Stefaan Verhulst

Paper by Siu-Ming Tam: “To meet growing demand for granular demographic and socioeconomic indicators under tighter budgets, national statistical offices must continually develop new methods. These include using big data, satellite imagery, and transactional sources to improve or redesign data collection. Artificial intelligence can support this work, but algorithms generated with AI should not be trusted for production without rigorous verification.
This paper focuses on two foundations of trust in the use of AI in official statistics: independent statistical verification before production use, and disciplined protection of respondent confidentiality during development and testing. The approach is illustrated through the author’s experience directing AI to construct and implement a Mini Max Hierarchical Bayes sampling algorithm. Applied to a synthetic labour force population, the method met all specified precision targets while reducing the required sample size by 80 percent, as confirmed by a Monte Carlo study with 1000 replications. Applied to 2021 Australian Census microdata, it achieved a 90 percent reduction while producing national point estimates accurate to well below 1 percent.
The paper concludes with a practical evaluation checklist aligned with the UN Fundamental Principles of Official Statistics and the HLG MOS Quality Framework for Statistical Algorithms…(More)”.

Paper by Stefaan Verhulst, Johannes Jutting and Roeland Beerten: “Official statistics face a fundamental paradox: data has never been more abundant, yet public trust in the institutions that produce it has never felt more precarious. This paper argues that the crisis is not primarily one of methodological failure or statistical illiteracy, but of representational legitimacy: aggregate indicators systematically fail to capture lived experience, and citizens increasingly do not recognize themselves in the numbers that purport to describe them. We situate this argument within a broader body of work on moving “from averages to agency”. We place lived experience at the analytical center, drawing on three intellectual traditions that official statistics has engaged less systematically: the mixed methods tradition in social research, the citizen science movement as recently codified in the Copenhagen Framework on Citizen Data, and the participation literature descending from Arnstein’s ladder. Drawing on emerging practices from statistical agencies across more than a dozen countries, we take stock of pathways through which official statistics are beginning to shift from passive measurement toward active participation. Because participation is not a single practice but a family of practices, we propose a matrix of engagement that crosses depth of participation with the stages of the data value chain, arguing for fit-for-purpose rather than maximal participation. We conclude with a research agenda organized around methodological integration, scalability, the ethics of social licence, and institutional transformation…(More)”.

Paper by Morten Ryen Loe, Subina Shrestha and Sophie-Marie Ertelt: “Visions of the smart city have become increasingly influential in guiding contemporary urban governance, particularly within the domain of mobility, where digital technologies and data-driven systems are expected to enable more sustainable and efficient transport systems. While existing research has highlighted the role of sociotechnical imaginaries in shaping smart city agendas, less attention has been given to how such visions are enacted and made consequential within everyday governance practices. This paper addresses this gap by examining how smart mobility initiatives derive value through their association with dominant imaginaries of smart urban futures. Empirically, the paper analyses four initiatives in Stavanger (Norway) and Gothenburg (Sweden). Drawing on literature on sociotechnical imaginaries and smart urbanism, we conceptualise smartwashing as the process through which initiatives selectively mobilise dominant visions of smartness to enhance legitimacy and political viability. Adopting a project-level perspective, we find that smart mobility projects derive value through interrelated processes of articulating projects through narratives of smartness, mobilising these narratives to advance projects within their political contexts, and aligning projects with existing policy goals and local governance settings, generating legitimacy and support even where their impacts remain partial or uncertain. We thus contend that, rather than deliberate misrepresentation, smartwashing captures the performative use of smartness as a governing frame through which projects are framed and promoted as meaningful and actionable, thereby embedding them within contemporary urban governance…(More)”.

Initiative by Tiago C. Peixoto, Luke Jordan and Manuel Ramos-Maqueda: “RADAR (Readiness for AI Discovery and Agentic Reach) measures how AI and agents can reach government services. Across 166 countries, it runs live model queries and autonomous agent attempts against real government services, scoring whether a service can be located, whether the information returned is country-specific and traceable to an official source, and whether an agent can get far enough to file an actual request. The results are somewhat counterintuitive: several governments that rank well on standard digital-government indices fare less well here, and many do better than those same rankings would suggest.

The paper closes on what it calls sovereign legibility, the deliberate work of making authoritative government content readable and actionable by AI systems. Many of the recommendations are low cost and no regret, and the last section sets out where the research goes next…(More)”.

Toolkit by the Canadian Institute for Health Information: “…houses an evolving collection of resources, documents and tools designed to support implementation of the Health Data Stewardship Framework. Complementing these tools is the Pan-Canadian Resource Inventory (XLSX), which brings together a curated collection of Canadian and international data stewardship resources that support pan-Canadian health data access, sharing and use.

Who is this implementation toolkit for?

This toolkit is designed for organizations, teams and individuals seeking to understand, assess and strengthen health data stewardship practices. It is for anyone involved in the capture, management, use and governance of health data.

You can use the resources within this toolkit to

• Support operationalization of the framework to improve data sharing, access and use
• Enable consistent monitoring of progress over time
• Learn from leading and emerging stewardship-related practices across health systems

Content will continue to expand as new tools are developed and as best practices evolve to continuously support you in your health data stewardship journey…(More)”

World Development Report 2026 by the World Bank: “In a time when development progress has dipped to its weakest pace in 75 years, artificial intelligence (AI) offers developing economies a rare path to greater prosperity. World Development Report 2026 provides the first comprehensive assessment of what AI means for these economies—how firms and governments are already using it, what is holding them back, where the largest gains may lie, and how the risks can be managed.

Its central message is both practical and ambitious. Developing countries do not need to build trillion-dollar, all-purpose models to benefit from AI. But importing AI tools is also not enough. Countries must adapt AI to local languages, institutions, data, and development needs; ensure that national systems can work seamlessly with multiple platforms and providers; and steadily build the skills and infrastructure needed to do more. Low-cost tools—“small AI”—can put scarce expertise within reach of millions, through text messages, voice calls, basic phones, and other technologies that work even where electricity, computing power, and internet access are limited. The gains are already visible. AI is helping to accelerate medical screening, assisting farmers with more accurate weather forecasts, and aiding teachers in creating better lessons for students.

The Report offers a clear framework—adopt, adapt, and advance—for the road ahead to help countries capture AI’s benefits without wasting scarce resources or deepening dependence on any single supplier. Earlier technological revolutions left much of the developing world behind. This landmark edition of the World Development Report offers developing economies a roadmap to prevent a repeat of that outcome…(More)”.

Guidebook by Jane Anderson and Vanessa Smith: “…outlines data types, legal and governance foundations, provenance, collection & consent, storage infrastructure & access, use & reuse, attribution & accountability, and common misconceptions…(More)”.

Article by Merlyn Thomas and Paul Brown: “Google has rolled back its new AI tool that allowed people to create fake images on top of its satellite imagery, following a BBC Verify report in which experts raised concerns about misuse and the potential to spread misinformation.

Less than 48 hours after the tech giant announced the integration of its AI image generator Nano Banana 2 into Google Earth, it said it was pausing the feature “while we work on implementing stronger guardrails”.

In its statement on Friday, Google said it had seen “people sharing screenshots of generated imagery that appear to violate our policies”.

The retracted feature enabled users to use text prompts to generate false scenarios on top of a base layer of real satellite, aerial or 3D imagery – which could then be downloaded and shared on other platforms.

“We know that people uniquely trust Google Earth for a reliable view of the world,” it added.

Experts told BBC Verify the tool could be used to spread misinformation with the appearance of Google’s legitimacy – and highlighted the potential for bad actors to abuse it.

A collapsed Eiffel Tower, a sinkhole swallowing the Great Pyramid of Giza and Russian tanks in Ukraine’s capital were among the images BBC Verify was able to create when testing the feature, which initially launched on Thursday…(More)”.

Book edited by Mark Findlay, Sofie Schönborn, and Noha Lea Halim: “In this volume, young voices craft a fresh exploration of living and working in virtual worlds. Using Alice in Wonderland as a guiding metaphor, contributors address profound and urgent questions: Who am I online? Who decides what is possible in virtual worlds? How can these spaces be made safe, fair, and empowering?

Through specially commissioned short essays and reflections, emerging voices with extensive experience of digital environments evaluate key challenges of governance and personhood within the metaverse. Drawing on diverse disciplinary insights, chapters investigate how design choices subtly function as constraints and possibilities, how identities transform across platforms and how communities build their own norms. Ultimately, the book emphasises the importance of treating the metaverse as a lived social space and prioritising the voices of its first-hand navigators. It outlines strategies for designing policies that protect individuals while simultaneously promoting agency, imagination and inclusion within virtual worlds like the metaverse, both now and in the future.

Governing Virtual Wonderland is an essential read for scholars, students, and those interested in regulation and governance in the new digital age. It is also useful for those across the disciplines of technology and AI, law, political science, philosophy of data science and computer science…(More)”.

Map by Power for Democracies: “AI has been reshaping how information spreads, how governments operate, and how citizens participate. Deciding where to direct limited resources to protect democracy from these rapid developments has been far from straightforward.

While various research communities have been working in parallel, producing valuable but fragmented analyses, no single resource exists that brings these findings together into a coherent body of work….

Given how fast AI is developing, we began filling these gaps as a priority. Over six weeks, our team reviewed a wide body of existing literature and selected ten leading frameworks mapping AI threats.

The selected literature spans multiple levels of abstraction, disciplinary lenses, and democratic contexts – from the Carnegie Endowment for International Peace’s broad survey of AI and democracy to the Brennan Center for Justice’s focus on US electoral integrity, to the global perspective of the 2026 International AI Safety Report.

We extracted and standardised entries from these sources into a unified, publicly available database containing:

• 144 documented AI threats to democracy
• 103 pro-democracy strategies for addressing them
• 44 independent opportunities for strengthening democratic resilience

Each entry is mapped onto the aspects of democracy it affects, using an adapted International IDEA framework of democracy that clusters around: citizenship, law and rights; representative and accountable government; civil society and popular participation; and a category covering international dynamics…(More)”.