why models failScale and faithfulness of explanations
Content provenance standardsLabelling synthetic mediaAdoption and robustness to removal
AI for scientific discoveryFaster hypotheses and simulationValidation and reproducibility
04Build and test

From idea to tested capability.

Promising work can be built in Foundry and tested under controlled conditions through 유니버스. No technology is described as proven before it has been tested and reviewed.

05출처

Where this page’s references lead.

이 페이지를 읽을 때 기준이 되는 기구와 문서. 상태와 판은 바뀌며, 각 링크는 발행 기구로 연결됩니다.

06질문

질문과 답변.

Does the platform endorse products?
No. It evaluates technologies and publishes what it finds, with limits. It does not endorse, certify or recommend products or vendors.
보고서기여하기

이 페이지에서 증거를 기여하십시오.

보고서 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRI인공지능과 자율 시스템기하급수 기술Labs 근거
인공지능과 자율 시스템

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