IUCRC Planning Proposal Grant University of Miami: Center for Standards and Ethics in Artificial Intelligence CSEAI
IUCRC Planning Proposal Grant University of Miami: Center for Standards and Ethics in Artificial Intelligence CSEAI
批准号:
2137148
负责人:
Daniel Diaz
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:
2022-02-15 至 2023-07-31
中文摘要
在过去的二十年里,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有社会责任保护消费者并提高产品和服务的可信度。因此,监管团体正在制定全球人工智能(AI)伦理标准。人工智能标准与伦理中心(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伦理实践。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、安全、高效和可持续的人工智能。有效和道德的AI标准。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技术的负责任,公平,可追溯,可靠和可治理的发展相关的各种基础研究挑战。该中心位于迈阿密大学,将重点研究统计发展中存在的偏见以及程序员对算法的影响,并提出相应的建议,以确保去偏见和可重复性。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AI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,并培养一支受过标准化和道德化人工智能培训的多元化劳动力队伍。该中心将发布特定的道德评估工具,人工智能最佳实践将通过出版物,会议演示和CSEAI暑期学校授权或提供给各种利益相关者。公开访问的存储库和安全的会员专用存储库(包括会议材料,研讨会信息,研究主题和细节,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,CSEAI将使用一个公共和安全的存储库,以促进不同站点之间工作和信息的连续性。在该中心的生命周期内,可通过贝勒大学公开列出的URL(https://cseai.center)访问该存储库,一旦不再维护,将转移到存档服务。该奖项反映了NSF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. The center site at the University of Miami will focus, among others, on examining the presence of bias in statistical developments and the influence of programmers in algorithms, with its corresponding proposal to ensure debiasing and reproducibility.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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
海外基金