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IUCRC Planning Grant Rutgers University: Center for Standards and Ethics in Artificial Intelligence (CSEAI)

IUCRC Planning Grant Rutgers University: Center for Standards and Ethics in Artificial Intelligence (CSEAI)
IUCRC 规划拨款 罗格斯大学:人工智能标准与道德中心 (CSEAI)
批准号:
2137245
负责人:
Jorge Ortiz
金额:
$2.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-03-01 至 2023-07-31

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中文摘要
翻译
在过去的20年里,几乎每个行业都出现了前所未有的人工智能技术增长。最近,重点放在确保使用或生产人工智能技术的行业和政府机构承担社会责任,以保护消费者并提高产品和服务的可信度。因此,监管机构正在全球范围内制定人工智能(AI)伦理标准。人工智能标准与道德中心(CSEAI)旨在通过研究、推广和教育,为行业和政府提供必要的资源,以采用和有效实施人工智能标准和道德实践。CSEAI的使命是与行业和政府研究伙伴密切合作,研究人工智能协议、程序和技术,以实现安全、有效和道德的人工智能标准的设计、实施和采用。CSEAI教师的各种人工智能技能使该中心能够解决与人工智能驱动技术的负责任、公平、可追溯、可靠和可治理发展相关的各种基础研究挑战。例如,罗格斯大学的中心网站将研究深度感知环境和网络物理系统的可理解模型解释,感知应用的隐私感知学习,以及非凸问题的联合学习。CSEAI将帮助使用或生产人工智能技术的行业和政府组织为消费者和用户提供安全的标准化、道德产品,帮助公众重新获得对人工智能技术的信任和信心。该中心将招募、培训和指导来自不同背景的本科生、研究生和博士后,激励他们从事人工智能伦理方面的职业,并培养一支接受标准化和道德人工智能培训的多元化劳动力队伍。该中心将发布特定的伦理评估工具,人工智能的最佳实践将通过出版物、会议演讲和CSEAI暑期学校的形式获得许可或提供给各种利益相关者。公开访问的存储库和安全的仅限成员的存储库(包括会议资料、研讨会信息、研究主题和详细信息、出版物等)将在贝勒大学现场和/或政府/国防部批准的云服务上进行维护。在允许的情况下,将为CSEAI使用一个单一的公共和安全存储库,以促进不同地点之间的工作和信息的连续性。在该中心的生命周期内,可以通过Baylor University的公开URL (https://cseai.center)访问该存储库,并在不再维护时转移到归档服务中。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The last twenty years have seen an unprecedented growth of AI-enabled technologies in practically every industry. More recently, an emphasis has been placed on ensuring industry and government agencies that use or produce AI-enabled technology have a social responsibility to protect consumers and increase trustworthiness in products and services. As a result, regulatory groups are producing standards for artificial intelligence (AI) ethics worldwide. The Center for Standards and Ethics in Artificial Intelligence (CSEAI) aims to provide industry and government the necessary resources for adopting and efficiently implementing standards and ethical practices in AI through research, outreach, and education. CSEAI’s mission is to work closely with industry and government research partners to study AI protocols, procedures, and technologies that enable the design, implementation, and adoption of safe, effective, and ethical AI standards. The varied AI skillsets of CSEAI faculty enable the center to address various fundamental research challenges associated with the responsible, equitable, traceable, reliable, and governable development of AI-fueled technologies. For example, the center site at Rutgers University will examine intelligible model explanations for deeply sensed environments and cyber-physical systems, privacy-aware learning for sensing applications, and federated learning for nonconvex problems.The CSEAI will help industry and government organizations that use or produce AI technology to provide standardized, ethical products safe for consumers and users, helping the public regain trust and confidence in AI technology. The center will recruit, train, and mentor undergraduates, graduate students, and postdocs from diverse backgrounds, motivating them to pursue careers in AI ethics and producing a diverse workforce trained in standardized and ethical AI. The center will release specific ethics assessment tools, and AI best practices will be licensed or made available to various stakeholders through publications, conference presentations, and the CSEAI summer school.Both a publicly accessible repository and a secured members-only repository (comprising meeting materials, workshop information, research topics and details, publications, etc.) will be maintained either on-site at Baylor University and/or on a government/DoD-approved cloud service. A single public and secured repository will be used for CSEAI, where permissible, to facilitate continuity of efforts and information between the different sites. This repository will be accessible at a publicly listed URL at Baylor University, https://cseai.center, for the lifetime of the center and moved to an archiving service once no longer maintained.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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