Stefaan Verhulst

Book by Nasim Afsar: “It was built to react and manage illness only after symptoms occur and it’s not even succeeding at that: chronic disease rates climb relentlessly, outcomes worsen year after year, and health and care grow more expensive. Worse still, the person who should be at the center is treated as a vessel for their illness, only valued for the revenue they generate.

Meanwhile, healthcare systems, payers, pharmaceutical companies, device manufacturers, and technology firms compete fiercely for their growth and survival. But no one is competing to make you healthier. We’ve reached a breaking point where the system doesn’t just fail; it actively harms people through preventable suffering and bankrupts families through inexcusable waste.

Enter Intelligent Health. A fundamental reimagining of health and care around a different center of gravity: you. It begins by unifying all your health and care data—clinical, behavioral, environmental, genetic—to see the complete picture of what shapes your health. It applies artificial intelligence to transform that data into actionable insight for today and predictive foresight about the future, catching problems before they cascade into crises. Most radically, it aligns the entire ecosystem of health and care around you.

Today, consumer health solutions multiply while outcomes stagnate. Costs spiral while access shrinks. Technology advances while coordination collapses. Intelligent Health offers what incremental reform cannot: a fundamental reimagining of health and care to create a system that is more human, more intelligent, and built to advance health…(More)”

Article by Clive Thompson: “…Computer programming has been through many changes in its 80-year history. But this may be the strangest one yet: It is now becoming a conversation, a back-and-forth talk fest between software developers and their bots.

This vertiginous shift threatens to stir up some huge economic consequences. For decades, coding was considered such wizardry that if you were halfway competent you could expect to enjoy lifetime employment. If you were exceptional at it (and lucky), you got rich. Silicon Valley panjandrums spent the 2010s lecturing American workers in dying industries that they needed to “learn to code.”

Now coding itself is being automated. To outsiders, what programmers are facing can seem richly deserved, and even funny: American white-collar workers have long fretted that Silicon Valley might one day use A.I. to automate their jobs, but look who got hit first! Indeed, coding is perhaps the first form of very expensive industrialized human labor that A.I. can actually replace. A.I.-generated videos look janky, artificial photos surreal; law briefs can be riddled with career-ending howlers. But A.I.-generated code? If it passes its tests and works, it’s worth as much as what humans get paid $200,000 or more a year to compose.

You might imagine this would unsettle and demoralize programmers. Some of them, certainly. But I spoke to scores of developers this past fall and winter, and most were weirdly jazzed about their new powers.

“We’re talking 10 to 20 — to even 100 — times as productive as I’ve ever been in my career,” Steve Yegge, a veteran coder who built his own tool for running swarms of coding agents, told me. “It’s like we’ve been walking our whole lives,” he says, but now they have been given a ride, “and it’s fast as [expletive].” Like many of his peers, though, Yegge can’t quite figure out what it means for the future of his profession. For decades, being a software developer meant mastering coding languages, but now a language technology itself is upending the very nature of the job…(More)”.

Paper by Ajay K. Agrawal, John McHale & Alexander Oettl: “We explore the impact of artificial intelligence (AI) on the knowledge production function. We characterize AI as a tool, not for full automation but rather for augmentation through enhanced search over combinatorial spaces. This leads to increased scientific productivity. We decompose knowledge production into a multi-stage process to shed light on the “jagged frontier” of AI in science, revealing differential returns to different tools across domains (e.g., data-rich biology vs. anomaly-sparse physics) and workflow stages (e.g., strong design aids like AlphaFold vs. subtler question generation tools). We treat human judgment as indispensable for tasks involving abductive inference, contextual nuance, and trade-offs, particularly in data-sparse environments. Drawing on a task-based model that distinguishes “ordinary” from AI-expert scientists, we describe how exogenous improvements in AI yield nonlinear productivity gains amplified by the share of scientists that are AI-experts to underscore the role of AI complements like skills training and organizational design…(More)”.

Article by Anwar Aridi, Henning Kroll: “Today, emerging economies must contend with a shifting landscape of global technology governance. As fields such as artificial intelligence, quantum computing, and synthetic biology become subject to new national security concerns, access to knowledge and participation in the shaping of international trade, finance, and standards regulations are increasingly contested. Moreover, established conventions of international economic and technological collaboration are being challenged, and old partnerships may no longer be relied upon. Yet certain areas—notably health and climate—remain less fraught within the context of geopolitics, offering entry points for emerging economies even during times of heightened global tension. A recent example can be found in the successes of global effort to produce vaccines during the COVID-19 pandemic, even in a politically contested environment.

In this new geopolitical landscape, technology dependence still signals vulnerability. Emerging economies under political pressure to reduce dependence may encourage domestic production of goods to replace more advanced, imported ones: a policy dubbed import substitution. But, if pursued prematurely, before domestic producers are ready to compete, import substitution can backfire, allowing a small number of established firms to capture state resources and hurting domestic consumers.

These risks are intimately related to political forces that shape how industrial policy priorities are chosen and the state’s capacity for implementing them. For these reasons, industrial policy must be embedded in transparent, accountable, and performance-based governance mechanisms. Emerging economies, much like developed ones, must avoid the pitfalls of politically driven resource allocation when the government becomes involved in steering the country’s economic future.

Even as today’s geopolitical complexities put added stress on emerging economies, a targeted strategy for industrial policy—as well as international collaboration—continues to be essential in enabling national economies’ transition toward more advanced stages of technological development. Countries cannot attempt to “go it alone” before attaining sufficient capacity. Yet, when collaboration becomes fraught with uncertainty, policies should carefully address how to invest resources to catch up with leading economies. Only by tailoring strategies to each stage of development, investing in knowledge institutions, and navigating the geopolitics of technological governance with agility can emerging economies secure a path toward technological sovereignty…(More)”.

OECD Policy Brief: “Shipbuilding underpins competitiveness, economic security, and higher energy efficiency. Yet across major shipbuilding economies, industrial policy decisions are frequently taken with incomplete, inconsistent, or poorly aligned evidence. Four structural data challenges stand out: inconsistent statistical definitions that undermine international comparability; limited visibility on where value is created and which factors drive productivity; delayed identification of emerging skills needs; and insufficient, non-standardised metrics to track technological upgrading and decarbonisation progress. Strengthening shipbuilding data is a strategic priority. Building on OECD tools such as the Structural Analysis (STAN) Database, Inter-Country Input-Output (ICIO) Tables, Trade in Value Added (TiVA) and the Ocean Economy Monitor, improved definitions, labour intelligence, and innovation indicators can support improved policy targeting, monitoring, and cross-country benchmarking — enabling more effective and resilient shipbuilding industrial policy…(More)”.

Article by Ananya Bhattacharya: “Already, seven in 10 social media images are AI-generated using tools like Midjourney or DALL-E, and eight in 10 content recommendations rely on AI. Nearly half of all social media content by businesses will be AI-generated in 2026. Meanwhile, AI tools are leaving behind non-English speakers.

The key question now is whether the Oversight Board has the capacity and regional reach to identify systemic harms at scale and create precedents that actually shifts product and policy decisions, Rachel Adams, founder and CEO of the Global Center on AI Governance and author of The New Empire of AI: The Future of Global Inequality, told Rest of World.

What won’t work is if you see some of the early AI safety boards that some of the big majors set up — they’ve got all American boards. That is not going to work.”

“With AI-generated content and AI-driven enforcement and moderation, the volume, velocity, and cross-language nature of problems the board was established to monitor and conduct oversight over have exploded,” Adams said. “That would require either a larger board, or a stronger surrounding capacity, in terms of research, regional advisory mechanisms, and faster procedures for urgent situations.”

The Oversight Board is not the first line of defense. Moderation across Meta’s platforms happens at both a machine and a human level (and sometimes both). Users who are unhappy with the moderation outcomes can appeal to the independent, external board. Not all of the appeals will be addressed — the board takes on only the cases it believes will have the biggest lasting impact. In addition to the 21 board members, the Oversight Board has staff members from around the world, and it leans on professional translation services and country context briefings to deliver decisions…(More)”.

Handbook by Centre for Strategic Futures: “articulates the CSF’s updated understanding of foresight—what we find true in theory and useful in practice. Here, we share what we have learned, from both our own experience and others’.

What is in this publication?

This publication has three sections:

1. Foundations—explaining what foresight is, the value it brings, and the dispositions that its work requires.

2. Forms—describing different kinds of foresight projects and offering examples.

3. Footholds—providing heuristics and ideas for putting foresight to work.

Who is this publication for?

This publication is written mainly for public sector foresight practitioners, which is who we are.

But if you find anything written so far interesting, then this handbook is for you, too. We wrote it to be readable by avoiding jargon and writing plainly.

How should one treat this publication?

You can read it linearly or modularly. To encourage you to meander through the handbook, we made wayfinding easy and left breadcrumbs along the way.

There is no single right way to do foresight. Throughout, we invite you to treat what you read as a starting point. Whether you are new to foresight or have practised it for a long time, we hope this handbook will be a useful and enjoyable companion on your journey into the future we are all heading into.

Article by Thomas B. Edsall: “Sixteen years ago, Peter Thiel, the multibillionaire co-founder of PayPal and Palantir Technologies, was strikingly prescient. Speaking at the 2010 Libertopia conference in San Diego, Thiel, who would go on to bankroll JD Vance’s entry into politics, told the gathering:

We could never win an election on getting certain things because we were in such a small minority, but maybe you could actually unilaterally change the world without having to constantly convince people and beg people and plead with people who are never going to agree with you through technological means, and this is where I think technology is this incredible alternative to politics.

Sometime in the not-too-distant future, Thiel and his tech allies may well have no need to win an election to exert control of the United States and other nations.

As artificial intelligence — led by Nvidia, Microsoft, Alphabet, Meta, Amazon, OpenAI and Anthropic — drives to become the nation’s dominant industry, one of the most pressing questions is how technology is affecting, if not supplanting, politics, potentially diminishing the centrality of elections.

Even more important: Will A.I. continue to increase the concentration of market, political and cultural power, undermining democratic control of the economic and social order? To what degree will A.I. exacerbate inequality?

And will A.I., empowered to operate beyond the reach of public institutions and the electorate, in effect transfer government control and regulatory authority to private corporations, political cadres or both?..(More)”.

Article by Anna Desmarais: “Experts are sounding the alarm over fresh threats to Middle Eastern data centres, warning that this month’s inaugural reported strikes signal a dangerous new trend.

Amazon said two of its data centres in the United Arab Emirates were hit by drone strikes on March 1 and a third centre in Bahrain was damaged by debris from a nearby strike.

Iran’s Islamic Revolutionary Guard Corps (IRGC) claimed responsibility for the attacks, telling state media that the attacks were aimed at identifying the role of these centres in supporting the enemy’s military and intelligence activities.

Analysts say these may be some of the first known physical attacks on data centres, the buildings hold all the infrastructure to power everything from banking apps to cloud services, and artificial intelligence (AI) platforms.

Amazon declined to comment further on the attacks in the Middle East, referring Euronews Next to a health dashboard. As of March 11, several Amazon services are still unavailable or disrupted for customers in the UAE and Bahrain.

Why are data centres a target?

“It’s very likely that data centres will be targeted in the future,” said Vincent Boulanin, director of the governance of AI programme at the Stockholm International Peace Research Institute (SIPRI).

Boulanin said he was not surprised that Iran had mounted attacks against data centres in the United Arab Emirates and Bahrain. Data centres power AI by providing the computer power, storage and high-speed internet needed to train the models.

“Data centres are a critical building block of AI capabilities at the national level,” Boulanin said. “From that perspective, data centres can be considered a very critical infrastructure.”..(More)”.

Report by James Tebrake, El Bachir Boukherouaa, Jeff Danforth, and Miss Nivashini Harikrishnan: “National statistical systems generate the statistics that underpin policy, economic analysis, and public trust. Yet, despite decades of investment in statistical capacity, two persistent challenges, data accessibility and interpretability, limit the impact of these official statistics. The rise of large language models (LLMs) and GenAI applications such as ChatGPT and Gemini appeared to offer a solution by enabling users to retrieve statistics using natural language. However, testing demonstrates that while the GenAI applications excel at synthesizing text, they perform poorly at delivering official statistics: they frequently provide dangerously “reasonable” but incorrect figures. This paper introduces StatGPT, an initiative by the IMF Statistics Department that leverages LLMs not to generate statistics, but to generate structured queries against APIs of official statistical agencies. StatGPT ensures that users receive the exact published figures, every time, while benefiting from natural language interaction. This paper examines the limitations of off-the-shelf GenAI applications, outlines how StatGPT overcomes these limitations, and proposes a roadmap for making official statistics AI-ready through open data access, enriched metadata standards, and strengthened data governance. By aligning technological innovation with statistical rigor, StatGPT represents a critical step toward a future where official statistics remain authoritative, trusted, and universally accessible in an AI-driven world…(More)”.