AI Service-Learning (AISL) in Higher Education

Summary

This paper introduces Artificial Intelligence Service-Learning (AISL), an emerging pedagogical model that integrates artificial intelligence (AI) tools with the well-established framework of service-learning in higher education. Service-learning, rooted in civic engagement and experiential learning, has long emphasized student participation, community collaboration, and reflective practice. As AI becomes increasingly prevalent in education, AISL offers a unique opportunity to prepare students for an AI-driven world while addressing real-world challenges in local communities. The AISL model is structured into five key phases: AI literacy and training, community needs analysis, community-based learning, reflective practice, and evaluation and feedback. This phased approach ensures both educational rigor and meaningful community engagement. Example applications include AI-powered chatbots for nonprofits, intergenerational AI workshops, and community data projects. The model also supports multiple community engagement frameworks, such as participatory design and capacity-building. Despite its promise, AISL presents challenges, including ethical considerations, bias in AI tools, and the need for faculty development. Research gaps remain, particularly around the long-term impacts of AISL and best practices for culturally responsive AI applications. The paper concludes that AISL not only enriches student learning but also strengthens community ties and enhances digital equity. As a forward-looking educational strategy, AISL has the potential to redefine civic engagement and experiential learning in the age of artificial intelligence.