NSF Award
2413654
The goal of the project is to train current and future research workforce members in trustworthy artificial intelligence (AI) by developing instructional materials that expose students to various challenges of trustworthy AI systems. The project is focused on the vital national need for well-trained and highly knowledgeable researchers in trustworthy AI who are capable of solving real world problems in complex AI systems and help enable secure and safe adoption of AI systems. The project will have direct and long-term impact in both the public and private sectors by training the research workforce to address trustworthy AI challenges. Georgia State University is a minority-serving institution (MSI), and the project will form a coordination network consisting of research universities, 4-year colleges, historically black colleges and universities (HBCUs), Hispanic-serving institutions (HSIs), and women’s colleges in Metro Atlanta and the broader region. The collaboration will significantly increase the collective impact of the project, benefit numerous students from underrepresented groups and help increase the diversity of the research workforce. <br/><br/>The project team will develop interactive instructional materials including a set of hands-on labs that employ state-of-the-art trustworthy AI techniques to address the various challenges of AI systems. The instructional materials to be developed include modules on adversarial machine learning, evasion attacks and defenses, data poisoning attacks and defenses, privacy attacks and defenses, testing and verification, and fairness, accountability, transparency, and ethics (FATE). The project employs learning science principles, specifically the active learning and inquiry-based learning strategies that result in deeper understanding by students and provide formative feedback to instructors. The instructional materials are based on real-world systems and are designed to systematically cover fundamental principles in trustworthy AI and practical skills. The project also will provide guidelines to help instructors integrate the modules into their curriculum. The hands-on labs will be built based on only open-source software and tools that are free to use for educational purposes and will be distributed via free cloud platforms. The project evaluation includes formative and summative evaluations that use both quantitative and qualitative approaches and will be conducted by an experienced external evaluator with help from the project team. The project will disseminate the developed materials through training workshops for the educational and research communities.<br/><br/>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.
