# Can AI mediation improve democratic deliberation?

arXiv: https://arxiv.org/abs/2601.05904 · HTML: https://mlsanity.com/paper/2601.05904/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 29 of its 81 references that are in the map.
- First posted on arXiv 9 Jan 2026.

## Builds on (most cited first, 29 of 29)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context](https://mlsanity.com/paper/2403.05530/) (2024)
- [Concrete Problems in AI Safety](https://mlsanity.com/paper/1606.06565/) (2016)
- [Artificial Intelligence, Values and Alignment](https://mlsanity.com/paper/2001.09768/) (2020)
- [Towards Measuring the Representation of Subjective Global Opinions in Language Models](https://mlsanity.com/paper/2306.16388/) (2023)
- [AI safety via debate](https://mlsanity.com/paper/1805.00899/) (2018)
- [Self-critiquing models for assisting human evaluators](https://mlsanity.com/paper/2206.05802/) (2022)
- [Recursively Summarizing Books with Human Feedback](https://mlsanity.com/paper/2109.10862/) (2021)
- [Measuring Progress on Scalable Oversight for Large Language Models](https://mlsanity.com/paper/2211.03540/) (2022)
- [Fine-tuning language models to find agreement among humans with diverse preferences](https://mlsanity.com/paper/2211.15006/) (2022)
- [Power to the People? Opportunities and Challenges for Participatory AI](https://mlsanity.com/paper/2209.07572/) (2022)
- [Collective Constitutional AI: Aligning a Language Model with Public Input](https://mlsanity.com/paper/2406.07814/) (2024)
- [The Ethics of Advanced AI Assistants](https://mlsanity.com/paper/2404.16244/) (2024)
- [STaR-GATE: Teaching Language Models to Ask Clarifying Questions](https://mlsanity.com/paper/2403.19154/) (2024)
- [Scalable AI Safety via Doubly-Efficient Debate](https://mlsanity.com/paper/2311.14125/) (2023)
- [Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discrimination](https://mlsanity.com/paper/2406.08818/) (2024)
- [Generative Social Choice](https://mlsanity.com/paper/2309.01291/) (2023)
- [Debate Helps Supervise Unreliable Experts](https://mlsanity.com/paper/2311.08702/) (2023)
- [Opportunities and Risks of LLMs for Scalable Deliberation with Polis](https://mlsanity.com/paper/2306.11932/) (2023)
- [Towards Human-AI Deliberation: Design and Evaluation of LLM-Empowered Deliberative AI for AI-Assisted Decision-Making](https://mlsanity.com/paper/2403.16812/) (2024)
- [Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking](https://mlsanity.com/paper/2411.06116/) (2024)
- [Democratic Policy Development using Collective Dialogues and AI](https://mlsanity.com/paper/2311.02242/) (2023)
- [Language Agents as Digital Representatives in Collective Decision-Making](https://mlsanity.com/paper/2502.09369/) (2025)
- [AI and the Future of Digital Public Squares](https://mlsanity.com/paper/2412.09988/) (2024)
- [Distortion Under Public-Spirited Voting](https://mlsanity.com/paper/2305.11736/) (2023)
- [A Statistical Decision-Theoretic Framework for Social Choice](https://mlsanity.com/paper/1410.7856/) (2014)
- [Learning to Manipulate under Limited Information](https://mlsanity.com/paper/2401.16412/) (2024)
- [Human-AI Complementarity: A Goal for Amplified Oversight](https://mlsanity.com/paper/2510.26518/) (2025)
- [Can LLMs advance democratic values?](https://mlsanity.com/paper/2410.08418/) (2024)

## Abstract (arXiv)

The strength of democracy lies in the free and equal exchange of diverse viewpoints. Living up to this ideal at scale faces inherent tensions: broad participation, meaningful deliberation, and political equality often trade off with one another (Fishkin, 2011). We ask whether and how artificial intelligence (AI) could help navigate this "trilemma" by engaging with a recent example of a large language model (LLM)-based system designed to help people with diverse viewpoints find common ground (Tessler, Bakker, et al., 2024). Here, we explore the implications of the introduction of LLMs into deliberation augmentation tools, examining their potential to enhance participation through scalability, improve political equality via fair mediation, and foster meaningful deliberation by, for example, surfacing trustworthy information. We also point to key challenges that remain. Ultimately, a range of empirical, technical, and theoretical advancements are needed to fully realize the promise of AI-mediated deliberation for enhancing citizen engagement and strengthening democratic deliberation.