Towards Collaborative Brain-storming among Humans and AI Agents: An Implementation of the IBIS-based Brainstorming Support System with Multiple AI Agents

Brainstorming is a crucial process for stimulating the generation of creative ideas, and it continues to be widely used today. Group brainstorming offers the advantage of obtaining diverse opinions from others, perspectives that may not arise in individual brainstorming sessions. However, group brainstorming is susceptible to decreased overall productivity due to three factors: The first is the phenomenon known as "Free riding" or "social loafing," where certain members overly rely on others, leading to a decrease in individual contributions. The second is "Social inhibition," which suppresses individual performance due to the presence of others. The third is "Production blocking," where individuals’ ideas are inhibited by other group members when presented. In this study, we focus on addressing the first two factors of "Free riding/social loafing" and "Social inhibition" by implementing a brainstorming support system. This system assigns the roles of others in group brainstorming to agents. By interacting with individuals using different functionalities, the agents mimic human group brainstorming, enabling individuals to enjoy the benefits of group brainstorming while mitigating the decrease in individual performance. We designed agents based on the concept of the IBIS structure (Issue, Idea, Pros, Cons). GPT-3.5-turbo was used for creating these agents. The four types of agents include (1) Those that freely generate ideas from the theme; (2) Those that generate ideas from other ideas; (3) Those that generate issues from ideas; and (4) Those that generate ideas from issues. Agents (2)-(4) have the function of replying to ideas and issues while prioritizing human posts. To validate the effectiveness of the agents, we conducted a comparative experiment using the bulletin board-style discussion platform D-Agree. We compared scenarios where brainstorming was conducted by humans alone (A), humans collaborated with agents (B), and agents alone (C). In scenario (A), two groups of three individuals each conducted separate brainstorming sessions on different themes. In scenario (B), individuals conducted brainstorming sessions with agents on themes they had not brainstormed in scenario (A). The results of the evaluation experiment show a tendency for the number of comments and ideas to increase per individual in scenario (B), where humans collaborated with agents, compared to scenario (A), where only humans participated. Moreover, the number of ideas and topics per brainstorming session was highest in scenario (B). However, these increases varied significantly among individuals. Furthermore, questionnaire results indicate a decrease in hesitation to contribute ideas and an increase in the ability to generate many ideas in scenario (B) compared to scenario (A). The significant differences observed in the increases in the number of comments per individual, the number of ideas per individual, the number of ideas per brainstorming session, and the number of topics per brainstorming session suggest the need for system improvements to ensure a consistent increase in the number of ideas, regardless of the user. Furthermore, additional experiments with increased sample sizes are needed to confirm the statistical significance of the results obtained in this study.