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

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 researchers1. 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 FactoryHidden 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.

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Publication Details

Published
2026-04-13
DOI
https://doi.org/10.1145/3772318.3790879
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

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

Toby Jia-jun Li, Bingsheng Yao, April Yi Wang, Dakuo Wang
Ethics and Social Impacts of AI
article

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

Toby Jia-jun Li, Bingsheng Yao, April Yi Wang, Dakuo Wang
article en

Abstract

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 researchers1. 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 FactoryHidden 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.

University of Notre Dame (US), Northeastern University (US), ETH Zurich (CH), Rice University (US)
Openalex Percentile: Top 100%
Ethics and Social Impacts of AI
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