Digital Repository of Linguistics and AI

Objectives

In the 2023-2024 academic year, the Department of Linguistics at Georgetown University piloted an innovative, multiphase final project in its introductory course, LING 1000: Introduction to Language, to explore the intersection of language and AI. This initiative aimed to educate students, primarily freshmen, on foundational concepts in language and AI, such as Large Language Models (LLMs), computational linguistics, natural language processing (NLP), spoken language processing (SLP), and machine translation (MT). 

Students were guided through an exploration of cutting-edge research, engaging in independent analysis and presenting original data on topics such as ethical concerns in LLMs, AI-generated linguistic content, machine translation quality, and the implications of AI for low-resource and endangered languages. They completed the final project by working on three scaffolded milestones, making sure that students were familiar with the core issues of computational linguistics and the ethical issues surrounding AI and language. 

Outcomes

Over two semesters, 108 undergraduate students contributed to this groundbreaking project, culminating into a digital repository that serves as a platform to showcase student presentations, reflections, and data. This platform serves as a model for educators and program administrators who are looking to implement AI in their own curricula and illustrates how to set up a collaborative project exploring topics related to language and AI. Researchers and other students can also access valuable data, methodologies, and results from the repository to inform their own studies. Furthermore, the repository offers students a professional platform to share their work beyond the classroom, supporting their academic and career development. 

By disseminating these projects, the repository aims to inspire interdisciplinary approaches to integrating AI in education. It emphasizes the ethical use of AI as a tool to address contemporary challenges and encourages other humanities and social science disciplines to explore the potential of AI to enhance learning and critical engagement. Additionally, researchers or other students interested in data related to language and AI will have access to resources developed by students in our course. These resources may include data collection instruments, methods, and results from testing could be shared and adapted for use in other contexts or domains. Finally, the platform will be useful for students who want to share their work in other professional spaces.

Team