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.

Political Watch’s “What Our Representatives Do” tool (QHLD) organizes thousands of congressional initiatives into clear, searchable themes, making political priorities visible, comparable, and actionable. By exposing imbalances like the 198 initiatives on squatting versus just 54 on social housing, QHLD shows how structured, understandable data can reconnect citizens with their representatives. Yet the project also highlights a global challenge for civic tech: limited funding, slow adoption, and the high cost of responsible AI integration. Making democracy legible is possible, but only if we invest in tools designed to share power, not just document it.

The Solving Public Problems course has helped learners worldwide tackle complex challenges. The course teaches how to leverage technology, data, and collective wisdom in our communities to design powerful solutions to contemporary problems. Now, Beth Simone Noveck is exploring how to remake it for the AI era, using technology to make problem-solving skills easier to learn without losing the human connection at its core. Your input is needed!

Princeton’s Mihir Kshirsagar breaks down why predictive-policing algorithms fail and how to distinguish meaningful diagnostic tools from misguided prediction products. Congress renews its push to bloc

In late October, the Roux Institute hosted Foundations for the Digital Commons with Bernstein Shur and RadicalxChange, convening technologists, policymakers, civic innovators, journalists, and funders to chart a path for renewing the digital systems that underpin democratic life. Over two days, participants examined practical models, from information flows and large-scale deliberation to data governance, while outlining actionable pathways for building modern digital infrastructure. Held in Maine, a state defined by democratic reforms and pragmatic problem-solving, the gathering reinforced a central insight that institutional design, more than technology, will determine whether digital innovation ultimately strengthens public trust.

AI agents are beginning to make market-shaping decisions. Hadfield and Koh’s new study reveals why this shift is significant. Current agents do not reason like economists, do not reflect human preferences, and do not fit into accountability structures. As governments experiment with agents in benefits, procurement, and infrastructure, Elana Banin reflects on the policy challenge of re-designing the rules before agents erode the market foundations on which democratic governance relies.