Dave Cole, New Jersey’s Chief Innovation Officer, argues that states now have both the opportunity and the responsibility to build durable public infrastructure for responsible AI. With support from the new Public Benefit Innovation Fund, New Jersey will expand its statewide generative AI platform to develop secure tools to automate enrollments and reduce administrative burden, and rigorously test these solutions across partner agencies. Through open-source code, shared training resources, and cross-government coordination, the state aims to model how AI can meaningfully strengthen service delivery.

Italy has become the first European country to move beyond implementing the EU AI Act and enact its own sovereignty-driven AI law; one that anchors innovation in public oversight, workers’ rights, human accountability, and sector-specific democratic safeguards. The statute challenges the accelerating, corporate-centric governance model emerging in the U.S., yet it also suffers from limited vision, modest investment, and operational ambiguity. Italy may not win a global race for AI supremacy, but it is trying to redefine the terms of that race by insisting that democratic institutions and not commercial imperatives set the boundaries for how AI enters civic life.

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.

In November 2025, global justice leaders met in Madrid for the OECD Roundtable on Equal Access to Justice to examine how systems can adapt to rising demand and rapid technological change. New Jersey’s Public Defender Jennifer Sellitti's experience highlighted that AI can strengthen fairness and access when deployed with clear safeguards and purpose. By building secure tools, improving legal workflows, and shaping statewide standards on transparency and bias, New Jersey is showing how responsible innovation can reinforce trust and improve justice outcomes.

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!

AI is reshaping the workplace faster than public policy can keep up, often in ways that expand corporate power, weaken worker rights, and undermine democratic oversight. But across sectors, workers and unions are showing that this trajectory isn’t inevitable. Through collective bargaining, policy advocacy, and new uses of AI for organizing, they’re securing real guardrails on surveillance, algorithmic management, and job displacement. This piece explores how worker power will determine whether AI serves people or replaces them.

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.

This essay argues that predictive policing continues to fail not because police departments lack data, but because they are using the wrong kind of data, in the wrong way. Applying low-stakes commercial algorithms to high-stakes decisions can produce dangerous false positives, reinforce biased patterns, and erode public trust in policing. Using examples from Plainfield, NJ, and Chicago, the piece illustrates how predictive systems replicate past police behavior rather than accurately forecasting crime, thereby creating self-reinforcing feedback loops. It contrasts these failures with diagnostic approaches in Oakland and Richmond that utilize data to understand harm, guide outreach, and reduce violence without relying on algorithmic surveillance. The core argument is that policing needs better mirrors, not crystal balls.

Today, we are pleased to share the ranked Top 10 Priority Questions for Women’s Health. These questions reflect a broad global consensus on the areas where innovation, funding, and research can generate the greatest impact, spanning reproductive health, chronic disease, mental health, aging, equity, and the structural barriers that continue to limit women’s access to high-quality care.

When refugees needed language support, Tarjimly turned everyday volunteers into lifelines. In this reflection, CEO Atif Javed traces how the platform evolved from a Facebook Messenger experiment into a global translation network, one now partially powered by AI. His key lesson is that designing for trust means using technology to amplify, not replace, human empathy in moments of crisis.

The Air Force is quietly auctioning off slices of its bases for private AI data centers. They call it innovation; it looks like privatization. Fifty-year leases, 3,000 acres of military land, and no public say. If this is how we build the future, who’s really in command?

When Brazil's federal government launched its 2023 Participatory Pluriannual Plan, the response was massive: 1.4 million participants submitted over 8,200 proposals through the Brasil Participativo platform. But volume creates a challenge, as manually processing thousands of contributions is slow and resource-intensive, often causing valuable insights to slip through the cracks. Now, Brazil is pioneering an open-source AI system that automatically analyzes citizen feedback, generates comprehensive reports, and tracks which suggestions made it into final policies. The result is a new model for democratic intelligence, one that transforms the flood of public input into structured, actionable knowledge without losing the nuance of individual voices.

The Agentic State is an ambitious and inspiring blueprint for rebuilding government around AI agents that can act and decide autonomously. It powerfully diagnoses real failures in how the public sector designs, delivers, and manages services. While AI is giving us ways to accelerate change, the prescribed cure may be premature: most of what’s broken in government requires organizational reform, not automation.

The danger isn’t that AI will make us dumber—it’s that governments, companies, and schools won’t make us smarter with it. As policymakers stall and corporations automate, the burden of using AI wisely now falls on us. Like shoppers at the fish counter, we need to learn to read the labels—to know what’s safe, what’s risky, and how to choose well.

Public service professionals from across the globe have come together to learn from one another how to use AI to improve governance. From St. Louis cutting hiring times from 12 to 2 months, Hamburg analyzing 11,000 public comments in days, and New Jersey reducing Spanish-language form completion from 4 hours to 25 minutes, it becomes clear that AI works for democracy when we build the foundation first.

As headlines warn of “superintelligent AI” threatening human extinction, a new open letter reignites familiar fears. But beneath the apocalyptic rhetoric lies a deeper problem. The narrative around artificial superintelligence, long embraced by Big Tech, diverts attention from the real and immediate challenges of AI and how our democratic institutions can address them.

After two years of research, the RethinkAI collaborative released Making AI Work for the Public—a comprehensive field review of how U.S. governments adopt AI. Since 2019, over 1,600 AI-related bills have been introduced, but most focus on guardrails, not proactive strategy. Meanwhile, cities are piloting translation tools, engagement platforms, and predictive systems, often led by Chief Information Officers, taking on new strategic roles. The report challenges civic tech’s efficiency-first legacy and proposes a new governance model—ALT: Adapt to anticipate needs, Listen to understand communities, and build Trust through two-way accountability.

Officials in Hamburg had long struggled with the fact that while citizens submitted thousands of comments on planning projects, only a fraction could realistically be read and processed. Making sense of feedback from a single engagement could once occupy five full-time employees for more than a week and chill any desire to do a follow-up conversation. Learn about how Hamburg built its own open source artificial intelligence to make sense of citizen feedback on a scale and speed that was once unimaginable.

Boston became a living laboratory for democratic innovation last week, as two major convenings—the Civic AI Summit at Northeastern and Harvard’s Digital Democracy showcase—brought together leaders reshaping how technology serves the public good. From new tools that open up lawmaking and procurement to partnerships that align city and state AI strategies, Boston’s approach offers a model nationally for how AI can strengthen democracy through human-centered design, transparency, and collaboration.

As states take center stage in shaping how the U.S. adapts to artificial intelligence, their choices will determine not just whether America keeps pace, but whether it thrives. This summer, Princeton University’s Center for Information Technology Policy convened state AI officers, researchers, entrepreneurs, and technologists for “Shaping the Future of AI: A National Gathering for State AI Leaders.” The two-day working conference focused on building practical, responsible frameworks for public-sector AI implementation. New America CEO Anne-Marie Slaughter closed the convening with a wide-ranging keynote that called for public AI infrastructure, trust-based governance, and co-creation across sectors. What follows is a summary of her 10 core takeaways.

New York City has thousands of parks, plazas, and public courtyards, but no easy way to find them. Using “vibe coding,” open data, and generative AI, one civic technologist built a map of every public space in the five boroughs. This is the story of NYC Public Space, an app that stitches together fragmented government datasets, AI-generated descriptions, and community-sourced updates to make the city’s public realm more visible and usable. It’s also a case study in how AI can help public interest technologists move faster, build smarter, and turn open data into real public value.

In late September, the UN adopted a global AI resolution backed by all 193 Member States, a diplomatic milestone. But one that risks repeating old patterns of top-down governance. The new Reboot Democracy Blog Editor, Elana Banin, argues that legitimacy doesn’t come from declarations, but from grounded, democratic practice. From California to Vietnam, she explores what real AI governance looks like and lays out three strategic tests the UN must pass to matter.

Large Language Models are becoming common tools in the communications toolkit, but not all uses are created equal. In this new post from the AIMES Lab at Northeastern University, John Wihbey and Samantha D’Alonzo offer research-backed guidance on when to use LLMs in the survey pipeline and when to steer clear. The research indicates that AI is a powerful assistant for refining survey questions and testing hypotheses, but a poor substitute for actual human respondents. Drawing on more than 30 academic studies, this piece lays out a practical, hybrid approach to “silicon sampling” that helps practitioners strengthen research integrity without falling for AI’s easy shortcuts.

Today, we release the first version of the Women’s Health Topic Map. The Topic Map is part of 100 Questions initiative under the Gates-funded R&I project, where CEPS and The GovLab  have teamed up to ask: what are the most important questions that could truly advance women’s health innovation?

AI’s biggest breakthroughs were built on public datasets; the next wave should be, too. If governments make data AI-ready and keep access open, we can power tools that explain laws, improve services, and widen participation. In return, companies that train on taxpayer data should give back, through open licenses, benchmarks, and capacity that strengthen public institutions.

Law professor and political commentator José Luis Martí argues that Spain’s Supreme Court ruling on Bosco is a democratic milestone—establishing algorithmic transparency as a constitutional principle and putting AI at the service of democracy.

In today’s geopolitical environment with 61 active conflicts around the world, the need for PeaceTech has never been more critical.

Co-designed with parents, the AIEP tool is both a technical solution and a catalyst for civic power for families of children with diverse abilities. By building AI literacy through in-person training and WhatsApp-based courses, the project offers a model for community-centered technology, making education systems more navigable and equitable. AI tools can open doors to access and advocacy, but it’s human connection and support networks that give those tools meaning. That is where the most powerful change is taking shape, and where investment matters most.

In this post, we highlight five recent additions to the repository that exemplify the diversity and innovation of AI Localism. These examples—spanning Reykjavík to Manchester—show how local governments are using distinct mechanisms such as risk-tiered staff guidelines, bright-line safeguards in high-risk domains, procurement nudges, AI-assisted public deliberation, and community literacy roadshows to build more responsive, inclusive, and future-proof approaches to AI.

Over the first two sessions of Reboot Democracy: Designing Democratic Engagement for the AI Era, we’ve explored why participation too often falls short, and how to make it matter. From rebuilding the link between voice and implementation, to matching digital tools with public purpose, this early reflection captures key lessons so far and tees up what’s next: a practical, nine-step framework for smarter, AI-supported engagement.

The New York City subway would never accept an ad for a hitman-for-hire service, or for a pill that claimed to cure depression but wasn’t FDA-approved, or a social network designed exclusively to groom minors. Those would be illegal, unethical—and obviously dangerous. So why is the MTA running a massive ad campaign for friend.com, a product that, if not already illegal, certainly should be?

The State of Open Data Policy Summit is an annual conference hosted by the Open Data Policy Lab (a collaboration between The GovLab and Microsoft) to explore how policy and technology shape access to data for public interest re-use. 

In past years, the summit has looked at ways institutions have pursued purpose-driven data re-use and operationalized collaborative governance models. It has also examined the possible challenges represented by a “data winter”—a period marked by reduced data access.

On 4 September 2025, the Open Data Policy Lab hosted its Fourth Annual State of Open Data Policy Summit to focus on how generative AI and open data intersect.

Choosing a digital participation platform is a governance choice. Dane Gambrell's latest post explores what the new Guide to Digital Participation Platforms gets right, the idea that participation only works when tools are matched to purpose, capacity, and follow-through. Join us tomorrow, September 24 at 3pm ET, for a hands-on InnovateUS workshop with Greta Ríos and Nikhil Kumar to learn how to select the right tool for the job to apply AI to advance democracy.

Seoul showed 25 years ago that transparency and accountability built into digital systems can blunt corruption. Albania’s chatbot minister will stand or fall on the same test: whether it reduces opportunities for bribery.

Agueda Quiroga (InnovateUS) and Sarah Hubbard (Allen Lab) reflect on insights from the Reboot Democracy workshop series with Beth Noveck and Danielle Allen, and why 21st-century democracy needs better ways to connect citizen input to real outcomes. Their takeaway is that by repairing the broken links between voice, decision-making, and implementation, participation can shift from symbolic to systematic.

A new national survey finds that Americans overwhelmingly believe AI will diminish key human capacities, like empathy, deep thinking, and personal agency, by 2035. Writing for the Reboot Democracy Blog, Lee Rainie, Director, Imagining the Digital Future Center, explains why this skepticism poses a threat to the foundations of democratic life and calls for AI systems that reinforce dignity, trust, and civic strength.

Law enforcement agencies are under pressure to explore AI, but the real lesson is to treat it like any other power tool. In a recent workshop, Rutgers Senior Fellow Mark Genatempo stressed that AI should support, not replace, human decision-making. From distinguishing between machine learning, predictive analytics, and generative AI, to auditing data and building community trust, the key is preparation, oversight, and transparency. With the right training and safeguards, AI can enhance public safety without undermining accountability.

With its new 2025 AI policy, New Jersey has advanced from interim guidance that encouraged experimentation to a framework that enables safe, large-scale use. Building on two years of training and adoption by more than 15,000 public servants, the state is now focused on using AI not just to streamline work, but to deliver better services where it matters most.

The concept of digital twins has quickly become the new darling of the smart city world. By 2030, more than 500 cities plan to launch some kind of digital twin platform, often wrapped in dazzling promises: immersive 3D models of entire neighborhoods, holographic maps of traffic flows, real-time dashboards of carbon emissions. These visuals capture headlines and the political imagination. But beneath the glossy graphics lies a harder question: what actually makes a digital twin useful, trustworthy, and sustainable?

Having recently worked directly on a U.S. metropolitan digital twin pilot, we know the answer is not just shiny and sophisticated imagery. A genuine twin is a living ecosystem of different stakeholders and diverse datasets — integrating maps, open government data, IoT sensors, predictive AI models, synthetic data, and mobility data into a single responsive platform. Done right, a digital twin becomes a decision-making sandbox: where planners can simulate how pedestrianizing a street shifts congestion, for example, or how a Category 3 hurricane might inundate vulnerable neighborhoods.

While the West races toward artificial general intelligence, Vietnam is charting a different path with “Applied AI", using tools like ChatGPT to overcome language barriers, limited budgets, and institutional bottlenecks. At the Academy of Public Administration and Governance in Vietnam, civil servants are building AI literacy and shifting to adaptive, tech-savvy governance. With 136 AI-assisted case studies developed in one summer, a new handbook on AI for development, and plans for an AI-powered support chatbot, Vietnam shows how even modest experiments can spark a culture of curiosity, collaboration, and public sector transformation.

A report on a recent workshop cohosted by RAND, the Stimson Center, and the Tony Blair Institute for Global Change explores how AI can support more effective policymaking. AI shows promise for automating routine tasks and democratizing access to analysis tools, but there are significant structural barriers to realizing AI's potential in policymaking. To move forward, we need more real-world case studies of AI use in governance and strategic adoption focused on maintaining human oversight and building the skills to deploy these tools responsibly.

Public engagement has long been too time-consuming and costly for governments to sustain, but AI offers tools to make participation more systematic and impactful. Our new Reboot Democracy Workshop Series replaces lectures with hands-on sessions that teach the practical “how-to’s” of AI-enhanced engagement. Together with leading practitioners and partners at InnovateUS and the Allen Lab at Harvard, we’ll explore how AI can help institutions tap the collective intelligence of our communities more efficiently and effectively.

Non-Traditional Data (NTD) — data digitally captured, mediated, or observed through instruments such as satellites, social media, mobility apps, and wastewater testing — holds immense potential when re-used responsibly for purposes beyond those for which it was originally collected. If combined with traditional sources and guided by strong governance, NTD can generate entirely new forms of public value — what we call the Third Wave of Open Data.

In this update, we have curated recent advances where researchers and practitioners are using NTD to close monitoring gaps in climate resilience, track migration flows more effectively, support health surveillance, and strengthen urban planning. Their work demonstrates how satellite imagery can provide missing data, how crowdsourced information can enhance equity and resilience, and how AI can extract insights from underused streams.

Join People Powered on September 16 for the release of new guidance based on global case studies for AI for Digital Democracy.

The Center for Public Sector AI has launched a new recognition initiative called The AI 50, which honors people and institutions that are playing important roles in implementing and developing artificial intelligence within government agencies.

Over the last six months, The GovLab’s Open Data Policy Lab has documented use cases of data commons—collectively governed data ecosystems—that provide critical infrastructure for responsible AI development around the world. By generating access to high quality, AI-ready datasets, these initiatives are unlocking new possibilities for solving pressing public challenges. Through our Data Commons for Generative AI Repository, we have identified 60 examples of data commons ranging from cultural and language preservation initiatives to biomedical imaging archives for cancer research. 

We conducted a quantitative analysis of the full repository (60 use cases) with the goal of understanding trends in existing efforts and where additional support is needed. Below we provide a summary of these trends. However, it is important to note that our search for data commons was conducted in English and likely excludes examples from countries where most initiatives are in non-English languages.

Data commons (collaboratively governed data ecosystems) are providing critical infrastructure in the age of AI. When designed responsibly, they can help provide access to high quality, AI-ready datasets for use in the public interest. Yet: What data commons currently exist? Where are they being developed? What data commons are needed most?

Over the last six months, The GovLab’s Open Data Policy Lab (ODPL) has sought to answer these questions by curating and documenting examples of data commons for AI from across the globe. Our Data Commons for Generative AI Repository now contains 60 real-world examples from over 20 countries across 5 continents. 

Global declarations on AI governance abound—but the real test lies in implementation, much of which is unfolding in cities. Yet local initiatives are rarely monitored or shared across jurisdictions. The AI Localism Repository aims to bridge that gap by spotlighting governance mechanisms developed at the city level.

In this post, we highlight six recent additions to the repository that exemplify the diversity and innovation of AI Localism or city-level AI governance.

Artificial intelligence can transform evidence-based policymaking by enabling policymakers to cast a wider net for evidence, synthesize evidence more rapidly, and incorporate better and deeper engagement with communities. However, this transformation also presents significant challenges from bias and transparency concerns to the risk of over-reliance on algorithmic outputs. By understanding the promise and the pitfalls of AI-enabled research tools, while keeping human expertise at the center of the process, we can harness these powerful tools to serve the public interest while preserving the democratic values of transparency, accountability, and inclusive governance.

How are governments and researchers using generative AI to make better use of open data? In what ways can AI help make public information more accessible, interpretable, or actionable? And what new types of public services or research tools are emerging at this intersection?

These are some of the questions explored in our Observatory of Open Data and Generative AI —a growing collection of real-world use cases showing how open data from official sources is being used with generative AI technologies.

Launched last year, the Observatory builds on the findings of our report, "A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI.” 

A new Code for America assessment looks at how states are adopting artificial intelligence to support the design, delivery, and evaluation of public services. While most states remain in early development stages, the three leading states distinguished themselves by building comprehensive governance frameworks, investing in workforce training, and establishing dedicated leadership structures to support the responsible and effective use of AI.

HEKA, the Highway Engineer Knowledge Agent chatbot created through the AI for Impact co-op program is empowering design engineers in the MassDOT Highway Division to efficiently query department manuals and documentation, aiding in the design of quicker and safer infrastructure projects for commuters in Massachusetts. It was recently highlighted by NBC 10 Boston.

The 2025 Europe edition of the Data for Policy conference, held 12–13 June at Leiden University in The Hague, gathered researchers, policymakers, and practitioners around the theme “Twin Transitions in Data and Policy for a Sustainable and Inclusive Future.” Over two days of presentations and discussion, participants explored how data systems and digital technologies are reshaping governance and what it will take to make them serve climate goals, social equity, and democratic accountability.

New research from the UK Gov shows how AI could make it easier for institutions to do public engagement. A new process called "Consult" combined AI with human oversight to analyze public consultation responses with 76% accuracy in seconds.

While Washington fights over who gets to say "no" to AI, they're missing the bigger question: how can we actually use these tools to fix our broken institutions? States like Ohio and New Jersey are already proving AI's transformative potential—cutting millions in bureaucratic waste, speeding up citizen services, and making government actually work for people. The real debate shouldn't be about regulation versus innovation, but about the AI we need to build, buy, and design to strengthen democracy.

How can we build and sustain data commons that balance openness, and trust, while fueling innovation for the public good? Can they ensure that communities and other networks have a say in how their data is used? Can they ensure that public interest organizations can get access to the data they need to meet societal challenges?

In “Data Commons for the Public Good,” the Open Data Policy Lab’s fourth panel on the Fourth Wave of Open Data, Vivienne Ming (Chief Scientist, The Human Trust), Angie Raymond (Director of Data Management and Information Governance, Ostrom Workshop), Heather Coates (Data Steward & Data Librarian,  Indiana University), and Alek Tarkowski (Director of Strategy, Open Future) joined The GovLab’s Stefaan Verhulst to answer these questions. 

Last week, we closed applications for our New Commons Challenge—an open innovation challenge seeking to foster the use of data commons for the development of AI for local decision-making and humanitarian response.

Civic trust is essential for strong, functional communities and effective governments. It gives institutions the license to operate. It allows people to form relationships within their communities.

However, trust is also abstract and little understood. It is difficult to define and even more difficult to quantify. For city leaders, this presents a conundrum: How can they act to improve civic trust if they don’t fully understand what it looks like?

The GovLab and the  Centre for European Policy Studies (CEPS), with support from The Gates Foundation, are pleased to announce the launch of a new domain within The 100 Questions Initiative: Women’s Health Innovation. The 100 Questions Initiative seeks to identify and prioritize the most pressing, data-actionable questions that can advance evidence-based policy making, and research on societal issues.

This week’s Research Radar highlights The Agentic State, an ambitious whitepaper arguing that AI agents could reshape the core functions of government. It’s a timely vision for public sector transformation —worth reading, debating, and building on.

We are developing "Civic and Democratic AI," an 8-part WhatsApp course that teaches people how to use generative AI to navigate government processes, understand complex documents, and organize for community action. The course aims to provide practical AI skills for civic engagement. We are seeking feedback on the course content. Share your insights and expertise as we roll out this free program to help communities use AI to understand their government, access their rights, and organize for change.

As artificial intelligence systems become more reliant on data from low- and middle-income countries (LMICs), fundamental questions arise about who controls that data and who benefits from its use and reuse. In many cases, the people and communities who generate this data have little say in how it’s used, and few mechanisms for recourse when harms occur.

To address these challenges, The GovLab and Agence Française de Développement (AFD) have partnered on a new project exploring more equitable, participatory approaches to data governance in AI ecosystems. Today, we are pleased to release the outcome of that collaboration: Reimagining Data Governance for AI: Operationalizing Social Licensing for Data Reuse.

The Fourth Wave of Open Data, based around the combination of open data and generative AI, offers significant potential. When put together, open datasets can be made more open and conversational. Systems themselves can be better trained to answer questions.

The Open Data Policy Lab’s Observatory of Examples of How Open Data and Generative AI Intersect provides real-world use cases of how open data from official sources intersects with generative artificial intelligence (AI), building on insights from our report, A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI.

$200,000 in funding available for innovative data commons that enhance local decision-making and disaster response

Non-Traditional Data (NTD)—digitally captured, mediated, or observed data such as mobile phone records, online transactions, or satellite imagery—is reshaping how we identify, understand, and respond to public interest challenges. As part of the Third Wave of Open Data, these often privately held datasets are being responsibly re-used through new governance models and cross-sector collaboration to generate public value at scale.

This update profiles recent initiatives that push the boundaries of what NTD can do. Together, they highlight the evolving domains where this type of data is helping to surface hidden inequities, improve decision-making, and build more responsive systems.

The GovLab with the support of the Wellcome Trust Discovery Research team is beginning a new initiative called Social Data 4 Health. The initiative aims to understand how these new forms of social data can transform health-related research in the humanities, social sciences, and public health domains.

In today’s rapidly evolving AI landscape, it is critical to broaden access to diverse and high-quality data to ensure that AI applications can serve all communities equitably. Yet, we are on the brink of a potential “data winter,” where valuable data assets that could drive public good are increasingly locked away or inaccessible.

Data commons — collaboratively governed ecosystems that enable responsible sharing of diverse datasets across sectors — offer a promising solution. By pooling data under clear standards and shared governance, data commons can unlock the potential of AI for public benefit while ensuring that its development reflects the diversity of experiences and needs across society.

To accelerate the creation of data commons, The Open Data Policy, today, releases “A Blueprint to Unlock New Data Commons for AI” — a guide on how to steward data to create data commons that enable public-interest AI use cases.

Generative AI tools have attracted enormous attention. Yet, questions remain about how it intersects with open data. How can generative AI help people better engage with open data? How can open data be used to enable societal beneficial use cases of generative AI? How can we address the many risks and challenges facing these systems?

On February 11, 2025, The Governance Lab (The GovLab) and Urban AI co-hosted an official side event of the Paris AI Action Summit, titled "Aligning Urban AI and Global AI Governance." Held in collaboration with Mouvement des Entreprises de France (MEDEF), Open Data France, DemocracyNext, and UN-Habitat, the event brought together policymakers, researchers, and city representatives to discuss how urban AI initiatives can align with broader governance frameworks to ensure responsible and inclusive AI deployment. 

Over the last year, the Open Data Policy Lab (a collaboration between The GovLab and Microsoft) has been exploring how to harness artificial intelligence responsibly and effectively as part of its work on Fourth Wave of Open Data, an approach to data openness that explores intersections between open data from official sources and generative AI.

The way to unlock data responsibly for this fourth wave, we believe, lies with data commons—collaboratively governed data ecosystems designed to pool and provide responsible access to diverse, high-quality datasets across sectors. 

The Technology Modernization Fund (TMF) currently funds multiyear technology projects to help agencies improve their service delivery. However, many agencies abdicate responsibility for project outcomes to vendors, lacking the internal leadership and project development teams necessary to apply a product model approach focused on user needs, starting small, learning what works, and making adjustments as needed. 

Why responsible data stewardship could help addressing today’s pressing environmental challenges resulting from artificial intelligence and other data-related technologies.

Today, we're excited to announce the launch of the newly updated AI Localism Repository—a curated resource designed to help local governments, researchers, and citizens understand how AI is being governed at the state, city, or community level.

This week, The GovLab and the Burnes Center for Social Change published two new resources aimed at leveraging the power of artificial intelligence and collective intelligence to tackle pressing public challenges. 

In the Open Data Policy Lab's new report, the team provides a framework and recommendations to support open data providers and other interested parties in making open data “ready” for generative AI.

On April 17, 2024, during AI Week, The GovLab and UrbanAI hosted a webinar on AI localism, titled "Empowering Communities through Digital Self-Determination". The session aimed at investigating how AI governance can be localized to better serve community-specific needs.

Hannah Garden-Monheit, Director of the Office of Policy Planning of the Federal Trade Commission (FTC) talks with Seth Harris on the Power at Work Blog about the FTC's new rule banning almost all non-compete agreements in employment relationships. 

To increase civic trust, we need to know what we mean by it and how to measure it, which turns out to be a challenging exercise. Toward that end, The GovLab at New York University and the New York Civic Engagement Commission joined forces to catalogue and identify methodologies to quantify and understand the nuances of civic trust. 

From 29 to 31 January 2024, UNICEF and UNHCR and The Governance Lab at New York University hosted three 90-minute webinars on ways they can support the well-being of children through data, highlighting the ways development and humanitarian practitioners around the world can reinforce data responsibility principles and practices in their daily work with and for children.

Join us for a book talk with Urs Gasser as he delves into his latest work, "Guardrails." In this talk, Gasser will explore the ways in which societal norms shape our decision-making processes in an era saturated with data and dominated by rapidly advancing technologies like artificial intelligence. 

From 29 to 31 January 2024, UNICEF and UNHCR and The Governance Lab at New York University (The GovLab) will host three 90-minute webinars to inform humanitarian practitioners around the world of ways they can reinforce data responsibility principles and practices in their daily work...

Welcome to our end of year 5 x 5 curation of books published in 2023: five books across five domains! 

Every week, the Living Library, and its newsletter The Digest, curate the most up-to-date knowledge on governance and data innovation.  As we bid farewell to 2023, we took a moment to select five books across five domains (5X5).

On Thursday, November 16, the Burnes Center for Social Change and the GovLab hosted Sir Geoff Mulgan,  Professor of Collective Intelligence, Public Policy and Social Innovation at University College London (UCL), for a thought-provoking lecture on “Combining Human and Machine Intelligence to Enhance Democracy” as part of the "Rebooting Democracy in the Age of AI" series. Mulgan discussed the challenges facing contemporary democracies and proposed innovative solutions to steer them into a more responsive and effective future.

In the latest episode of The GovLab's Collective Intelligence Podcast,  Prateek Buch and Brendan Arnold from the UK Government's Policy Lab and its innovative Collective Intelligence Lab are interviewed by Beth Simone Noveck, Director of the GovLab and the Burnes Center for Social Change. Prateek, a renowned advocate for responsible technology use, and Brendan, the government's first Creative Technologist, shed light on their work leveraging technology to engage UK residents and address policy challenges.

In an interview with Raven Santana on NJ Biz Beat, we discussed the creation of New Jersey's AI Task Force, focusing on the responsible use of generative AI to improve government, create new jobs and advance literacy and equity, and how to balance the benefits and the risks.

The cautious yet optimistic adoption of these technologies by cities like Boston, and states like New Jersey and California, signals a significant shift in the public sector landscape.

The journey from skepticism to the beginnings of strategic implementation reflects a growing recognition of the transformative potential of AI for public good. From enhancing public engagement through sentiment analysis and accessibility to optimizing government operations and cybersecurity, generative AI is not just an auxiliary tool but a catalyst for a more efficient, inclusive, and responsive government.

Embracing the same responsible experimentation approach taken in Boston and New Jersey and expanding on the examples in those interim policies, this November, the State of California, issued an Executive Order and a lengthy but clearly-written report, enumerating potential benefits from the use of generative AI.

In the rapidly evolving technological landscape of the 21st century, the role of government in serving its citizens is undergoing a profound transformation. Emerging technologies, particularly Artificial Intelligence (AI), have become integral tools that everyone, including  public servants, will need to leverage in order to improve efficiencies across business and government alike. Recognizing the urgency of this moment, President Biden's Executive Order on Artificial Intelligence has underscored the opportunity ahead of us: to train public servants in the responsible use of AI to best be able to service their constituents using top of the line technology.

Artificial Intelligence (AI) is not just transforming economies and industries; it holds the key to revolutionizing public engagement with the federal government.

At almost 20,000 words, President Biden’s behemoth executive order on AI mandates a laundry list of actions from federal departments and agencies.  While there’s a lot to like here, we have to ask: are we focusing so much on the risks that we are failing to invest in and maximize the potential for AI to do good? 

Google.org is providing $2 million in funding and pro bono support to InnovateUS to help them provide digital skills training to public sector employees.

The term “data collaborative” refers to a new form of collaboration, beyond the public–private partnership model, in which participants from different sectors ,  in particular companies in the private sector, exchange their data to create public value. In this sense, data collaboratives are emerging as a powerful tool to enable data flows and unleash the full potential of data in addressing societal challenges. However, designing and implementing effective data collaboratives can be complex and challenging.