Stefaan Verhulst

Article by Stefaan Verhulst: “The European Union’s pursuit to create a single data market has always been a balancing act between fostering public interest goals and safeguarding private enterprise. The Data Act (Regulation (EU) 2023/2854), which became applicable on September 12 2025, codified this tension, particularly in its Business-to-Government (B2G) provisions under Chapter V.

Initially, these provisions required data holders to share data with public sector bodies in cases of “exceptional need”, which was divided into two tracks: urgent Public Emergencies and non-emergency Public Interest Tasks.

However, the European Commission’s Digital Omnibus Package, published last month, has signaled a definitive pivot. The core message: B2G data sharing is now being refined and confined as a measure of last resort. This narrowing protects the private sector but simultaneously creates a critical challenge: without a designated data steward within both the public and private sector this restrictive, haphazard approach will fail to build the trusted, long-term data ecosystems necessary to address emergency and non-emergency, systemic societal challenges…(More)”.

Report by the American Statistical Association (ASA):”… The report documents significant challenges facing the 13 federal statistical agencies and outlines nine new recommendations to strengthen the nation’s statistical infrastructure.

Federal statistics—produced by agencies including the Bureau of Labor Statistics, the Census Bureau and the National Center for Health Statistics—serve as essential infrastructure for economic policy, public health decisions and democratic governance. These data inform everything from interest rate decisions to public health responses and business planning.

“Federal statistics are fundamental infrastructure, similar to roads, bridges and power grids,” said ASA Executive Director Ron Wasserstein. “This report shows that immediate investment and coordination are needed to ensure these agencies can meet current and future information needs.”

Key Findings

The report documents the following concerning trends:

• Staffing losses: Most agencies have lost 20-30% of their staff, affecting their ability to innovate and meet expanding demands for more timely and granular data.
• Budget constraints: Eight of 13 agencies have lost at least 16% of purchasing power since FY2009, even as congressional mandates have increased.
• Declining public trust: The percentage of US.adults who trust federal statistics declined from 57% in June 2025 to 52% in September 2025, according to surveys conducted by NORC at the University of Chicago.
• System coordination challenges: The decentralized structure of the federal statistical system, while promoting subject-matter expertise, lacks dedicated funding for system-wide initiatives such as joint IT upgrades and coordinated data-sharing…(More)”.

Essay by Daniel Benaim: “When U.S. President Donald Trump visited the Arab Gulf in May, his focus was not on Gaza, Iran, or even normalization between Israel and Saudi Arabia. Instead, it was on business deals and, above all, artificial intelligence. During the trip, Trump agreed to sell advanced U.S. chips to Saudi Arabia and the United Arab Emirates and to invest in AI mega-campuses in the Gulf that will host U.S. firms. One such site, in Abu Dhabi, could become the worldʼs largest concentrated cluster of the computing power fueling artificial intelligence. The Gulf countries, in turn, promised to invest tens of billions of dollars in AI on U.S. soil. And last month, during his trip to Washington, Saudi Crown Prince Mohammed bin Salman (also known as MBS) won final approval to import tens of thousands of advanced U.S. semiconductors, which had been promised to Saudi Arabia earlier in the year.

Armed with chips, sovereign wealth, and abundant energy, Gulf states could surpass Europe and India in terms of AI infrastructure—eventually becoming the world’s third biggest hub for AI computing power, behind the United States and China. Computing power has now taken its place alongside crude oil as a pillar of the U.S.-Gulf relationship, and the Gulf states have become a partner of first resort for the Trump administration.

The upside of this AI cooperation is significant. If done right, the deals will channel the vast wealth of Gulf states into American AI companies and allow these firms to expand to areas with few power and permitting bottlenecks. With the Gulf’s connectivity to surrounding regions, the reach of the United States’ AI stack—that is, the layers of hardware and software that AI is built on—could extend to billions of users across Africa, Central Asia, and the Middle East. The deals could also enable the United States to dislodge China as the Gulf’s top technology partner, which would be a big win for Washington over Beijing…(More)”.

Paper by Liza Dahiya & Rachit Bagga: “Social media platforms, particularly Reddit’s r/Epilepsy community, offer a unique perspective into the experiences of people with epilepsy (PWE) & their caregivers. This study analyzes 57k posts & 533k comments to uncover linguistic, emotional, and thematic patterns across demographics such as age, gender, and relationship to the PWE. We identify significant variation in language and discussion topics across these groups, as validated by statistical tests and topic modeling. Group-specific concerns emerged: teenagers frequently discuss marijuana and gaming-related triggers; women emphasize pregnancy and hormonal impacts; and caregivers, particularly parents and romantic partners, express a heightened emotional burden. We further examine the prevalence of depression signals across demographics, revealing that 39.75% of posts exhibit signs of severe depression, frequently co-occurring with anxiety and emotional distress. To quantify engagement within the community, we introduce a novel metric, F(P), which integrates post length, sentiment polarity, and readability. Posts expressing emotional or mental health concerns show significantly higher F(P) scores, underscoring the platform’s potential as a real-time support and outreach mechanism…(More)”.

Paper by Sebastian Singler, Ali A. Guenduez & Mehmet A. Demircioglu: “Public sector innovations often fail if they do not meet citizens’ expectations. However, little is known about how well public servants understand these expectations. This study identifies a perception gap between citizens and public servants regarding innovation characteristics, which are specific attributes of public sector innovations that shape citizen support and legitimacy. Using Q-methodology with Swiss citizens and public servants, we identify four distinct citizen groups: result-centric, trust-centric, certainty-centric, and cost- and rule-of-law-centric. Each group emphasizes different characteristics, such as ease of use, efficiency, trialability, and trust. By contrast, public servants perceive only three homogenized citizen groups – customer-centric, trust-centric, and result-centric – overlooking expectations related to democratic participation and co-creation. This mismatch risks undermining the legitimacy and adoption of innovations. The study advances a citizen-centred view of innovation characteristics, highlights the importance of citizen heterogeneity, and provides practical guidance on designing innovations that align with diverse citizen expectations…(More)”.

Article by Emanuel Maiberg: “Online survey research, a fundamental method for data collection in many scientific studies, is facing an existential threat because of large language models, according to new research published in the Proceedings of the National Academy of Sciences (PNAS). The author of the paper, associate professor of government at Dartmouth and director of the Polarization Research Lab Sean Westwood, created an AI tool he calls “an autonomous synthetic respondent,” which can answer survey questions and “demonstrated a near-flawless ability to bypass the full range” of “state-of-the-art” methods for detecting bots. 

According to the paper, the AI agent evaded detection 99.8 percent of the time.

“We can no longer trust that survey responses are coming from real people,” Westwood said in a press release. “With survey data tainted by bots, AI can poison the entire knowledge ecosystem.”

Survey research relies on attention check questions (ACQs), behavioral flags, and response pattern analysis to detect inattentive humans or automated bots. Westwood said these methods are now obsolete after his AI agent bypassed the full range of standard ACQs and other detection methods outlined in prominent papers, including one paper designed to detect AI responses. The AI agent also successfully avoided “reverse shibboleth” questions designed to detect nonhuman actors by presenting tasks that an LLM could complete easily, but are nearly impossible for a human…(More)”.

Article by Wycliffe Muia: “Kenya has signed a historic five-year health agreement with the US, the first such pact since Donald Trump’s administration overhauled its foreign aid programme.

The $2.5bn (£1.9bn) deal is aimed at combating infectious diseases in Kenya, with similar agreements expected to be rolled out in other African countries aligned with Trump’s broader foreign policy goals.

The government-to-government deal aims to boost transparency and accountability but has raised fears it could give the US real-time access to critical health databases, including sensitive patient information.

Kenya’s Health Minister Aden Duale sought to allay such fears, saying “only de-identified, aggregated data” would be shared…However, some Kenyans are demanding the disclosure of the full agreement, with fears that it would allow the US to view personal medical records such as the HIV status, TB treatment history, and vaccination data of Kenyan patients.

“What specific data categories are being shared? Are genomic data, disease patterns, mental health data, insurance claims, hospital records, or biometrics included? If not, why is that not explicitly written?” lawyer Willis Otieno posted on X.

Well-known whistle-blower Nelson Amenya voiced similar concerns, urging the Kenyan government to release the full agreement so “we can read it for ourselves”.

Minister Duale has dismissed such fears, insisting that Kenya’s health data remained secure and fully protected by Kenyan laws.

“Your health data is a national strategic asset,” Duale added.

US officials are yet to comment on the data concerns…(More)”.

Press Release: “The Linux Foundation, the nonprofit organization enabling mass innovation through open source, today announced the formation of the Agentic AI Foundation (AAIF), and founding contributions of three leading projects driving innovation in open source AI; Anthropic’s Model Context Protocol (MCP), Block’s goose, and OpenAI’s AGENTS.md.

The advent of agentic AI represents a new era of autonomous decision making and coordination across AI systems that will transform and revolutionize entire industries. The AAIF provides a neutral, open foundation to ensure this critical capability evolves transparently, collaboratively, and in ways that advance the adoption of leading open source AI projects. Its inaugural projects, AGENTS.md, goose and MCP, lay the groundwork for a shared ecosystem of tools, standards, and community-driven innovation…

The launch of the AAIF comes just one year after the release of MCP by Anthropic, provider of advanced AI systems grounded in safety research, including Claude and the Claude Developer Platform. MCP has rapidly become the universal standard protocol for connecting AI models to tools, data and applications, with more than 10,000 published MCP servers now covering everything from developer tools to Fortune 500 deployments. The protocol has been adopted by Claude, Cursor, Microsoft Copilot, Gemini, VS Code, ChatGPT and other popular AI platforms, as developers and enterprises gravitate toward its simple integration method, security controls, and faster deployment…(More)”.

Conversation between Barrett and Greene and Nicklas Berild Lundblad: “…Q. How do you best use technology to facilitate that learning?

NBL:  The first question you ask before you use technology is “What is the problem I want to solve?” To some degree, this can be a political exercise with great value. You can ask citizens, “What are the ten most pressing problems in our city that we need to solve.”

Once you know that, look for the data; look for the solutions. Look for the different things you need to learn about your city to solve the problems.

Q. In your experience, do governments know the right questions to ask?

NBL: When I worked at Google, one of the things that we said when we went to a government or to a business was “We have this amazing technology. What can it do to answer your questions?” Nine cases out of ten, people would say “We don’t know what our questions are.” 

That’s because modern institutions are not built to generate questions or to encourage curiosity in a way that encourages learning over time.

Q. What are some of the ways in which cities around the world are expanding the kinds of data that will help them learn?

NBL: Sensors provide a whole range of data we never had access to before and they have become measurably cheaper in the last couple of decades and are now biodegradable, so you don’t need to worry about spreading them out. Barcelona and other European cities have been installing sensors but then the question is “What do you want to do with the sensor data?”’ It’s the first question you ask yourself before you use technology. What is the problem you want to solve?

You can have sensors that measure pollution in an area and sensors that measure noise and they are really interesting because they allow you to slowly improve on the general living environment of a city. Sensors that measure movements give us a sense of what the rhythms and flows of the city are. 

For technologists, a super interesting question is what kinds of sensors do you give? What kind would you refrain from giving? A camera is a sensor, but you may not want cameras everywhere as that leads you to a discussion about surveillance…(More)”.

Article by Kevin Starr: “Sometimes a prosaic AI query produces something that looks more like parody. The other day, I asked Claude to give me the latest definition of “impact investing” and it served up this gem:

“There’s ongoing discussion in 2024 about whether the definition should evolve beyond intentionality toward emphasizing real-world change and the additionality of capital.”

The conclusion of that discussion was basically, “Um, no.” And the increasingly obvious reason is that “real-world change” often requires something less than market rates of return. I’m old enough to remember the heady days when impact investing was about “patient capital” and concessionary finance and maybe—gasp—trying to be accountable for impact. Now what we get is “intentionality.”

And sometimes we don’t even get that. Anyone who works in Sub-Saharan Africa has witnessed the steady dwindling of capital that would qualify for even the most generous definition of impact investing. There are continually fewer practitioners, investing continually less money, and trying to mitigate risk with increasingly onerous due diligence. Given the dramatic contraction of Big Aid, we need market-based solutions more than ever, and it’s a really bad time for impact investing to be failing us.

Luckily, I have a solution to the myriad disappointments of impact investing: Get rid of it.

The fundamental problem is that impact investing is neither fish nor fowl. Philanthropists look at the returns impact investors are seeking and think they’re greedy. Investors look at the concessionary deals necessary to drive “real world change” and think they’re dumb. Funders who are at pains to be risk-taking and generous in their grantmaking suddenly become steely-eyed, risk-averse nitpickers when looking at high-impact for-profits. Nobody’s happy.

Impact investing is supposed to occupy a space between philanthropy and commercial investing. Intentions without concessions have left that space mostly empty. This stifles much-needed innovation in poor countries, because the things that make them poor are the same things that make them hard places to start and grow businesses. It’s not going to happen without concessionary finance. “Concessionary” means you’re taking a hit on expected return because you’re serious about impact. That means cheap loans, risky equity positions on generous terms without expectation of higher returns, and even straight-up grants…(More)”

That hit you take in the service of impact has a name. It’s “philanthropy.” It takes a different form than traditional nonprofit grantmaking, but it’s still philanthropy…(More)”.