NRT-AI: AI advancements and convergence in computational, environmental, and social sciences (AI-ACCESS)

The National Science Foundation awarded a $2,990,135 Project Grant through the STEM Education program (CFDA 47.076) to The Washington University Office of Sponsored Research Services Division to establish the AI Advancements and Convergence in Computational, Environmental, and Social Sciences (AI-ACCESS) National Science Foundation Research Traineeship (NRT) program. The AI-ACCESS program will prepare 49 doctoral students, including 24 funded trainees, with skills to leverage the convergence of artificial intelligence, environmental science, and social sciences to address environmental and social challenges. The program will provide transdisciplinary education, research, and mentoring opportunities, including coursework in AI, machine learning, causal inference, and environmental sustainability, as well as training in communication, teamwork, and ethics. The program aims to increase diversity in STEM fields through targeted recruitment, retention, and training efforts.

Abstract

Emerging AI and computational tools have the potential to bring about significant transformation of scientific practice, especially in the environmental and social sciences. In fact, the very nature of important questions in those fields are themselves shifting as social systems are increasingly embedded within computational platforms that mediate daily human activity. However, while huge datasets are rapidly becoming commonplace across the environmental and social sciences, the right methods for understanding data generated by human behavior, as well as accessible tools for studying them, are lacking. In response to this urgent need, this national science foundation research traineeship (NRT) award establishes the AI advancements and convergence in computational, environmental, and social sciences (AI-ACCESS) NRT program at washington university in ST. Louis (WASHU) in collaboration with university of houston-downtown (UHD). The AI-ACCESS program will prepare a cohort of new investigators, trained at the intersection of AI, environmental science, and social sciences, with the skills to capitalize on the synergy in the convergence of AI and environmental social science. The program anticipates training forty-nine (49) doctoral students, including twenty-four (24) funded trainees. AI-ACCESS trainees will fill a growing need for organizations that aspire to develop data-driven policies and computational algorithms to address environmental and social challenges. The AI-ACCESS program leverages WASHU's graduate programs in computer science, environmental science, environmental engineering, public health, and social work to develop a new transformative training program with transdisciplinary education, research, and mentoring opportunities. The program includes prefatory courses in AI and machine learning, statistical and causal inference, and environmental sustainability; required courses in communication, teamwork, and ethics; and specialization in one of three research tracks -- computational sciences, environmental sciences, and social sciences. The program also includes recruitment efforts focused on increasing diversity through outreach and by exploiting the synergistic potential between the REU site at WASHU and partner UHD, a minority-serving institution; diversity retention efforts through community building activities and peer support programs; and diversity training efforts to ensure that all AI-ACCESS personnel belong in a diverse, inclusive, and connected environment. The NSF research traineeship (NRT) program is designed to encourage the development and implementation of bold, new potentially transformative models for stem graduate education training. The program is dedicated to effective training of stem graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs. 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.