Collaborative Data Driven Research
The lab collaborates with faculty and students on interdisciplinary research, bringing together diverse domains and methodological approaches to address complex social and scientific questions.
AI, Literacy & Ethics
Led by Dr. Seul Lee, the lab examines the social, cultural, and epistemic dimensions of AI, with a particular focus on questions of bias, literacy, and ethics, drawing on mixed-methods research.
Workshops & Infrastructure
The lab supports data-driven research through research infrastructure, workshops, and educational materials, fostering computational approaches to the humanities.
Focus
AI Data & Society
AI Data Lab examines the social, cultural, and epistemic dimensions of artificial intelligence, with particular attention to bias, literacy, ethics, and human-computer interaction. Through interdisciplinary and data-intensive research, the lab collaborates with faculty and students while supporting digital humanities through workshops, shared resources, and research infrastructure.
Services
Supporting Your Research
The lab provides a shared research environment, high-performance computing resources, and workshops and training programs which support collaborative, data-intensive, and computational research across domains.
- A dedicated physical environment designed to support collaborative research
- Access to high-performance computing resources for data-intensive computational research
- Workshops and training programs that support methodological development and research skills across domains
Research
Research Areas
Social Media & Critical Internet Studies
Critical studies of digital platforms, online publics, and the social dynamics of the internet.
AI Society & Ethics
Research on bias, literacy, and the social and ethical implications of AI.
Data-Driven Research & Digital Humanities
Digital humanities research using computational approaches to the study of culture, history, and society.
