Augmented Collective Intelligence in Collaborative Ideation: Agenda and Challenges

• URL: http://arxiv.org/abs/2303.18010v1
• Date: Fri, 31 Mar 2023 12:31:29 GMT
• Title: Augmented Collective Intelligence in Collaborative Ideation: Agenda and Challenges
• Authors: Emily Dardaman (1) and Abhishek Gupta (1, 2, and 3) ((1) BCG Henderson Institute, (2) Montreal AI Ethics Institute, and (3) Boston Consulting Group)
• Abstract summary: This paper explores applications of augmented collective intelligence (ACI) beneficial to collaborative ideation. The investigation described combines humans and large language models (LLMs) to ideate on increasingly complex topics. The paper concludes that researchers should address these challenges to conduct empirical studies of ACI in collaborative ideation.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: AI systems may be better thought of as peers than as tools. This paper explores applications of augmented collective intelligence (ACI) beneficial to collaborative ideation. Design considerations are offered for an experiment that evaluates the performance of hybrid human- AI collectives. The investigation described combines humans and large language models (LLMs) to ideate on increasingly complex topics. A promising real-time collection tool called Polis is examined to facilitate ACI, including case studies from citizen engagement projects in Taiwan and Bowling Green, Kentucky. The authors discuss three challenges to consider when designing an ACI experiment: topic selection, participant selection, and evaluation of results. The paper concludes that researchers should address these challenges to conduct empirical studies of ACI in collaborative ideation.

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