TY - GEN
T1 - Hyperdemocracy
T2 - 2025 IEEE International Conference on Agentic AI, ICA 2025
AU - Ito, Takayuki
AU - Dong, Yihan
AU - Haqbeen, Jawad
AU - Matsuo, Tokuro
AU - Sahab, Sofia
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Effective consensus building is a critical challenge in diverse domains, including international disputes, societal polarization, and organizational decision-making. This research project envisions a future termed 'Hyperdemocracy,' where a multitude of AI agents collaborate with humans to support consensus building while fostering democratic deliberation. These AI agents, based on Large Language Models (lLMs), can introduce diverse perspectives through text-based dialogue, guiding discussions toward mutual understanding. Advances in LLMs offer a promising avenue for mitigating persistent issues in group decision-making, such as groupthink and cognitive biases. Field experiments conducted in Afghanistan and Indonesia have demonstrated that our multi-agent system can stimulate deliberation and promote opinion change among participants, even in highly fragmented contexts. This paper details the system's design philosophy, presents the results of its real-world validation, and discusses the ethical considerations and future prospects. We suggest that this technology holds transformative potential for conflict resolution and fostering inclusive dialogue.
AB - Effective consensus building is a critical challenge in diverse domains, including international disputes, societal polarization, and organizational decision-making. This research project envisions a future termed 'Hyperdemocracy,' where a multitude of AI agents collaborate with humans to support consensus building while fostering democratic deliberation. These AI agents, based on Large Language Models (lLMs), can introduce diverse perspectives through text-based dialogue, guiding discussions toward mutual understanding. Advances in LLMs offer a promising avenue for mitigating persistent issues in group decision-making, such as groupthink and cognitive biases. Field experiments conducted in Afghanistan and Indonesia have demonstrated that our multi-agent system can stimulate deliberation and promote opinion change among participants, even in highly fragmented contexts. This paper details the system's design philosophy, presents the results of its real-world validation, and discusses the ethical considerations and future prospects. We suggest that this technology holds transformative potential for conflict resolution and fostering inclusive dialogue.
KW - AI Agents
KW - Consensus Building
KW - Hyperdemocracy
KW - Large Language Models
KW - Multi-Agent Systems
UR - https://www.scopus.com/pages/publications/105033367005
UR - https://www.scopus.com/pages/publications/105033367005#tab=citedBy
U2 - 10.1109/ICA67499.2025.00034
DO - 10.1109/ICA67499.2025.00034
M3 - Conference contribution
AN - SCOPUS:105033367005
T3 - Proceedings - 2025 IEEE International Conference on Agentic AI, ICA 2025
SP - 116
EP - 121
BT - Proceedings - 2025 IEEE International Conference on Agentic AI, ICA 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 December 2025 through 7 December 2025
ER -