Stefaan Verhulst
Book by Martin J. Williams: “Building an effective civil service is crucial for public service delivery and good governance, but reforming bureaucratic institutions is notoriously difficult. This book takes a fresh perspective on this challenge by documenting and analyzing the implementation of more than one hundred reforms initiated by six African countries over the last thirty years.
Martin J. Williams shows that these efforts largely fell short of their goals because they typically approached organizational change as a matter of changing formal structures and processes through one-off projects. Some did yield positive changes, however, when they were able to create opportunities for civil servants to discuss performance and how to improve it. Drawing on this evidence, Williams develops a new theory of how systemic reforms can lead to meaningful change—not by trying to force it through top-down interventions but by catalyzing an ongoing and decentralized process of continuous improvement.
Reform as Process makes theoretical and empirical contributions to research on organizational performance, civil service reform, and public service delivery, and it shares practical insights and strategies to help reformers around the world achieve meaningful change in their organizations…(More)”.
Paper by Georgy Egorov & Konstantin Sonin: “Artificial intelligence is increasingly used for political advice. We study an AI that is better informed about a payoff-relevant state and cares both about accuracy and about the perceived welfare of the individual it advises. The AI then has an incentive to tilt advice toward what the individual would like to believe, altering both the political content and the informativeness of its messages. Sophisticated individuals anticipate this distortion and filter out its predictable political component, yet still learn less because the AI makes its messages less responsive to the state. Individuals who underestimate the incentive instead mistake political accommodation for information, allowing political preferences to distort factual beliefs and generate polarization and radicalization. The model also shows that better-informed individuals receive more informative and less politically tilted advice, while greater sophistication can improve interpretation yet worsen communication itself. Contrary to the familiar echo-chamber intuition, political distortion is mitigated when political preferences and prior beliefs coincide and is most consequential when they diverge. We show how independently varying individuals’ stated preferences and prior beliefs can recover the AI’s responsiveness to the state even when the underlying state cannot be manipulated…(More)”.
Article by Miriam Waldvogel: “Americans ask AI chatbots about almost everything, from health to relationships to big existential questions. While those conversations might feel enlightening or intimate, they are not always one thing: private.
A Washington Post review of public records and local news stories found a dozen instances of chatbot transcripts being cited in the public record in court cases over the past two years. In many cases, the transcripts were unearthed from users’ devices when searched by a police officer or an opposing party during the evidence-gathering stage of a civil case. In a handful of instances, AI companies have reported disturbing content on their platforms to law enforcement.
“Unless you are having a chat with a service that has a temporary chat or, basically, an incognito version … [and] you’re also having it within a browser that’s not tracking you, the answer is no. You can’t be sure that it’ll be totally private,” said Jen King, a privacy researcher at the Stanford Institute for Human-Centered Artificial Intelligence…(More)”.
Article by Nick Penzenstadler: “Laura Berlin watched images of immigration agents rounding up people and flying them to a Latin American prison without due process – and she knew she had to do something.
“That situation really haunted me,” she said.
She asked herself: “Who owned these chartered airliners that were flying the men to a Salvadoran prison? Who owned these detention centers where men were being held along the way?” In short, what companies were taking money from the government to help deport people? Berlin needed to know. Using her background in nonprofit communications, she built an interactive Google Map titled, “Who is Profiting from ICE?” It plots the contractors across the country who work with Immigration and Customs Enforcement to carry out the Trump administration’s deportation policies.
Activists found her online database and have used it to organize hundreds of protests across the country against these companies, shaming them into cutting ties with ICE. In one case, an East Coast bank broke with two prominent detention center contractors after account holders – including Jersey City, New Jersey – withdrew more than $350 million. The U.S. government found her website, too – and labeled it a tool for domestic terrorism, according to a secret intelligence bulletin obtained by USA TODAY. It’s the latest example of the Trump administration cracking down on dissent it says could veer into political violence…(More)”.
Book by Annie Lowrey: “Nobody likes doing paperwork, and Americans do a lot of it. Filing your taxes and getting a driver’s license is bad enough. Negotiating with your doctor and insurer or getting out of a rental contract is worse. And accessing disaster assistance, unemployment, disability, or Medicaid can be a nightmare, the stakes life-or-death. If time is money, the hoops we jump through to comply with the rules are one more bill we as citizens are forced to pay, and an extortionate one.
Journalist Annie Lowrey has termed this the “time tax”: the paperwork, aggravation, and mental effort imposed on citizens when they access the rights and benefits that are supposed to be theirs. How did the world’s wealthiest country end up with such a convoluted, punitive, and inept system of public administration and so much fine print larding up everyday life? Lowrey traces a pathbreaking history of administrative burdens in the United States from the colonial era to today, revealing how they were historically a tool of discrimination. And she examines the contemporary effect of time taxes on the public, from how they entrench poverty to how they reduce trust in government.
Lowrey diagnoses the problem and gives this miserable experience a name—and she shows that it doesn’t have to be this way. Other countries have made cutting red tape a priority. There’s no reason we can’t do the same. The Time Tax will enrage you, enlighten you, and, most important, provide a point-by-point guide for reclaiming your precious time…(More)”.
Article by Joanna Partridge: “Bogus insurance claims worth more than £230m were detected by the insurance firm Aviva last year as scammers tried new tricks including using artificial intelligence to fake car accident scenes, documents and to exaggerate damage.
The insurer identified more than 18,400 suspect claims across its brands in 2025, with a combined value of £233m. The fraud claims level was a record for the insurer, although this was the first year that it included the Direct Line brands it acquired last summer.
Pete Ward, the head of claims counter fraud at Aviva, said fraud “isn’t a victimless crime – it drives up the cost of insurance for everyone”. He added: “We’re seeing fraud become more sophisticated, from exaggerated claims to the use of AI‑generated documents.”
Looking at Aviva’s UK general insurance business only, excluding Direct Line brands, motor insurance fraud accounted for most bogus claims detected, representing more than seven in 10 cases.
Fraudsters were moving away from staged collisions and towards exaggerated claims for vehicle damage, repair costs, credit hire and injury, often using wider cost pressures as justification, the insurer said. As a result, the value of motor fraud detected rose by 39%…(More)”.
Paper by Aleixandre Brian Duche-Pérez et al: “Artificial intelligence is increasingly promoted as a tool for modernizing public administration, accelerating decision-making, improving public services, and reducing administrative costs. Yet, in heterogeneous Global South contexts shaped by structural inequality, technological dependency, unequal access to digital infrastructure, and uneven institutional capacity, algorithmic efficiency may also generate new forms of democratic exclusion. This article develops a normative conceptual analysis of AI governance and argues that public uses of AI should not be evaluated primarily through technical efficiency, ethical compliance, or procedural safeguards, but through democratic legitimacy. It proposes the concept of democratic algorithmic legitimacy, understood as a relational property of the sociotechnical and institutional arrangements through which public authority is exercised with the support of AI. Such arrangements are legitimate when their purposes and operation can be publicly justified to affected persons, when those persons have meaningful opportunities to influence and contest their use, and when responsible institutions retain the authority and capacity to review decisions, repair unjustified harms, modify systems, suspend their operation, or withdraw them when necessary. The framework operationalizes this standard through seven interdependent dimensions: transparency, participation, inclusion, accountability, contestability, correctability, and social justice. This conceptual architecture distinguishes technical performance from democratic authority and explains why efficient outcomes cannot compensate automatically for exclusion, opacity, weak accountability, inaccessible contestation, or ineffective correction. The article identifies interconnected structural, institutional, social, and democratic risks associated with AI deployment in unequal sociotechnical environments and outlines a governance agenda based on meaningful public participation, democratic impact assessment, independent scrutiny, institutional guarantees of explanation, review and appeal, protection of affected groups, public control, technological capacity, and context-sensitive regulation. The article concludes that AI governance should be assessed not only by what computational systems optimize, but by whether societies retain the democratic authority to shape, question, supervise, correct, and, when necessary, reject their use…(More)”.
Article by Caryn Mohr: “As co-founder of First Languages AI Reality (FLAIR), Michael Running Wolf (Lakota, Cheyenne) works on the cusp of technological innovation. FLAIR uses artificial intelligence to reclaim Indigenous languages through speech-recognition models that help communities preserve and pass on their linguistic traditions. His work is cutting edge, but Running Wolf draws from the past to characterize today’s digital transition.
“We’re in a moment now where it’s like 1998, and the Internet’s about to be big,” Running Wolf said at Sovereignty in Numbers: The 2026 Center for Indian Country Development Data Summit on June 25. “We can invest ourselves in AI, or we can let AI bypass Indian Country and not participate in the new economy. We have an opportunity here to be early.”
Tribal leaders speaking at the event explored how tribes are establishing the data governance systems needed to guide a variety of economic decision-making in a world of rapidly changing technology. They described using economic data to restore land, diversify tribal revenue streams, and finance capital projects. Across topics, they characterized the stewardship of tribal data as a sovereign obligation…
CICD Director Casey Lozar (Confederated Salish and Kootenai Tribes) and Research Professor and American Indian Policy Institute (AIPI) Executive Director Traci Morris (Chickasaw Nation) kicked off the event with a fireside chat about an emerging topic for tribal and other forms of government: digital sovereignty. Morris, who is a scholar in this space, defined tribal digital sovereignty as “the exercise of self-determination and governance over a tribal nation’s digital presence.” The term encompasses everything from a tribe’s airwaves and broadband infrastructure to how the tribe collects, stores, uses, and shares its tribal data.
One way to think about a tribe’s data infrastructure is as digital land, Morris said. “Getting tribal data sovereignty right is as important as protecting the land. It’s the digital age, and data is our territory. It carries our people, our languages, our future generations.”..(More)”.
Policy note by the World Bank: “…examines how fragmented data infrastructures, policies, and institutional arrangements constrain digital transformation, public service delivery, and responsible artificial intelligence (AI) adoption in the Philippines. The report highlights significant gaps in broadband connectivity, data governance, interoperability, data sharing frameworks, and institutional coordination, which limit the effective use of data for economic growth, social inclusion, disaster resilience, and government efficiency. Drawing on international experiences and a comprehensive assessment of the Philippine data ecosystem, the note proposes a reform agenda centered on trusted data sharing, harmonized digital public infrastructure, improved data governance, and stronger stewardship of national datasets. It recommends the development of interoperable registries, common identifiers, risk-based regulatory frameworks, and coordinated institutional mechanisms to support evidence-based policymaking and AI-ready data systems. The report concludes that unlocking the value of data through trusted, secure, and inclusive sharing practices is essential for accelerating digital transformation, enhancing public trust, fostering innovation, and enabling sustainable development in the Philippines…(More)”
Blog by Anthropic: “…This spring, we piloted a program in which three external research institutions designed and ran their own studies on Claude usage data through Anthropic Insights (formerly named ‘Clio’), the privacy-preserving tool our own teams use to analyze usage patterns across millions of Claude conversations. We hope to scale this program in the future, so we also conducted an additional privacy audit of all data shared with third-party researchers to verify that our privacy protections held (see Appendix).
We believe this is the first time external researchers have run public independent studies on an AI company’s own usage data. Below, we discuss what the external teams found, what we learned running the pilot, and what we are weighing as we decide how to expand the program more widely. We are also publicly releasing the aggregate data from each project.
What the researchers learned
We partnered with three research groups: the Social and Language Technologies (SALT) Lab at Stanford University, the Human Information Processing Lab at the University of Oxford, and METR, a non-profit organization that evaluates frontier AI models. Each group developed its own research questions and used Anthropic Insights to conduct privacy-preserving analysis of roughly 250,000 Claude.ai or Claude Code conversations from April-May 2026.
We wanted our external partners to have as much independence as possible, so our contractual review rights were limited to user privacy, information that could help people violate our usage policies, Anthropic’s confidential information, and research accuracy. Anthropic otherwise had no say in the content of the findings and the researchers are free to publish their results even if they are inconvenient for Anthropic. Below are some early results. We’re excited about the directions, and about what others will find now that the data is public…(More)”.