How can many people (who may disagree) come together to answer a question or
make a decision? "Collective response systems" are a type of generative
collective intelligence (CI) facilitation process meant to address this
challenge. They enable a form of "generative voting", where both the votes, and
the choices of what to vote on, are provided by the group. Such systems
overcome the traditional limitations of polling, town halls, standard voting,
referendums, etc. The generative CI outputs of collective response systems can
also be chained together into iterative "collective dialogues", analogously to
some kinds of generative AI.
Technical advances across domains including recommender systems, language
models, and human-computer interaction have led to the development of
innovative and scalable collective response systems. For example, Polis has
been used around the world to support policy-making at different levels of
government, and Remesh has been used by the UN to understand the challenges and
needs of ordinary people across war-torn countries. This paper aims to develop
a shared language by defining the structure, processes, properties, and
principles of such systems.
Collective response systems allow non-confrontational exploration of divisive
issues, help identify common ground, and elicit insights from those closest to
the issues. As a result, they can help overcome gridlock around conflict and
governance challenges, increase trust, and develop mandates. Continued progress
toward their development and adoption could help revitalize democracies,
reimagine corporate governance, transform conflict, and govern powerful AI
systems -- both as a complement to deeper deliberative democratic processes and
as an option where deeper processes are not applicable or possible.

本文介绍了一种名为 “群体响应系统” 的基于集体智慧的决策过程，可以帮助人们跨越传统投票、公投等方式限制，探索分裂性议题、建立共识以及促进治理。这些系统已经得到广泛的应用，例如在不同级别的政策制定和解决战争时代国家的困难和需求中，具有较高的可扩展性。本文旨在共同定义这些系统的结构、流程、特性和原则，并将其应用于民主治理、企业治理、冲突转化和强大的人工智能系统的治理。