How an Autonomous Information Retrieval Agent Affects Divergent Thinking by a Group

Abstract

We have been developing a creativity support system called "AIDE, " which is equipped with various agents to stimulate creative group conversations. In this paper, we describe an autonomous information retrieval agent called "Conversationalist, " which is one of the agents of AIDE and is responsible for stimulating human divergent thinking. This agent analyzes the relationships among utterances and the structure of the topic in a conversation, and autonomously extracts various pieces of information relevant to the current conversation. Furthermore, we also show subjective experiments of AIDE applied to brainstorming sessions. From the results of the experiments, we confirmed that the agent is effective in stimulating human divergent thinking and in extracting more ideas from subjects, than in brainstorming sessions without the agent. Based on the results, we discuss what kind of information retrieval method is effective and when extracted pieces of information should be provided. Consequently, the following results are suggested : 1) when a conversation is active, the frequency of information provision by the agent should be rather low, and the relationship between the topic of the conversation and the pieces of information should not be so far, and 2) when a conversation is not active, i.e., is stagnate, or asynchronously executed, the frequency of information provision by the agent should be rather high, and the pieces of information should include some hidden relations with the topic of the conversation.