In Part II, we examine the project’s core claim that AI agents could represent citizens in democratic deliberation. We argue that representation requires more than predicting preferences, that democratic participation is essential to civic learning and self-government, and that increasingly capable AI agents risk shifting authority away from citizens and toward algorithms. Democracy depends on people governing together, not on delegating judgment to machines.

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.

Seven Signals Shaping the Future of Data Access and Reuse

The Data Tank and The GovLab, in a call hosted by Stefaan Verhulst, organized the second Data Stewardship Trends to Watch session for 2026. The Trends to Watch series brings together our global Data Stewards alumni every two months to explore and discuss the latest developments shaping the data stewardship landscape. From the value of data and digital sovereignty to licensing regimes that could unlock data's untapped potential, the June session offered a vivid reminder of just how dynamic, complex, and crucial the data stewardship ecosystem has become.

The Incubator is a capacity-building initiative that provides mentorship, training, technical guidance, and proposal development support.

The Incubator is a capacity-building initiative that provides mentorship, training, technical guidance, and proposal development support. Participants will receive an in-person opportunity to collaborate and network with other participants...

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.

Beth Simone Noveck and José Marti critique Habermolt, an experimental project that uses AI agents to deliberate and vote on behalf of people. They argue that the project reflects a longstanding strain of democratic theory that views public participation as a problem rather than a resource. At a moment of declining trust and growing institutional challenges, there should be less focus on whether AI can simulate democracy and more on how it can help governments listen, learn, and solve problems with the public. This Essay is Part 1 of 2 by Noveck and Martí.

Beth Simone Noveck recently appeared on the Brookings TechTank podcast to discuss her forthcoming book, Reboot: AI and the Race to Save Democracy (Yale University Press), arguing that AI offers powerful opportunities to strengthen democratic institutions and making the case for a "possibilist" approach to building tools that make democracy more responsive and effective.

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.

Beth Simone Noveck spoke to The Herald (Scotland) about the role of AI in education and the need for decision-makers to engage with the technology rather than fear it, ahead of her talk at the Edinburgh Futures Institute's Civic University – Democracy, AI, and the Public Imagination."

Billions of people are about to watch the World Cup. And millions of them will spend part of it furious, not at the teams, but at football's most contentious technology: the Video Assistant Referee. In this article, Anirudh Dinesh argues we are making the same mistake in how we design, build, and use AI, and shares four lessons VAR can teach us about what happens when you build tech without asking who it's actually meant for.

Local government generates enormous amounts of public knowledge, but much of it remains buried in disconnected PDFs and difficult-to-navigate archives. This post explores how the Block Party team used AI, semantic search, and human expertise to build a searchable archive of 17 years of Manhattan Community Board 3 resolutions, making local government decisions, institutional memory, and civic participation more accessible to residents, journalists, and public officials.

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.

In this interview with Cool Science Radio, Beth Simone Noveck discusses the central argument of her new book, Reboot: AI and the Race to Save Democracy, that AI is not simply a threat to democracy but a tool that can help make governments more effective, responsive, and participatory. Drawing on examples from around the world, she explores how AI can improve public services, strengthen civic engagement, and rebuild trust in democratic institutions.

Kazakhstan built one of the world’s most advanced digital governments in less than two decades. Now the country is racing into the next phase: AI-enabled governance, sovereign AI infrastructure, and nationwide AI deployment. But this transition is exposing a harder question beneath the ambition: what happens when countries move toward frontier AI systems before large parts of the population have reliable electricity, affordable internet, laptops, or the skills needed to use AI meaningfully?

AI data centers are arriving in communities long before most public institutions have figured out how to govern them. Drawing on recent analysis, fieldwork, and an InnovateUS workshop, Deborah Stine examines the questions public officials are now confronting around electricity, water, jobs, infrastructure, public trust, and community impact. She argues that AI data centers are far more than technology projects; they are major public policy decisions that will shape how communities experience the AI economy.

Ahead of a timely conversation around the civic role of the university in an age of democratic uncertainty and rapid technological change, Beth Simone Noveck spoke to the Scotsman about how Scotland's universities are uniquely place to reinvent the purpose of higher education.

Public servants are asking for leadership training at the same moment AI is reshaping government work. This reflection on InnovateUS’s Foundations of Leadership workshop series explores why the most important leadership challenges today are often deeply human ones: creating psychological safety, building real teams instead of loose groups, giving honest feedback, understanding strengths, and helping people perform under pressure and uncertainty. Across five sessions, participants wrestled with the gap between knowing what good leadership looks like and consistently practicing it within real organizations.

This article highlights a number of emerging warning signs and recurring challenges around hantavirus that deserve more serious attention.

Mariana Becerra of the Eleanor Crook Foundation went to the Rockefeller Foundation’s Bellagio Center expecting a conversation about AI and geopolitical competition with bipartisan, bicameral members of Congress. She came back convinced that AI is already reshaping how public health systems function, how advocacy operates, and which organizations will have the capacity to influence policy. Drawing on conversations with lawmakers, researchers, and philanthropy leaders, this piece examines the growing gap between where AI governance debates are happening and the resulting consequences.

AI for Impact Fellows Sai Punith Kolla and Swaapnika Chowdary Cherukuru built Public Voice, a lightweight voice-based feedback tool designed to capture concrete examples of how learners apply AI in practice. The piece explores the design challenge behind the tool, why voice responses may produce richer evidence than text surveys, and what it means to measure whether public-sector AI training is translating into real workflow change.

As governments rush to regulate AI, many governance frameworks still overlook what happens when people are harmed. This piece argues that AI governance will be tested by legal systems already struggling to deliver equal access to justice. Drawing on the recent report "A People-Centered Justice Approach to Implementing AI Governance," examples from Australia, the Netherlands, and the United States make the case for bringing courts, legal aid organizations, and justice institutions into the center of AI governance design.

Europe has invested heavily in data infrastructure through initiatives like the European Open Science Cloud (EOSC) and the European Health Data Space (EHDS), yet these frameworks remain largely focused on traditional, sector-specific data. This CEPS R&D Perspective argues that non-traditional data — generated by digital platforms, sensors, mobility systems, and consumption patterns — represents a largely untapped resource for health and well-being research. Drawing on evidence from over 290 studies, the note argues that non-traditional data can enable earlier detection of health risks, reveal nutritional and access inequalities, and link environmental exposure to disease outcomes. Grocery transaction records, wearable devices, satellite imagery, and mobility data have each shown measurable value when responsibly linked with conventional datasets. Realising this potential at scale requires addressing persistent barriers: fragmented access, complex data linkage, fragile public trust, and short-term funding cycles. The paper proposes six integrated policy actions — expanding EOSC's mandate, broadening EHDS to cover health determinants, leveraging Horizon Europe for sustainable data reuse, activating DSA Article 40 for platform data access, professionalising data stewardship, and embedding social licence frameworks in governance structures. Together, these measures would transform Europe's data spaces from compliance infrastructure into genuine decision intelligence for health, well-being, and beyond.

As governments search for ways to operationalize AI ethics inside public institutions, Türkiye’s new YAZEK system offers an early example of what procedural AI governance can look like in practice. The piece examines how the Ministry of Education embedded mandatory AI ethics declarations into everyday administrative workflows, while also exploring the system’s limits around verification, oversight, and remedy when automated systems cause harm.

In a new piece for the Rethinking Regulation series, Dane Gambrell examines how San Francisco used a custom AI tool developed with Stanford’s RegLab to scan 16 million words of municipal code and identify hundreds of outdated and duplicative reporting requirements across city government. The effort ultimately produced a 351-page ordinance proposing the deletion or consolidation of 174 mandates. The piece offers a grounded look at how AI can help governments make sprawling bureaucratic systems more legible and manageable.

A reflection from Rob Asaro-Angelo, Senior Fellow at the Burnes Center, from the 2026 Code for America Summit on why optimism in government depends on implementation. Drawing from conversations on procurement reform, service delivery, and AI in the public sector, the piece explores how public servants across the country are turning institutional frustration into practical change and why hope becomes credible when people have the tools, authority, and persistence to make systems work better.

In an article originally published in The Times (Scottish Edition), Beth Simone Noveck argues that AI’s most important democratic use is helping governments listen. Drawing on examples from Camden and Scotland, the piece explores how AI could help public institutions process large-scale public input, strengthen participation, and rebuild trust at a time when governments face rising demand and declining capacity.

In the afterword to Gustavo Maia’s forthcoming book Zero-Click Government, Beth Simone Noveck explores the democratic risks and possibilities of anticipatory governance. While supporting efforts to reduce the administrative burdens placed on citizens, she argues that traditional requests and applications also served as an important democratic feedback signal, one that anticipatory systems risk losing when governments act on inferred demand. Her response examines what kinds of participation, transparency, contestation, and institutional learning are needed if public action is increasingly shaped by data and AI.

In a new piece for Reboot Democracy, Rodrigo Cetina-Presuel, Marco Tello, and Jose M. Martinez-Sierra examine how Ecuador’s judiciary responded to the rapid arrival of AI by building a participatory governance process rooted in the country’s institutional and cultural realities. Through consultations with judicial officials, the process surfaced a critical gap ignored by most international AI frameworks: current AI systems cannot reliably interpret Indigenous languages or legal contexts such as Kichwa. The result was one of the region’s first judicial AI moratoriums, temporarily prohibiting the use of AI in Indigenous-language cases while Ecuador develops more legitimate and locally grounded governance mechanisms for the future.

Congressional information has long been technically public but practically inaccessible, scattered across government sites and locked behind expensive subscription platforms. In response, Zach Florman, Communications Director for Rep. Laura Friedman, created the Capitol Wire tool. The Capitol Wire shows how AI can close that gap by turning floor schedules, bill texts, and legislative updates into real-time alerts and searchable policy briefs that are fast, verifiable, and free. The result is a tool that makes public information more legible for staffers, reporters, and citizens alike, and increases the likelihood of public engagement.

The 2026 CAIDP AI Index, ranking AI policy commitments across 90 countries, shows that while most governments now agree on core governance principles, the real divide lies in implementation. Many are advancing laws, oversight, and public participation, but progress lags in turning commitments into practice. As the baseline shifts from whether to govern AI to how, the report underscores that outcomes depend less on frameworks and more on the capacity of public institutions—and the civil servants within them—to operationalize these principles in everyday decisions.

A new WHO discussion paper explores how AI can accelerate research synthesis and keep evidence continuously up to date. Elana Banin welcomes the push to use AI to strengthen the evidence-to-policy pipeline, but argues the more consequential question is whether AI will redefine what counts as evidence in the first place. The harder constraint will ultimately be institutional, as most health workers lack the training and infrastructure to adopt these tools. Government decision-makers must start building the processes to test AI outputs against frontline knowledge and the capacity to make that adoption defensible.

A high school journalist reflects on who is shaping the public conversation about AI. While headlines focus on risk and disruption, everyday uses of AI are already helping families access benefits, students learn, and cities deliver services. The gap, Amedeo Bettauer argues, is in between those whose experiences count in defining the debate and those in power who seek out diverse experiences.

As the Basque Government moves to pass a new Transparency Law this May, it is redefining what transparency means. No longer just about access to information, the law embeds collaborative governance into its core, requiring that decision-making processes be open, traceable, and shaped with others. This piece explores what it looks like to turn participation from a principle into a legal obligation, and what it takes to make participation a structured, accountable part of how policy is made.

Last week, at Jesus College, Cambridge University, the inaugural cohort of Digital Statecraft Fellows gathered — alongside a diverse group of policymakers, technologists, scholars, and practitioners — to grapple with a deceptively simple yet profound question: how do we govern in the age of AI?

A new entry in our Rethinking Regulation series, this in-depth case study by Dane Gambrell includes an interview with Reeve Bull, who led the state’s regulatory modernization effort. It traces how Virginia used AI to review decades of accumulated rules, cut regulatory requirements by over a third, and make them clearer and more accessible. It shows how governments can pair strong institutional processes with AI to modernize regulation and improve how it works for the public.

A mayor presents a plan, residents push back, and everyone leaves frustrated, not because people weren’t heard, but because listening and engagement happened at the wrong moment. This piece reframes participation as a cycle: listening to set the agenda, engagement to shape decisions, and follow-through to prove input mattered. The example of St. Louis shows how sequencing these stages turns public input into real outcomes, with AI enabling reflection on input at scale.

What happens when governments rely on systems that sound right instead of being right? Drawing on OpenFisca’s spread from France to governments across Europe, Africa, and Oceania, Beth Simone Noveck’s interview with Matti Schneider makes the case for public infrastructure that computes the law, as well as the risks of sidelining it as generative AI scales globally.

Using AI to analyze over 2,400 employee comments, California’s Engaged California team found that the challenge wasn’t the scale of the data, but making sense of complex, layered input without oversimplifying it. Their experience shows why human judgment remains essential, from building taxonomies to catching errors, as results can shift significantly depending on how AI is applied and what people choose to trust and prioritize.

AI governance is expanding fast, but not evenly. A new analysis from MIT and Georgetown’s CSET maps over 1,000 governance documents to show that while policies are proliferating, they cluster around familiar risks and sectors, leaving key gaps across socioeconomic impacts, upstream design, and everyday domains. The result, as relayed by research member Yan Zhu, is a more precise picture of what AI governance actually covers, what it still overlooks, and where policymakers should focus in the future.

The Data Tank in collaboration with Fondazione Cariplo, and as part of the Data Stewards Academy, completed, in the words of participants, a ‘unique’ one-month hybrid Data Stewardship Bootcamp in Milan. The bootcamp brought together and trained 23 participants from across civil society, social enterprises, and local and regional public and non-profit entities. Covering the entire Data Stewards Canvas via a step-by-step approach, the participants worked with several use-cases starting with identifying the demand for data and all the way to measuring impact for data-driven projects or services. The bootcamp combined lectures, including by affiliated guest faculty, with expert-led field visits to data driven institutions active in Milan. With three days in person in Milan and three online sessions, the bootcamp brought together local data and AI voices, but also managed to tap into global ones representing different contexts.

On March 27, as part of NYC Open Data Week, The GovLab, Brooklyn Public Library, and the Alliance for Public Interest Technology at New York University convened a “Questions Lab” to explore how open data can better reflect and respond to the needs of New Yorkers. The session was supported by a group of volunteers and collaborators, including students and faculty from NYU, some of whose reflections on the event are featured below.

Across contexts like India, where author Anirudh Dinesh’s family lives, AI chatbots such as xAI’s Grok are increasingly used not to inform but to generate arguments that reinforce existing political views, creating “generative echo chambers.” Unlike passive social media exposure, users actively prompt AI to validate positions, often producing confident but inaccurate claims that go unchecked. While some research suggests AI can moderate views in neutral dialogue, real-world use skews toward advocacy, compounded by low verification and high trust in outputs. The result is that AI may not just reflect polarization, but actively deepen it, depending on how these systems are designed and used.

More than $1 trillion in federal grants flows to communities each year, but complexity keeps much of it out of reach. This piece by Beth Simone Noveck, published by Fast Company, explores how AI can either deepen that gap or help close it. The solution is GrantWell, a community-centered tool designed with local governments to make funding accessible and public systems work as intended. Launched in Massachusetts and expanding to additional states, it shows how AI can help communities claim the resources already set aside for them.

In “Building a Human Resilience Infrastructure for the AI Age,” based on insights from 386 global experts, a warning emerges: the greatest risk is not a single catastrophic event, but a slow drift toward diminished human agency, fragmented reality, and growing dependence on automated systems. Lee Raine and Janna Anderson reflect on how, as AI becomes society’s invisible operating system, individual resilience is no longer enough. The report argues for urgent, coordinated action to build resilience as shared infrastructure across governments, institutions, and communities to ensure people can still question, contest, and shape the systems increasingly shaping them.

The AI Index Report 2026, released this week by Stanford HAI, offers a compelling portrait of what can only be described as an ongoing AI Summer. The indicators are striking: rapid adoption reaching more than half the population within three years, surging investment, near-human performance across multiple domains, and widespread deployment in science, medicine, and the economy. By nearly every conventional metric — capability, capital, and diffusion — AI is accelerating.  Image copyrights: Picture by Deborah Lupton / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/

Developed by the International Training Centre of the International Labour Organization with and for employer organizations, ReguLens responds to a growing policy bottleneck. The rapid surge in complex, overlapping regulations is outpacing institutional capacity. Built through iterative co-creation with users across regions, the tool helps organizations analyze proposals, identify impacts, and engage earlier in policy debates.

Stefaan Verhulst and Adam Zable argue that the biggest challenge in open data is no longer access, but usability, as official statistics remain difficult to find, interpret, and apply. Drawing on the International Monetary Fund’s StatGPT new research, it shows how artificial intelligence could transform access through natural language interfaces, while warning that accuracy and trust depend on retrieving authoritative data rather than generating answers. The article situates this shift within a broader “Fourth Wave of Open Data,” calling for new data systems and governance approaches that make information truly usable and reliable.

Stefaan Verhulst and Adam Zable argue that the biggest challenge in open data is no longer access, but usability, as official statistics remain difficult to find, interpret, and apply. Drawing on the International Monetary Fund’s StatGPT new research, it shows how artificial intelligence could transform access through natural language interfaces, while warning that accuracy and trust depend on retrieving authoritative data rather than generating answers. The article situates this shift within a broader “Fourth Wave of Open Data,” calling for new data systems and governance approaches that make information truly usable and reliable.

As artificial intelligence systems rapidly evolve and start to impact nearly every sector of society, the conversation around governance has mainly focused on models (and their output): their transparency, fairness, accountability, and alignment. Yet this focus, while necessary, is incomplete. AI systems are only as reliable, equitable, and effective as the data (input) on which they are trained and operate.

This piece by John Wihbey and Jill Abramson distills lessons from the InnovateUS Amplify workshop series, where public-sector communicators grappled with how AI is reshaping their work amid declining public trust. Across sessions, we learn that AI can accelerate research, synthesis, and storytelling, but it cannot replace judgment, verification, or institutional values. As communicators adopt new tools, the opportunity lies in using AI to strengthen transparency, credibility, and connection with the public, rather than erode them.

Following the success of a 1,200-person pilot across eight state agencies, New York is scaling InnovateUS' AI training initiative to more than 100,000 state employees, the largest program of its kind in the nation. Read the NYS press release detailing the expansion, which focuses on helping public servants build the skills and knowledge to responsibly use emerging technologies for the public good.

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.

AI agents are reshaping how systems operate across sectors. This piece argues that the imminent challenge to address is autonomy, including how agents act, interact, and scale in open environments. It outlines a three-part blueprint for governments to build trust infrastructure, prepare for multi-agent risks, and develop the institutional capacity needed to govern an increasingly agentic world.

On March 2026, we organized our bi-monthly 'Data Stewardship Trends to Watch' session exclusively for our data stewardship alumni community, made available to the general public.

In what follows we highlight several examples of PeaceTech launched or updated in 2025 and explain how they are being applied before, during, and after a conflict. We conclude with cross-cutting takeaways across these examples.

Artificial intelligence (AI) is becoming more integrated into scientific research, shaping how knowledge is produced, how research is conducted, and which questions are formulated and prioritized. Across these readings, AI appears as both a tool that can support speeding up tasks such as data analysis, hypothesis generation, and experiment design, and as a force that is influencing research practices, incentives, and areas of focus. This edition of selected readings show that while AI can increase the speed and scale of research, it also raises questions about how knowledge is developed, how scientific work is evaluated, and how reliance on AI may affect learning, diversity of ideas, and long-term scientific progress.

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.

The Healey-Driscoll Administration has launched GrantWell, a free AI-powered tool developed with Northeastern University’s Burnes Center for Social Change to help municipalities more easily access and apply for federal and state funding. GrantWell helps you summarize complex grant requirements, identify opportunities, and draft early-stage proposals, reducing administrative burden and expanding capacity to secure resources

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.

This scan curates recent developments and maps them to the stages of the data life cycle where they are most relevant in practice: planning, collecting, processing, sharing, analyzing, and using data.

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.

To monitor open data policies across the world, we developed the Open Data Policy Lab Policy Repository. This quarter, we added 11 new policy developments within and across Africa, Europe, Asia, and North America.

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 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.

We are pleased to launch DataStewards.net — dedicated to training and supporting data stewards.

We are pleased to launch DataStewards.net — dedicated to training and supporting data stewards.

We are pleased to launch DataStewards.net — dedicated to training and supporting data stewards.

On 5 February, The Governance Lab and the Centre for European Policy Studies (CEPS) convened researchers, policymakers, technologists, funders, and advocates for a joint workshop focused on Building a Research Agenda for Women’s Health Innovation. The workshop marked the next step in the 100 Questions Initiative: shifting from identifying priorities to operationalising and institutionalising them within the European context.

Data governance has become a catch-all term, used to describe everything from data quality and metadata to privacy, compliance, and digital strategy.

As part of an ongoing effort to contribute to current topics in data, technology, and governance, The GovLab’s Selected Readings series provides an annotated and curated collection of recommended readings on themes such as open data, data collaboration, and civic technology.

A practical reference for policy, institutional, and operational design

Kicking-off the 2026 Data Stewardship Trends to Watch

Kicking-off the 2026 Data Stewardship Trends to Watch

Questions to Signal and Capture Community Preferences and Expectations

A conversation that looked at the forces that shaped 2025 and may define 2026 across data, AI, and governance.

On January 8, 2026, The GovLab and the Open Data Policy Lab hosted “Looking Back to the Future”—a conversation that looked at the forces that shaped 2025 and may define 2026 across data, AI, and governance.

This paper proposes strategic data stewardship as a complementary institutional function...

Earlier this year, in collaboration with the Centre for European Policy Studies (CEPS) and the Gates-funded Research & Innovation (R&I) project, we added women’s health innovation to the list. Crowdsourcing a list of questions from an expert body of  more than 70 bilinguals, we identified the Top 10 Questions that should guide women’s health research and innovation.  In this article, we describe our methodology--part of a broader effort to create a new science of questions--list and briefly describe the top ten questions, and conclude with a discussion of reoriented priorities that should flow from these questions. 

Non-Traditional Data (NTD) — data that is digitally captured, mediated, or observed through sources such as satellites, sensors, online platforms, mobility traces, and crowdsourcing...

On January 8, 2026, The GovLab will host a small group of thinkers across regions and sectors to exchange insights on what will shape the…

The Data Tank, in collaboration with The Governance Lab, continued to work towards a critical and often missing strategic role: navigating responsible data governance and access as foundational human infrastructure for AI development.

In this blog, we summarize some of the work that took place over the course of 2025 at The GovLab.

To wrap up the year, our co-founder, Stefaan Verhulst, hosted the final edition for the year of our “Data Stewardship Trends to Watch” series for our growing alumni community, now 180+ strong and spanning the globe.

Recapping the 2025 Data Stewardship Trends; Now in 10 S’s!

The European Union’s pursuit to create a single data market has always been a balancing act between fostering public interest goals and safeguarding private enterprise.

Hosted by Bertelsmann Stiftung, the event welcomed around 50 participants from across the public, private, civil society, philanthropic and academic sectors.

The blog is part of a larger initiative to examine and illustrate how data commons (collaboratively governed data ecosystems) can enable responsible AI development.

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.

As part of a series of events in Europe, The Data Tank organised a workshop in Bologna in collaboration with Fondazione Compagnia Di San Paolo.

Authors: Paulina Behluli and Rodolphe Doité

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?

On a bi-monthly basis, Stefaan Verhulst (Co-founder of The GovLab and The Data Tank) goes over emerging trends in data stewardship. 

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

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.

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.

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.

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.

n the July 2025 edition, Stefaan Verhulst, lead of the Data Stewards Courses, shared updates based on the five identified functions of data stewardship...

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.

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.” 

Paulina Behluli, The Data Tank ⎜Natalia Mejia Pardo, The Data Tank

Earlier this month, I attended the DeSci.Berlin 2025 Conference at Molecule HQ, where scientists, blockchain developers, and investors gathered to examine how scientific research might evolve in the Web3 environment.

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.

How can we build and sustain data commons that balance openness, and trust, while fueling innovation for the public good? Can they ensure…

With over 170 applicants spread across six continents and countless sectors, it's clear that there is an urgent need for resources to...

With over 170 applicants spread across six continents and countless sectors, it’s clear that there is an urgent need for resources to develop data commons.

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.

On 5 May, the discussion looked at something more foundational: How do we make data ready for AI? How do we future-proof open data?

With only five days left to apply — the deadline being June 2, 2025 at 11:59 PM PT–prospective applicants are encouraged to submit their concept notes for the chance to receive $100,000

A new report on how communities can gain a say in how their data is reused in AI systems.

A new report on how communities can gain a say in how their data is reused in AI systems.

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.

Governments around the world have been rushing to celebrate public and private investments in artificial intelligence (AI) and AI’s supporting infrastructure in their country.

Takeaways from the April Data Stewards Meeting

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

The Open Data Policy Lab—a collaboration between Microsoft and The GovLab—is seeking out interesting ideas on how data commons might be used to support AI for local decision-making and generative AI.

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 paper subsequently outlines the core competencies required for effective data stewardship, explains the distinction between data stewards and Chief Data Officers (CDOs)...

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.

Data stewardship has emerged as a cornerstone of responsible data and AI innovation. To support this growing field, The GovLab and The Data Tank have been offering executive education programs across Europe...

Data commons — collaboratively governed ecosystems that enable responsible sharing of diverse datasets across sectors — offer a promising solution to data sharing.

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.

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.

The GovLab talks with experts on the past, present, and future of open data

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.

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

To includes latest scholarship and practice, we are calling upon all interested parties to provide feedback…

The GovLab is seeking experts to review a forthcoming report on how the concept of a social license can allow AI to serve global development goals

In 2024, and building on earlier work by The GovLab, The Data Tank has delivered a programme of Data Stewardship bootcamps to meet the growing demand across sectors.

As 2024 comes to a close, The GovLab's Data Program reflects on a year of continued efforts to advance data-driven problem-solving and...

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.

We are thrilled to announce the launch of our new Observatory of Examples of How Open Data and Generative Artificial Intelligence Intersect!

Forecasting the openness of data in 2024, assessing the impact of generative AI on open data, and identifying trends in data stewardship

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.