Stefaan Verhulst
Paper by Kalena Cortes, Brian Holzman, Melissa D. Gentry & Miranda I. Lambert: “This study examines how digital incentives influence survey participation and engagement in a large randomized controlled trial of parents across seven Texas school districts. We test how incentive amount and information about vendor options affect response behavior and explore differences by language background. Incentivized parents were more likely to start and complete surveys and claim gift cards, though Spanish-speaking parents exhibited distinct patterns—greater completion rates but lower redemption rates, often selecting essential-goods vendors. Increasing incentive value and providing advance information both improved engagement. Findings inform the design of equitable, effective digital incentive strategies for diverse populations…(More)”.
World Bank Report: “Text and voice messages have emerged as a low-cost and popular tool for nudging recipients to change behavior. This paper presents findings from a randomized controlled trial designed to evaluate the impact of an information campaign using text and voice messages implemented in Punjab, Pakistan during the COVID-19-induced school closures. This campaign sought to increase study time and provide academic support while schools were closed and to encourage reenrollment when they opened, to reduce the number of dropouts. The campaign targeted girls enrolled in grades 5 to 7. Messages were sent out by a government institution, and the campaign lasted from October 2020 until November 2021, when schools had permanently re-opened. Households were randomized across three treatment groups and a control group that did not receive any messages. The first treatment group received gender-specific messages that explicitly referenced daughters in their households, and the second treatment group received gender-neutral messages. A third group was cross randomized across the first two treatment arms and received academic support messages (practice math problems and solutions). The results show that the messages increased reenrollment by 6.0 percentage points approximately three months after the intervention finished. Gender neutral messages (+8.9 percentage points) showed larger effect size on enrolment than gender-specific messages (+ 4.3 percentage points), although the difference is not statistically significant. The message program also increased learning outcomes by 0.2 standard deviation for Urdu and 0.2 standard deviation for math. The paper finds a small positive effect on the intensive margin of remote learning and an (equivalent) small negative effect on the intensive margin of outside tutoring. In line with similar studies on pandemic remediation efforts, the paper finds no effect of the academic support intervention on learning. The findings suggest that increased school enrollment played a role in supporting the observed increase in learning outcomes…(More)”.
Article by Tony Curzon Price: “Is 2026 the year that data collectives – unions, trusts, mutuals and clubs – tilt the balance of power in cyberspace away from mega-platforms and towards the citizen?
Last year, tech boss Sam Altman enabled ChatGPT to better remember past conversations in some jurisdictions, meaning that the AI might soon know us better than anyone else. In response to this sort of shift in power, we saw the creation of the First International Data Union (FIDU) to ensure that the data, knowledge and intimacy that Altman wants for ChatGPT would remain under members’ control and be managed according to their values.
Generative AI is causing a major overhaul of humanity’s life in cyberspace. There aren’t many examples of this sort of change – the web itself, Web 2.0 platforms, social media and mobile. The arrival of generative AI is upturning a decades-old equilibrium. ChatGPT has been the fastest-growing consumer application in history. It is displacing Google search in many lives. Open source models, especially from China, suggest that there are no natural moats in the technology, which means businesses can easily be overtaken by competitors with similar ideas.
Since the 2010s, many citizens and countries have become uncomfortable with how mega platforms have shaped the web. Scholars have pointed to these changes as important contributors to the deterioration of the mental health of children, the economic growth crisis and even falling global average IQs.
With the pieces of the cyberspace puzzle thrown into the air, citizens and governments do not want what happens next to be a repeat of what came before. Yet governments have discovered that their traditional policy tools against market power, like antitrust, are largely ineffective. Moreover, with the United States pushing back against tighter regulation abroad, even direct regulation by non-US states is proving difficult.
With other avenues of control largely defanged, this might be the moment for data unions. Data mutualisation promises to harness the collective power of citizens, providing a direct challenge to platforms…(More)”.
Article by Simon Ilyushchenko: “The Italian aphorism traduttore, traditore – the translator is a traitor – encapsulates a deep-seated suspicion about the act of translation: that to carry meaning from one language to another is always, to some degree, a corruption.
The writer and semiotician Umberto Eco took this charge seriously. In Experiences in Translation, Eco treats translation as an interpretive act – negotiation, compromise, loss. Every translation is an imperfect reproduction of the original. Every translator, in choosing what to preserve, chooses what to betray.
This is the situation confronting anyone who works with geospatial data – human or AI.
In 2019, Colombian researchers studied the relationship between armed conflict and forest cover in their country. Using the Global Forest Change dataset – a widely respected product derived from satellite imagery – they found something striking: if analysis is not done carefully, armed conflict appeared to be correlated with increases in forest cover.
One might infer, perversely, that violence was somehow good for forests. The authors’ interpretation of the ground data was the opposite.
Here is the mechanism they propose: armed conflict destabilized the rule of law, which enabled the rapid clearing of native forests for oil palm plantations. These plantations are monocultures – ecological deserts compared to the biodiverse forests they replaced. But to a satellite sensor, a mature oil palm plantation can read as ‘forest’. It has trees. The canopy closes. The pixels are green.
And even this example gets messy fast. The relationship between Colombian conflict and forest cover has generated substantial literature – but no consensus. Ganzenmüller et al. (2022) identified seven distinct categories of deforestation dynamics across Colombian municipalities; the same peace agreement drove opposite outcomes in different regions. Bodini et al. (2024), using loop analysis to model the socio-ecological system, found that causal pathways connecting violence, coca, cattle, and deforestation were so intertwined that their models for left-wing guerrilla dynamics showed “very low agreement with observed correlations.” The data didn’t fit a simple narrative – any simple narrative…(More)”.
Article by Thomas R. Karl, Stephen C. Diggs, Franklin Nutter, Kevin Reed, and Terence Thompson: “From farming and engineering to emergency management and insurance, many industries critical to daily life rely on Earth system and related socioeconomic datasets. NOAA has linked its data, information, and services to trillions of dollars in economic activity each year, and roughly three quarters of U.S. Fortune 100 companies use NASA Earth data, according to the space agency.
Such data are collected in droves every day by an array of satellites, aircraft, and surface and subsurface instruments. But for many applications, not just any data will do.
Leaving reference quality datasets (RQDs) to languish, or losing them altogether, would represent a dramatic shift in the country’s approach to managing environmental risk.
Trusted, long-standing datasets known as reference quality datasets (RQDs) form the foundation of hazard prediction and planning and are used in designing safety standards, planning agricultural operations, and performing insurance and financial risk assessments, among many other applications. They are also used to validate weather and climate models, calibrate data from other observations that are of less than reference quality, and ground-truth hazard projections. Without RQDs, risk assessments grow more uncertain, emergency planning and design standards can falter, and potential harm to people, property, and economies becomes harder to avoid.
Yet some well-established, federally supported RQDs in the United States are now slated to be, or already have been, decommissioned, or they are no longer being updated or maintained because of cuts to funding and expert staff. Leaving these datasets to languish, or losing them altogether, would represent a dramatic—and potentially very costly—shift in the country’s approach to managing environmental risk…(More)”.
Paper by Cheng-Chun Lee et al: “Using novel data and artificial intelligence (AI) technologies in crisis resilience and management is increasingly prominent. AI technologies have broad applications, from detecting damages to prioritizing assistance, and have increasingly supported human decision-making. Understanding how AI amplifies or diminishes specific values and how responsible AI practices and governance can mitigate harmful outcomes and protect vulnerable populations is critical. This study presents a responsible AI roadmap embedded in the Crisis Information Management Circle. Through three focus groups with participants from diverse organizations and sectors and a literature review, we develop six propositions addressing important challenges and considerations in crisis resilience and management. Our roadmap covers a broad spectrum of interwoven challenges and considerations on collecting, analyzing, sharing, and using information. We discuss principles including equity, fairness, explainability, transparency, accountability, privacy, security, inter-organizational coordination, and public engagement. Through examining issues around AI systems for crisis management, we dissect the inherent complexities of information management, governance, and decision-making in crises and highlight the urgency of responsible AI research and practice. The ideas presented in this paper are among the first attempts to establish a roadmap for actors, including researchers, governments, and practitioners, to address important considerations for responsible AI in crisis resilience and management…(More)”.
Article by Dilek Fraisl et al: “The termination in February 2025 of the Demographic and Health Surveys, a critical source of data on population, health, HIV, and nutrition in over 90 countries, supported by the United States Agency for International Development, constitutes a crisis for official statistics. This is particularly true for low- and middle-income countries that lack their own survey infrastructure1. At a national level, in the United States, proposed cuts to the Environmental Protection Agency by the current administration further threaten the capacity to monitor and achieve environmental sustainability and implement the SDGs2,3. Citizen science—data collected through voluntary public contributions—now can and must step up to fill the gap and play a more central role in official statistics.
Demographic and Health Surveys contribute directly to the calculation of around 30 of the indicators that underpin the Sustainable Development Goals (SDGs)4. More generally, a third of SDG indicators rely on household surveys data5.
Recent political changes, particularly in the United States, have exposed the risks of relying too heavily on a single country or institution to run global surveys and placing minimal responsibility on individual countries for their own data collection.
Many high-income countries, particularly European ones, are experiencing similar challenges and financial pressures on their statistical systems as their national budgets are increasingly prioritizing defense spending6. Along with these budget cuts comes a risk that perceived efficiency gains from artificial intelligence are increasingly viewed as a pretense to put further budgetary pressure on official statistical agencies7.
In this evolving environment, we argue that citizen science can become an essential part of national data gathering efforts. To date, policymakers, researchers, and agencies have viewed it as supplementary to official statistics. Although self-selected participation can introduce bias, citizen science provides fine-scale, timely, cost-efficient, and flexible data that can fill gaps and help validate official statistics. We contend that, rather than an optional complement, citizen science data should be systematically integrated into national and global data ecosystems…(More)”.
Working Paper by Geoff Mulgan and Caio Werneck: “City governments across the world usually organise much of their work through functional hierarchies – departments or secretariats with specialised responsibility for transport, housing, sanitation, education, environment and so on. Their approaches mirror those of national governments and the traditional multi-divisional business which had separate teams for manufacturing, marketing, sales, and for different product lines.
Those hierarchical structures became the norm in the late 19th century and they still work well for stable, bounded problems. They ensure clear accountability; a concentration of specialised knowledge; and a means to engage relevant stakeholders. Often, they bring together officials and professionals with a strong shared ethos – whether for policing or education, transport or housing.
But vertical silos have also always created problems. Many priorities don’t fit them neatly. Sometimes departments clash, or dump costs onto each other. They may fail to share vital information.
There is a long history of attempts to create more coherent, coordinated ways of working, and as cities face overlapping emergencies (from pandemics to climate disasters), and slow-burning crises (in jobs, care, security and housing) that cut across these silos, many are looking for new ways to coordinate action.
Some of the new options make the most of digital technologies which make it much easier to organise horizontally – with shared platforms, data or knowledge, or one-stop shops or portals for citizens. Some involve new roles (for digital, heat or resilience), new types of team or task force (such as I-Teams for innovation). And many involve new kinds of partnership or collaboration, with mesh-like structures instead of the traditional pyramid hierarchies of public administration…(More)”
Paper by Edith Darin: “The digital era has transformed the production and governance of demographic figures, shifting it from a collective, state-led endeavour to one increasingly shaped by private actors and extractive technologies. This paper analyses the implications of these shifts by tracing the evolving status of demographic figures through the lens of Ostrom’s typology of goods: from a club good in royal censuses, to a public good under democratic governance, and now towards a private asset whose collection has become rivalrous and its dissemination excludable. Drawing on case studies involving satellite imagery, mobile phone data, and social media platforms, the study shows how new forms of passive data collection while providing previously unseen data opportunities, disrupt also traditional relationships between states and citizens, raise ethical and epistemic concerns, and challenge the legitimacy of national statistical institutes. In response, the paper advocates for the reconstitution of demographic figures as a common good, proposing a collective governance model that includes increased transparency, the sharing of anonymised aggregates, and the creation of a Public Demographic Data Library to support democratic accountability and technical robustness in demographic knowledge production…(More)”.
Report by OpenAI: “More than 5% of all ChatGPT messages globally are about healthcare, averaging billions of messages each week. Of our more than 800 million regular users, one in four submits a prompt about healthcare every week. More than 40 million turn to ChatGPT every day with healthcare questions.
In the United States, the healthcare system is a long-standing and worsening pain point for many. Gallup finds that views of US healthcare quality have sunk to a 24-year-low; that Americans give the system a C+ on access and a D+ on costs; and that a combined 70% believe the system has major problems or is in a state of crisis. In our own research, three in five Americans say the current system is broken, and strong majorities tell us that hospital costs (87%), poor healthcare access (77%), and a lack of nurses (75%) are all serious problems.
For both patients and providers in the US, ChatGPT has become an important ally, helping people navigate the healthcare system, enabling them to self-advocate, and supporting both patients and providers for better health outcomes.
Based on anonymized ChatGPT message data:
– Nearly 2 million messages per week focus on health insurance, including for comparing plans, understanding prices, handling claims and billing, eligibility and enrollment, and coverage and cost-sharing details.
– In underserved rural communities, users send an average of nearly 600,000 healthcare-related messages every week.
– And seven in 10 healthcare conversations in ChatGPT happen outside of normal clinic hours.
This report details: (1) how users are turning to ChatGPT for help in navigating the US healthcare system; (2) how they’re turning to ChatGPT to help them close healthcare access gaps, including in “hospital deserts” across the country; and (3) how healthcare providers and workers are using AI in their roles now…(More)”.