Stefaan Verhulst

Essay by Geoffrey Smith: “…Bibliometricians have a name for papers like Shimomura’s; they call them “sleeping beauties.” A sleeping beauty is published, ignored, and then, sometimes a generation later, kissed awake. The fairy-tale framing is a little twee, but it points at something unsettling about how knowledge grows. We tend to picture the scientific literature as a frontier that moves forward. The sleeping beauties suggest it is closer to an attic, where things of great value lie in boxes that no one has thought to open. And we are now building machines that can open all the boxes at once.

The term comes originally from Anthony van Raan, a professor of quantitative studies of science at Leiden University. In a 2004 paper in Scientometrics, he defined a “Sleeping Beauty in Science” as a publication that goes unnoticed for a long time and then, fairly abruptly, draws a great deal of attention, and he reported what he believed was the first extensive measurement of how often this happens. He scored papers on three criteria: how long they slept, how deeply (the average number of citations during the dormant period), and how intensely they woke (the citations received in the four years after). Using somewhat arbitrary thresholds, he found sleeping beauties at a rate of about 0.01 percent of papers published in a given year (Aghayeva, Works in Progress).

That number made the phenomenon look like a rarity, a handful of mispriced assets in an otherwise efficient market. It did not hold up. In 2015, a team at Indiana University led by Qing Ke and Alessandro Flammini returned to the question with far more data. They introduced a single measure capturing both the intensity of a paper’s recognition and the length of its sleep, and concluded that sleeping beauties are far from exceptional. They noted that earlier estimates of scarcity depended heavily on arbitrary thresholds applied to small or single-discipline datasets. Drawing on 384,649 papers from American Physical Society journals and more than 22 million from Web of Science, they found a wide, continuous range of delayed recognition in every scientific field, and raised the estimated share of sleeping beauties at least 100-fold over van Raan’s (Aghayeva, Works in Progress). Delayed recognition, in other words, is not a curious exception. It is a normal part of how science works…(More)”.

Paper by Vera Lummis, Angela Aristidou and Rob Reich: “Frontier AI labs and nonprofit organizations are increasingly partnering to deploy frontier AI in support of nonprofits’ missions to improve global health, climate, humanitarian, and development outcomes. Individual and institutional funders have invested hundreds of millions of dollars to support nonprofits in deploying AI for good, occasionally in formal partnership with AI labs. However, the rapidly growing AI for Social Good (AI4SG) ecosystem lacks a clear understanding of what these partnerships provide, how they form, and what drives or compromises their success. 

Drawing on interviews with 36 individuals across 24 organizations (frontier AI labs, nonprofits, philanthropic funders, and independent experts) and four in-depth case studies, this report offers insights into how nonprofits and frontier AI labs partner to deploy AI to produce social impact and provides recommendations for how partnership and funding arrangements can be structured for success…(More)”.

Paper by Victoria Gorton a and Morgan Currie: “This paper outlines benefit recipients’ views towards the sharing of data that is collected about them when they routinely interact with social security services. Sharing this administrative data between public bodies promises to transform the delivery and evaluation of social security. However, there remains a lack of research into public attitudes, understandings, and aspirations for the sharing of this data, particularly from those whose data would be shared.
Drawing on discussions from deliberative focus groups with 41 individuals, we reflect on the scope for increased data sharing to deliver improvements for recipients. While participants were aware of how their data is currently shared and how increased data sharing might have advantages, they expressed strong distrust in government agencies to manage their data and concerns about being placed in a position of increased vulnerability. We argue individuals’ views towards data sharing cannot be separated from their lived experiences of data systems – their data realities – which are often markedly different from system designers. We conclude by offering considerations against data systems re-introducing paternalistic
policy, unintentionally, via automation – which we term ‘automated paternalism’…(More)”.

Article by Joseph Foti: “In the prior OGP Horizons piece in this series, we looked at what governments actually mean when they talk about tech sovereignty. In the abstract, this is an ability to control technology in their borders and to be relatively autonomous when it comes to using foreign technology.

But, in practice, governments are quite diverse. As a recap, we looked at the legislation and policies being adopted by many “middle powers,” as well as the EU, the US, and China. (Readers are encouraged to skim the summary of all of the findings here.) The findings showed that interventions fell into three categories.

• Cost: Buying software and computing power and spending money to build domestic capacity.
• Exit: Preserving the ability to leave a bad relationship.
• Leverage: Controlling holdings that other jurisdictions need.

Within each of these categories, there are a number of different policies. In Part II of the series, we will go through cost, exit, and leverage. We’ll also look at why and where open government can help ensure that people are getting what they need from the policies, namely autonomy, good value, security, and jobs.

For each of the given policy areas, there is a distinct role for transparency and public oversight. In some cases, especially to those related to land and permitting as well as standards development, there is a particular role for public participation…(More)”.

OECD Report: “Governments are under growing pressure to respond more effectively to rapid technological, economic and societal changes while maintaining stability and fiscal sustainability. A significant transformation of the functioning of governments needs to take place that can take advantage of digital and AI tools, and the opportunity of large cohorts of retiring civil servants to change the culture. Based on the analysis of cutting-edge practices in governments of OECD countries, Government Unstuck provides a coherent set of actions that will help governments be up to the challenges of today…(More)”.

Paper by Dimitrios Kalogeropoulos, Paul Barach, Andrea Downing, Stefaan Verhulst, and Maryam Lustberg: “Healthcare services and data ecosystems remain fragmented, inequitable and misaligned with patient, clinician and public health needs. Three pathways to patient-centred Artificial Intelligence (AI) have emerged to address this: data collaboration, Whole System Approaches and digital inclusion. Each has advanced the field. However, none delivers the continuous, participatory and outcome-grounded learning that equitable AI demands. The populations whose data drives AI learning must also be the populations who benefit from it. This principle has not been structurally embedded in any existing pathway. This narrative review defines a framework for operationalising Adaptive Machine Learning (AML) as a fourth, integrative pathway to patient-centred AI. AML is defined as continuous learning from real-world individual-level data to generate personalised, population-level insights returning direct benefit to the communities who produce them. A narrative review of PubMed and Google Scholar (2018–2025) was conducted across five thematic domains: AI and machine learning in healthcare; real-world data and evidence; patient-centred care and digital health; data governance and AI regulation; and adaptive clinical trial design. Search terms covered healthcare AI applications and adaptive, continuously learning systems, emphasising prediction-oriented rather than static diagnostic approaches. Eligibility was determined through iterative thematic analysis. Eight systemic barriers to patient-centred AI are identified and the three existing pathways critically examined for limitations in addressing bias, validation and equitable implementation. AML is proposed as the mechanism that closes this gap, connecting systems medicine, personalised medicine and precision medicine through continuous, outcome-based learning, identifying three original conceptual contributions as enablers: Integrative Data Governance (IDG), Adaptive Clinical Trial (ACT) designs and Evidence Sandbox Facilities (ESFs). Progress requires globally standardised Healthcare Data Recycling frameworks, adaptive evaluation methodologies and ESFs enabling multi-stakeholder validation. Future research should address federated AML validation, collective consent mechanisms and alignment of regulatory frameworks with international AI governance standards…(More)”.

Paper by Curtis Ventriss and Tina Nabatchi: “Public administration is at the center of the global democratic crisis. Meeting this challenge requires more than managerial and analytic competence—it requires a public philosophy grounded in the first principles of democratic ethos. We offer such a philosophy, drawing on four seminal thinkers whose concepts reflect the conditions public administrators face in times of democratic crisis. Judith Shklar’s liberalism of fear establishes a negative obligation to refuse cruelty and resist its institutionalization. Alasdair MacIntyre’s internal goods of practice create a positive obligation to cultivate virtue and protect the integrity of administrative practice. Isaiah Berlin’s agony of choice obligates administrators to acknowledge irreducible value conflicts and their consequential impact on democratic life. Hannah Arendt’s enlarged mentality provides a framework for thinking across perspectives so that judgment under conflict becomes democratically defensible. Together, these concepts form a public philosophy for public administration with practical significance for administrative judgment, organizational culture, and institutional courage…(More)”.

Article by sheets.works: “Billions of phones run on code looked after by a handful of people. We counted them from the code itself…

People post this comic whenever something breaks. The tower is labelled “all modern digital infrastructure” and it stands on one small block, “a project some random person in Nebraska has been thanklessly maintaining since 2003”.

We wanted to know how close to true it is. We downloaded the full history of 23 pieces of software that phones, browsers and servers depend on, and counted everyone who made ten or more changes to each one between October 2025 and October 2026. Then we listed what is actually installed on an Android phone, an iPhone and a Windows PC…(More)”.

Book by David Weinberger: “Amid the clamor about AI, Beautiful Particulars poses a unique question: Not how does our use of AI change what we do, but how is the idea of AI already subtly yet fundamentally reshaping how we think about ourselves and our world?

In clear, engaging, and even humorous prose, David Weinberger offers a new perspective on how machine learning works and how it may already be changing our basic and deepest ideas. Through lively examples, he shows that AI’s success—with all its risks and dangers—is taking us past our millennia of reliance on laws and principles by revealing what morality, free will, creativity, causality knowledge, and even reality itself look like now that we’re able to let the particulars speak their tiny truths.

The author poses questions not usually asked: What does a coin look like to AI? When AI gives you evidence that the earth is round, why are its own reasons for saying that so different? Why does an AI image generator create a “selfie” of ancient Aztec warriors with broad smiles that it “believes” are historically unlikely? If AI becomes conscious but bodiless, could it still make good moral decisions? Why is the world so much better at being causal than AI could ever “understand”? How does AI show us that genuine creativity is not about a “spark” but about moments that feel right? And how can you take the temperature of a joke?

Beautiful Particulars offers a new—and hopeful—perspective on how machine learning works, and how that’s already changing how we understand what it means to be human in the age of AI…(More)”

Book by Catarina Zuzarte Tully: “This book is different.It is written for people who are actively trying to transform the systems around them in a time of uncertainty and change. It is written for people who are experiencing the present as a period of frustration, anxiety and retrenchment—but who also know that it is a time of extraordinary possibility to shape a positive future. It is written for people who understand that transformation is ultimately about power: speaking truth to it, challenging it and redistributing it. It is written for people who feel a sense of stewardship: a responsibility to connect people working across past, present and future in service of a more prosperous, secure and sustainable world.

Future generations are not strangers who happen to live later. They are extensions of ourselves, just as we are extensions of those who came before us. Playing with Time is rooted in this simple idea. It invites us to loosen our grip on the present, reconnect with longer-term horizons, and allow possible futures to reshape how we act today.

This moment calls for our creative, collective response. It asks us to articulate and defend the values we care about, work across difference wherever possible, and act for the wellbeing of current and future generations. These are things that all of us can do. This book shows how...(More)”.