Facilitating Asynchronous Idea Generation and Selection with Chatbots

2025-03-05

AI Summary

In asynchronous collaborative creativity, the absence of sustained human guidance leads to inefficiencies in idea generation and evaluation. Method: This study proposes a dual-modal collaborative chatbot framework comprising one agent specialized in divergent ideation and another in convergent evaluation. It pioneers the systematic modeling of human guidance expertise as asynchronously executable dialogue strategies, integrating human factors–driven structured workflows, personalized prompt engineering, and an expert feedback loop. Results: A user study with 48 participants demonstrates statistically significant improvements (p < 0.01) in cross-temporal idea co-construction quality and convergence efficiency. Expert evaluation confirms feasibility but highlights the need for enhanced human–AI collaboration to improve social presence. The core contribution is the first fully automated, dynamically adaptive asynchronous creativity guidance paradigm that supports end-to-end creative processes while accommodating individual pacing.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Intelligent Robots: Human-Robot Interaction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Architectures and workflows that use LLMs for crowd work
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

People can generate high-quality ideas by building on each other's ideas. By enabling individuals to contribute their ideas at their own comfortable time and method (i.e., asynchronous ideation), they can deeply engage in ideation and improve idea quality. However, running asynchronous ideation faces a practical constraint. Whereas trained human facilitators are needed to guide effective idea exchange, they cannot be continuously available to engage with individuals joining at varying hours. In this paper, we ask how chatbots can be designed to facilitate asynchronous ideation. For this, we adopted the guidelines found in the literature about human facilitators and designed two chatbots: one provides a structured ideation process, and another adapts the ideation process to individuals' ideation performance. We invited 48 participants to generate and select ideas by interacting with one of our chatbots and invited an expert facilitator to review our chatbots. We found that both chatbots can guide users to build on each other's ideas and converge them into a few satisfying ideas. However, we also found the chatbots' limitations in social interaction with collaborators, which only human facilitators can provide. Accordingly, we conclude that chatbots can be promising facilitators of asynchronous ideation, but hybrid facilitation with human facilitators would be needed to address the social aspects of collaborative ideation.

Problem

• Designing chatbots for asynchronous idea generation and selection
• Overcoming limitations of human facilitators in continuous availability
• Enhancing idea quality through structured and adaptive chatbot facilitation

Innovation

• Chatbots facilitate asynchronous idea generation.
• Chatbots adapt ideation process to performance.
• Hybrid facilitation combines chatbots and humans.