REU Site: Summer Undergraduate Program in Engineering Research at Berkeley-Responsible Artificial Intelligence (SUPERB-RAI)

REU 网站：伯克利负责任人工智能工程研究暑期本科生项目 (SUPERB-RAI)

• 批准号: 1950668
• 负责人: David Wagner
• 金额: $ 32.98万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1950668&HistoricalAwards=false
• 关键词: REU; Site; Summer; Undergraduate; Program

The UC Berkeley Department of Electrical Engineering and Computer Sciences (EECS) proposes a suite of projects to deal with the challenges and risks from the widespread adoption of Artificial Intelligence (AI) in areas such as marketing, finance, law enforcement, health care and entertainment. With the successes and benefits of AI come great risks. These Research Experiences for Undergraduates (REU) projects tackle many of the challenges in the responsible development of AI systems. Leading researchers in Electrical Engineering and Computer Science will mentor students on their REU projects. Faculty identified as mentors have excellent track records of mentoring undergraduate research. The projects in this proposal cover many key challenges in responsible AI including: fairness in machine learning algorithms, safety in human-robot interaction, fairness in law enforcement, provably-safe AI systems, defense against adversarial attacks, managing unpredictability in AI-engineered artificial proteins, and AI-enhanced neural sensors. The research team consists of leaders in these respective areas.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.

加州大学伯克利分校电气工程和计算机科学系（EEC）提出了一套项目，以应对在营销，财务，执法，医疗保健和娱乐等领域广泛采用人工智能（AI）所面临的挑战和风险。随着人工智能的成功和好处，带来了巨大的风险。这些针对本科生（REU）项目的研究经验应对AI系统负责任开发的许多挑战。电气工程和计算机科学领域的领先研究人员将指导学生对REU项目。被确定为指导者的教师拥有指导本科研究的出色记录。该提案中的项目涵盖了负责AI的许多关键挑战，包括：机器学习算法中的公平性，人类机器人互动的安全性，执法公平性，可证明是安全的AI系统，防御对抗性攻击的防御，管理AI-Inde Geantere的人工蛋白质中的不可预测性以及AI-Anapechenced Neural Sensors。研究团队由这些各个领域的领导者组成。该奖项反映了NSF的法定任务，并被认为是使用基金会的知识分子优点和更广泛影响的评论标准来评估值得支持的。