To Understand Global Migration, You Have to See It First

Curated on Posted on by Stefaan Verhulst

Data visualization by The New York Times: “In the maps below, Times Opinion can provide the clearest picture to date of how people move across the globe: a record of permanent migration to and from 181 countries based on a single, consistent source of information, for every month from the beginning of 2019 through the end of 2022. These estimates are drawn not from government records but from the location data of three billion anonymized Facebook users all over the world.

The analysis — the result of new research published on Wednesday from Meta, the University of Hong Kong and Harvard University — reveals migration’s true global sweep. And yes, it excludes business travelers and tourists: Only people who remain in their destination country for more than a year are counted as migrants here.

The data comes with some limitations. Migration to and from certain countries that have banned or restricted the use of Facebook, including China, Iran and Cuba, is not included in this data set, and it’s impossible to know each migrant’s legal status. Nevertheless, this is the first time that estimates of global migration flows have been made publicly available at this scale. The researchers found that from 2019 to 2022, an annual average of 30 million people — approximately one-third of a percent of the world’s population — migrated each year.

If you would like to see the data behind this analysis for yourself, we made an interactive tool that you can use to explore the full data set…(More)”

Inside arXiv—the Most Transformative Platform in All of Science

Curated on Posted on by Stefaan Verhulst

Article by Sheon Han: “Nearly 35 years ago, Ginsparg created arXiv, a digital repository where researchers could share their latest findings—before those findings had been systematically reviewed or verified. Visit arXiv.org today (it’s pronounced like “archive”) and you’ll still see its old-school Web 1.0 design, featuring a red banner and the seal of Cornell University, the platform’s institutional home. But arXiv’s unassuming facade belies the tectonic reconfiguration it set off in the scientific community. If arXiv were to stop functioning, scientists from every corner of the planet would suffer an immediate and profound disruption. “Everybody in math and physics uses it,” Scott Aaronson, a computer scientist at the University of Texas at Austin, told me. “I scan it every night.”

Every industry has certain problems universally acknowledged as broken: insurance in health care, licensing in music, standardized testing in education, tipping in the restaurant business. In academia, it’s publishing. Academic publishing is dominated by for-profit giants like Elsevier and Springer. Calling their practice a form of thuggery isn’t so much an insult as an economic observation. Imagine if a book publisher demanded that authors write books for free and, instead of employing in-house editors, relied on other authors to edit those books, also for free. And not only that: The final product was then sold at prohibitively expensive prices to ordinary readers, and institutions were forced to pay exorbitant fees for access…(More)”.

Data Cooperatives: Democratic Models for Ethical Data Stewardship

Curated on Posted on by Stefaan Verhulst

Paper by Francisco Mendonca, Giovanna DiMarzo, and Nabil Abdennadher: “Data cooperatives offer a new model for fair data governance, enabling individuals to collectively control, manage, and benefit from their information while adhering to cooperative principles such as democratic member control, economic participation, and community concern. This paper reviews data cooperatives, distinguishing them from models like data trusts, data commons, and data unions, and defines them based on member ownership, democratic governance, and data sovereignty. It explores applications in sectors like healthcare, agriculture, and construction. Despite their potential, data cooperatives face challenges in coordination, scalability, and member engagement, requiring innovative governance strategies, robust technical systems, and mechanisms to align member interests with cooperative goals. The paper concludes by advocating for data cooperatives as a sustainable, democratic, and ethical model for the future data economy…(More)”.

Behavioral AI: Unleash Decision Making with Data

Curated on Posted on by 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)”

Working With Cracks

Curated on Posted on by Stefaan Verhulst

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)”.

Energy and AI

Curated on Posted on by Stefaan Verhulst

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)”.

The Future of Health Is Preventive — If We Get Data Governance Right

Curated on Posted on by Stefaan Verhulst

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)”.

Unlocking Public Value with Non-Traditional Data: Recent Use Cases and Emerging Trends

Curated on Posted on by Stefaan Verhulst

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)”.

2025 Technology and innovation report

Curated on Posted on by Stefaan Verhulst

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)”

Fostering Open Data

Curated on Posted on by Stefaan Verhulst

Paper by Uri Y. Hacohen: “Data is often heralded as “the world’s most valuable resource,” yet its potential to benefit society remains unrealized due to systemic barriers in both public and private sectors. While open data-defined as data that is available, accessible, and usable-holds immense promise to advance open science, innovation, economic growth, and democratic values, its utilization is hindered by legal, technical, and organizational challenges. Public sector initiatives, such as U.S. and European Union open data regulations, face uneven enforcement and regulatory complexity, disproportionately affecting under-resourced stakeholders such as researchers. In the private sector, companies prioritize commercial interests and user privacy, often obstructing data openness through restrictive policies and technological barriers. This article proposes an innovative, four-layered policy framework to overcome these obstacles and foster data openness. The framework includes (1) improving open data infrastructures, (2) ensuring legal frameworks for open data, (3) incentivizing voluntary data sharing, and (4) imposing mandatory data sharing obligations. Each policy cluster is tailored to address sector-specific challenges and balance competing values such as privacy, property, and national security. Drawing from academic research and international case studies, the framework provides actionable solutions to transition from a siloed, proprietary data ecosystem to one that maximizes societal value. This comprehensive approach aims to reimagine data governance and unlock the transformative potential of open data…(More)”.