title: Opportunities and Risks of LLMs for Scalable Deliberation with Polis
summary: Polis is a platform that leverages machine intelligence to scale up
  deliberative processes. In this paper, we explore the opportunities and risks
  associated with applying Large Language Models (LLMs) towards challenges with
  facilitating, moderating and summarizing the results of Polis engagements. In
  particular, we demonstrate with pilot experiments using Anthropic's Claude that
  LLMs can indeed augment human intelligence to help more efficiently run Polis
  conversations. In particular, we find that summarization capabilities enable
  categorically new methods with immense promise to empower the public in
  collective meaning-making exercises. And notably, LLM context limitations have
  a significant impact on insight and quality of these results.
    However, these opportunities come with risks. We discuss some of these risks,
  as well as principles and techniques for characterizing and mitigating them,
  and the implications for other deliberative or political systems that may
  employ LLMs. Finally, we conclude with several open future research directions
  for augmenting tools like Polis with LLMs.
paper_authors._id: 6493b9c5b9bf46518a8a07f6
paper_authors.name: Christopher T. Small
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-06-23T07:32:00.347Z
paper_authors._id: 6494b19fec014de6a926aa5a
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/3fYEaKLQCuKpLeYUGCr0W.jpeg
paper_authors.fullname: Christopher T Small
paper_authors.type: user
paper_authors.user: csmall
paper_authors._id: 6493b9c5b9bf46518a8a07f7
paper_authors.name: Ivan Vendrov
paper_authors._id: 6493b9c5b9bf46518a8a07f8
paper_authors.name: Esin Durmus
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-06-23T07:32:04.815Z
paper_authors._id: 627dd7dbba19b19eff6aaa46
paper_authors.avatarUrl: /avatars/6e43025ccb96e48339d1db477da043b0.svg
paper_authors.fullname: Esin Durmus
paper_authors.type: user
paper_authors.user: esdurmus
paper_authors._id: 6493b9c5b9bf46518a8a07f9
paper_authors.name: Hadjar Homaei
paper_authors._id: 6493b9c5b9bf46518a8a07fa
paper_authors.name: Elizabeth Barry
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-06-27T07:28:02.214Z
paper_authors._id: 6499ca881ced6847e30b8def
paper_authors.avatarUrl: /avatars/d4d022733d325776b0ae8a51d7c178cf.svg
paper_authors.fullname: Elizabeth
paper_authors.type: user
paper_authors.user: lizbarry
paper_authors._id: 6493b9c5b9bf46518a8a07fb
paper_authors.name: Julien Cornebise
paper_authors._id: 6493b9c5b9bf46518a8a07fc
paper_authors.name: Ted Suzman
paper_authors._id: 6493b9c5b9bf46518a8a07fd
paper_authors.name: Deep Ganguli
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-06-22T08:43:01.566Z
paper_authors._id: 63924e6b2bfa48413aa0a4ad
paper_authors.avatarUrl: /avatars/f8219c475af6995b6fb9ebe727c5be43.svg
paper_authors.fullname: Deep Ganguli
paper_authors.type: user
paper_authors.user: dganguli
paper_authors._id: 6493b9c5b9bf46518a8a07fe
paper_authors.name: Colin Megill
paper_title: Opportunities and Risks of LLMs for Scalable Deliberation with Polis
paper_summary: Polis is a platform that leverages machine intelligence to scale up
  deliberative processes. In this paper, we explore the opportunities and risks
  associated with applying Large Language Models (LLMs) towards challenges with
  facilitating, moderating and summarizing the results of Polis engagements. In
  particular, we demonstrate with pilot experiments using Anthropic's Claude that
  LLMs can indeed augment human intelligence to help more efficiently run Polis
  conversations. In particular, we find that summarization capabilities enable
  categorically new methods with immense promise to empower the public in
  collective meaning-making exercises. And notably, LLM context limitations have
  a significant impact on insight and quality of these results.
    However, these opportunities come with risks. We discuss some of these risks,
  as well as principles and techniques for characterizing and mitigating them,
  and the implications for other deliberative or political systems that may
  employ LLMs. Finally, we conclude with several open future research directions
  for augmenting tools like Polis with LLMs.
paper_ai_keywords: Large Language Models (LLMs) summarization manual parameter insight quality risk principles techniques characterizing mitigating collective meaning-making