《人工智能权利法案蓝图》
输入“/”快速插入内容
《人工智能权利法案蓝图》
《人工智能权利法案蓝图》
飞书用户9042023年11月14日修改
⏰ 发布日期：2022年10月
Blueprint for an AI Bill of Rights
人工智能权利法案蓝图
Among the great challenges posed to democracy today is the use of technology, data, and automated systems in ways that threaten the rights of the American public. Too often, these tools are used to limit our opportunities and prevent our access to critical resources or services. These problems are well documented. In America and around the world, systems supposed to help with patient care have proven unsafe, ineffective, or biased. Algorithms used in hiring and credit decisions have been found to reflect and reproduce existing unwanted inequities or embed new harmful bias and discrimination. Unchecked social media data collection has been used to threaten people’s opportunities, undermine their privacy, or pervasively track their activity—often without their knowledge or consent.
当今民主面临的巨大挑战之一是以威胁美国公众权利的方式使用技术、数据和自动化系统。这些工具常常被用来限制我们的机会并阻止我们获取关键资源或服务。这些问题都有详细记录。在美国和世界各地，事实证明旨在帮助患者护理的系统不安全、无效或存在偏见。人们发现，招聘和信贷决策中使用的算法反映和再现了现有的不必要的不平等，或嵌入了新的有害偏见和歧视。未经检查的社交媒体数据收集被用来威胁人们的机会、破坏他们的隐私或普遍跟踪他们的活动——通常是在他们不知情或不同意的情况下。
These outcomes are deeply harmful—but they are not inevitable. Automated systems have brought about extraordinary benefits, from technology that helps farmers grow food more efficiently and computers that predict storm paths, to algorithms that can identify diseases in patients. These tools now drive important decisions across sectors, while data is helping to revolutionize global industries. Fueled by the power of American innovation, these tools hold the potential to redefine every part of our society and make life better for everyone.
这些结果是极其有害的——但它们并非不可避免。自动化系统带来了非凡的好处，从帮助农民更有效地种植粮食的技术、预测风暴路径的计算机到可以识别患者疾病的算法。这些工具现在推动了跨部门的重要决策，而数据正在帮助变革全球行业。在美国创新力量的推动下，这些工具有可能重新定义我们社会的各个部分，让每个人的生活变得更美好。
This important progress must not come at the price of civil rights or democratic values, foundational American principles that President Biden has affirmed as a cornerstone of his Administration. On his first day in office, the President ordered the full Federal government to work to root out inequity, embed fairness in decision-making processes, and affirmatively advance civil rights, equal opportunity, and racial justice in America.[i] The President has spoken forcefully about the urgent challenges posed to democracy today and has regularly called on people of conscience to act to preserve civil rights—including the right to privacy, which he has called “the basis for so many more rights that we have come to take for granted that are ingrained in the fabric of this country.”[ii]
这一重要进展绝不能以牺牲公民权利或民主价值观为代价，而这些是拜登总统确认为其政府基石的美国基本原则。在上任第一天，总统命令整个联邦政府努力消除不平等，将公平纳入决策过程，并积极推进美国的公民权利、平等机会和种族正义。[i] 总统已他有力地谈论了当今民主面临的紧迫挑战，并经常呼吁有良知的人们采取行动保护公民权利，包括隐私权，他称之为“我们已经接受的更多权利的基础”理所当然，这些已经在这个国家的结构中根深蒂固。”[ii]
To advance President Biden’s vision, the White House Office of Science and Technology Policy has identified five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence. The Blueprint for an AI Bill of Rights is a guide for a society that protects all people from these threats—and uses technologies in ways that reinforce our highest values. Responding to the experiences of the American public, and informed by insights from researchers, technologists, advocates, journalists, and policymakers, this framework is accompanied by From Principles to Practice—a handbook for anyone seeking to incorporate these protections into policy and practice, including detailed steps toward actualizing these principles in the technological design process. These principles help provide guidance whenever automated systems can meaningfully impact the public’s rights, opportunities, or access to critical needs.
为了推进拜登总统的愿景，白宫科技政策办公室确定了五项原则，指导自动化系统的设计、使用和部署，以在人工智能时代保护美国公众。 《人工智能权利法案蓝图》是一个社会指南，旨在保护所有人免受这些威胁，并以增强我们最高价值观的方式使用技术。该框架回应了美国公众的经验，并汲取了研究人员、技术专家、倡导者、记者和政策制定者的见解，并附有《从原则到实践》——一本为任何寻求将这些保护措施纳入政策和实践的人提供的手册，包括在技术设计过程中实现这些原则的详细步骤。当自动化系统能够对公众的权利、机会或关键需求的获取产生有意义的影响时，这些原则有助于提供指导。
Safe and Effective Systems
安全有效的系统
You should be protected from unsafe or ineffective systems. Automated systems should be developed with consultation from diverse communities, stakeholders, and domain experts to identify concerns, risks, and potential impacts of the system. Systems should undergo pre-deployment testing, risk identification and mitigation, and ongoing monitoring that demonstrate they are safe and effective based on their intended use, mitigation of unsafe outcomes including those beyond the intended use, and adherence to domain-specific standards. Outcomes of these protective measures should include the possibility of not deploying the system or removing a system from use. Automated systems should not be designed with an intent or reasonably foreseeable possibility of endangering your safety or the safety of your community. They should be designed to proactively protect you from harms stemming from unintended, yet foreseeable, uses or impacts of automated systems. You should be protected from inappropriate or irrelevant data use in the design, development, and deployment of automated systems, and from the compounded harm of its reuse. Independent evaluation and reporting that confirms that the system is safe and effective, including reporting of steps taken to mitigate potential harms, should be performed and the results made public whenever possible.
您应该受到保护，免受不安全或无效系统的影响。自动化系统的开发应与不同社区、利益相关者和领域专家协商，以确定系统的关注点、风险和潜在影响。系统应经过部署前测试、风险识别和缓解以及持续监控，以证明它们根据其预期用途是安全有效的，缓解不安全结果（包括超出预期用途的结果），并遵守特定领域的标准。这些保护措施的结果应包括不部署系统或停止使用系统的可能性。自动化系统的设计不应有意或合理预见危及您或社区安全的可能性。它们的设计应能够主动保护您免受自动化系统意外但可预见的使用或影响所造成的伤害。您应该受到保护，以免在自动化系统的设计、开发和部署中使用不当或不相关的数据，以及避免重复使用数据带来的复合危害。应进行独立评估和报告，以确认系统安全有效，包括报告为减轻潜在危害而采取的步骤，并尽可能公布结果。
从原则到实践：安全有效的系统
Algorithmic Discrimination Protections
算法歧视保护
You should not face discrimination by algorithms and systems should be used and designed in an equitable way. Algorithmic discrimination occurs when automated systems contribute to unjustified different treatment or impacts disfavoring people based on their race, color, ethnicity, sex (including pregnancy, childbirth, and related medical conditions, gender identity, intersex status, and sexual orientation), religion, age, national origin, disability, veteran status, genetic information, or any other classification protected by law. Depending on the specific circumstances, such algorithmic discrimination may violate legal protections. Designers, developers, and deployers of automated systems should take proactive and continuous measures to protect individuals and communities from algorithmic discrimination and to use and design systems in an equitable way. This protection should include proactive equity assessments as part of the system design, use of representative data and protection against proxies for demographic features, ensuring accessibility for people with disabilities in design and development, pre-deployment and ongoing disparity testing and mitigation, and clear organizational oversight. Independent evaluation and plain language reporting in the form of an algorithmic impact assessment, including disparity testing results and mitigation information, should be performed and made public whenever possible to confirm these protections.
您不应该面临算法的歧视，系统应该以公平的方式使用和设计。当自动化系统因种族、肤色、民族、性别（包括怀孕、分娩和相关医疗状况、性别认同、双性人身份和性取向）、宗教、年龄而对人们产生不公正的不同待遇或影响时，就会发生算法歧视、国籍、残疾、退伍军人身份、遗传信息或受法律保护的任何其他分类。根据具体情况，这种算法歧视可能会违反法律保护。自动化系统的设计者、开发者和部署者应采取主动和持续的措施，保护个人和社区免受算法歧视，并以公平的方式使用和设计系统。这种保护应包括作为系统设计一部分的主动公平评估、使用代表性数据和针对人口特征代理的保护、确保残疾人在设计和开发、预部署和持续差异测试和缓解中的无障碍性，以及明确的组织结构。监督。应以算法影响评估的形式进行独立评估和简单语言报告，包括差异测试结果和缓解信息，并尽可能公开以确认这些保护。
从原则到实践：算法歧视保护
Data Privacy 数据隐私
You should be protected from abusive data practices via built-in protections and you should have agency over how data about you is used. You should be protected from violations of privacy through design choices that ensure such protections are included by default, including ensuring that data collection conforms to reasonable expectations and that only data strictly necessary for the specific context is collected. Designers, developers, and deployers of automated systems should seek your permission and respect your decisions regarding collection, use, access, transfer, and deletion of your data in appropriate ways and to the greatest extent possible; where not possible, alternative privacy by design safeguards should be used. Systems should not employ user experience and design decisions that obfuscate user choice or burden users with defaults that are privacy invasive. Consent should only be used to justify collection of data in cases where it can be appropriately and meaningfully given. Any consent requests should be brief, be understandable in plain language, and give you agency over data collection and the specific context of use; current hard-to-understand notice-and-choice practices for broad uses of data should be changed. Enhanced protections and restrictions for data and inferences related to sensitive domains, including health, work, education, criminal justice, and finance, and for data pertaining to youth should put you first. In sensitive domains, your data and related inferences should only be used for necessary functions, and you should be protected by ethical review and use prohibitions. You and your communities should be free from unchecked surveillance; surveillance technologies should be subject to heightened oversight that includes at least pre-deployment assessment of their potential harms and scope limits to protect privacy and civil liberties. Continuous surveillance and monitoring should not be used in education, work, housing, or in other contexts where the use of such surveillance technologies is likely to limit rights, opportunities, or access. Whenever possible, you should have access to reporting that confirms your data decisions have been respected and provides an assessment of the potential impact of surveillance technologies on your rights, opportunities, or access.
您应该通过内置保护措施免受滥用数据行为的影响，并且您应该对如何使用有关您的数据拥有代理权。您应该通过设计选择来保护您免受隐私侵犯，确保默认情况下包含此类保护，包括确保数据收集符合合理的期望，并且仅收集特定上下文严格必需的数据。自动化系统的设计者、开发者和部署者应寻求您的许可并尊重您以适当方式并最大程度地收集、使用、访问、传输和删除您的数据的决定；如果不可能，应使用替代的隐私设计保护措施。系统不应采用混淆用户选择的用户体验和设计决策，或通过侵犯隐私的默认设置给用户带来负担。仅在可以适当且有意义地给予同意的情况下，才应使用同意来证明数据收集的合理性。任何同意请求都应该简短，用简单的语言可以理解，并为您提供数据收集和具体使用环境的代理权；当前广泛使用数据的难以理解的通知和选择做法应该改变。加强对与敏感领域（包括健康、工作、教育、刑事司法和金融）相关的数据和推论以及与青少年相关的数据的保护和限制应该把您放在第一位。在敏感领域，您的数据和相关推论只能用于必要的功能，并且您应该受到道德审查和使用禁令的保护。 您和您的社区应该免受不受控制的监视；监视技术应受到加强的监督，至少包括对其潜在危害和范围限制进行部署前评估，以保护隐私和公民自由。持续监视和监测不应用于教育、工作、住房或使用此类监视技术可能限制权利、机会或访问的其他环境。只要有可能，您就应该有权访问报告，以确认您的数据决策已得到尊重，并评估监控技术对您的权利、机会或访问权限的潜在影响。
从原则到实践：数据隐私