Inquiry as Infrastructure: Defining Good Questions in the Age of Data and AI


Paper by Stefaan Verhulst: “The most consequential failures in data-driven policymaking and AI deployment often stem not from poor models or inadequate datasets but from poorly framed questions. This paper centers question literacy as a critical yet underdeveloped competency in the data and policy landscape. Arguing for a “new science of questions,” it explores what constitutes a good question-one that is not only technically feasible but also ethically grounded, socially legitimate, and aligned with real-world needs. Drawing on insights from The GovLab’s 100 Questions Initiative, the paper develops a taxonomy of question types-descriptive, diagnostic, predictive, and prescriptive-and identifies five essential criteria for question quality: questions must be general yet concrete, co-designed with affected communities and domain experts, purpose-driven and ethically sound, grounded in data and technical realities, and capable of evolving through iterative refinement. The paper also outlines common pathologies of bad questions, such as vague formulation, biased framing, and solution-first thinking. Rather than treating questions as incidental to analysis, it argues for institutionalizing deliberate question design through tools like Q-Labs, question maturity models, and new professional roles for data stewards. Ultimately, the paper contends that the questions are infrastructures of meaning. What we ask shapes not only what data we collect or what models we build but also what values we uphold and what futures we make possible…(More)”.

Guiding the provision of quality policy advice: the 5D model


Paper by Christopher Walker and Sally Washington: “… presents a process model to guide the production of quality policy advice. The work draws on engagement with both public sector practitioners and academics to design a process model for the development of policy advice that works in practice (can be used by policy professionals in their day-to-day work) and aligns with theory (can be taught as part of explaining the dynamics of a wider policy advisory system). The 5D Model defines five key domains of inquiry: understanding Demand, being open to Discovery, undertaking Design, identifying critical Decision points, and shaping advice to enable Delivery. Our goal is a ‘repeatable, scalable’ model for supporting policy practitioners to provide quality advice to decision makers. The model was developed and tested through an extensive process of engagement with senior policy practitioners who noted the heuristic gave structure to practices that determine how policy advice is organized and formulated. Academic colleagues confirmed the utility of the model for explaining and teaching how policy is designed and delivered within the context of a wider policy advisory system (PAS). A unique aspect of this work was the collaboration and shared interest amongst academics and practitioners to define a model that is ‘useful for teaching’ and ‘useful for doing’…(More)”.

Brazil’s AI-powered social security app is wrongly rejecting claims


Article by Gabriel Daros: “Brazil’s social security institute, known as INSS, added AI to its app in 2018 in an effort to cut red tape and speed up claims. The office, known for its long lines and wait times, had around 2 million pending requests for everything from doctor’s appointments to sick pay to pensions to retirement benefits at the time. While the AI-powered tool has since helped process thousands of basic claims, it has also rejected requests from hundreds of people like de Brito — who live in remote areas and have little digital literacy — for minor errors.

The government is right to digitize its systems to improve efficiency, but that has come at a cost, Edjane Rodrigues, secretary for social policies at the National Confederation of Workers in Agriculture, told Rest of World.

“If the government adopts this kind of service to speed up benefits for the people, this is good. We are not against it,” she said. But, particularly among farm workers, claims can be complex because of the nature of their work, she said, referring to cases that require additional paperwork, such as when a piece of land is owned by one individual but worked by a group of families. “There are many peculiarities in agriculture, and rural workers are being especially harmed” by the app, according to Rodrigues.

“Each automated decision is based on specified legal criteria, ensuring that the standards set by the social security legislation are respected,” a spokesperson for INSS told Rest of World. “Automation does not work in an arbitrary manner. Instead, it follows clear rules and regulations, mirroring the expected standards applied in conventional analysis.”

Governments across Latin America have been introducing AI to improve their processes. Last year, Argentina began using ChatGPT to draft court rulings, a move that officials said helped cut legal costs and reduce processing times. Costa Rica has partnered with Microsoft to launch an AI tool to optimize tax data collection and check for fraud in digital tax receipts. El Salvador recently set up an AI lab to develop tools for government services.

But while some of these efforts have delivered promising results, experts have raised concerns about the risk of officials with little tech know-how applying these tools with no transparency or workarounds…(More)”.

Exit to Open


Article by Jim Fruchterman and Steve Francis: “What happens when a nonprofit program or an entire organization needs to shut down? The communities being served, and often society as a whole, are the losers. What if it were possible to mitigate some of that damage by sharing valuable intellectual property assets of the closing effort for longer term benefit? Organizations in these tough circumstances must give serious thought to a responsible exit for their intangible assets.

At the present moment of unparalleled disruption, the entire nonprofit sector is rethinking everything: language to describe their work, funding sources, partnerships, and even their continued existence. Nonprofit programs and entire charities will be closing, or being merged out of existence. Difficult choices are being made. Who will fill the role of witness and archivist to preserve the knowledge of these organizations, their writings, media, software, and data, for those who carry on, either now or in the future?

We believe leaders in these tough days should consider a model we’re calling Exit to Open (E2O) and related exit concepts to safeguard these assets going forward…

Exit to Open (E2O) exploits three elements:

  1. We are in an era where the cost of digital preservation is low; storing a few more bytes for a long time is cheap.
  2. It’s far more effective for an organization’s staff to isolate and archive critical content than an outsider with limited knowledge attempting to do so later.
  3. These resources are of greatest use if there is a human available to interpret them, and a deliberate archival process allows for the identification of these potential interpreters…(More)”.

Hundreds of scholars say U.S. is swiftly heading toward authoritarianism


Article by Frank Langfitt: “A survey of more than 500 political scientists finds that the vast majority think the United States is moving swiftly from liberal democracy toward some form of authoritarianism.

In the benchmark survey, known as Bright Line Watch, U.S.-based professors rate the performance of American democracy on a scale from zero (complete dictatorship) to 100 (perfect democracy). After President Trump’s election in November, scholars gave American democracy a rating of 67. Several weeks into Trump’s second term, that figure plummeted to 55.

“That’s a precipitous drop,” says John Carey, a professor of government at Dartmouth and co-director of Bright Line Watch. “There’s certainly consensus: We’re moving in the wrong direction.”…Not all political scientists view Trump with alarm, but many like Carey who focus on democracy and authoritarianism are deeply troubled by Trump’s attempts to expand executive power over his first several months in office.

“We’ve slid into some form of authoritarianism,” says Steven Levitsky, a professor of government at Harvard, and co-author of How Democracies Die. “It is relatively mild compared to some others. It is certainly reversible, but we are no longer living in a liberal democracy.”…Kim Lane Scheppele, a Princeton sociologist who has spent years tracking Hungary, is also deeply concerned: “We are on a very fast slide into what’s called competitive authoritarianism.”

When these scholars use the term “authoritarianism,” they aren’t talking about a system like China’s, a one-party state with no meaningful elections. Instead, they are referring to something called “competitive authoritarianism,” the kind scholars say they see in countries such as Hungary and Turkey.

In a competitive authoritarian system, a leader comes to power democratically and then erodes the system of checks and balances. Typically, the executive fills the civil service and key appointments — including the prosecutor’s office and judiciary — with loyalists. He or she then attacks the media, universities and nongovernmental organizations to blunt public criticism and tilt the electoral playing field in the ruling party’s favor…(More)”.

Test and learn: a playbook for mission-driven government


Playbook by the Behavioral Insights Team: “…sets out more detailed considerations around embedding test and learn in government, along with a broader range of methods that can be used at different stages of the innovation cycle. These can be combined flexibly, depending on the stage of the policy or service cycle, the available resources, and the nature of the challenge – whether that’s improving services, testing creative new approaches, or navigating uncertainty in new policy areas.

Almost all of the methods set out can be augmented or accelerated by harnessing AI tools – from using AI agents to conduct large-scale qualitative research, to AI-enhanced evidence discovery and analysis, and AI-powered systems mapping and modelling. AI should be treated as a core component of the toolkit at each stage.  And the speed of evolution of the application of AI is another strong argument for maintaining an agile mindset and regularly updating our ways of working. 

We hope this playbook will make test-and-learn more tangible to people who are new to it, and will expand the toolkit of people who have more experience with the approach. And ultimately we hope it will serve as a practical cheatsheet for building and improving the fabric of life…(More)”.

The Future is Coded: How AI is Rewriting the Rules of Decision Theaters


Essay by Mark Esposito and David De Cremer: “…These advances are not happening in isolation on engineers’ laptops; they are increasingly playing out in “decision theaters” – specialized environments (physical or virtual) designed for interactive, collaborative problem-solving. A decision theater is typically a space equipped with high-resolution displays, simulation engines, and data visualization tools where stakeholders can convene to explore complex scenarios. Originally pioneered at institutions like Arizona State University, the concept of a decision theater has gained traction as a way to bring together diverse expertise – economists, scientists, community leaders, government officials, and now AI systems – under one roof. By visualizing possible futures (say, the spread of a wildfire or the regional impact of an economic policy) in an engaging, shared format, these theaters make foresight a participatory exercise rather than an academic one. In the age of generative AI, decision theaters are evolving into hubs for human-AI collaboration. Picture a scenario where city officials are debating a climate adaptation policy. Inside a decision theater, an AI model might project several climate futures for the city (varying rainfall, extreme heat incidents, flood patterns) on large screens. Stakeholders can literally see the potential impacts on maps and graphs. They can then ask the AI to adjust assumptions – “What if we add more green infrastructure in this district?” – and within seconds, watch a new projection unfold. This real-time interaction allows for an iterative dialogue between human ideas and AI-generated outcomes. Participants can inject local knowledge or voice community values, and the AI will incorporate that input to revise the scenario. The true power of generative AI in a decision theater lies in this collaboration.

Such interactive environments enhance learning and consensus-building. When stakeholders jointly witness how certain choices lead to undesirable futures (for instance, a policy leading to water shortages in a simulation), it can galvanize agreement on preventative action. Moreover, the theater setup encourages asking “What if?” in a safe sandbox, including ethically fraught questions. Because the visualizations make outcomes concrete, they naturally prompt ethical deliberation: If one scenario shows economic growth but high social inequality, is that future acceptable? If not, how can we tweak inputs to produce a more equitable outcome? In this way, decision theaters embed ethical and social considerations into high-tech planning, ensuring that the focus isn’t just on what is likely or profitable but on what is desirable for communities. This participatory approach helps balance technological possibilities with human values and cultural sensitivities. It’s one thing for an AI to suggest an optimal solution on paper; it’s another to have community representatives in the room, engaging with that suggestion and shaping it to fit local norms and needs.

Equally important, decision theaters democratize foresight. They open up complex decision-making processes to diverse stakeholders, not just technical experts. City planners, elected officials, citizens’ groups, and subject matter specialists can all contribute in real time, aided by AI. This inclusive model guards against the risk of AI becoming an opaque oracle controlled by a few. Instead, the AI’s insights are put on display for all to scrutinize and question. By doing so, the process builds trust in the tools and the decisions that come out of them. When people see that an AI’s recommendation emerged from transparent, interactive exploration – rather than a mysterious black box – they may be more likely to trust and accept the outcome. As one policy observer noted, it’s essential to bring ideas from across sectors and disciplines into these AI-assisted discussions so that solutions “work for people, not just companies.” If designed well, decision theaters operationalize that principle…(More)”.

Deliberative Approaches to Inclusive Governance


Series edited by Taylor Owen and Sequoia Kim: “Democracy has undergone profound changes over the past decade, shaped by rapid technological, social, and political transformations. Across the globe, citizens are demanding more meaningful and sustained engagement in governance—especially around emerging technologies like artificial intelligence (AI), which increasingly shape the contours of public life.

From world-leading experts in deliberative democracy, civic technology, and AI governance we introduce a seven-part essay series exploring how deliberative democratic processes like citizen’s assemblies and civic tech can strengthen AI governance…(More)”.

Spaces for Deliberation


Report by Gustav Kjær Vad Nielsen & James MacDonald-Nelson: “As citizens’ assemblies and other forms of citizen deliberation are increasingly implemented in many parts of the world, it is becoming more relevant to explore and question the role of the physical spaces in which these processes take place.

This paper builds on existing literature that considers the relationships between space and democracy. In the literature, this relationship has been studied with a focus on the architecture of parliament buildings, and on the role of urban public spaces and architecture for political culture, both largely within the context of representative democracy and with little or no attention given to spaces for facilitated citizen deliberation. With very limited considerations of the spaces for deliberative assemblies in the literature, in this paper, we argue that the spatial qualities for citizen deliberation demand more critical attention.

Through a series of interviews with leading practitioners of citizens’ assemblies from six different countrieswe explore what spatial qualities are typically considered in the planning and implementation of these assemblies, what are the recurring challenges related to the physical spaces where they take place, and the opportunities and limitations for a more intentional spatial design. In this paper, we synthesise our findings and formulate a series of considerations for the spatial qualities of citizens’ assemblies aimed at informing future practice and further research…(More)”.

Democratic Resilience: Moving from Theoretical Frameworks to a Practical Measurement Agenda


Paper by Nicholas Biddle, Alexander Fischer, Simon D. Angus, Selen Ercan, Max Grömping, andMatthew Gray: “Global indices and media narratives indicate a decline in democratic institutions, values, and practices. Simultaneously, democratic innovators are experimenting with new ways to strengthen democracy at local and national levels. These both suggest democracies are not static; they evolve as society, technology and the environment change.

This paper examines democracy as a resilient system, emphasizing the role of applied analysis in shaping effective policy and programs, particularly in Australia. Grounded in adaptive processes, democratic resilience is the capacity of a democracy to identify problems, and collectively respond to changing conditions, balancing institutional stability with transformative. It outlines the ambition of a national network of scholars, civil society leaders, and policymakers to equip democratic innovators with practical insights and foresight underpinning new ideas. These insights are essential for strengthening both public institutions, public narratives and community programs.

We review current literature on resilient democracies and highlight a critical gap: current measurement efforts focus heavily on composite indices—especially trust—while neglecting dynamic flows and causal drivers. They focus on the descriptive features and identify weaknesses, they do not focus on the diagnostics or evidence to what strengths democracies. This is reflected in the lack of cross-sector networked, living evidence systems to track what works and why across the intersecting dynamics of democratic practices. To address this, we propose a practical agenda centred on three core strengthening flows of democratic resilience: trusted institutions, credible information, and social inclusion.

The paper reviews six key data sources and several analytic methods for continuously monitoring democratic institutions, diagnosing causal drivers, and building an adaptive evidence system to inform innovation and reform. By integrating resilience frameworks and policy analysis, we demonstrate how real-time monitoring and analysis can enable innovation, experimentation and cross-sector ingenuity.

This article presents a practical research agenda connecting a national network of scholars and civil society leaders. We suggest this agenda be problem-driven, facilitated by participatory approaches to asking and prioritising the questions that matter most. We propose a connected approach to collectively posing key questions that matter most, expanding data sources, and fostering applied ideation between communities, civil society, government, and academia—ensuring democracy remains resilient in an evolving global and national context…(More)”.