Visualizing "We the People": Bridging the Perception Gap through Pluralistic Data Storytelling
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 18 references that are in the map. First posted on arXiv 23 Jun 2026.
Builds on
3 of 18 references.
References · 3
- 2023Bridging Systems: Open Problems for Countering Destructive Divisiveness across Ranking, Recommenders, and Governancecited by 17
- 2024AI and the Future of Digital Public Squarescited by 6
- 2026The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagementcited by 2
Built on by
Not cited yet.