Designing a one-hour course on democratic engagement and AI means confronting genuinely hard questions about representativeness, political framing, and audience, where thoughtful experts disagree, and every choice involves a real tradeoff. Over the past week, we drafted, debated, and cut more than 25,000 words to a working script, informed by over 300 comments from 50 advisors across 24 countries and a room full of democratic theorists in Barcelona. This post explains the three hardest calls we had to make and why we made them.

Millions of Americans miss out on health and food assistance benefits due to fragmented systems and complex enrollment processes. This piece explores how Link Health, in partnership with the AI for Impact program, is combining AI tools with human navigators to rethink how public benefits are delivered in healthcare settings. It argues that the next frontier is better evidence. States should fund research to compare enrollment approaches, portal design, and navigator support to determine which improve health outcomes and guide smarter public investment.

Growing up in Kakuma refugee camp, Nhial Deng experienced what it means to be excluded from opportunities. Returning years later, he saw young people using AI not as aid, but as a tool to build skills, income, and futures in real time. This piece argues that AI is already functioning as an economic opportunity layer, but one that remains uneven and fragile without intentional design. Drawing on examples from Canada, Singapore, and Kenya, Deng outlines how governments can move from accidental access to structured opportunity by connecting AI to jobs, embedding it in trusted institutions, and building safeguards alongside deployment.

Massachusetts municipalities are eligible for an estimated $17.5 billion in federal funding, but accessing it is often harder than securing it. In partnership with the Massachusetts Federal Funds and Infrastructure Office, the Burnes Center for Social Change is launching GrantWell, an AI-powered tool designed to reduce the friction that keeps many communities from applying. Anjith Prakash, lead engineer at GrantWell, explains how the tool helps users find opportunities, understand requirements, and move local needs into competitive applications, expanding access to funding.

In this post, Eileen Twiggs draws on lessons from the InnovateUS workshop "Effective Use of Social Media: Storytelling, Trust, and Institutional Brand" to explore how public servants can move beyond risk-averse messaging to tell more human, compelling stories. From finding the “true thing” in everyday work to using AI as a thoughtful teammate, these practical strategies show how to communicate more effectively in today’s fast-moving information environment and rebuild trust one story at a time.

Dr. Sara Bazoobandi examines how Iran’s doctrine of “knowledge jihad” shaped the development of its digital and AI infrastructure, transforming technology into an instrument of state control. The piece traces how this system, built for surveillance and centralized authority, has also created strategic fragility, offering a cautionary lesson for democracies designing the foundations of AI governance.

More than 50 practitioners, researchers, and civic technologists from 24 countries reviewed the draft curriculum for Designing Democratic Engagement for the AI Era, providing over 300 comments and suggestions. The feedback, relayed by Dane Gambrell and Sarah Hubbard, highlighted the need for clearer guidance on institutional readiness, trust, inclusion, and the risks and limits of AI in public participation. This post summarizes the key themes that emerged, explains how AI tools were used to synthesize the feedback, and outlines the next steps in developing the course.

Cities often treat nearby universities as occasional partners rather than strategic collaborators. But as artificial intelligence reshapes local economies and public services, that relationship may need to change. Drawing on a new policy brief, The AI Lab Next Door, Neil Kleiman argues that city–university “compacts” can transform transactional ties into intentional partnerships, helping communities harness the growing AI capacity already taking shape on college campuses.

InnovateUS and the Center for Civic Futures are launching a new series exploring how AI can help human services agencies reduce administrative burden and improve benefits delivery. Drawing on Robert Asaro-Angelo’s experience as Commissioner of New Jersey’s Department of Labor and Workforce Development, this post examines how agencies can use AI to help the public sector improve benefits delivery, reduce administrative burden, and better support both frontline staff and the people they serve.

In this commentary, originally published by InDaily South Australia, Matt Ryan argues that artificial intelligence can help governments deliver more effective, human-centered services, but only if it builds public trust and democratic legitimacy. Drawing on examples from Spain, San Francisco, and the UK, he outlines a path for South Australia to develop “sovereign AI capability.” His proposal focuses on three priorities: participatory AI governance, stronger public-sector AI skills, and reinvesting efficiency gains into public services, ensuring AI improves government while strengthening democracy.

In this conversation with Elana Banin, Lorelei Kelly argues that rebuilding democratic resilience requires redesigning the institutional infrastructure connecting citizens to Congress. Drawing on constitutional history and emerging technologies, she explores how deliberative technology and AI could help revive the First Amendment’s promises of assembly and petition for the digital age.

Artificial intelligence is often portrayed as a force that will destroy jobs. In this essay, Seth Harris argues that it can also expand opportunity. By using AI to identify and remove unnecessary college degree requirements in state hiring, governments can reduce barriers to public employment, address racial and class disparities, and fill critical roles more efficiently. Backed by new research underway from the Burnes Center for Social Change, supported by the GitLab Foundation, he outlines how thoughtfully deployed AI can break down barriers and accelerate the shift to skills-based hiring.

The current controversy over the Pentagon’s AI contracts reveals a deeper issue: governments are shaping the AI market through procurement in the wrong ways or not at all, failing to make demands that AI strengthen democracy and improve governance. As AI becomes core public infrastructure, public institutions must use their purchasing power deliberately by requiring portability, accountability, and interoperability and prioritizing use in the public interest. This post explains the public conversation we are having about public and democratic AI andhow governments can buy, build, and govern AI on the public’s terms.

As governments move from AI pilots to workforce-wide access, the hardest questions are practical: What does it cost at scale? Who gets access? How do you log usage and manage risk? How do we pair access with training so it’s safe — and actually useful?Drawing on lessons from New Jersey and Boston, this post outlines how to structure AI deployment using usage-based pricing, cloud infrastructure you control, and training designed to drive real impact.

This week on Reboot Democracy, Max Stier explores how AI can strengthen internal government culture by building real-time recognition systems for civil servants. Elana Banin examines the UbuntuGuard b

In Argentina, the Red de Innovación Local (RIL) experimented with its AI-powered platform, PortalRIL, to shift from fragmented work plans to an inquiry-driven planning process anchored in a “Question Tree.” By surfacing patterns, trade-offs, and synergies across teams, AI helped compress months of coordination into weeks of shared clarity. The result suggests that AI’s real promise is to expand strategic horizons and accelerate collective insight, freeing public servants to focus on judgment, identity, and long-term public value.

RebootDemocracy.AI - We believe that artificial intelligence can and should be harnessed to strengthen participatory democracy.

Artificial intelligence will increase demand for government services before it increases efficiency.

As Korea aims to become a top-three global AI power, the government has staked its strategy on “sovereign AI” as both an economic and national security priority. In this reflection, originally published in the Herald Insight Collection, Merve Hickok examines Korea’s multibillion-dollar investment in a national foundation model amid U.S.–China competition and the rise of Open-Source AI, asking whether alternative investments—such as small language models, compute and energy efficiency, and AI governance and evaluation—might better secure Korea’s long-term autonomy and global leadership.

As the AIEP project concludes its first pilot in San Francisco, it offers more than a new AI tool for navigating IEPs. It shows what becomes possible when families, educators, designers, and researchers co-design technology from the ground up. Through a free, open-source tool, a civic AI learning course, a community-centered playbook, and academic research, this work demonstrates a practical model for public-purpose AI rooted in lived experience, shared learning, and accountability. What began as support for parents has grown into a blueprint for building AI with communities, not just for them.

Leaders increasingly believe public engagement matters, but lack the practical know-how to do it well. Beth Simone Noveck and Dane Gambrell examine how institutions use AI and collective intelligence to engage the public at scale. Across countries and levels of government, engagement can move from performative to consequential when institutions build the capacity to design it well. That work now comes together in a new free course, Designing Democratic Engagement for the AI Era, created by InnovateUS, The GovLab, and the Allen Lab for Democracy Renovation, to help public professionals turn these lessons into practice.

What if the problem with government wasn’t too many rules, but how they’re organized? Boston’s permitting overhaul with AI for Impact shows how AI and collective intelligence can simplify the user experience without eroding the safeguards that matter.

Families are expected to advocate for their children using IEP documents that are dense, technical, and often inaccessible. Instead of treating AI as a black box that produces generic summaries, this project takes a different approach of "unboxing the prompt" and inviting parents into the system's core logic. This post traces how community feedback reshaped the tool at every stage, from moving beyond one-size-fits-all summaries to extracting legally meaningful details, to designing for privacy, to preserving meaning across languages, and to foregrounding student strengths.

Governments are adopting powerful new technologies faster than their systems are built to learn. This piece by Cassandra Madison at the Center for Civic Futures argues that responsible innovation requires more than access to tools. It requires safe, structured spaces for experimentation. By treating experimentation as public infrastructure, governments can learn early, surface risks before they scale, and make better decisions when the stakes are highest.

Mapping schools in Uzbekistan and Bhutan revealed how data that appeared complete on paper often missed what mattered on the ground, like distance, access, and everyday conditions. By treating geography as essential, spatial data, participatory collection, and AI analysis reshaped how evidence-informed public investment and policy decisions are made.

A hiring tool changes your "personality" score based on whether there's a bookshelf behind you in an interview. A hospital model suggests asthmatics are safer—because it learned how to respond to the triage system, not the disease. This InnovateUS workshop explains why predictive AI needs governance, not just accuracy.

We’re launching the Observatory of Public Sector AI, a new research initiative of InnovateUS and The GovLab that draws on data from more than 150,000 public servants nationwide. By analyzing how public employees learn, use, and adapt AI at work, the Observatory aims to identify which investments in skills and training actually strengthen government capacity, improve services, and deliver better outcomes for residents.

Reeve Bull shows how Virginia is using AI to improve regulatory review, from analyzing statutes to streamlining outdated rules. Anirudh Dinesh looks to India, where the Bhashini platform expands democ

India's Bhashini platform is democratizing access to digital services for 1.4 billion people by treating multilingual capability as public infrastructure. Through crowdsourced voice donations and open APIs, this initiative could transform how underserved populations access rights and resources that were previously locked behind language barriers.

This piece examines how the Commonwealth of Virginia is using artificial intelligence to modernize regulatory review, shifting the focus from regulating AI to governing with it. Drawing on recent reforms led by the Virginia Office of Regulatory Management under Governor Glenn Youngkin, the article outlines how AI tools are being applied to analyze regulations, reduce administrative burden, and improve transparency. The "Virginia Model" offers a practical model for other states exploring how AI can strengthen core government functions.

U.S. labor law is shaped by thousands of decisions issued each year by the National Labor Relations Board (NLRB) and the courts, yet much of this precedent remains difficult for workers, organizers, and even lawyers to access in practice. This piece examines how the NLRB’s fragmented document publication system creates real information barriers for workers and their advocates. A new tool, NLRB Research, uses open-source software and AI to make labor law searchable and and usable, demonstrating how improving access to public legal information can help empower workers to understand and act on their rights.

New Jersey’s Office of Innovation has received a Public Benefit Innovation Fund grant to expand its AI platform with tools that help residents access benefits faster and with fewer errors. In this conversation, Beth Simone Noveck and NJ Chief Innovation Officer Dave Cole discuss how document processing, eligibility matching, feedback analysis, and memo-generation tools are already improving programs such as Medicaid, Unemployment Insurance, and Summer EBT, and what it takes to deploy AI responsibly within government.

Conventional wisdom presents mid-sized economies with two options for accessing advanced AI: rely on American or Chinese systems, or fall behind. Neither choice preserves the technological sovereignty that countries increasingly see as essential. But there is a third path we explore in detail in a recent memo. Collectively, nations outside the US-China duopoly possess substantial computing infrastructure, a majority of the world’s top researchers, and the growing political will to create a third path. The question is whether they can come together to make it work.

The City as Mesh by Geoff Mulgan and Caio Werneck offers a powerful new framework for organizing cities to tackle cross-cutting challenges. This Research Radar examines their new paper and argues for going further: using AI as a coordination layer, treating skills as design choices, and leveraging public engagement as operational intelligence.

Governments are increasingly using AI to identify redundant, outdated, and burdensome regulations. But efficiency alone is not reform: without public judgment, simplification can weaken essential protections. The Green Tape Challenge shows how pairing AI with collective intelligence can modernize regulation while preserving legitimacy, equity, and purpose.From Red Tape to Green Tape: Decluttering the State with AI and Collective Intelligence

This Research Radar examines how California’s Office of Data and Innovation used a rigorous, community-driven approach to translate thousands of survivor contributions from the LA wildfires into a concrete recovery action plan. Combining deliberative design, large-scale digital participation, AI-assisted analysis, and human review, the engagement shows how public institutions can listen at scale, synthesize insight with integrity, and move from data to decisions when it matters most.

In this workshop, Audrey Tang and Danielle Allen discuss how AI-enabled civic technologies, paired with radical transparency and thoughtful institutional design, can help democracies respond to problems faster, govern more fairly, and rebuild public trust. Lessons from Taiwan, California, and other contexts show how combining digital tools with in-person engagement can surface common ground and reduce polarization. Together, the speakers argue that democracy can meet today’s challenges when it is designed to be fast, fair, and genuinely engaging for the people it serves.

Beth Simone Noveck testifies before Congress on how AI can help lawmakers move beyond performative public engagement to use constituent input at scale meaningfully. Agueda Quiroga announces the launch

On Wednesday, December 17, 2025, at 10:00am ET, the Subcommittee on Modernization and Innovation of the Committee on House Administration will hold a hearing titled, “The Future of Constituent Engagement with Congress.” The hearing will be held in room 1310 of the Longworth House Office Building.

As governments experiment with AI to simulate public opinion, new questions are emerging about who these systems truly represent. This Research Radar examines the Collective Intelligence Project’s Digital Twin Evaluation Framework—a developing method for testing whether AI models can mirror real human opinion patterns—and explores the democratic risks of relying on synthetic publics in policymaking.

This week, our new Research Radar warns that the White House’s Genesis Mission to merge federal AI, data, and supercomputing power could sideline universities, communities, and public oversight. In a

As governments and international bodies race to establish guardrails for AI, most of the global agenda still focuses on managing what AI systems produce—their outputs. This article argues that such an approach is incomplete. The real foundations of safe, rights-respecting, and equitable AI lie upstream in how data is collected, governed, shared, and stewarded. Without integrating mature data governance practices, such as data stewardship and data commons, into AI governance, countries will struggle to protect fundamental rights or ensure that AI’s economic and social benefits are distributed fairly. A future-ready AI governance framework must therefore unite input and output governance into a single, coherent system.

The Trump Administration’s Genesis Mission aims to unify federal supercomputers, datasets, and AI systems into a single national platform for scientific discovery. But as Beth Simone Noveck argues, the plan centralizes unprecedented research power while offering almost no role for universities, communities, or the public, raising urgent questions about access, transparency, and democratic accountability.

AI is already shaping government decisions, but bright-line bans on automated decisions are not enough to manage the complex “middle space” where most automation now operates. Effective governance requires both individual rights — so people can understand and challenge decisions about them — and collective oversight that lets journalists, civil society, and regulators scrutinize systems as a whole. By blending transparency, redress, and sustained human responsibility, governments can harness AI to improve services while safeguarding democratic accountability.