Insights on AI governance, public sector innovation, and democracy
In a New York Times guest essay, Beth Simone Noveck makes the case for putting A.I. behind every public servant. She draws on examples from New Jersey, California, the U.K., South Korea and South Australia, and calls for three investments: training the public workforce, giving workers secure access to multiple models, and using government purchasing power to build open, accountable A.I.
After the 2025 Los Angeles wildfires, California's Office of Data and Innovation used Engaged California to gather more than 1,300 resident comments. AI helped turn that input into 19 policy options, which residents then deliberated over and ranked. Jeffery Marino explains how clear ownership, with state agencies, local governments, and community groups acting together with support from the Governor's office, turned those priorities into a five-part recovery action plan.
Three-Year Multistate Initiative Will Combine Free Mobile AI Learning with Library-Based Programs Helping Residents Navigate Government, Participate in Civic Life, and Solve Community Problems with AI
A new free course from the Allen Lab for Democracy Renovation, The GovLab, and InnovateUS teaches public servants how to design AI-enabled public engagement that turns comments into policy, drawing on 42 real-world examples from 20 countries.
The public conversation about AI has swung from exuberance to alarm, casting AI as an unstoppable force. That framing overlooks the fact that public institutions design, build, buy, and regulate AI, and societies still choose where it leads. This fall, Reboot is organizing its coverage around four connected questions: what capabilities public institutions need, how they can become institutions that listen and learn, what public AI infrastructure requires, and how we measure whether AI is actually creating public value.
AI is making it possible for governments to listen at a scale that was previously impossible, turning thousands of comments, service interactions and other signals into usable knowledge. But automated synthesis is not neutral: every act of compression determines what becomes visible, what disappears and ultimately what institutions come to know. If AI is to strengthen democracy rather than flatten it, AI-assisted listening must meet a higher standard: fidelity to what people actually said, preservation of plurality and disagreement, traceability back to the underlying evidence, contestability by those being represented, and a clear connection between what is heard and consequential decisions.
Two trends are unfolding in parallel around the world. Public anxiety about artificial intelligence is growing while communities’ satisfaction in how they participate in civic activities and contribute to government policy and programs is declining. Pathways to resolve this tension are emerging as governments find ways to use these technologies to help communities participate more meaningfully. Examples from Bogotá, Hamburg, Brazil, Mexico and elsewhere show how AI can improve the quality and experience of public engagement while reducing its time and cost. If done poorly, or without safeguards, it can also introduce new risks. However, these can be managed with appropriate process design, regulation and delivery by skilled practitioners.
Mississippi has released its statewide AI framework. The harder challenge is turning guidance into practice. Drawing on firsthand experience leading the state’s AI workforce efforts, Dr. Kollin Napier of MAIN examines why successful AI adoption depends on sustained investment in training, governance, staffing, and implementation.
AI adoption in government is accelerating. The next challenge is making sure it creates public value. InnovateUS’s Fall 2026 Live Learning Series explores how public professionals can move beyond using AI to measuring its impact, governing it responsibly, and ensuring it improves outcomes for the people and communities government serves.
This excerpt from Reboot: AI and the Race to Save Democracy was originally published in Fast Company on June 25, 2026.
A new report from the Canadian Anti-Monopoly Project argues that cloud sovereignty is about more than building domestic alternatives. It is about ensuring governments, businesses, and public institutions have autonomy and agency. Using Canada’s highly concentrated cloud market as a case study, the authors explore how procurement policy, competition rules, and interoperability standards could reduce dependence on hyperscalers and create a more competitive marketplace for compute.
A new AI for Impact-engineered public engagement coach is helping public servants turn what they learned about engagement into practical action. Built by The GovLab, the tool guides practitioners through real planning decisions, asks targeted questions about their specific project, and draws on engagement frameworks, case studies, and practitioner expertise to help them design more effective public participation processes.
A new accelerator in Barcelona is exploring what it takes to prepare future leaders to navigate the emerging field of public-interest AI. The experience underscored that moving from principles to practice demands leaders who understand the technical, political, economic, and ethical dimensions of AI. Leaders who are equipped to ensure these technologies serve public goals, protect rights, and respond to the needs of diverse communities.
What happens when the people working closest to families are forced to confront AI? In this conversation with Elana Banin, journalist Anya Kamenetz reflects on a three-day workshop that brought together service providers, advocates, technologists, policymakers, journalists, and philanthropists to wrestle with that question. The discussion explores why families have been largely absent from AI governance debates, how to shape the trajectory of technological change, and what it would take to build AI with communities rather than for them.
As AI transforms how we work, learn, and govern, what role should universities play? In this wide-ranging conversation, Beth Noveck argues that universities should become laboratories for democratic problem-solving, where students work with communities to address public challenges. She outlines a vision for "democratic AI" that puts public purpose, participation, and impact at the center of technological innovation.
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