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Citizen Infrastructure

Engaged California: wildfire recovery (2025, in progress)

In February 2025, California launched Engaged California, described as a first-in-the-nation state effort to use digital tools for public deliberation. Its first topic: how to recover from the Eaton and Palisades wildfires that devastated parts of Los Angeles. It adapts the Taiwan model — broad listening plus AI-assisted sensemaking — to an American state of 40 million people, working with the same Stanford partners.

At a glance

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Process typeState-run digital deliberation / broad listening on a live crisis
WhenLaunched 23 February 2025 (ongoing)
WhereCalifornia, USA (online), on LA wildfire recovery
Run byThe Newsom administration (Office of Data and Innovation), with Stanford’s Deliberative Democracy Lab
Participants900+ people affected by the Eaton and Palisades fires (first phase)
The questionHow should California recover better from the wildfires?
StatusIn progress — input feeding long-term recovery plans

What happened

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Engaged California was chosen as a pilot precisely because wildfire recovery fits the conditions that make these processes work: it is urgent, it demands clarity, and it is far beyond any single department’s remit — an all-of-society problem. As Audrey Tang, who advised the effort, frames it, a shared real crisis lets people look past ideological differences and focus on what to actually build together — burying utility lines, better support for those who lost homes — rather than re-fighting the culture war.

The platform pairs online deliberation with AI that produces a balanced, grounded summary of what participants said — closing the loop quickly so people can see their input reflected, instead of waiting years for the next election or referendum.

Inputs → outputs

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In: the experiences and recovery priorities of 900+ Californians directly affected by the Eaton and Palisades fires.

Out: (in progress) synthesised input intended to shape California’s long-term wildfire recovery plans. Because the effort is recent, durable outcomes are not yet established — we’ll update this report as results are published.

Impact

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The significance so far is the precedent: a large US state adopting a method pioneered in Taiwan, signalling that AI-assisted civic listening and deliberation can run at state scale, not just city or national-island scale. A parallel, smaller US example is Better Bowling Green in Kentucky, run with Polis and open-source sensemaking tools — evidence that any community can pick up the same free software.

How it went

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Too early to judge outcomes — this report is marked in progress. The open questions are the usual ones for an imported model: whether trust built over a decade in Taiwan transfers quickly to a US context, and whether the synthesised input genuinely steers recovery decisions or stays advisory. The infrastructure-building point stands either way: standing up the capacity before the next crisis means the next urgent topic can be addressed fast.

Sources

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