CAP: Capacity Building for Trustworthy AI in Medical Systems (TAIMS)

CAP：医疗系统中值得信赖的人工智能的能力建设（TAIMS）

• 批准号: 2334391
• 负责人: Vibhuti Gupta
• 金额: $ 39.57万
• 依托单位: Meharry Medical College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334391&HistoricalAwards=false
• 关键词: CAP; Capacity; Building; Trustworthy; AI

This project is an ExpandAI Capacity building pilot (CAP), which focuses on establishing and growing AI related activities at Meharry Medical College by conducting important use-inspired research in trustworthy, ethical, explainable and responsible artificial intelligence (AI) for the mitigation of the problem of algorithmic bias in AI-powered medical systems. Existing clinical AI methods are limited by attendant algorithmic and societal biases during systems design and development resulting in misdiagnosis and ultimately poor treatment and health disparities. Through enhanced understanding of the nature of “black box” AI algorithms, researchers at Meharry Medical College (MMC) will develop interpretable methods and tools for secure, private and reliable bias-free clinical decisions. The project is a collaborative effort between Meharry’s School of Dentistry, School of Graduate Studies, and School of Applied Computational Sciences (SACS) to provide American graduate students and medical professionals, with advanced training in AI and machine learning (ML) techniques to prepare them with skills for future AI-powered career pathways. Research capacity building plans include training of diverse faculty in the use of cutting-edge AI/ML techniques. On the educational side, short courses, summer school and tutorial series will be established to cover important topics such as overview of ethics in AI/ML, explainable AI methods, algorithmic bias and mitigation strategies and data privacy. Several research themes were identified as potential growth areas for AI technologies across the Meharry campus including (i) explainable AI in medical systems, (ii) ethical and responsible AI for medical systems. For example, explainable AI systems are ones in which humans better understand the reasoning behind decisions made by AI systems other than predictive accuracy and statistical performance. Many practitioners, clinicians, researchers, and patients are reluctant to use AI unless it is explainable, verifiable, and trustable. Ethical and responsible AI deals with establishment of well-defined guidelines and legal regulations for ethical use of AI tools and technologies. The ethical use of AI tools is critical for preservation of fundamental human rights, health and public safety. Educational capacity building is planned through several initiatives including (i) training activities to disseminate awareness among medical professionals, graduate students, staff, and faculty; (ii) short course and tutorial series to cover topics such as overview of ethics in AI/ML, explainable AI methods, algorithmic bias and mitigation; (iii) new course focusing on Trustworthy AI in medical systems for the graduate programs; (iv) outreach to high school educators and summer academies for K-12 students. By providing a broad swath of diverse faculty, professionals, educators and students with AI knowledge and immersive learning experiences, AI literacy and skill development, will be significantly enhanced. The ExpandAI Program supports AI-powered education and workforce development, infrastructure and research at Minority Serving Institutions to strengthen and diversify U.S. research and education pathways and provide historically marginalized communities with new opportunities in STEM careers.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.

该项目是一个ExpandAI能力建设试点项目（CAP），其重点是在Meharry医学院建立和发展AI相关活动，通过在值得信赖的，道德的，可解释的和负责任的人工智能（AI）方面进行重要的使用启发研究，以缓解AI驱动的医疗系统中的算法偏见问题。现有的临床人工智能方法受到系统设计和开发过程中伴随的算法和社会偏见的限制，导致误诊，最终导致治疗和健康差异。通过加强对“黑盒”人工智能算法性质的理解，梅哈里医学院（MMC）的研究人员将开发可解释的方法和工具，以实现安全、私密和可靠的无偏见临床决策。该项目是Meharry牙科学院，研究生院和应用计算科学学院（SACS）之间的合作努力，为美国研究生和医疗专业人员提供人工智能和机器学习（ML）技术的高级培训，为他们未来的人工智能驱动的职业道路做好准备。研究能力建设计划包括培训不同的教师使用尖端的AI/ML技术。在教育方面，将建立短期课程，暑期学校和教程系列，涵盖AI/ML道德概述，可解释的AI方法，算法偏见和缓解策略以及数据隐私等重要主题。几个研究主题被确定为整个Meharry校园人工智能技术的潜在增长领域，包括（i）医疗系统中可解释的人工智能，（ii）医疗系统的道德和负责任的人工智能。例如，可解释的人工智能系统是人类更好地理解人工智能系统决策背后的推理，而不是预测准确性和统计性能。许多从业者、临床医生、研究人员和患者不愿意使用人工智能，除非它是可解释的、可验证的和可信赖的。道德和负责任的人工智能涉及为人工智能工具和技术的道德使用建立明确的指导方针和法律的规定。人工智能工具的道德使用对于维护基本人权、健康和公共安全至关重要。教育能力建设计划通过几项举措，包括（i）培训活动，以传播医疗专业人员，研究生，工作人员和教师的认识;（ii）短期课程和教程系列，涵盖AI/ML伦理概述，可解释的AI方法，算法偏见和缓解等主题;（iii）新课程，重点是研究生课程的医疗系统中值得信赖的AI;（iv）向高中教育工作者和K-12学生暑期学校进行宣传。通过为各种各样的教师、专业人员、教育工作者和学生提供人工智能知识和沉浸式学习体验，人工智能素养和技能发展将得到显著提高。ExpandAI计划支持少数民族服务机构的人工智能驱动的教育和劳动力发展，基础设施和研究，以加强和多样化美国的研究和教育途径，并为历史上被边缘化的社区提供STEM职业的新机会。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。