Authors:
Louis Rosenberg
1
;
Hans Schumann
1
;
Christopher Dishop
2
;
Gregg Willcox
1
;
Anita Woolley
2
and
Ganesh Mani
2
Affiliations:
1
Unanimous AI, 2200 North George Mason Dr, Arlington, VA, U.S.A.
;
2
Carnegie Mellon University, Pittsburgh, Pennsylvania, U.S.A.
Keyword(s):
Collaboration, Deliberation, Collective Intelligence, Generative Ai, Conversational Swarm Intelligence, Deliberative Problem Solving, Large Language Models, Brainstorming, Alternative Use Tasks.
Abstract:
Conversational Swarm Intelligence (CSI) is an GenAI-based method for enabling real-time conversational deliberations among networked human groups of potentially unlimited size. Based on the biological principle of Swarm Intelligence and modelled on the decision-making dynamics of fish schools, CSI has been shown in prior studies to enable thoughtful conversations among hundreds of real-time participants while amplifying group intelligence. It works by dividing a large population into a set of subgroups that are woven together by real-time AI agents called Conversational Surrogates. The present study focuses on the use of a CSI platform called Thinkscape to enable real-time brainstorming and prioritization among groups of 75 networked users. The study employed a variant of a common brainstorming intervention called an Alternative Use Task (AUT) and compared brainstorming using a CSI platform to a traditional text-chat environment. This comparison revealed that participants significant
ly preferred using CSI, reporting that it felt (i) more collaborative, (ii) more productive, and (iii) was better at surfacing quality answers. In addition, participants using CSI reported (iv) feeling more ownership and more buy-in in the top answers the group converged on and (v) reported feeling more heard as compared to a traditional chat environment. Overall, the results suggest that CSI is a promising GenAI-based method for brainstorming and prioritization at large scale.
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