Collecting Public Opinion During Conflict: Case Studies from UN to the Paris Peace Forums скачать в хорошем качестве

Collecting Public Opinion During Conflict: Case Studies from UN to the Paris Peace Forums

WAPOR Webinar on January 29, 2026 Collecting Public Opinion During Conflict: Case Studies from UN to the Paris Peace Forums Extensive research has shown that AI-assisted methods — utilizing large language models, social choice methods, and collective dialogues — can help resolve differences and find consensus in controlled laboratory environments. But what role can these methods play in the real world? We present a case study applying these techniques to find common ground between Israeli and Palestinian peacebuilders in the period following October 7th, 2023. From April to July 2024, in partnership with the Alliance for Middle East Peace, we conducted an iterative deliberative process combining large language models, bridge-based ranking, and collective dialogues. Approximately 138 civil society peacebuilders participated, including Israeli Jews, Palestinian citizens of Israel, and Palestinians from the West Bank and Gaza. The process resulted in a series of collective statements, including demands to world leaders, with at least 84% agreement from participants on each side. In this paper, we document the entire process, results, challenges, and important unresolved questions. This study demonstrates how AI-assisted methods can be applied to actual public opinion research, especially on highly sensitive and polarized issues. It provides valuable insights for exploring new methods of polling and consensus-building. Our speaker for this webinar is Andrew Konya, a physicist by training who has spent the past eight years applying A.I. and machine learning algorithms to a wide range of problems – from material science and bio-sensing to peacekeeping with the United Nations. In 2014, he co-founded Remesh with the goal of using AI to establish the Truth of a population through live conversation.