Stefaan Verhulst
Book edited by Cecilia Biancalana and Eric Montigny: “Democracy and data have a complicated relationship. Under the influence of big data and artificial intelligence, some democracies are being transformed as relations between citizens, political parties, governments, and corporations are gradually redrawn.
Artificial Democracy explores the ways in which data collection and analytics and their application are changing political practices, government policies, and even democratic policies themselves. With an international roster of multidisciplinary contributors, this topical collection takes a comprehensive approach to big data’s effect on democracy, from the use of micro-targeting in electoral campaigns to the clash between privacy and surveillance in the name of protecting society.
The book tackles both the dangers and the potentially desirable changes made possible by the symbiosis of big data and artificial intelligence. It explores shifts in how we conceptualize the citizen-government relationship and asks important questions about where we could be heading…(More)”.
Article by Eric Holthaus: “A critical US atmospheric data collection program will be halted by Monday, giving weather forecasters just days to prepare, according to a public notice sent this week. Scientists that the Guardian spoke with say the change could set hurricane forecasting back “decades”, just as this year’s season ramps up.
In a National Oceanic and Atmospheric Administration (Noaa) message sent on Wednesday to its scientists, the agency said that “due to recent service changes” the Defense Meteorological Satellite Program (DMSP) will “discontinue ingest, processing and distribution of all DMSP data no later than June 30, 2025”.
Due to their unique characteristics and ability to map the entire world twice a day with extremely high resolution, the three DMSP satellites are a primary source of information for scientists to monitor Arctic sea ice and hurricane development. The DMSP partners with Noaa to make weather data collected from the satellites publicly available.
The reasons for the changes, and which agency was driving them, were not immediately clear. Noaa said they would not affect the quality of forecasting.
However, the Guardian spoke with several scientists inside and outside of the US government whose work depends on the DMSP, and all said there are no other US programs that can form an adequate replacement for its data.
“We’re a bit blind now,” said Allison Wing, a hurricane researcher at Florida State University. Wing said the DMSP satellites are the only ones that let scientists see inside the clouds of developing hurricanes, giving them a critical edge in forecasting that now may be jeopardized.
“Before these types of satellites were present, there would often be situations where you’d wake up in the morning and have a big surprise about what the hurricane looked like,” said Wing. “Given increases in hurricane intensity and increasing prevalence towards rapid intensification in recent years, it’s not a good time to have less information.”..(More)”.
Book by Todd L. Pittinsky: “From the early days of navigating the world with bare hands to harnessing tools that transformed stones and sticks, human ingenuity has birthed science and technology. As societies expanded, the complexity of our tools grew, raising a crucial question: Do we control them, or do they dictate our fate? The trajectory of science and technology isn’tpredetermined; debates and choices shape it. It’s our responsibility to navigate wisely, ensuring technology betters, not worsens, our world. This book explores the complex nature of this relationship, with 18 chapters posing and discussing a compelling ‘big question.’ Topics discussed include technology’s influence on child development; big data; algorithms; democracy; happiness; the interplay of sex, gender, and science in its development; international development efforts; robot consciousness; and the future of human labor in an automated world. Think critically. Take a stand. With societal acceleration mirroring technological pace, the challenge is, can we keep up?…(More)”.
Paper by xiaohui jiang and Masaru Yarime: “The Chinese government has been playing an important role in stimulating innovation among Chinese enterprises. Small and medium-sized enterprises (SMEs), with their limited internal resources, particularly face a severe challenge in implementing innovation activities that depend upon data, funding sources, and talents. However, the rapidly developing smart city projects in China, where significant amounts of data are available from various sophisticated devices and generous funding opportunities, are providing rich opportunities for SMEs to explore data-driven innovation. Chinese Governments are trying to actively engage SMEs in the process of smart city construction. When cooperating with the government, the availability of and access to data involved in the government contracts and the ability required in the project help SMEs to train and improve their innovation ability.In this article, we intend to address how obtaining different types of government contracts (equipment supply, platform building, data analysis) can influence firms’ performance on innovation. Obtaining different types of government contracts are regarded as receiving different types of treatments. The hypothesis is that the data analysis type of contracts has a larger positive influence on improving the innovation ability compared to the platform building type, while the platform building type of contracts can have a larger influence compared to equipment supply. Focusing on the case of SMEs in China, this research aims to shed light on how the government and enterprises collaborate in smart city projects to facilitate innovation. Data on companies’ registered capital, industry, and software products from 1990– 2020 is compiled from the Tianyancha website. A panel dataset is established with the key characteristics of the SMEs, software productions, and their record on government contracts. Based on the company’s basic characteristics, we divided six pairs of treatment and control groups using propensity score matching (PSM) and then ran a validity test to confirm that the result of the division was reliable. Then based on the established control and treatment pairs, we run a difference-in-difference (DID) model, and the result supports our original hypothesis. The statistics shows mixed result, Hypothesis 1 which indicates that companies obtaining data analysis contracts will experience greater innovation improvements compared to those with platform-building contracts, is partially confirmed when using software copyright as an outcome variable. However, when using patent data as an indicator, the statistics is insignificant. Hypothesis 2, which posits that companies with platform-building contracts will show greater innovation improvements than those with equipment supply contracts, is not supported. Hypothesis 3 which suggests that companies receiving government contracts will have higher innovation outputs than those without, is confirmed. The case studies later have revealed the complex mechanisms behind the scenario…(More)”.
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)”.