HCC: Medium: Understanding and Supporting the Effectiveness of Groups Working with Generative AI

Generative AI tools like ChatGPT and Microsoft Copilot are rapidly changing how teams work together by helping people brainstorm ideas, write documents, and make decisions. But while these tools can boost productivity, they may also disrupt collaboration or strain team relationships. This project asks: What does good teamwork look like in the age of AI? And how can we design AI systems that make teamwork not just faster and more productive, but also more sustainable, supportive, and individually rewarding in the long term? Drawing from decades of research on what makes teams effective, the project will investigate how generative AI tools affect team dynamics, relationships, and individual well-being—not just task performance. The goal is to shape the next generation of AI tools so that they help teams thrive over time, both professionally and personally. This project applies a comprehensive framework of team effectiveness to investigate and design generative AI tools that support team interaction across three key dimensions: instrumental performance, team viability, and individual growth. Using a mix of qualitative interviews, fieldwork, and controlled laboratory studies, we will examine how current generative AI systems influence interaction patterns and effectiveness in text-based team collaboration platforms (e.g., Slack, MS Teams). We will then iteratively design new AI tools to improve team viability and individual well-being which are dimensions often overlooked in AI-supported collaboration research. These tools will be evaluated through rigorous empirical studies measuring outcomes across all three dimensions. The work contributes to research in human-computer interaction, computer supported cooperative work (CSCW), and computer mediated communication (CMC) by developing theory, design principles, and real-time intervention techniques for AI-mediated teamwork. It also builds technical foundations for integrating generative AI into everyday collaborative systems in ways that foster effective and sustainable work in teams. 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.