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English(EN) Toward Collective-Centric Evaluation of Preference Inference for Participatory Democracy

新框架评估AI对民主偏好推断的影响

研究人员开发了一个新的框架,用于评估参与式民主平台中使用的偏好推断模型。这些模型可以预测大规模在线审议中的缺失投票,但可能会无意中扭曲共识和少数群体支持模式。新的集体中心评估框架超越了个人预测准确性,评估推断出的投票在多大程度上保留了偏好的整体结构。这项工作还引入了一个大型多语言数据集,以支持开发在规模化决策中维护民主诚信的AI系统。 AI

影响 这项研究旨在确保用于民主进程的AI系统不会扭曲集体决策,从而维护公众讨论的完整性。

排序理由 这是一篇在arXiv上发表的研究论文,详细介绍了一个新的AI模型评估框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新框架评估AI对民主偏好推断的影响

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这是一篇在arXiv上发表的研究论文,详细介绍了一个新的AI模型评估框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Pierre-Antoine Lequeu, Salim Hafid, Paul Lerner, Nazanin Shafiabadi, Laur\`ene Cave, David Mas, Jean-Philippe Cointet, Benjamin Piwowarski, Fran\c{c}ois Yvon ·

    迈向偏好推断的集体中心评估以促进参与式民主

    arXiv:2609.02990v1 Announce Type: cross Abstract: To scale up collective decision-making, participatory democracy platforms such as Polis and Remesh enable online deliberation among thousands of participants. However, at this scale, participants cannot review every opinion submit…