At Google, a central team is dedicated to ethical reviews of new AI and advanced technologies before launch, working with internal domain experts in machine-learning fairness, security, privacy, human rights, the social sciences, and, for cultural context, Google's employee resource groups.
AI 治理有方:严格审核、稳健运营
AI Governance reviews and operations
我们会审慎评估新的 AI 研究和应用提案,确保其符合我们的原则。随着先进技术的不断涌现和发展,我们将继续优化相关流程。
We assess proposals for new AI research and applications for alignment with our Principles. As advanced technologies emerge and evolve, we'll continue to refine our process.
概览
Overview
任何团队都可以寻求 AI 原则建议。审核人员还会将层出不穷的新 AI 研究论文、产品创意和其他项目纳入审核范围。
Any team can request AI Principles advice. Reviewers also consider an ongoing pipeline of new AI research papers, product ideas, and other projects.
审核人员会分析技术潜在利弊的影响面。
Reviewers analyze the scale and scope of a technology's potential benefits and harms.
审核人员会提出技术评估建议(例如,检查 ML 模型是否持有不公平的偏见)。
Reviewers recommend technical evaluations (e.g., checking for unfair bias in ML models).
审核人员会决定是否要准许继续推进所审核的 AI 应用(例如 Cloud AI Hub 和"文字转语音")。
Reviewers decide whether to pursue or not pursue the AI application under review (e.g., Cloud AI Hub and text-to-speech).
践行我们的 AI 原则
Implementing Our AI Principles
AI 的构建和部署方式将对社会产生深刻影响。欢迎详细了解我们如何在研究和产品中切实践行我们的 AI 原则。
The ways in which artificial intelligence is built and deployed will significantly affect society. Learn more about how we are applying our AI principles across Google research and products.
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负责任地开发 Bard
Responsible Development of Bard
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负责任地开发 SGE
Responsible Development of SGE
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负责任地开发 Lookout
Responsible Development of Lookout
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Responsible GenAI:3 种新兴的推荐实践
Responsible generative AI: 3 emerging practices
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Responsible AI:回顾 2022,展望未来
Responsible AI: Looking back at 2022, and to the future
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Responsible AI:2022 年及之后的 Google 研究动向
Google Research, 2022 & beyond: Responsible AI
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负责任地创新:我们的最新工作进展
An update on our work in responsible innovation
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Dynamic World
Dynamic World
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AI 原则如何指引 Fitbit ML 功能开发
How AI Principles helped guide the development of a Fitbit ML feature
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一个用于评估 ML 翻译模型中的性别偏见的数据集
A Dataset for Evaluating Gender Bias in ML Translation Models
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我们采用的人脸识别方法
Our approach to facial recognition
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Responsible AI 创新:我们的最新进展
An update on our progress in responsible AI innovation
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人像光效
Portrait Light