Stefaan Verhulst
Article by Lori Regattieri: “What if I told you that one of the most well-capitalized AI companies on the planet is asking volunteers to help them uncover “lost cities” in the Amazonia—by feeding machine learning models with open satellite data, lidar, “colonial” text and map records, and indigenous oral histories? This is the premise of the OpenAI to Z Challenge, a Kaggle-hosted hackathon framed as a platform to “push the limits” of AI through global knowledge cooperation. In practice, this is a product development experiment cloaked as public participation. The contributions of users, the mapping of biocultural data, and the modeling of ancestral landscapes all feed into the refinement of OpenAI’s proprietary systems. The task itself may appear novel. The logic is not. This is the familiar playbook of Big Tech firms—capture public knowledge, reframe it as open input, and channel it into infrastructure that serves commercial, rather than communal goals.
The “challenge” is marketed as a “digital archaeology” experiment, it invites participants from all around the world to search for “hidden” archaeological sites in the Amazonia biome (Brazil, Bolivia, Columbia, Ecuador, Guyana, Peru, Suriname, Venezuela, and French Guiana) using a curated stack of open-source data. The competition requires participants to use OpenAI’s latest GPT-4.1 and the o3/o4-mini models to parse multispectral satellite imagery, LiDAR-derived elevation maps (Light Detection and Ranging is a remote sensing technology that uses laser pulses to generate high-resolution 3D models of terrain, including areas covered by dense vegetation), historical maps, and digitized ethnographic archives. The coding teams or individuals need to geolocate “potential” archaeological sites, argue their significance using verifiable public sources, and present reproducible methodologies. Prize incentives total $400,000 USD, with a first-place award of $250,000 split between cash and OpenAI API credits.
While framed as a novel invitation to “anyone” to do archaeological research, the competition focuses mainly on the Brazilian territory, transforming the Amazonia and its peoples into an open laboratory for model testing. What is presented as scientific crowdsourcing is in fact a carefully designed mechanism for refining geospatial AI at scale. Participants supply not just labor and insight, but novel training and evaluation strategies that extend far beyond heritage science and into the commercial logics of spatial computing…(More)”.
Article by Sam A. Reynolds: “Over the past few decades, evidence synthesis has greatly increased the effectiveness of medicine and other fields. The process of systematically combining findings from multiple studies into comprehensive reviews helps researchers and policymakers to draw insights from the global literature1. AI promises to speed up parts of the process, including searching and filtering. It could also help researchers to detect problematic papers2. But in our view, other potential uses of AI mean that many of the approaches being developed won’t be sufficient to ensure that evidence syntheses remain reliable and responsive. In fact, we are concerned that the deployment of AI to generate fake papers presents an existential crisis for the field.
What’s needed is a radically different approach — one that can respond to the updating and retracting of papers over time.
We propose a network of continually updated evidence databases, hosted by diverse institutions as ‘living’ collections. AI could be used to help build the databases. And each database would hold findings relevant to a broad theme or subject, providing a resource for an unlimited number of ultra-rapid and robust individual reviews…
Currently, the gold standard for evidence synthesis is the systematic review. These are comprehensive, rigorous, transparent and objective, and aim to include as much relevant high-quality evidence as possible. They also use the best methods available for reducing bias. In part, this is achieved by getting multiple reviewers to screen the studies; declaring whatever criteria, databases, search terms and so on are used; and detailing any conflicts of interest or potential cognitive biases…(More)”.
Article by Sarah Bush and Jennifer Hadden: “The 1990s were a golden age for nongovernmental organizations. It was a time when well-known groups such as Amnesty International, Greenpeace, and Oxfam grew their budgets and expanded their global reach. Between 1990 and 2000, the number of international NGOs—not-for-profit groups that are largely independent from government and work in multiple countries in pursuit of the public good—increased by 42 percent. Thousands of organizations were founded. Many of these organizations championed liberal causes, such as LGBTQ rights and gun control. Conservative groups emerged, too, with rival policy agendas.
As their numbers grew, NGOs became important political players. Newly minted organizations changed state policies. The International Campaign to Ban Landmines, a coalition of NGOs formed in 1992, successfully pushed for the adoption of the Anti-Personnel Mine Ban Convention in 1997—an effort that won it the Nobel Peace Prize. Transparency International, a Berlin-based NGO established in 1993, raised the profile of corruption issues through its advocacy, building momentum toward the adoption of the UN Convention Against Corruption in 2003. Future UN Secretary-General Kofi Annan declared at the 1993 World Conference on Human Rights that “the twenty-first century will be an era of NGOs.” In an influential 1997 essay in Foreign Affairs, Jessica Mathews argued that the end of the Cold War brought with it a “power shift”: global civil society, often formalized as NGOs, was wresting authority and influence from states. More and more often, Mathews contended, NGOs were taking over responsibilities for the delivery of development and humanitarian assistance, pushing governments around during international negotiations, and setting the policy agenda on issues such as environmental protection and human rights.
Today, however, the picture looks remarkably different…(More)”.
Article by Damilare Dosunmu: “A battle for data sovereignty is brewing from Africa to Asia.
Developing nations are challenging Big Tech’s decades-long hold on global data by demanding that their citizens’ information be stored locally. The move is driven by the realization that countries have been giving away their most valuable resource for tech giants to build a trillion-dollar market capitalization.
In April, Nigeria asked Google, Microsoft, and Amazon to set concrete deadlines for opening data centers in the country. Nigeria has been making this demand for about four years, but the companies have so far failed to fulfill their promises. Now, Nigeria has set up a working group with the companies to ensure that data is stored within its shores.
“We told them no more waivers — that we need a road map for when they are coming to Nigeria,” Kashifu Inuwa Abdullahi, director-general of Nigeria’s technology regulator, the National Information Technology Development Agency, told Rest of World.
Other developing countries, including India, South Africa, and Vietnam, have also implemented similar rules demanding that companies store data locally. India’s central bank requires payment companies to host financial data within the country, while Vietnam mandates that foreign telecommunications, e-commerce, and online payments providers establish local offices and keep user data within its shores for at least 24 months…(More)”.
Article by Maddy Crowell: “…Most of St. Lucia, which sits at the southern end of an archipelago stretching from Trinidad and Tobago to the Bahamas, is poorly mapped. Aside from strips of sandy white beaches that hug the coastline, the island is draped with dense rainforest. A few green signs hang limp and faded from utility poles like an afterthought, identifying streets named during more than a century of dueling British and French colonial rule. One major road, Micoud Highway, runs like a vein from north to south, carting tourists from the airport to beachfront resorts. Little of this is accurately represented on Google Maps. Almost nobody uses, or has, a conventional address. Locals orient one another with landmarks: the red house on the hill, the cottage next to the church, the park across from Care Growell School.
Our van wound off Micoud Highway into an empty lot beneath the shade of a banana tree. A dog panted, belly up, under the hot November sun. The group had been recruited by the Humanitarian OpenStreetMap Team, or HOT, a nonprofit that uses an open-source data platform called OpenStreetMap to create a map of the world that resembles Google’s with one key exception: Anyone can edit it, making it a sort of Wikipedia for cartographers.
The organization has an ambitious goal: Map the world’s unmapped places to help relief workers reach people when the next hurricane, fire, or other crisis strikes. Since its founding in 2010, some 340,000 volunteers around the world have been remotely editing OpenStreetMap to better represent the Caribbean, Southeast Asia, parts of Africa and other regions prone to natural disasters or humanitarian emergencies. In that time, they have mapped more than 2.1 million miles of roads and 156 million buildings. They use aerial imagery captured by drones, aircraft, or satellites to help trace unmarked roads, waterways, buildings, and critical infrastructure. Once this digital chart is more clearly defined, field-mapping expeditions like the one we were taking add the names of every road, house, church, or business represented by gray silhouettes on their paper maps. The effort fine-tunes the places that bigger players like Google Maps get wrong — or don’t get at all…(More)”
Article by James Plunkett: “…Unlike many political soundbites, however, missions have a strong academic heritage, drawing on years of work from Mariana Mazzucato and others. They gained support as a way for governments to be less agnostic about the direction of economic growth and its social implications, most obviously on issues like climate change, while still avoiding old-school statism. The idea is to pursue big goals not with top-down planning but with what Mazzucato calls ‘orchestration’, using the power of the state to drive innovation and shape markets to an outcome.
For these reasons, missions have proven increasingly popular with governments. They have been used by administrations from the EU to South Korea and Finland, and even in Britain under Theresa May, although she didn’t have time to make them stick.
Despite these good intentions and heritage, however, missions are proving difficult. Some say the UK government is “mission-washing” – using the word, but not really adopting the ways of working. And although missions were mentioned in the spending review, their role was notably muted when compared with the central position they had in Labour’s manifesto.
Still, it would seem a shame to let missions falter without interrogating the reasons. So why are missions so difficult? And what, if anything, could be done to strengthen them as Labour moves into year two? I’ll touch on four characteristics of missions that jar with Whitehall’s natural instincts, and in each case I’ll ask how it’s going, and how Labour could be bolder…(More)”.
Article by Brian Johnston: “Scientists are always short of research funds, but the boom in the popularity of expedition cruising has given them an unexpected opportunity to access remote places.
Instead of making single, expensive visits to Antarctica, for example, scientists hitch rides on cruise ships that make repeat visits and provide the opportunity for data collection over an entire season.
Meanwhile, cruise passengers’ willingness to get involved in a “citizen science” capacity is proving invaluable for crowdsourcing data on everything from whale migration and microplastics to seabird populations. And it isn’t only the scientists who benefit. Guests get a better insight into the environments in which they sail, and feel that they’re doing their bit to understand and preserve the wildlife and landscapes around them.
Citizen-science projects produce tangible results, among them that ships in Antarctica now sail under 10 knots after a study showed that, at that speed, whales have a far greater chance of avoiding or surviving ship strikes. In 2023 Viking Cruises encountered rare giant phantom jellyfish in Antarctica, and in 2024 discovered a new chinstrap penguin colony near Antarctica’s Astrolabe Island.
Viking’s expedition ships have a Science Lab and the company works with prestigious partners such as the Cornell Lab of Ornithology and Norwegian Polar Institute. Expedition lines with visiting scientist programs include Chimu Adventures, Lindblad Expeditions and Quark Expeditions, which works with Penguin Watch to study the impact of avian flu…(More)”.
UNESCO Report: “Generative Artificial Intelligence (Gen AI) has become an integral part of our digital landscape and daily life. Understanding its risks and participating in solutions is crucial to ensuring that it works for the overall social good. This PLAYBOOK introduces Red Teaming as an accessible tool for testing and evaluating AI systems for social good, exposing stereotypes, bias and potential harms. As a way of illustrating harms, practical examples of Red Teaming for social good are provided, building on the collaborative work carried out by UNESCO and Humane Intelligence. The results demonstrate forms of technology-facilitated gender-based violence (TFGBV) enabled by Gen AI and provide practical actions and recommendations on how to address these growing concerns.
Red Teaming — the practice of intentionally testing Gen AI models to expose vulnerabilities — has traditionally been used by major tech companies and AI labs. One tech company surveyed 1,000 machine learning engineers and found that 89% reported vulnerabilities (Aporia, 2024). This PLAYBOOK provides access to these critical testing methods, enabling organizations and communities to actively participate. Through the structured exercises and real-world scenarios provided, participants can systematically evaluate how Gen AI models may perpetuate, either intentionally or unintentionally, stereotypes or enable gender-based violence.By providing organizations with this easy-to-use tool to conduct their own Red Teaming exercises, participants can select their own thematic area of concern, enabling evidence-based advocacy for more equitable AI for social good…(More)”.
Paper by Warren Liang et al: “In the age of ubiquitous computing, the convergence of wearable technologies and social sentiment analysis has opened new frontiers in both consumer engagement and patient care. These technologies generate continuous, high-frequency, multimodal data streams that are increasingly being leveraged by artificial intelligence (AI) systems for predictive analytics and adaptive interventions. This article explores a unified, integrated framework that combines physiological data from wearables and behavioral insights from social media sentiment to drive proactive engagement strategies. By embedding AI-driven systems into these intersecting data domains, healthcare organizations, consumer brands, and public institutions can offer hyper-personalized experiences, predictive health alerts, emotional wellness interventions, and behaviorally aligned communication.
This paper critically evaluates how machine learning models, natural language processing, and real-time stream analytics can synthesize structured and unstructured data for longitudinal engagement, while also exploring the ethical, privacy, and infrastructural implications of such integration. Through cross-sectoral analysis across healthcare, retail, and public health, we illustrate scalable architectures and case studies where real-world deployment of such systems has yielded measurable improvements in satisfaction, retention, and health outcomes. Ultimately, the synthesis of wearable telemetry and social context data through AI systems represents a new paradigm in engagement science — moving from passive data collection to anticipatory, context-aware engagement ecosystems…(More)”.
Conference Proceedings edited by Josef Drexl, Moritz Hennemann, Patricia Boshe, and Klaus Wiedemann: “The increasing relevance of data is now recognized all over the world. The large number of regulatory acts and proposals in the field of data law serves as a testament to the significance of data processing for the economies of the world. The European Union’s Data Strategy, the African Union’s Data Policy Framework and the Australian Data Strategy only serve as examples within a plethora of regulatory actions. Yet, the purposeful and sensible use of data does not only play a role in economic terms, e.g. regarding the welfare or competitiveness of economies. The implications for society and the common good are at least equally relevant. For instance, data processing is an integral part of modern research methodology and can thus help to address the problems the world is facing today, such as climate change.
The conference was the third and final event of the Global Data Law Conference Series. Legal scholars from all over the world met, presented and exchanged their experiences on different data-related regulatory approaches. Various instruments and approaches to the regulation of data – personal or non-personal – were discussed, without losing sight of the global effects going hand-in-hand with different kinds of regulation.
In compiling the conference proceedings, this book does not only aim at providing a critical and analytical assessment of the status quo of data law in different countries today, it also aims at providing a forward-looking perspective on the pressing issues of our time, such as: How to promote sensible data sharing and purposeful data governance? Under which circumstances, if ever, do data localisation requirements make sense? How – and by whom – should international regulation be put in place? The proceedings engage in a discussion on future-oriented ideas and actions, thereby promoting a constructive and sensible approach to data law around the world…(More)”.