NSF Workshop on Safety and Trust in Artificial Intelligence Enabled Systems

NSF 人工智能支持系统安全与信任研讨会

• 批准号: 2231543
• 负责人: Taylor Johnson
• 金额: $ 4.91万
• 依托单位: Vanderbilt University
• 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
• 起止时间: 2022-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2231543&HistoricalAwards=false
• 关键词: NSF; Workshop; Safety; Trust; Artificial

This aim of this workshop is to identify emerging issues, challenges, basic research questions, and potential approaches to study and address safety and trust in AI-enabled systems across application domains. The workshop will bring together researchers from academia, industry, and government research labs that are working in the areas of artificial intelligence, and formal methods, and application domains such as autonomous systems, business and finance, and education. The main deliverable of the workshop is a report summarizing the discussions and findings of the workshop, which will be made publicly available.Fostering the development of collaborations and the exchange of ideas between the formal methods, AI/ML, and broader research communities and stakeholders is critical and may lead to advances in methods that improve both AI/ML and formal methods, as well as the broader concerns about safety and trust of these AI-enabled systems across science, engineering, and society. The workshop will particularly encourage participation and perspectives from persons coming from underrepresented groups.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.

本次研讨会的目的是确定新出现的问题，挑战，基础研究问题，以及研究和解决跨应用领域的AI支持系统的安全和信任的潜在方法。该研讨会将汇集来自学术界，工业界和政府研究实验室的研究人员，这些研究人员正在人工智能，正式方法和应用领域，如自主系统，商业和金融以及教育等领域工作。研讨会的主要成果是总结研讨会讨论和发现的报告，该报告将公开发布。促进正式方法，AI/ML和更广泛的研究社区和利益相关者之间的合作和思想交流至关重要，并可能导致改进AI/ML和正式方法的方法的进步，以及对这些人工智能系统在科学、工程和社会中的安全和信任的更广泛关注。这个奖项反映了NSF的法定使命，并被认为值得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来支持。