我们相信，AI [包括其核心方法，比如机器学习 (ML)] 是一项颠覆性奠基技术。AI 为各种工具、产品和服务赋予了创新用途，每天都会被数十亿人以及诸多企业、政府和其他组织使用。从习以为常的琐事到天马行空的创新，AI 技术可在几乎所有领域为人类提供帮助、补充、动力和启迪。AI 能“解锁”科学新发现，帮助人类攻坚克难、把握机遇、与时俱进。

正如许多人已强调的那样，我们相信 AI 可凭借它的以下能力造福人类和社会：

• 使信息变得更加实用、更易获取，方便世界各地更多人使用，这往往还有助于克服资源获取、残疾和语言等障碍
• 帮助个人和组织做出决策、解决问题、提高日常生活与工作的成效和创造力
• 推动创新，助力开发新颖又实用的产品和服务，让个人、组织乃至整个社会受益
• 帮助应对当下紧迫的现实挑战，例如公共卫生危机、自然灾害、气候变化和可持续发展
• 帮助发现并缓解社会偏见和结构性不平等（例如社会经济、社会人口及区域的不平等）
• 助力科学领域和其他领域开拓创新，以应对人类未来的最大机遇和挑战（例如医疗诊断、药物研发、气候预测）

AI 的奠基性意味着它将赋能现有基础设施、工具、软件、硬件和设备，甚至那些通常被视为与 AI 无关的产品和服务，让它们发生巨变。以 Google 搜索、Google 地图、Google 相册、Google Workspace、Android 和 Pixel 手机为例，AI 已使我们的产品和服务焕然一新。它将显著增强这些产品和服务的实用性，为用户创造更大的价值。它还将孕育出全新类别的辅助工具、产品和服务，且通常会为这些工具和服务赋予独特、突破性的创新功能和性能。这包括更强大更包容的语言翻译器、对话式 AI 和助理、生成式多模态 AI、机器人技术以及无人驾驶汽车。而这一切只是序幕。

We believe that AI, including its core methods such as machine learning (ML), is a foundational and transformational technology. AI enables innovative new uses of tools, products, and services, and it is used by billions of people every day, as well as businesses, governments, and other organizations. AI can assist, complement, empower, and inspire people in almost every field ,from everyday tasks to bold and imaginative endeavors. It can unlock new scientific discoveries and opportunities, and help tackle humanity's greatest challenges -today and in the future.

As many have highlighted, we believe that AI has the potential to benefit people and society through its capacity to:

• Make information more useful and available to more people, everywhere, often helping overcome barriers including access, disabilities and language
• Assist people and organizations to make decisions, solve problems, be more productive and creative in their daily and work lives
• Enable innovation that leads to new, helpful products and services for people, organizations, and society more broadly
• Help tackle current and pressing real world challenges, such as public health crises, natural disasters, climate change, and sustainability
• Help identify, and mitigate societal biases and structural inequities (e.g. socio-economic, socio-demographic and regional inequities)
• Enable scientific and other breakthroughs to address humanity's greatest future opportunities and challenges (e.g. medical diagnosis, drug discovery, climate forecasting)

The foundational nature of AI means that AI will also power and transform existing infrastructure, tools, software, hardware, and devices-including products and services not normally thought of as AI. Examples in our case that are already being transformed by AI include Google Search, Google Maps, Google Photos, Google Workspace, Android, and Pixel phones. It will significantly enhance their usefulness and multiply their value to people. It will also lead to new categories of assistive tools, products, and services, often with breakthrough capabilities and performance made possible only through AI. This includes more powerful and inclusive language translators, conversational AI and assistants, generative and multi-modal AI, robotics and driverless cars. And this is just the beginning.

Google 及其母公司 Alphabet 谨记初心，致力于运用 AI 实现创新，造福大众和社会。在推动科技不断取得突破性进展的同时，我们持续拓展和提升 AI 能力，努力研发能改善民众生活的创新成果，而这些成果所带来的可持续价值也将激励我们继续投资于颠覆性创新。

我们正在通过以下几种方式来践行并实现这一愿景：

推动前沿科技迅速发展，研发更强大的 AI 系统，造福人类和社会。

• 引领开创性奠基 AI 研究，开发更强大更有助益的 AI，协助人们更加轻松高效地处理各种任务。我们贡献的创新成果不仅已推动整个领域取得显著进展，还被 Google 内外广泛借鉴，这些创新成果包括：Transformer、Word2Vec、序列到序列学习、联邦学习、模型蒸馏、diffusion 模型、深度强化学习、带有树搜索的神经网络、自学习系统、神经架构搜索、自回归模型、带有外部记忆的网络、大规模分布式深度网络、张量处理单元
• 利用 AI 在科学和其他领域取得突破性进展，力求最终推动科学和工程技术不断进步。我们在 AI 和科学领域取得了广受关注的突破性成果，它们能造福全人类，包括：绘制几乎所有已知蛋白质的图谱、预测蛋白质的功能、在神经科学研究中绘制大脑局部图谱、发现更快速的算法、量子计算和物理学领域的进步（包括核聚变方面的创新）

将颠覆性 AI 技术融入各种实用的基础设施、产品和服务，让更多的个人、企业、组织（无论规模大小）和经济体受益。

• 构建安全可靠、便捷易用的先进 AI 基础设施，包括计算工具（例如张量处理单元、Google Tensor 和 Colab）以及广泛使用的软件框架（例如 TensorFlow、Jax、Android ML和 Private Compute）。通过大量开源工具分享这一 AI 基础设施，方便全球数百万开发者、学生和各类组织的科研人员使用。
• 将我们取得的 AI 成就应用于我们的核心产品与服务，促成颠覆性的改进、变革和新体验，增强并提高我们所有核心产品与服务的实用性和价值，让全球数十亿人受益。这些产品与服务包括 Google 搜索、Google 相册、Google 地图、Google Workspace、硬件设备（例如 Pixel 和 Nest），以及可为残障人士带来诸多便利的无障碍应用（例如 Android Voice Access、实时转写）。
• 开发 AI 赋能的新产品、服务和体验，以便：
  • 让消费者所用的辅助工具更得心应手，例如谷歌翻译、Google 智能镜头、Google 助理、Project Starline、语音转文字、Pixel 通话助理和录音机、实时信息建议和摘要，以及可辅助人类从事许多创意活动和生产活动的各种生成式功能。为了优化所有使用语音的 Google 产品，我们构建了一种能识别 400 种语言的通用语音模型，并会致力打造一种更强大的模型来支持全球 1,000 种常说语言，让数十亿人都能通过语音轻松使用我们的产品
  • 助力各行各业、各个地区、各种规模的企业和组织发展业务，相应开发成果包括客服中心辅助坐席；AutoML、Vertex AI、Cloud TPU、Glass Enterprise 等工具；编码、设计等方面的辅助产品；以及更多尚未推出的创新
  • 直接助力或通过合作伙伴和协作者间接为那些能从 AI 发展中受益最多的行业赋能，例如制造业、生命科学（例如糖尿病性视网膜病变、成像诊断、DeepVariant）等不同行业
• 培养一个庞大的 AI 生态并助其蓬勃发展，吸引开发者和合作伙伴汇聚一堂，不断构建并让 AI 应用遍地开花，惠及全球更多用户、行业和地区。为此，我们会竭尽所能，比如为开发者和合作伙伴提供丰富多样的工具和 API，以及在必要时与他们携手共同开发并共同部署实用创新。
• 利用 AI 开创只有借助 AI 的力量才可实现的新企业和新公司，改写行业品类的定义，例如无人驾驶汽车 (Waymo)、药物研发（例如 Isomorphic Labs）和机器人技术（例如 Intrinsic）等各种领域。

与 Google 以外的众多组织密切协作，助其将 AI 研发成果应用于实践，从容应对当下和今后社会面临的严峻挑战和重大机遇。

• 与全球各地的其他组织精诚合作，运用 AI 攻克社会发展过程中遇到的棘手难题，化解自然灾害、公共卫生危机、气候变化和可持续发展等挑战，共创美好未来。示例包括造福社会的 AI、AI 助力实现联合国可持续发展目标、Data Commons、野火警报、珊瑚礁保护和洪水预测等，这些项目已在全球 20 多个国家/地区落地且收效颇佳。
• 拓展并赋能 AI 领域，通过分享重大突破及相关成果（例如论文、开源项目和诸如 AlphaFold 蛋白质数据集之类的数据集），开展协作研究。我们还为学生和教育工作者广泛提供各种工具（例如 Google 学术搜索和 Colab，经常被数百万学习者使用），包括允许科学家免费使用尖端 ML 计算硬件（例如 TPU Research Cloud），帮助他们迅速提升能力（例如借我们与美国国家科学基金会合作之机），并与其他研究人员分享最佳实践（例如关于安全性）。

不断应用我们的 AI 创新成果，持续提升 Google 作为业界领先组织之一的非凡实力；同时，积极与其他组织（包括客户、政府机构和非政府组织）分享我们积累的丰富开发经验。我们注重的关键领域包括：

• 利用 AI 为我们的所有产品和服务保驾护航，实现先进的现实安全和网络安全保障
• 利用 AI 为我们的所有职能部门提速增效
• 利用 AI 实现我们公司在气候变化与可持续发展方面的宏伟抱负（例如帮助提高数据中心的能源效率）

截至目前，我们在上述所有领域都已取得重大进展，且已产生巨大影响（在某些情况下造福了数十亿人）。科技发展任重道远。我们深信，未来仍有更多机遇可把握，有更多奇迹可创造。

As Google and Alphabet, our goal is to bring to users useful innovations made possible by AI that benefit people and society. Advancing the state of the art helps us expand and progress AI capability to deliver innovations that can assist and improve the lives of many, while generating sustaining value that enables us to continue investing in transformative innovations.

We are pursuing and delivering on this aspiration in several ways:

Advance the state of the art for more capable AI that can benefit people and society.

• Lead foundational and field-defining breakthrough AI research to generate AI that is more capable and assistive across a variety of tasks. Examples of our contributions that have helped advance the field and have been leveraged by many at and beyond Google include Transformers, Word2Vec, Sequence to Sequence Learning, Federated Learning, Model Distillation, Diffusion Models, Deep Reinforcement Learning, Neural Nets with Tree Search, Self-learning Systems, Neural Architecture Search, Autoregressive Models, Networks with External Memory, Large Scale Distributed Deep Networks, Tensor Processing Units
• Use AI to make breakthrough progress in science and other areas where we aim to advance scientific and engineering progress. Examples of our widely-acknowledged breakthroughs in AI and science that can benefit all of humanity include: mapping nearly all known proteins, predicting the function of proteins, mapping a piece of the brain in neuroscience research, discovering faster algorithms, advances in quantum computing and physics including innovating in nuclear fusion

Bring useful and transformational AI-powered infrastructure, products, and services to more people, businesses, organizations (large and small), and economies everywhere.

• Build state of the art AI infrastructure that is secure and easy to use, including compute (e.g. Tensor Processing Units, Google Tensor and Colab) and widely-used software frameworks (e.g. TensorFlow, Jax, Android ML and Private Compute). Make this AI infrastructure available (with many open source tools) to millions of developers, students, and researchers in various organizations throughout the world.
• Apply our AI advances to our core products and servicesto make step-change improvements, innovations and new experiences that enhance and multiply the usefulness and value of all our core products and services for billions of people across Google Search, Google Photos, Google Maps, Google WorkspaceGoogle Workspace, hardware devices (e.g. Pixel and Nest), and for those with disabilities via accessibility applications ( Android Voice Access, Live Transcribe)
• Develop new AI-powered products, services and experiences for:
  • Consumers with assistive tools like Google Translate, Google Lens, Google Assistant, Project Starline, speech-to-text, Pixel Call Assist and Recorder, real-time text suggestions and summarization, and generative human-assistive capabilities across many creative and productivity endeavors. To enhance all products that use speech, we've developed a Universal Speech Model capable of 400 languages and we are committed to building a model to support the 1000 most-spoken languages, improving access for billions of people
  • Businesses and organizations of all sizes, across industries and regions, with examples like contact center assistive agents, tools such as AutoML, Vertex AIVertex AI, Cloud TPUs, Glass Enterprise, and assistive products for coding, design, and more still to come
  • Sectors that can most benefit from AI, from manufacturing to life sciences (e.g. diabetic retinopathy, imaging diagnostics, DeepVariant), directly and indirectly though our partners and collaborators
• Grow and enable a large AI ecosystem of developers and partners to build and bring more AI applications to more users, sectors, and regions of the world, for example through our provision of tools, APIs, and in some cases through co-development and co-deployments of useful innovations
• Use AI to create new category-defining businesses and companiesthat are only possible through the power of AI in a variety of fields from driverless cars ( Waymo) and drug discovery (e.g. Isomorphic Labs) to robotics ( e.g. Intrinsic)

Work with and enable many others beyond Google to apply AI to help tackle society's greatest challenges and opportunities today and in the future.

• Collaborate with others around the worldto apply AI to society's most pressing challenges such as natural disasters, public health crises, climate change, and sustainability. Examples include AI for Social Good, AI for the UN Sustainable Development Goals, Data Commons, wildfire alerts, coral reef conservation, and flood forecasting so far in more than 20 countries around the world.
• Expand and enable the field of AIby sharing major breakthroughs and related artifacts (e.g. papers, open-source releases, and datasets such as AlphaFoldAlphaFold protein datasets), engaging in research collaborations. We also make tools widely available to students and educators (e.g. Google Scholar and Colab, regularly used by millions of learners), including free access to leading-edge ML computation hardware for scientists (e.g. TPU Research Cloud), help build their capacity (e.g. with our partnership with the National Science Foundation), and share best practices (e.g. on safety) with other researchers.

Apply our AI innovations to continually improve Google itself as a leading organization, and to share what we learn with other organizations, including customers, governments, and non-governmental organizations. Key areas of focus include:

• Leveraging AI to achieve industry-leading safety and cybersecurity across all our products and services
• Applying AI to improve our own productivity and operations across all functions
• Using AI to help realize our company's bold ambitions in climate and sustainability(e.g. energy efficiency in our data centers)

We are compelled by the progress we are making across all the above, as well as our impact to date, in some cases benefitting billions of people. However, we believe still more opportunities for useful and beneficial impact lie ahead.

与其他任何颠覆性技术一样，AI 也自带复杂问题和风险，而且这些因素会随着时间的推移而改变。AI 尚处于早期阶段，相关功能和用途不断演变，这就可能会导致误用、滥用，乃至产生出乎意料或无法预见的后果。我们将未雨绸缪，随着 AI 持续发展、部署规模增长和适用范围扩大，主动充分了解不断演变的复杂问题和风险，同时继续听取用户和广大社区的反馈。

在我们自身和其他组织的不懈努力下，许多复杂问题和风险已被预警。这些风险会在下述情况下显现：

• AI 未能按预期运行（例如安全性、质量、准确度）
• AI 依赖的数据被以不当方式不负责任地使用
• AI 部署方式不安全（例如部署过早或测试不足）
• 开发者或用户以错误或有害的方式使用 AI
• AI 造成或加剧负面的社会偏见和危害（例如歧视）
• AI 造成或加剧网络安全风险
• AI 造成或加剧信息危害（例如缺乏依据、不真实、虚假信息）
• AI 让人误以为它拥有实际上并不具备的能力（例如将对话式 AI 误解为具有人类的特质）
• AI 造成或加剧不平等或其他社会经济危害，包括在劳动力市场中的影响

我们已意识到这些问题和风险可能会带来的害处，特别是会对全球不同群体和环境产生的负面影响。因此，我们将不遗余力地协助缓解上述风险，从而增强信任并确保安全包容的用户体验，使 AI 真正造福人类和社会。

As with any transformational technology, AI comes with complexities and risks, and these will change over time. As an early-stage technology, its evolving capabilities and uses create potential for misapplication, misuse, and unintended or unforeseen consequences. We are taking a proactive approach to understand the evolving complexities and risks as AI advances, deployment grows, and use expands, while continuing to learn from users and the wider community.

Many of the complexities and risks have been highlighted through our own work and that of many others. Such risks become manifest when AI:

• Does not perform as intended (e.g. safety, quality, accuracy)
• Relies on data that is not used appropriately and responsibly
• (Is) Deployed unsafely (e.g. too early or with insufficient testing)
• (Is) Misapplied or used in harmful ways by its developers or users
• Creates or amplifies negative societal biases and harms (e.g. discrimination)
• Creates or worsens cybersecurity risks
• Creates or worsens information hazards (e.g. lack of groundedness, non-factuality, misinformation)
• Creates the impression of having capabilities it does not actually have (e.g. interpreting conversational AI to have human traits)
• Creates or worsens inequality or other socio-economic harms including in the labor markets

We recognize the harms that these failures can cause, especially for different communities and contexts across the globe, and it is critical to invest in mitigating the above risks to increase trust, ensure safe and inclusive user experiences, and enable AI to fully benefit people and society.

鉴于 AI 的复杂程度和潜在风险，作为一家公司，我们必须以负责任的方式推动 AI 稳步发展。作为 AI 领域的先驱之一，我们必须双管齐下，不仅要在尖端 AI 技术方面引领潮流，还要在先进 Responsible AI（AI 相关创新和实现）方面树立典范。2018 年，我们成为首批提出 AI 原则的公司之一，将切实有益、用户至上、安全为先、规避危害的理念置于商业利益之上。我们还率先制定了许多最佳实践，例如现今被其他组织广泛使用的模型卡和数据卡。我们并非纸上谈兵，而是将 AI 原则落到了实处。知行合一至关重要，持续研究和评估我们采用的方法亦是如此。

我们采用的 Responsible AI 方法包括：

• 专注于对用户和社会有益的 AI 创新。优先考虑能帮助和造福人类与社会的 AI 研发、应用和用途，并确保整个研发过程中资源和环境的可持续性。
• 恪守我们的 AI 原则（以切实有益和规避危害为出发点），大力落实相关流程和治理措施，妥善开展从研究重点到产品化和实际使用等各项 AI 工作。随着经验的日积月累和具体问题的陆续显现，我们将不断诠释并完善这些原则和流程。我们会定期分享 AI 原则最新进展。
• 使用科学的方法开展 AI 研发，坚持严谨研究、同行评审、就绪情况审核，并以负责任的方式向外界开放、推广并使用我们的创新成果。。设定基准，并衡量 Responsible AI 各个方面的效果和进展。打造创新工具（例如为保障安全），紧跟 AI 技术发展步伐。持续进行对抗性测试和其他相关形式的测试。这些流程可确保我们以谨慎的差异化方法使用和部署 LaMDA、PaLM 和 Waymo 等新颖系统。
• 与跨学科专家协作，包括社会科学家、伦理学家以及其他拥有社会技术专业知识的团队（例如我们专注于产品、研究和工程的 Responsible AI 团队，以及专注于产品、业务和政策的 Responsible Innovation 团队）。在关乎社会福祉的重要领域，与研究人员、开发者和用户协作（例如计算机科学研究指导计划、研究资助和各种协作项目）。
• 积极听取开发者、用户、专家、政府机构以及受影响社区（例如 AI Test Kitchen、Google 众包计划）的代表提供的反馈，并做出相应改进；同时，邀请人工评审员评估 AI 模型，确保其符合 AI 原则。
• 定期审核我们的 AI 研究与应用开发工作，包括相关用例（比如由我们的先进技术审核委员会进行审核）。公开相关学习成果（例如 PAIR 指南）。将我们的经验分享给其他组织（例如政府机构），帮助他们制定应对问题和风险的方法。
• 及时了解当前存在且不断演变的问题和风险领域（例如安全性、偏见、恶意、真实性），并处理、研究和创新，以便在相关挑战/风险显现时从容应对。分享经验/教训和创新成果（例如将 Monk 量表开源、将用于检测合成语音的工具开源）。开发实用方法来监控已部署的系统，确保我们能快速缓解生产环境中和用户所用服务中实时显现的风险。
• 积极倡导并协助制定负责任的治理、问责和监管机制，在鼓励创新的同时最大限度地发挥 AI 的优势，并设法缓解风险（例如，我们在建立 AI 合作伙伴关系方面发挥的作用、我们对全球 AI 合作伙伴关系的支持，以及我们对主要 AI 治理工作的贡献，包括欧盟的《AI 法案》、NIST AI 风险管理框架和 OECD AI 原则）。
• 帮助用户和社会了解 AI 是什么（以及不是什么）、如何利用 AI 潜力获益 [例如 AI 在日常生活中（比如在教育方面）有何用处]、存在哪些风险，以及如何缓解这些风险。

作为 AI 引导者之一，我们一直在努力推动许多 Responsible AI 领域的变革。与此同时，我们也始终保持虚心学习的态度，积极从用户、其他研究人员、受影响的社区和我们的实践经验中汲取新知，不断完善自我。因此，我们将持续改进所用方法，确保在所有工作中全面考量上述事项，并在问题显现时尽快解决。我们的目标是，开展有意义的工作，努力促进变革但绝不拖慢创新步伐，从而造福人类和社会。

Given its risks and complexities, we believe that we as a company must pursue AI responsibly. As leaders in AI, we must lead not only in state-of-the-art AI technologies, but also in state-of-the-art responsible AI-its innovation and implementation. In 2018, we were one of the first companies to articulate AI 原则AI Principles that put beneficial use, users, safety, and avoidance of harms above business considerations, and we have pioneered many best practices, like the use of model and data cards now widely used by others. More than words on paper, we apply our AI Principles in practice. Doing so-along with continual research and review of our approaches-is critical.

Our responsible AI approach includes the following:

• Focus on AI that is useful and benefits users and society. Prioritize AI R&D, applications, and uses that assist and benefit people and society. Ensure resource and environmental sustainability throughout R&D.
• Intentionally apply our AI Principles (which are grounded in beneficial uses and avoidance of harm), processes, and governance to guide our work in AI, from research priorities to productization and uses. Continually interpret and update these principles and processes as we learn more and as specific issues arise. We provide regular updates on the progress on our AI Principles.
• Apply the scientific method to AI R&D with research rigor, peer review, readiness reviews, and responsible approaches to providing access and to the externalization and use of our innovations. Set benchmarks and measure performance and progress on different factors of responsible AI. Create innovative tools (e.g. for safety) to keep pace with AI technologies. Continuously perform adversarial and related forms of testing. Through these processes, we take a differentiated and careful approach to access and deployment of novel systems such as LaMDA, PaLM and Waymo.
• Collaborate with multidisciplinary experts, including social scientists, ethicists, and other teams with socio-technical expertise (e.g. our Responsible AI team focused on research, product, and engineering and our Responsible Innovation team focused on products, business, and policy). Work with researchers, developers, and users in areas of societal importance (e.g. CS Research Mentorship Program, research grants, and collaborations).
• Listen, learn and improve based on feedback from developers, users, experts, governments, and representatives of affected communities (e.g. AI Test Kitchen, Crowdsource), and involve human raters to evaluate AI models.
• Conduct regular reviewsof our AI research and application development, including use cases (e.g. our Advanced Technology Review Council). Provide transparency on learnings (e.g. PAIR guidebook). Engage with others (e.g. governments) to provide the benefits of our experiences as they shape approaches to concerns and risks.
• Stay on top of current and evolving areas of concern and risk(e.g. safety, bias, toxicity, factuality) and address, research, and innovate to respond to challenges/risks as they emerge. Share learnings and innovations (e.g. open-sourcing the Monk scale and tools for detecting synthetic speech). Develop methods to monitor deployed systems, ensuring that we can quickly mitigate dynamically-occurring risks in production and in-use services.
• Lead on and help shape responsible governance, accountability, and regulation that encourages innovation and maximizes the benefits of AI while mitigating risks (e.g. our role in setting up Partnership on AI, our support for Global Partnership on Artificial Intelligence and our contributions to flagship AI governance efforts, including the EU AI Act, NIST AI Risk Management Framework, and OECD AI Principles).
• Help users and society understand what AI is (and is not) and how to benefit from its potential-how it might be helpful in their daily lives (e.g. education), what the risks are, and how to mitigate those risks.

We are leaders in driving change in many areas of Responsible AI, but at the same time we continue to learn from users, other researchers, affected communities, and our experiences. As a result, we are continually refining our approaches to ensure that the above considerations are incorporated in all we do and address issues as they arise. We aim to work in meaningful ways that help shape but don't slow down innovation that can benefit people and society.

我们相信，要想确保 AI 沿着正确的方向发展，就离不开集体的努力。诚然，我们无法给出所有问题的答案，但现有经验告诉我们，为了确保 AI 沿着正确的方向发展，AI 领域的所有参与者（包括研究人员、开发者、部署者、学术界、民间团体、政府机构和用户，涵盖个人、企业和其他组织）都必须通力合作，尤其是在以下领域：

We believe that getting AI right requires a collective effort. We don't have all the answers, but our experience so far suggests that everyone involved in AI (researchers, developers, deployers, academics, civil society, governments, and users, including individuals, businesses, and other organizations) must work together to get AI right including in the following areas:

• 采用负责任的方法开发并部署 AI 系统
• Responsible approaches to AI development and deployment of AI systems
• 遵循数据和隐私方面的推荐实践，力求既能保护隐私又能造福人类和社会（例如共享流量和公共安全数据）
• Data and privacy practices that protect privacy and enable benefits for people and society (e.g. sharing traffic and public safety data)
• 采用强有力的 AI 基础设施和网络安全措施，降低安全风险
• Robust AI infrastructure and cybersecurity to mitigate security risks
• 出台相关法规，既能鼓励创新，又能倡导以安全有益的方式使用 AI，还能提醒避免误用、滥用或以有害的方式使用 AI
• Regulations that encourage innovation and safe and beneficial uses of AI and avoid misapplications, misuse, or harmful uses of AI
• 开展跨社区协作，制定相关标准和最佳实践
• Cross-community collaboration to develop standards and best practices
• 与政府机构和民间团体的领导者沟通交流、一起学习
• Sharing and learning together with leaders in government and civil society
• 建立切实可行的问责机制，在社会广泛关注的领域建立公众信任
• Practical accountability mechanisms to build trust in areas of societal concern
• 加大对 AI 安全性、伦理和社会技术研究的投资力度
• Investment in AI safety, ethics, and sociotechnical research
• 培养更庞大、更多样的 AI 从业者社区，充分反映世界的多元化，并更加从容地应对相关挑战和机遇
• Growing a larger and more diverse community of AI practitioners to fully reflect the diversity of the world and to better address its challenges and opportunities