可视化“我们人民”：通过多元数据叙事弥合认知差距
Visualizing "We the People": Bridging the Perception Gap through Pluralistic Data Storytelling
AI总结：
针对传统二元可视化加剧政治极化的问题，提出利用AI驱动平台设计多元可视化，通过高维意见空间映射和共识/分歧区域展示，弥合群体间认知差距。
摘要：
传统的视觉数据叙事依赖于描绘两个简化群体冲突的二元图形。这可能会通过过度简化群体内部分歧、模糊模糊性和共享思想或价值观，从而加剧政治极化，并无意中助长“我们对他们”的思维。对于AI驱动的数字平台，有意的多元设计选择可以产生强调细微差别、意见分布和群体间共性的可视化。为了展示这一潜力，我们研究了绘制高维意见空间并突出共识与分歧区域的审议技术。本文重点介绍了Jigsaw和Napolitan研究所于2025年9月进行的“我们人民”审议活动，该活动邀请了来自全部435个国会选区的2400多名美国人参与一场AI支持的、关于自由与平等的异步对话。通过利用AI将长篇文本形式的参与者输入综合成交互式“意见景观”，该倡议为多元数据叙事提供了一种替代形式，使多样化的观点人性化，并揭示了隐藏的大量广泛共识区域。本文得出结论：从分裂的、对比强烈的视觉框架转向以分布为中心的交互式模型，是一种高度可扩展、低成本的干预措施，能够弥合认知差距，并培育更具韧性、更具协作性的民主文化。
英文摘要：
Traditional visual data storytelling relies on binary graphics that depict two simplified groups in conflict. This can increase political polarization by oversimplifying intra-group disagreements and erasing ambiguity and shared ideas or values. This can inadvertently foster "us versus them" thinking. Intentional, pluralistic design choices for AI-enabled digital platforms can produce visualizations that emphasize nuance, opinion distribution, and intergroup commonalities. To demonstrate this potential, we examine deliberative technologies that map high-dimensional opinion spaces and highlight areas of both consensus and dissensus. The paper highlights the We the People deliberation conducted by Jigsaw and the Napolitan Institute in September 2025, which engaged over 2,400 Americans across all 435 congressional districts in an AI-supported, asynchronous dialogue regarding freedom and equality. By utilizing AI to synthesize long-form, text-based participant inputs into interactive "opinion landscapes," the initiative provided an alternative format for pluralistic data storytelling that humanized diverse viewpoints and revealed hidden areas of substantial broad consensus. The paper concludes that shifting from divisive, contrast-heavy visual frameworks to distribution-focused, interactive models represents a highly scalable, low-cost intervention capable of bridging perceptual gaps and cultivating a more resilient, collaborative democratic culture.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
