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

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $900,000 · view on nsf.gov ↗

Abstract

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

Key facts

NSF award ID
2504533
Awardee
Cornell University (NY)
SAM.gov UEI
G56PUALJ3KT5
PI
Malte F Jung
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
MEDIUM PROJECT, Cyber-Human Systems
Estimated total
$900,000
Funds obligated
$900,000
Transaction type
Standard Grant
Period
09/01/2025 → 08/31/2028