Through the Lens of Human-Human Collaboration: An Configurable Research Platform for Exploring Human-Agent Collaboration

要旨

Intelligent systems have traditionally been designed as tools rather than collaborators, often lacking critical characteristics that collaboration partnerships require. Recent advances in large language model (LLM) agents open new opportunities for human-LLM-agent collaboration by enabling natural communication and various social and cognitive behaviors. Yet it remains unclear whether principles of computer-mediated collaboration established in HCI and CSCW persist, change, or fail when humans collaborate with LLM agents. To support systematic investigations of these questions, we introduce an open and configurable research platform for HCI researchers. The platform's modular design allows seamless adaptation of classic CSCW experiments and manipulation of theory-grounded interaction controls. We demonstrate the platform's research efficacy and usability through three case studies: (1) two Shape Factory experiments for resource negotiation with 16 participants, (2) one Hidden Profile experiment for information pooling with 16 participants, and (3) a participatory cognitive walkthrough with five HCI researchers to refine workflows of researcher interface for experiment setup and analysis.

著者
Bingsheng Yao
Northeastern University, Boston, Massachusetts, United States
Jiaju Chen
Rice University, Houston, Texas, United States
Chaoran Chen
University of Notre Dame, Notre Dame, Indiana, United States
April Yi. Wang
ETH Zurich, Zurich, Switzerland
Toby Jia-Jun. Li
University of Notre Dame, Notre Dame, Indiana, United States
Dakuo Wang
Northeastern University, Boston, Massachusetts, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Human-in-the-Loop Machine Learning Interfaces

P1 - Room 111
7 件の発表
2026-04-17 18:00:00
2026-04-17 19:30:00