Stefaan Verhulst

Book by Rogayeh Tabrizi: “…delivers an intuitive roadmap to help organizations disentangle the complexity of their data to create tangible and lasting value. The book explains how to balance the multiple disciplines that power AI and behavioral economics using a combination of the right questions and insightful problem solving.

You’ll learn why intellectual diversity and combining subject matter experts in psychology, behavior, economics, physics, computer science, and engineering is essential to creating advanced AI solutions. You’ll also discover:

• How behavioral economics principles influence data models and governance architectures and make digital transformation processes more efficient and effective
• Discussions of the most important barriers to value in typical big data and AI projects and how to bring them down
• The most effective methodology to help shorten the long, wasteful process of “boiling the ocean of data”

An exciting and essential resource for managers, executives, board members, and other business leaders engaged or interested in harnessing the power of artificial intelligence and big data, Behavioral AI will also benefit data and machine learning professionals…(More)”

Book by Glenn Adamson: “For millennia, predicting the future was the province of priests and prophets, the realm of astrologers and seers. Then, in the twentieth century, futurologists emerged, claiming that data and design could make planning into a rational certainty. Over time, many of these technologists and trend forecasters amassed power as public intellectuals, even as their predictions proved less than reliable. Now, amid political and ecological crises of our own making, we drown in a cacophony of potential futures-including, possibly, no future at all.

A Century of Tomorrows offers an illuminating account of how the world was transformed by the science (or is it?) of futurecasting. Beneath the chaos of competing tomorrows, Adamson reveals a hidden order: six key themes that have structured visions of what’s next. Helping him to tell this story are remarkable characters, including self-proclaimed futurologists such as Buckminster Fuller and Stewart Brand, as well as an eclectic array of other visionaries who have influenced our thinking about the world ahead: Octavia Butler and Ursula LeGuin, Shulamith Firestone and Sun Ra, Marcus Garvey and Timothy Leary, and more.

Arriving at a moment of collective anxiety and fragile hope, Adamson’s extraordinary bookshows how our projections for the future are, always and ultimately, debates about the present. For tomorrow is contained within the only thing we can ever truly know: today…(More)”.

Chapter by Andrew Heiss: “This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century.

I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations.

I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field…(More)”.

Essay by Julia Angwin and Ami Fields-Meyer: “…Heimans points to an increasingly hostile digital landscape as one barrier to effective grassroots campaigns. At the dawn of the digital era, in the two-thousands, e-mail transformed the field of political organizing, enabling groups like MoveOn.org to mobilize huge campaigns against the Iraq War, and allowing upstart candidates like Howard Dean and Barack Obama to raise money directly from people instead of relying on Party infrastructure. But now everyone’s e-mail inboxes are overflowing. The tech oligarchs who control the social-media platforms are less willing to support progressive activism. Globally, autocrats have more tools to surveil and disrupt digital campaigns. And regular people are burned out on actions that have failed to remedy fundamental problems in society.

It’s not clear what comes next. Heimans hopes that new tactics will be developed, such as, perhaps, a new online platform that would help organizing, or the strengthening of a progressive-media ecosystem that will engage new participants. “Something will emerge that kind of revitalizes the space.”

There’s an oft-told story about Andrei Sakharov, the celebrated twentieth-century Soviet activist. Sakharov made his name working as a physicist on the development of the U.S.S.R.’s hydrogen bomb, at the height of the Cold War, but shot to global prominence after Leonid Brezhnev’s regime punished him for speaking publicly about the dangers of those weapons, and also about Soviet repression.

When an American friend was visiting Sakharov and his wife, the activist Yelena Bonner, in Moscow, the friend referred to Sakharov as a dissident. Bonner corrected him: “My husband is a physicist, not a dissident.”

This is a fundamental tension of building a principled dissident culture—it risks wrapping people up in a kind of negative identity, a cloak of what they are not. The Soviet dissidents understood their work as a struggle to uphold the laws and rights that were enshrined in the Soviet constitution, not as a fight against a regime.

“They were fastidious about everything they did being consistent with Soviet law,” Benjamin Nathans, a history professor at the University of Pennsylvania and the author of a book on Soviet dissidents, said. “I call it radical civil obedience.”

An affirmative vision of what the world should be is the inspiration for many of those who, in these tempestuous early months of Trump 2.0, have taken meaningful risks—acts of American dissent.

Consider Mariann Budde, the Episcopal bishop who used her pulpit before Trump on Inauguration Day to ask the President’s “mercy” for two vulnerable groups for whom he has reserved his most visceral disdain. For her sins, a congressional ally of the President called for the pastor to be “added to the deportation list.”..(More)”.

An excerpt from Everyday Habits for Transforming Systems by Adam Kahane: “Systems are structured to keep producing the behaviors and results they are producing, and therefore often seem solid and unchangeable—but they are not. They are built, and they collapse. They crack and are cracked, which opens up new possibilities that some people find frightening and others find hopeful. Radical engagement involves looking for, moving toward, and working with these cracks—not ignoring or shying away from them. We do this by seeking out and working with openings, alongside others who are doing the same…

Al Etmanski has pioneered the transformation of the living conditions of Canadians with disabilities, away from segregation, dependency, and second-class status toward connection, agency, and justice. I have spoken with him and studied what he and others have written about his decades of experience, and especially about how his strategy and approach have evolved and enabled him to make the contributions he has. He has advanced through repeatedly searching out and working with openings or cracks (breakdowns and bright spots) in the social-economic-political-institutional-cultural “disability system.”..(More)”.

Report by the International Energy Agency (IEA): “The development and uptake of artificial intelligence (AI) has accelerated in recent years – elevating the question of what widespread deployment of the technology will mean for the energy sector. There is no AI without energy – specifically electricity for data centres. At the same time, AI could transform how the energy industry operates if it is adopted at scale. However, until now, policy makers and other stakeholders have often lacked the tools to analyse both sides of this issue due to a lack of comprehensive data. 

This report from the International Energy Agency (IEA) aims to fill this gap based on new global and regional modelling and datasets, as well as extensive consultation with governments and regulators, the tech sector, the energy industry and international experts. It includes projections for how much electricity AI could consume over the next decade, as well as which energy sources are set to help meet it. It also analyses what the uptake of AI could mean for energy security, emissions, innovation and affordability…(More)”.

Paper by Marc Schuilenburg and Yarin Eski: “Why do people voluntarily give away their personal data to private companies? In this paper, we show how data sharing is experienced at the level of Tesla car owners. We regard Tesla cars as luxury surveillance goods for which the drivers voluntarily choose to share their personal data with the US company. Based on an analysis of semi-structured interviews and observations of Tesla owners’ posts on Facebook groups, we discern three elements of luxury surveillance: socializing, enjoying and enduring. We conclude that luxury surveillance can be traced back to the social bonds created by a gift economy…(More)”.

Article by Stefaan Verhulst: “After a long gestation period of three years, the European Health Data Space (EHDS) is now coming into effect across the European Union, potentially ushering in a new era of health data access, interoperability, and innovation. As this ambitious initiative enters the implementation phase, it brings with it the opportunity to fundamentally reshape how health systems across Europe operate. More generally, the EHDS contains important lessons (and some cautions) for the rest of the world, suggesting how a fragmented, reactive model of healthcare may transition to one that is more integrated, proactive, and prevention-oriented.

For too long, health systems–in the EU and around the world–have been built around treating diseases rather than preventing them. Now, we have an opportunity to change that paradigm. Data, and especially the advent of AI, give us the tools to predict and intervene before illness takes hold. Data offers the potential for a system that prioritizes prevention–one where individuals receive personalized guidance to stay healthy, policymakers access real-time evidence to address risks before they escalate, and epidemics are predicted weeks in advance, enabling proactive, rapid, and highly effective responses.

But to make AI-powered preventive health care a reality, and to make the EHDS a success, we need a new data governance approach, one that would include two key components:

• The ability to reuse data collected for other purposes (e.g., mobility, retail sales, workplace trends) to improve health outcomes.
• The ability to integrate different data sources–clinical records and electronic health records (EHRS), but also environmental, social, and economic data — to build a complete picture of health risks.

In what follows, we outline some critical aspects of this new governance framework, including responsible data access and reuse (so-called secondary use), moving beyond traditional consent models to a social license for reuse, data stewardship, and the need to prioritize high-impact applications. We conclude with some specific recommendations for the EHDS, built from the preceding general discussion about the role of AI and data in preventive health…(More)”.

Article by Adam Zable and Stefaan Verhulst: “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.

In our previous post, we shared emerging case studies across health, urban planning, the environment, and more. Several months later, the momentum has not only continued but diversified. New projects reaffirm NTD’s potential—especially when linked with traditional data, embedded in interdisciplinary research, and deployed in ways that are privacy-aware and impact-focused.

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:

• Financial Inclusion
• Public Health and Well-Being
• Socioeconomic Analysis
• Transportation and Urban Mobility
• Data Systems and Governance
• Economic and Labor Dynamics
• Digital Behavior and Communication…(More)”.

UNCTAD Report: Frontier technologies, particularly artificial intelligence (AI), are profoundly transforming our economies and societies, reshaping production processes, labour markets and the ways in which we live and interact. Will AI accelerate progress towards the Sustainable Development Goals, or will it exacerbate existing inequalities, leaving the underprivileged further behind? How can developing countries harness AI for sustainable development? AI is the first technology in history that can make decisions and generate ideas on its own. This sets it apart from traditional technologies and challenges the notion of technological neutrality.
The rapid development of AI has also outpaced the ability of Governments to respond effectively. The Technology and Innovation Report 2025 aims to guide policymakers through the complex AI
andscape and support them in designing science, technology and innovation (STI) policies that foster inclusive and equitable technological progress.
The world already has significant digital divides, and with the rise of AI, these could widen even further. In response, the Report argues for AI development based on inclusion and equity, shifting the focus from
technology to people. AI technologies should complement rather than displace human workers and production should be restructured so that the benefits are shared fairly among countries, firms and
workers. It is also important to strengthen international collaboration, to enable countries to co-create inclusive AI governance.

The Report examines five core themes:
A. AI at the technological frontier
B. Leveraging AI for productivity and workers’ empowerment
C. Preparing to seize AI opportunities
D. Designing national policies for AI
E. Global collaboration for inclusive and equitable AI…(More)”