# Using Collective Dialogues and AI to Find Common Ground Between Israeli and Palestinian Peacebuilders

arXiv: https://arxiv.org/abs/2503.01769 · HTML: https://mlsanity.com/paper/2503.01769/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Mar 2025.

## Built on by (most cited first, 6 of 6)

- [AI-Enhanced Deliberative Democracy and the Future of the Collective Will](https://mlsanity.com/paper/2503.05830/) (2025)
- [PoliCon: Evaluating LLMs on Achieving Diverse Political Consensus Objectives](https://mlsanity.com/paper/2505.19558/) (2025)
- [Algorithmic Shortlisting in Participatory Budgeting](https://mlsanity.com/paper/2508.06577/) (2025)
- [Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflict](https://mlsanity.com/paper/2608.15634/) (2026)
- [Toward Collective-Centric Evaluation of Preference Inference for Participatory Democracy](https://mlsanity.com/paper/2609.02990/) (2026)
- [Social Choice Foundations for Simulation-Augmented Generation](https://mlsanity.com/paper/2609.38287/) (2026)

## Abstract (arXiv)

A growing body of work has shown that AI-assisted methods -- leveraging large language models, social choice methods, and collective dialogues -- can help navigate polarization and surface common ground in controlled lab settings. But what can these approaches contribute in real-world contexts? 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 an iterative deliberative process combining LLMs, bridging-based ranking, and collective dialogues was conducted in partnership with the Alliance for Middle East Peace. Around 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 set of collective statements, including demands to world leaders, with at least 84% agreement from participants on each side. In this paper, we document the process, results, challenges, and important open questions.