Integrating AI and Sustainability Education: Students as Innovators for Sustainability ^†

Undergraduates today are being pulled in two opposing directions of mastering Artificial Intelligence (AI) and addressing sustainability. On the one hand, students must learn the complexities of AI technology; on the other hand, they must engage with the pressing issue of sustainability. This study challenges the perception of AI and sustainability as opposing forces and explores the impact of integrating AI with sustainability action through the “Artificial Intelligence for Social Good (AI4SG)” project. AI4SG focuses on a project-based teaching module designed to educate students about sustainability action and AI. The AI4SG module is flexible and can be adapted to focus on multiple dimensions of sustainability and community engagement by leveraging the UN Sustainable Development Goals (SDGs). This module was applied in multiple courses, with a particular focus on an upper-division course on environmental modeling with GIS. The course is designed for undergraduates from diverse majors. For this intervention, students were divided into groups, tasked with ideating and developing an AI solution (e.g., chatbot) to tackle one issue in their communities. Pre- and post-assessment surveys were collected to measure students’ perceptions of self-efficacy, fear of AI, interest in AI, and sustainability. Using a paired-sample t-test with pre- and post-values, our analysis revealed that students in the AI4SG intervention reported a reduced fear of AI (e.g., “I fear AI,” mean = 0.97, p 0.002), while also showing an increase in their self-efficacy and confidence in AI (“I know how AI might help address some sustainability issues in my community,” mean = −0.58, p 0.014). Additionally, students demonstrated an increased understanding of the sustainability and expressed confidence in their ability to develop AI systems to address sustainability issues (“I have confidence in my ability to develop AI systems to address sustainability issues in my communities,” mean = −0.92, p 0.017). During the project, students learned how to identify issues in their communities and what strengths can be used to solve them. The module’s flexibility allows it to address various dimensions of sustainability and community engagement. Integrating AI into sustainability education can help students connect sustainability science to actionable solutions, fostering both technical proficiency and a deeper understanding of sustainability issues.