Stefaan Verhulst

Article by Sarah O’Connor: “In the early 20th century, a gifted engineer called Frederick Winslow Taylor embarked on an ambitious task: to extract knowledge from inside the heads of workers on America’s factory floors.

In the eyes of Taylor, who would go on to become one of the world’s first management consultants, factory workers possessed a “mass of rule-of-thumb or traditional knowledge” which had been “handed down from man to man by word of mouth” or “almost unconsciously learnt through personal observation”. Taylor thought it was about time this knowledge was “codified or systematically analysed or described”. To that end, he sent managers with stopwatches and notebooks on to shop floors to observe, time and record every stage of every job.

More than a century later, employers of white-collar professionals are beginning to confront a similar challenge. It is becoming increasingly clear that the knowledge required to make AI models genuinely powerful in a swath of workplaces is currently locked inside employees’ heads.

This isn’t true in every workplace. AI models have transformed the software profession, for example, because the task of writing code is testable and rules-based and there were vast reams of training data publicly available, thanks to online forums like Stack Overflow.

But for many other jobs, that sort of data just does not exist on the web. Indeed, some subtle but important skills are very hard to codify at all, which is why they are often learnt through experience and osmosis. This sort of tacit knowledge was famously summed up by the scientist and philosopher Michael Polanyi with the phrase: “we can know more than we can tell”.

As a result, general-purpose AI models are simply not very good at many specific tasks which require both domain and institutional knowledge. Investment firm Bridgewater Associates recently experimented, for example, with using LLMs to do something their human professionals do all the time: parsing reams of news stories and financial documents for information that might be relevant to their investment decisions.

While this could be a useful timesaver, Bridgewater found that variants of Gemini, Claude and GPT only tended to get it right about 50 per cent of the time..(More)”.

Article by The Economist: “WHEN THE leaders of the biggest Western economies gathered last month in the French Alps for the G7 summit, it was not just presidents and prime ministers in attendance. The bosses of America’s leading artificial-intelligence firms—Sam Altman of OpenAI, Sir Demis Hassabis of Google DeepMind and Dario Amodei of Anthropic—were seated alongside the political bigwigs. Even the stewards of the mightiest economies, it turns out, are buttering up the potentates of AI.

Days before the summit, America’s government had barred Anthropic from making its most advanced model available to foreigners. OpenAI soon imposed similar restrictions on some of its frontier systems. The move turned a simmering concern into a burning one: might countries without their own, home-grown AI firms end up excluded from the world-changing technology? Emmanuel Macron, France’s president, warned that no one would buy American AI if it could “turn off the switch” at will. The American AI labs’ Chinese rivals offer only faint reassurance. On July 7th Reuters reported that Chinese officials, too, were considering restricting foreigners’ access to leading AI models.

Sovereign chic

Caught between the world’s two AI superpowers, governments are increasingly pinning their hopes on “sovereign AI”: the idea that countries should limit their dependence on foreign providers of AI by actively developing domestic AI firms and infrastructure. Announcements of such initiatives are proliferating. The European Union has unveiled a technology-sovereignty package encompassing semiconductors, AI and cloud computing. Canada has launched its own plan to reduce reliance on American technology providers. India, Japan and Singapore are backing domestic AI infrastructure and models. The Centre for a New American Security (CNAS), a think-tank in Washington, estimates that the number of state-backed AI projects outside America and China grew fivefold over the course of 2024 and 2025 (see chart 1). Governments have announced investments of $70bn-plus in such initiatives, according to CNAS’s tally.

Yet turning these ambitions into reality will be extremely difficult. No matter what, most countries will still rely on American chips, Chinese open-source models or both to build their AI systems. Even then, most governments will find it prohibitively expensive to achieve anything remotely resembling AI sovereignty.

The incentive to seek it, however, is clear and compelling. Pablo Chavez of CNAS puts the restrictions on Anthropic in a “long line of events” demonstrating America’s willingness to use its technological dominion as a weapon. In the dying days of Joe Biden’s presidency in 2025, America proposed sweeping export controls that would have rationed access to advanced chips through a complex licensing regime. When Donald Trump became president a few weeks later he dropped the plan. But he has not hesitated to use America’s lead in AI as leverage in trade negotiations. The Department of Commerce is considering rules that would allow it to vet all sales of AI chips designed by American firms anywhere in the world. It might also insist that buyers allow inspections or monitoring to make sure chips are being used as promised. Another possible requirement could be to invest in American AI infrastructure in exchange for access…(More)”.

Report by the OECD: “..explores the opportunities and challenges of the adoption of artificial intelligence (AI) tools to improve citizen participation. To do so, it builds on desk research and analysis of 50 AI use cases in citizen participation processes from 22 OECD Member and partner countries.

It proposes a typology of applications to help government officials and practitioners navigate the landscape of AI tools for participation based on their needs and the challenges they face. The report also provides insights on emerging trends in the adoption of AI tools for participation, analyses the related risks, and outlines relevant mitigation strategies that allow governments to steer the trustworthy adoption of the technology…(More)“

Article by Stefaan Verhulst, Nadiya Safonova and Hannah Chafetz: “The world is facing increasingly complex challenges, including higher levels of conflict, displacement, political polarization and social fragmentation. Addressing these challenges requires new tools and approaches that can support conflict prevention, peacebuilding, and advancing resilient societies. 

PeaceTech is the intentional use of technologies and data to save lives, safeguard human dignity, prevent, mitigate, or recover from conflict, enable accountability, and help people live with dignity, agency, and security. 

Yet while enormous investment has gone into technologies of war, comparatively little attention has been devoted to technologies explicitly designed to prevent violence, protect civilians, strengthen resilience, and build lasting peace. This mapping seeks to help fill that gap.

Drawing on desk research conducted between February and May 2026 and learnings from supporting the 2023 – 2025 Kluz Prize for PeaceTech, we identified and curated 100 current and potential use cases of PeaceTech across the conflict cycle and for long-term peacebuilding. 

This mapping is intended to be illustrative rather than exhaustive. Given the rapid pace of technological innovation and the diversity of peacebuilding contexts, no single review can capture every current or emerging PeaceTech application. Instead, the 100 use cases are designed to demonstrate the breadth of possibilities, identify promising patterns, and stimulate further discussion, research, and innovation across the field.

More detailed case studies about these use cases along with the potential and risks of PeaceTech will be published in our forthcoming white paper this fall. 

The 100 Use Cases

Figure 1. Screen capture of 100 Use Cases of PeaceTech

The 100 Use Cases are categorized by maturity level. As shown in the above spreadsheet, we identified: 

• 20 established use cases that have been deployed at scale with evidence of impact; 
• 20 growing use cases that have active pilots or are in the early stages of deployment;
• 20 use cases in the conceptual stage of design; and 
• 40 unexplored use cases that have potential but have not yet been fully established or deployed. 

In what follows we outline several key themes across each of these categories. Three broader observations emerged from reviewing more than one hundred current and future examples:

• Most PeaceTech today focuses on responding to conflict rather than preventing it.
• AI starts to appear across nearly every stage of the conflict cycle.
• The largest innovation gap lies not in hardware but in coordination, governance, incentives, and trusted institutions…(More)”.

Paper by Stefaan Verhulst: “Across a range of fast growing urban markets, private developers are constructing a version of the smart city that operates largely outside the purview of municipal government, often at the explicit invitation of city officials seeking to shift the cost and complexity of digital infrastructure onto private capital. Gated residential and mixed use developments are increasingly marketed not merely on the basis of security and amenity, but on their smartness: integrated home automation, app mediated access control, and centralized energy and resource management, among other features. We refer to this phenomenon as the smart compound. Despite its rapid proliferation, it has received comparatively little sustained scholarly attention: the literatures on smart cities and on gated communities have developed largely independently of one another, even as developers are, in practice, merging the two. This paper introduces the smart compound as an emerging real estate and urban development phenomenon, considers the opportunities and risks it presents, and examines how questions of data governance differ when smart urban infrastructure is built and owned privately rather than publicly. It concludes with a set of research questions intended to orient researchers, planners, and regulators toward a phenomenon whose growth is outpacing the scholarship meant to account for it…(More)”.

Paper by Francesco Nasi: “While many debates frequently emphasize the threats artificial intelligence poses to democratic life, scholars are increasingly examining the role AI may play in supporting democracies. However, little attention has been given to a crucial question: how and under what conditions AI can be considered democratic, not only in its design but also in its societal outcomes. I argue that AI is democratic when it is democratically empowering, meaning it contributes to redistributing power and creating symmetrical power relations rather than centralizing them. This argument is rooted in the framework of participatory democracy, which prioritizes the active involvement of the citizenry and the redistribution of power across all social spheres. Drawing on participatory democracy, Foucauldian and Actor-Network Theory perspectives, the paper identifies three essential features of power that are needed for theorizing democratic AI: the pervasiveness of power relations in everyday life, the agency of technological artifacts understood as “actants”, and the way power structures relations that can be more or less symmetrical. To assess whether and how AI may be deemed democratic, the paper suggests investigating how AI shapes power dynamics in two dimensions: AI making (development, design, political economy, governance, and imaginaries) and AI action (how AI operates in fields like education, healthcare, information, and politics). This approach helps to take into account the complexity and ambiguity of power dynamics, critically examining whether and how AI contribute to the redistribution of power across different domains. Ultimately, this theoretical framework provides a roadmap for developers and policymakers interested in promoting a more democratic AI…(More)”.

Article by Daniella Fernández, and Andrea Paola Hernández: “After twin earthquakes struck northern Venezuela last month, thousands of people took to social media, pleading for help locating friends and family. The interim government was slow to act, but help came quickly from an unexpected source: developers and programmers.

“Who knew when the government was going to respond?” Jorge Bastidas, a 31-year-old Venezuelan programmer who lives in Buenos Aires, told Rest of World. “We decided to take action.”

Bastidas and his team of six created Desaparecidos Terremoto Venezuela, a website for citizens to report, identify, and reunite with missing family and friends. Using Claude Opus 4.8, and facial recognition software donated by Mexican company Lab-Co, Bastidas designed the site to load quickly, without requiring users to register or download an app. It received more than 30,000 missing-person reports in the first two days, he said.

Without AI, “it would have taken me about 24 hours without rest to build something that took me three hours,” Bastidas said…(More)”.

Review by Matt Elmore: “Byung-Chul Han is one of Europe’s most widely read philosophers. His audience in the United States has grown considerably over the last decade, though mostly outside the academy; in 2024, the New Yorker dubbed him “The Internet’s New Favorite Philosopher” — an ironic label for a thinker who keeps his distance from the online world. His latest book, The Tonality of Thought, gathers three public lectures that serve as windows into his work and way of life. In its own way, the book makes sense of why his writing has struck a chord in the digital age.

Han grew up in South Korea and now lives in Berlin. Most mornings, he begins his day not with his phone, not with email or headlines, but with Bach. A Steinway grand piano sits in his apartment, where he plays the aria from Bach’s Goldberg Variations — a spare, unhurried theme that opens and closes a set of thirty short pieces. He calls the piano his prayer wheel, like those found in temple courtyards across Asia. At the piano, he says, he does not so much think as let thinking take place. “For me, thinking is thanking.” When he plays, thoughts arrive like visitors, and he answers them with a quiet grazie.

A few steps from the piano stands an art nouveau writing desk. Every day he walks back and forth between the piano and his desk — twenty times, by his count — returning to Bach when he has no words. Han is a philosopher, though not the kind the last century prized. He builds no system, offers no program, stages no revolution. Nor does he stop at the unmasking of power. His books are unsparing in their critique of digital capitalism, but they do not end in critique; they rest on a deeper sense of beauty, friendship, and transcendence — themes as old as philosophy itself.

For more than two decades, Han has shaped a form of writing equal to his concerns: brief, concentrated books that think in movements rather than arguments. Their brevity feels deliberate, as if composed for the attention economy yet guided by another sense of time. Winding through subjects as varied as Zen, smartphones, and gardening, they often return to the same question: What has become of freedom in the digital age?..(More)”.

Coursebook by BJ Ard & Rebecca Crootof: “Technology law (“techlaw”) is the study of how law and technology foster, restrict, and otherwise shape each other’s evolution. New technologies raise questions for every area of the law, and the strategies and rhetorical arguments deployed to regulate technology and its impacts are helpful tools to have across legal contexts. Accordingly, this coursebook identifies common techlaw questions and presents a methodology for thoughtfully resolving them.

This coursebook is intended to be accessible and useful to all students, regardless of career interests or prior experience with technology. Each chapter includes “Comprehension Checks,” intended to be addressed by the reader in context, and “Discussion Questions” and “Putting It All Together” closers, which we have found to be helpful springboards for class discussion…(More)”.

Study published by the National Library of the Netherlands (KB) and the Europeana Foundation: “This document identifies a pathway to establishing the core of the European Books Data Commons: a shared infrastructure that would make the full text of millions of digitised public domain books held by libraries across Europe available for re-use in forms optimised for AI developers and researchers working with large-scale language datasets. If implemented, the EBDC would constitute a significant contribution to the European Commission’s 2025 Data Union Strategy, which aims to ensure that European AI developers have access to high quality data including cultural heritage collections.

The remainder of the document is structured as follows. Section 2 sets out the proposition — the demand for digitised public domain books and the supply-side constraints that currently prevent access to existing collections. Section 3 presents the recommended implementation scenario, arrived at through a process of developing, testing, and progressively refining a set of options with library partners and the steering group. Section 4 addresses the governance of the system and its relationship to related European initiatives. Section 5 outlines the way forward, including a two-track implementation approach, an integrated timeline, and indicative cost estimates. Section 6 makes the case for acting now to build the European Books Data Commons…(More)”.