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Towards Collective Superintelligence: Amplifying Group IQ Using Conversational Swarms

Topics: Autonomous Agents & Multi-Agent Systems; Group Decision Support Systems; Industrial Applications of Artificial Intelligence; Intelligent Agents; Natural Language Interfaces to Intelligent Systems; Problem Solving; Social Intelligence; Strategic Decision Support Systems

Authors: Louis Rosenberg 1 ; Gregg Willcox 1 ; Hans Schumann 1 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): Artificial Intelligence, Collective Intelligence, Generative AI, Conversational AI, Swarm Intelligence, Swarm AI, Collective Superintelligence, Collaboration, Deliberative Problem Solving, IQ, Large Language Models.

Abstract: Swarm Intelligence (SI) is a natural phenomenon that enables biological groups to amplify their combined intellect by forming real-time systems. Artificial Swarm Intelligence (or Swarm AI) is a technology that enables networked human groups to amplify their combined intelligence by forming similar systems. In the past, swarm-based methods were constrained to narrowly defined tasks like probabilistic forecasting and multiple-choice decision making. A new technology called Conversational Swarm Intelligence (CSI) was developed in 2023 that amplifies the decision-making accuracy of networked human groups through natural conversational deliberations mediated by artificial agents. The current study evaluated the ability of real-time groups using a CSI platform to take a common IQ test known as Raven’s Advanced Progressive Matrices (RAPM). First, a baseline group of participants took the Raven’s IQ test by traditional survey. This group averaged 45.7 correct. Then, groups of approximately 35 individuals answered IQ test questions together using a CSI platform called Thinkscape. These groups averaged 80.5% correct. This puts the CSI groups in the 97th percentile of IQ test-takers and corresponds to an effective IQ increase of 28 points (p<0.001). This is an encouraging result and suggests that CSI is a powerful method for enabling conversational collective intelligence in large, networked groups. In addition, because CSI deliberations are scalable across groups of potentially any size, these methods may provide a pathway to building a Collective Superintelligence. (More)

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Paper citation in several formats:
Rosenberg, L.; Willcox, G.; Schumann, H. and Mani, G. (2024). Towards Collective Superintelligence: Amplifying Group IQ Using Conversational Swarms. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7; ISSN 2184-4992, SciTePress, pages 759-766. DOI: 10.5220/0012687500003690

@conference{iceis24,
author={Louis Rosenberg. and Gregg Willcox. and Hans Schumann. and Ganesh Mani.},
title={Towards Collective Superintelligence: Amplifying Group IQ Using Conversational Swarms},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={759-766},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012687500003690},
isbn={978-989-758-692-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Towards Collective Superintelligence: Amplifying Group IQ Using Conversational Swarms
SN - 978-989-758-692-7
IS - 2184-4992
AU - Rosenberg, L.
AU - Willcox, G.
AU - Schumann, H.
AU - Mani, G.
PY - 2024
SP - 759
EP - 766
DO - 10.5220/0012687500003690
PB - SciTePress