Stefaan Verhulst
Paper by Federico Bartolomucci, Edoardo Ramalli and Valeria Maria Urbano: “The potential benefits deriving from inter-organizational data sharing have increased over time, leading to an intensified interest in data ecosystems. The governance of these endeavors depends on both collaborative and data governance dimensions. However, previous research has often treated these dimensions separately, creating silos that hinder the capacity to deliver value considering their socio-technical nature. Addressing this gap, this study investigates the intertwined relationship between these two dimensions within data ecosystems. It does so by questioning which existing and most relevant relationships exist between them, as well as the nature of these relationships. To this end, we adopt a multiple case study approach, analyzing five data ecosystems. The research led to the development of a conceptual framework for Integrated Governance, highlighting the need for a holistic socio-technical approach that addresses collaborative and data governance dimensions as intertwined. The framework unveils 24 core relationships between these dimensions in data ecosystems and provides insights on the nature of the relationships, distinguishing among causal, explanatory, concurrent, chronological, and overlapping ones. This work introduces a new perspective in the academic discourse on data sharing providing actionable insights for practitioners and enabling them to design and manage data ecosystems more effectively…(More)”.
Article by Julia Angwin: “We are in a phone war. Ever since cameras became embedded in cellphones, people have been using their devices to bear witness to state violence. But now, the state is striking back.
I don’t think it is any coincidence that Alex Pretti was holding his phone when he was shot to death by federal agents in Minneapolis. Or that Renee Good’s partner was filming a federal agent seconds before he killed Ms. Good. Agents have repeatedly knocked phones out of the hands of observers. They have beaten people filming them and followed them to their homes and threatened them. Of the 19 shootings by federal agents in the past year identified by The Trace, a news outlet that investigates gun violence, at least four involved people who were observing or documenting federal agents’ actions.
Courts have long granted citizens a First Amendment right to film in public. But this right on paper is now being increasingly contested on the streets as federal agents try to stop citizens from recording their activities…
Government officials have openly equated filming an agent with violence in statements and in court testimony. In July, Homeland Security Secretary Kristi Noem said that violence against agents includes “videotaping them where they are at, when they are out on operations.”
The nation’s founders worried that if the state had a monopoly on weapons, its citizens could be oppressed. Their answer was the Second Amendment. Now that our phones are the primary weapons of today’s information war, we should be as zealous about our right to bear phones as we are about our right to bear arms. To adopt the language of Second Amendment enthusiasts, perhaps the only thing that can eventually stop a bad guy with a gun is a good guy with a camera…(More)”
Article with Sami Mahroum: “In my experimentation with AI-augmented policy analysis for government clients, I have found that these systems excel at what I call “sentiment-aware policy design.” While traditional tools might show that a congestion charge reduces traffic by 22%, AI systems can remind you that the term “congestion charge” polls substantially worse than “clean-air fee”; that implementation during election years multiplies political risk; and that exempting delivery vehicles creates coalition-building possibilities with small-business groups.
The point isn’t to replace human judgment. It is to make experienced insiders’ implicit political knowledge more explicit, systematic, and testable. With AI, the abstract-rationality crowd gets quantitative rigor, the bounded-rationality practitioners get political intelligence, and – crucially – both can see the other’s perspective clearly.
Moreover, when combined with web-search capabilities, AI tools can contribute near-real-time sentiment analysis. This matters because policies designed to address last quarter’s concerns might no longer fit the political terrain when they launch in the coming quarter. By the time a pension reform reaches parliament, murmurs of a recession may have changed voters’ priorities entirely.
AI-powered analysis can reveal how specific issues are being discussed across news, social media, parliamentary debates, stakeholder communications, and other channels. It can identify rising concerns and flag when a window of political opportunity has opened or closed. Such insights can help governments counter the perception that they are slow, deaf, and disconnected from everyday realities. AI cannot make governments omniscient, but it can make them more responsive and less blind to the political consequences of technical decisions.
The high-trust technocracies succeed partly because they have systematized the integration of technical excellence with political responsiveness. Now, AI offers democracies the means to do so as well…(More)”.
Article by Brian Callaci and Sandeep Vaheesan: “…The scholarship on state capacity emphasizes the plurality and unevenness of state capacities. For example, states can strengthen their capacities in some areas, such as repression, while self-consciously weakening their capacities in others, such as corporate regulation. States exercise their power for different ends and use assorted means, some good, some bad. Some state agencies deliver health care for millions, while others target working-class people through tax audits and imprisonment. Moreover, we care not just about the state’s capacity to act, but also about the democratic legitimacy of those actions. States make some decisions through democratic means, such as legislation and regulation based on public input and consultation, and others through undemocratic methods, such as court decisions. And while state capacity entails the ability of the state to pursue its own goals autonomously from powerful social groups such as large corporations, there are other social groups, like poor communities suffering the effects of environmental racism, that do not have enough power to influence the state.
Taxation, spending, regulation, and public provision are all aspects of state capacity. A prerequisite for a state that meets even Weber’s minimal criteria would be fiscal capacity: the ability to collect taxes and direct public resources to the state’s desired ends. On the taxation front, U.S. state capacity is clearly heading in the wrong direction, with corporations and wealthy individuals openly pursuing a multitude of tax avoidance strategies with little fear of negative consequences. At the sub-federal level, states and municipalities compete with one another for private investment via offers of deregulation and subsidies, allowing powerful corporations to choose the level of regulation and taxation they desire. On the spending side, the federal government’s reliance on private contractors and unwillingness to use its bargaining power as a large buyer means it has limited control over military procurement costs…(More)”.
Blog by Mohamed Shareef: “…For two decades, Asian governments have counted broadband subscriptions, celebrated connectivity percentages, and commissioned policy frameworks.
Meanwhile, fishing communities in the Maldives still can’t afford 1GB of data, Pakistani e-government services crash during internet disruptions, and Tongan government operations collapsed for five weeks after a volcanic eruption severed their only submarine cable.
The gap between digital strategy documents and actual service delivery has never been wider. Here’s how Asian governments can close it.
Measure what citizens actually experience
Your ministry reports 85 per cent internet penetration. But can your citizens actually access government services during monsoon season when submarine cables fail? Can rural hospitals use your telemedicine platform on 3G networks? What percentage of median household income does meaningful connectivity actually cost? For Asian governments, this means replacing vanity metrics with citizen-centered measurements:
Instead of: “Fiber deployed to 500 district” . Measure: “Healthcare centers in 500 districts can access national health records during extreme weather events”
Instead of: “75 per cent smartphone penetration”. Measure: “Percentage of citizens who can afford data plans sufficient for essential government services”
Instead of: “E-government portal launched”. Measure: “Government services accessible to citizens using entry-level devices on congested networks”
Bangladesh’s experience with biometric identity systems, India’s Aadhaar implementation challenges, and Indonesia’s struggles with connectivity in remote islands offer lessons. The question isn’t whether you have digital infrastructure. It’s whether that infrastructure delivers services when citizens need them most…(More)”.
Paper by Pietro Bini, Lin William Cong, Xing Huang & Lawrence J. JinDo generative AI models, particularly large language models (LLMs), exhibit systematic behavioral biases in economic and financial decisions? If so, how can these biases be mitigated? Drawing on the cognitive psychology and experimental economics literatures, we conduct the most comprehensive set of experiments to date—originally designed to document human biases—on prominent LLM families across model versions and scales. We document systematic patterns in LLM behavior. In preference-based tasks, responses become more human-like as models become more advanced or larger, while in belief-based tasks, advanced large-scale models frequently generate rational responses. Prompting LLMs to make rational decisions reduces biases…(More)”.
Paper by Sándor Juhász, Johannes Wachs, Jermain Kaminski and César A. Hidalgo: “Despite the growing importance of the digital sector, research on economic complexity and its implications continues to rely mostly on administrative records—e.g. data on exports, patents, and employment—that have blind spots when it comes to the digital economy. In this paper we use data on the geography of programming languages used in open-source software to extend economic complexity ideas to the digital economy. We estimate a country’s software economic complexity index (ECIsoftware) and show that it complements the ability of measures of complexity based on trade, patents, and research to account for international differences in GDP per capita, income inequality, and emissions. We also show that open-source software follows the principle of relatedness, meaning that a country’s entries and exits in programming languages are partly explained by its current pattern of specialization. Together, these findings help extend economic complexity ideas and their policy implications to the digital economy…(More)”.
Article by Elie Dolgin: “AI is turning scientists into publishing machines—and quietly funneling them into the same crowded corners of research.
That’s the conclusion of an analysis of more than 40 million academic papers, which found that scientists who use AI tools in their research publish more papers, accumulate more citations, and reach leadership roles sooner than peers who don’t.
But there’s a catch. As individual scholars soar through the academic ranks, science as a whole shrinks its curiosity. AI-heavy research covers less topical ground, clusters around the same data-rich problems, and sparks less follow-on engagement between studies.
The findings highlight a tension between personal career advancement and collective scientific progress, as tools such as ChatGPT and AlphaFold seem to reward speed and scale—but not surprise.
“You have this conflict between individual incentives and science as a whole,” says James Evans, a sociologist at the University of Chicago who led the study.
And as more researchers pile onto the same scientific bandwagons, some experts worry about a feedback loop of conformity and declining originality. “This is very problematic,” says Luís Nunes Amaral, a physicist who studies complex systems at Northwestern University. “We are digging the same hole deeper and deeper.”
Evans and his colleagues published the findings 14 January in the journal Nature…(More)”.
Article by Mike McIntire: “Genetic researchers were seeking children for an ambitious, federally funded project to track brain development — a study that they told families could yield invaluable discoveries about DNA’s impact on behavior and disease.
They also promised that the children’s sensitive data would be closely guarded in the decade-long study, which got underway in 2015. Promotional materials included a cartoon of a Black child saying it felt good knowing that “scientists are taking steps to keep my information safe.”
The scientists did not keep it safe.
A group of fringe researchers thwarted safeguards at the National Institutes of Health and gained access to data from thousands of children. The researchers have used it to produce at least 16 papers purporting to find biological evidence for differences in intelligence between races, ranking ethnicities by I.Q. scores and suggesting Black people earn less because they are not very smart.
Mainstream geneticists have rejected their work as biased and unscientific. Yet by relying on genetic and other personal data from the prominent project, known as the Adolescent Brain Cognitive Development Study, the researchers gave their theories an air of analytical rigor…(More)”.
Report by Access Partnerships: “AI is reshaping work at a pace that most labor market information systems were not built to measure. Against this backdrop, the pressing question is not simply “who works where?” as it used to be in the past, but what people actually do, what skills they use, and how AI is changing tasks inside roles.
Today, many countries still rely on infrequent surveys, broad occupational categories, and siloed administrative datasets. That makes it harder to spot early signals of changing skills demand, target training investment, or support employers and workers as AI adoption accelerates.
Modernizing labor market data for the AI age
Our report, developed in partnership with Workday, helps governments modernize labor market data systems to better navigate AI-driven change. It establishes a global baseline across 21 countries, identifies system gaps, and sets out a practical pathway to strengthen readiness over time.
At the center is a maturity framework benchmarking countries across six dimensions of AI-ready labor market data: Forecasting readiness, Labor market granularity, Accessibility, Interoperability and integration, and Real-time responsiveness (FLAIR)…(More)”.