REU Site: Human-AI Interaction and Evaluation in Web and Information Systems

With the rapid proliferation of artificial intelligence (AI) technologies across the Web and information systems, the interaction between humans and AI has become a critical research area. This Research Experiences for Undergraduates (REU) Site recruits 8 undergraduate students each year from regional and national universities to participate in a 10-week research-intensive summer program at Old Dominion University, focusing on Human-AI Interaction in Web and information systems. The project's novelties are the following: it is the first REU program focusing on the Web and information system aspects of human-AI interaction and evaluation; it produces new datasets, methods, models, and assessment tools addressing open human-AI interaction research problems in health informatics, Web data, and robotics; and it introduces new knowledge to undergraduate students about human behavior and expectations regarding online AI systems. The project's broader significance and importance are the following: it expands human-AI education to undergraduate participants from diverse backgrounds and prepares them for graduate studies and careers in science, technology, engineering, and mathematics, strengthened by hands-on research, training, and publication experience; and it benefits first-generation college students by offering research opportunities that foster their growth into members of a globally competitive technical workforce. In this REU project, students learn Human-AI Interaction concepts, methods, and interfaces; tools and skills to access, clean, preprocess, and visualize diverse datasets including human-generated data, AI-generated data, and other Web-related data; state-of-the-art computational methods, including multimodal large language models and machine learning algorithms, to build analytical and predictive model prototypes using open-source programming tools for addressing research challenges in Human-AI Interaction; and important metrics to evaluate research tasks, compare baseline models, and produce publication-quality results. Students also develop essential research skills including critical thinking, technical writing, and research presentation. This program strengthens the nation's research capacity by training a new generation of well-prepared researchers in the rapidly growing field of human-AI interaction. 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.