Stefaan Verhulst
PressRelease: “The European Commission today presented the European Technological Sovereignty Package, a set of measures to strengthen Europe’s capacity in semiconductors, artificial intelligence (AI), cloud and open source.
Commission President, Ursula von der Leyen said: “We cannot afford to depend on others for the technologies that keep our hospitals running, our energy grids stable and our services secure. This is about protecting our citizens, defending our interests and making our own choices. Europe has the talent, the research excellence, the industrial base and the Single Market. Together, we must turn these strengths into technological sovereignty.”
The package includes two legislative proposals – the Chips Act 2.0 and the Cloud and AI Development Act – as well as the Open Source Strategy and a Strategic Roadmap for Digitalisation and AI in Energy.
Together, these measures support Europe’s ambition to become an AI continent, strengthen its digital autonomy and help build a more sustainable digital future. They will help widen choice in core technologies for EU businesses, citizens and public administrations.
The move comes as Europe remains heavily dependent on suppliers outside the European Union for core digital technologies and as demand for computing capacity rises sharply with the spread of AI. It is designed to reduce structural dependencies and make sure Europe can develop, deploy and secure the technologies Europeans rely on. It signals a major shift in the EU’s approach to technology…(More)”.
Article by Daniela Paolotti and Stefaan Verhulst: “The emergence of Hantavirus cases appeared, at first glance, to be a localized public health incident. Yet, when viewed alongside recurring Ebola outbreaks, growing concerns about avian influenza, and other zoonotic disease threats, these events highlight a broader lesson from COVID-19: our vulnerability to infectious disease outbreaks is shaped not only by the pathogens themselves but also by the preparedness of our data ecosystems and our ability to translate information into timely action. In particular, responsible access to non-traditional data sources -including mobility data, online search behavior, social media activity, transaction records, crowdsourced information, and other digital traces- has become critical in complementing traditional surveillance systems. These data sources can provide earlier, more timely, and more granular insights into emerging risks, helping decision-makers detect outbreaks sooner, understand behavioral dynamics, target interventions more effectively, and strengthen overall preparedness and response efforts
As such, these recent outbreaks provide a useful lens through which to revisit some of the insights of our recent research on non-traditional data and pandemic preparedness. In the below, we share key insights from our analysis of the COVID-19 response, reflect on their continued relevance in the context of the current Hantavirus and Ebola outbreaks, and outline three recommendations to help ensure that the barriers, delays, and missed opportunities of past crises are not repeated again.
This article is not intended to be a comprehensive assessment of either (on-going) outbreak -such an undertaking will require more extensive epidemiological, operational, and governance analysis (which we recommend). Rather, our objective is to highlight a number of emerging warning signs and recurring challenges that deserve more serious attention…(More)”.
Paper by Ankit Bhutani, Guillermo Ordoñez & Laura Veldkamp: “Data assets are increasingly vital in modern economies, yet macroeconomic measurement is not well-adapted to capturing their value. Part of the problem is that data is an intangible asset: investments in data are missed in national accounts, and depreciation losses are missed in firms’ balance sheets. Another part, unique to data, is that it serves as a means of payment in the modern economy: consumption bartered for data is also omitted from national accounts. We propose an output-based approach to measure the missing value of data. We treat data as an asset, measure its volume based on the quality of firms’ revenue forecasts, and endogenously determine its depreciation. We then capitalize the data value and explore what the measured GDP would be if the data were treated and transacted similarly to a physical asset. Our findings suggest that the aggregate value of data is about 1.5% of GDP….(More)”.
Article by David Adam: “When psychologist Raluca Rilla asked volunteers to complete a survey last year, she got the following response to one of her questions: “I don’t experience confusion in the same way humans do.”
Rilla, a PhD student at the Max Planck Institute for Human Development in Berlin, suspects that this is the obvious tip of a large and worrying iceberg — one that could scupper academic research on how people think and behave. She and her colleagues estimate that up to 45% of responses they receive to such surveys are now copied and pasted from the output of large language models (LLMs). In some cases, participants might simply be polishing their language. In others, Rilla thinks that the entire operation — signing up, reading the questions and submitting responses — is handled by a machine. Such answers, and the academic studies built on them, are unlikely to reflect the reality of human nature.
Experimental psychology is not alone in wrestling with the impact of LLMs on research. From political science and economics to opinion polling, researchers across the social sciences are sounding the alarm after finding the fingerprints of artificial intelligence and considering the implications. AI chatbots are infiltrating social-science surveys — and getting better at avoiding detection
Even if AI input into polls can be throttled, there’s a concern at the analysis stage, says David Lazer, a political and computer scientist at Northeastern University in Boston, Massachusetts: AI-assisted analyses in social science might flood journals with spurious findings by rapidly whipping up studies. One journal has already chronicled a vast increase in the number of manuscripts it has received that were wholly or mostly prepared using AI tools.
The explosion in the use and power of AI models touches researchers across all academic fields. But the impact on the social sciences is especially acute, says Joshua Tucker, a political scientist at New York University. That’s because, compared with other disciplines, much social-science research is heavily reliant on survey data and analysis. And when researchers aren’t gathering the data themselves, they are often analysing large, general data sets, such as censuses or other huge surveys that were usually collected for a different original purpose. This means that apparent signals in the data can be plucked from noise in a way that isn’t possible with experimental data obtained in narrow tests to check a hypothesis — information that tends to have a single use and a defined shelf life.
“I think we’re approaching a time where the trust in behavioural and social sciences will be undermined by this constant threat of LLM pollution,” says Björn Hommel, a psychologist at Leipzig University, Germany. “And there’s nothing that we are able to do about it right now.”
But it’s not all doom and gloom. An alternative view of the latest AI systems is that they could transform social science by making its findings more robust. The same algorithms that can be used for superficial work such as polishing language can also source and analyse complex data sets quickly and, by toggling through statistical techniques, check how sensitive an individual finding is to various analytical methods. AI-assisted review could help to spot methodological errors, and social-science journals might insist on the use of more-robust methods as AI makes it easier for researchers to attempt them…(More)”.
Article by Eric Niiler: “The Trump administration is dismantling a $368 million deep-ocean observation system that was put in place a decade ago to monitor coastal environments, marine ecosystems and powerful currents that affect the global climate.
The National Science Foundation said it would send ships in June to begin removing more than 900 deep-sea instruments anchored off Oregon, Washington State, Alaska, North Carolina, and an area between Greenland and Iceland known as the Irminger Sea.
Scientists have used data from the system to understand how the ocean is absorbing greenhouse gases from the atmosphere, how changes in ocean temperature such as marine heat waves might affect fisheries or signal bigger shifts in the climate, and coastal flooding along the East Coast…(More)”.
Roadmap by Centre for Social Impact: “How do you measure the real difference your work is making for people and communities – particularly when social issues are interconnected, persistent and solutions are constantly evolving?
For many organisations, social impact measurement can feel challenging. While it’s often easy to track activities or outputs, understanding whether meaningful change is happening over time is far more difficult.
The Roadmap to Social Impact is a practical guide to social impact measurement, designed to help you better plan, measure and communicate the change you’re helping create.
We hope it provides both guidance and inspiration as we work together for a better world…(More)”.
Paper by Global Solutions Initiative: “…introduces “plural protocol ecosystems” as a comprehensive alternative to the centralized, extractive digital infrastructures currently dominated by massive tech monopolies. It argues that while existing European regulatory approaches like competition law try to govern the behavior of digital gatekeepers, they fail to alter the architectural logic that causes power and value to concentrate in the hands of a few. By shifting focus away from single corporate-led platforms and toward community-led, open digital protocols—the fundamental rules determining how digital systems interact—the framework seeks to build a value-driven third path for the digital age. This new infrastructure aims to actively embed democratic values, human rights, and strategic sovereignty directly into technical designs rather than trying to enforce them after the fact.
To prevent digital systems from collapsing into winner-takes-all dynamics, the paper outlines a framework built across three deeply interconnected dimensions: technical, economic, and social. Technical plurality ensures structural resilience and neutrality through open-source code, decentralized architectures, and privacy-by-design. Economic plurality re-engineers value flows to create fair, non-extractive distribution systems where data creators, developers, and users are directly compensated for the value they generate. Finally, social plurality establishes participatory, multi-stakeholder governance models that prioritize broad deliberation, consensus across social differences, and the right for communities to exit or fork a protocol if it no longer serves them.
Ultimately, the paper positions this paradigm as a path toward a modern digital enlightenment, transitioning individuals from passive consumers of centralized systems into active co-creators with genuine agency over their digital lives. By satisfying these foundational technical, economic, and social blocks, a digital ecosystem can naturally foster higher-level qualities like verifiable trust and credible neutrality. This ground-up architecture provides a realistic roadmap for democratic powers to cultivate a competitive, resilient, and sovereign digital foundation that honors public interest and the common good…(More)”.
Paper by Robert Axelrod and Scott E. Page: “Sycophants praise and support leaders’ proposals to gain personal and professional advantage. A rational sycophant is an advisor who supports actions they expect to be harmful even when rewards and punishments for good and bad advice are equal in magnitude. Rational sycophancy arises when the outcome distribution of a proposed action has a negative expected value but a positive median (outcome asymmetry). The risk is greatest when a small yet meaningful fraction of outcomes are catastrophic, which occurs in long-tailed distributions. Given that single realizations from long-tailed distributions reveal little about the underlying distribution, even after outcomes are observed, a leader may be unable to distinguish rational sycophancy from wise counsel. As a result, rational sycophants may gain influence and increase the likelihood of catastrophic policy outcomes…(More)”
Article by Alice Xiang: “Every click, every photo, every search query we make creates a digital echo. These digital traces are the raw material fueling the AI revolution, powering technologies that are reshaping our world. Yet for the people creating it—all of us—this data has become functionally worthless.
The average internet user doesn’t think about the value of their data. They simply give it away to some of the wealthiest companies in the world, for free.
Because of this behavior, I fear we are living in an age of data nihilism, where our data means everything to AI developers yet almost nothing to us—not because our data actually is value-less, but because people feel powerless to stop it from being collected against their will. …
The next step is for the AI community and regulators to take ethical data curation seriously. The economic power dynamics between AI and humans will largely be determined at the data layer, and as a result, questions about consent and compensation mechanisms for data rights holders should be a major area of focus for AI researchers and regulators. Creating opt-in or opt-out schemes that provide meaningful control to people around the world whose data serves as AI’s raw materials is a challenging task, but one that is critical to address now. Moreover, as AI developers exhaust available data, future innovations will likely depend on the quality rather than simply the quantity of data.
Nietzsche’s cure for nihilism was to create personal meaning, but the scale of AI necessitates creating systems that affirm and protect the value of humanity’s contributions. We are now at a turning point: if we fail to build such protections, we will resign ourselves to a future where the benefits of AI are concentrated among a few, and the vast majority of people find their contributions worthless. The future of AI should not be built on a foundation of mass data appropriation. It must be built on a foundation of respect, consent, and shared value. The age of data nihilism is upon us; it is up to us to prevent it…(More)”.
Report by the Tony Blair Institute: “Modern states increasingly depend on digital infrastructure that is both critical and physically vulnerable. Identity systems, registries, payments, legal records, administrative platforms and public-service channels now form part of the state’s operational core. When these systems fail, the issue is not only service disruption, but also the continuity and credibility of government itself.
War, cyber-attacks, sabotage, terrorism and natural disasters can all affect the systems on which governments, economies and public services rely. Artificial intelligence intensifies this challenge. Governments will increasingly depend on concentrated, capital-intensive infrastructure – cloud, compute, energy, connectivity, secure data environments – that many states cannot fully build, finance or control domestically. As a result, the question is no longer whether states will depend on infrastructure beyond their borders, but how that dependence can be governed.
One concept attracting growing attention as a potential solution to these challenges is the digital embassy – a legally, technically and politically governed arrangement that allows states to preserve, restore or operate critical digital functions through trusted infrastructure beyond their territory. Building on the earlier data-embassy model, which focused on legally protected cross-border storage and recovery of critical state data and systems, digital embassies go even further. They can provide live-system continuity, service continuity and, in some cases, trusted access to cloud, compute or AI infrastructure. At their most advanced, digital embassies are designed to preserve the operational capacity of the state – including identification, authentication, access to records, legal administrative processes and communication with citizens – even when domestic infrastructure or normal administration is disrupted.
This paper argues that digital embassies should be understood as strategic instruments for resilience, security, sovereignty and capability. For guest states (those seeking to externalise elements of their sovereign digital infrastructure), they can reduce single points of failure, preserve state continuity and provide access to strategic infrastructure. For host states (those aiming to host such systems for other countries), they can attract investment, strengthen the economy, aggregate demand for cloud and compute, deepen strategic partnerships, and position countries within the emerging global digital and AI infrastructure ecosystem. But hosting also creates political, legal and security exposure, and therefore requires credible safeguards and institutional capacity…(More)”.