China is building an entire empire on data

Curated on Posted on by Stefaan Verhulst

The Economist: “CHINA’S 1.1BN internet users churn out more data than anyone else on Earth. So does the country’s vast network of facial-recognition cameras. As autonomous cars speed down roads and flying ones criss-cross the skies, the quality and value of the information flowing from emerging technologies will soar. Yet the volume of data is not the only thing setting China apart. The government is also embedding data management into the economy and national security. That has implications for China, and holds lessons for democracies.

China’s planners see data as a factor of production, alongside labour, capital and land. Xi Jinping, the president, has called data a foundational resource “with a revolutionary impact” on international competition. The scope of this vision is unparalleled, affecting everything from civil liberties to the profits of internet firms and China’s pursuit of the lead in artificial intelligence.

Mr Xi’s vision is being enacted fast. In 2021 China released rules modelled on Europe’s General Data Protection Regulation (GDPR). Now it is diverging quickly from Western norms. All levels of government are to marshal the data resources they have. A sweeping project to assess the data piles at state-owned firms is under way. The idea is to value them as assets, and add them to balance-sheets or trade them on state-run exchanges. On June 3rd the State Council released new rules to compel all levels of government to share data.

Another big step is a digital ID, due to be launched on July 15th. Under this, the central authorities could control a ledger of every person’s websites and apps. Connecting someone’s name with their online activity will become harder for the big tech firms which used to run the system. They will see only an anonymised stream of digits and letters. Chillingly, however, the ledger may one day act as a panopticon for the state.

China’s ultimate goal appears to be to create an integrated national data ocean, covering not just consumers but industrial and state activity, too. The advantages are obvious, and include economies of scale for training AI models and lower barriers to entry for small new firms…(More)”.

AI companies start winning the copyright fight

Curated on Posted on by Stefaan Verhulst

Article by Blake Montgomery: “…tech companies notched several victories in the fight over their use of copyrighted text to create artificial intelligence products.

Anthropic: A US judge has ruled that Anthropic, maker of the Claude chatbot, use of books to train its artificial intelligence system – without permission of the authors – did not breach copyright law. Judge William Alsup compared the Anthropic model’s use of books to a “reader aspiring to be a writer.”

And the next day, Meta: The US district judge Vince Chhabria, in San Francisco, said in his decision on the Meta case that the authors had not presented enough evidence that the technology company’s AI would cause “market dilution” by flooding the market with work similar to theirs.

The same day that Meta received its favorable ruling, a group of writers sued Microsoft, alleging copyright infringement in the creation of that company’s Megatron text generator. Judging by the rulings in favor of Meta and Anthropic, the authors are facing an uphill battle.

These three cases are skirmishes in the wider legal war over copyrighted media, which rages on. Three weeks ago, Disney and NBCUniversal sued Midjourney, alleging that the company’s namesake AI image generator and forthcoming video generator made illegal use of the studios’ iconic characters like Darth Vader and the Simpson family. The world’s biggest record labels – Sony, Universal and Warner – have sued two companies that make AI-powered music generators, Suno and Udio. On the textual front, the New York Times’ suit against OpenAI and Microsoft is ongoing.

The lawsuits over AI-generated text were filed first, and, as their rulings emerge, the next question in the copyright fight is whether decisions about one type of media will apply to the next.

“The specific media involved in the lawsuit – written works versus images versus videos versus audio – will certainly change the fair-use analysis in each case,” said John Strand, a trademark and copyright attorney with the law firm Wolf Greenfield. “The impact on the market for the copyrighted works is becoming a key factor in the fair-use analysis, and the market for books is different than that for movies.”…(More)”.

Bad data leads to bad policy

Curated on Posted on by Stefaan Verhulst

Article by Georges-Simon Ulrich: “When the UN created a Statistical Commission in 1946, the world was still recovering from the devastation of the second world war. Then, there was broad consensus that only reliable, internationally comparable data could prevent conflict, combat poverty and anchor global co-operation. Nearly 80 years later, this insight remains just as relevant, but the context has changed dramatically…

This erosion of institutional capacity could not come at a more critical moment. The UN is unable to respond adequately as it is facing a staffing shortfall itself. Due to ongoing austerity measures at the UN, many senior positions remain vacant, and the director of the UN Statistics Division has retired, with no successor appointed. This comes at a time when bold and innovative initiatives — such as a newly envisioned Trusted Data Observatory — are urgently needed to make official statistics more accessible and machine-readable.

Meanwhile, the threat of targeted disinformation is growing. On social media, distorted or manipulated content spreads at unprecedented speed. Emerging tools like AI chatbots exacerbate the problem. These systems rely on web content, not verified data, and are not built to separate truth from falsehood. Making matters worse, many governments cannot currently make their data usable for AI because it is not standardised, not machine-readable, or not openly accessible. The space for sober, evidence-based discourse is shrinking.

This trend undermines public trust in institutions, strips policymaking of its legitimacy, and jeopardises the UN Sustainable Development Goals (SDGs). Without reliable data, governments will be flying blind — or worse: they will be deliberately misled.

When countries lose control of their own data, or cannot integrate it into global decision-making processes, they become bystanders to their own development. Decisions about their economies, societies and environments are then outsourced to AI systems trained on skewed, unrepresentative data. The global south is particularly at risk, with many countries lacking access to quality data infrastructures. In countries such as Ethiopia, unverified information spreading rapidly on social media has fuelled misinformation-driven violence.

The Covid-19 pandemic demonstrated that strong data systems enable better crisis response. To counter these risks, the creation of a global Trusted Data Observatory (TDO) is essential. This UN co-ordinated, democratically governed platform would help catalogue and make accessible trusted data around the world — while fully respecting national sovereignty…(More)”

Cloudflare Introduces Default Blocking of A.I. Data Scrapers

Curated on Posted on by Stefaan Verhulst

Article by Natallie Rocha: “Data for A.I. systems has become an increasingly contentious issue. OpenAI, Anthropic, Google and other companies building A.I. systems have amassed reams of information from across the internet to train their A.I. models. High-quality data is particularly prized because it helps A.I. models become more proficient in generating accurate answers, videos and images.

But website publishers, authors, news organizations and other content creators have accused A.I. companies of using their material without permission and payment. Last month, Reddit sued Anthropic, saying the start-up had unlawfully used the data of its more than 100 million daily users to train its A.I. systems. In 2023, The New York Times sued OpenAI and its partner, Microsoft, accusing them of copyright infringement of news content related to A.I. systems. OpenAI and Microsoft have denied those claims.

Some publishers have struck licensing deals with A.I. companies to receive compensation for their content. In May, The Times agreed to license its editorial content to Amazon for use in the tech giant’s A.I. platforms. Axel Springer, Condé Nast and News Corp have also entered into agreements with A.I. companies to receive revenue for the use of their material.

Mark Howard, the chief operating officer of Time, said he welcomed Cloudflare’s move. Data scraping by A.I. companies threatens anyone who creates content, he said, adding that news publishers like Time deserved fair compensation for what they published…(More)”.

Enjoy TikTok Explainers? These Old-Fashioned Diagrams Are A Whole Lot Smarter

Curated on Posted on by Stefaan Verhulst

Article by Jonathon Keats: “In the aftermath of Hiroshima, many of the scientists who built the atomic bomb changed the way they reckoned time. Their conception of the future was published on the cover of The Bulletin of the Atomic Scientists, which portrayed a clock set at seven minutes to midnight. In subsequent months and years, the clock sometimes advanced. Other times, the hands fell back. With this simple indication, the timepiece tracked the likelihood of nuclear annihilation.

Although few of the scientists who worked on the Manhattan Project are still alive, the Doomsday Clock remains operational, steadfastly translating risk into units of hours and minutes. Over time, the diagram has become iconic, and not only for subscribers to The Bulletin. It’s now so broadly recognizable that we may no longer recognize what makes it radical.

12 - Fondazione Prada_Diagrams
John Auldjo. Map of Vesuvius showing the direction of the streams of lava in the eruptions from 1631 to 1831, 1832. Exhibition copy from a printed book In John Auldjo, Sketches of Vesuvius: with Short Accounts of Its Principal Eruptions from the Commencement of the Christian Era to the Present Time (Napoli: George Glass, 1832). Olschki 53, plate before p. 27, Biblioteca Nazionale Centrale di Firenze, Firenze. Courtesy Ministero della Cultura – Biblioteca Nazionale Centrale di Firenze. Any unauthorized reproduction by any means whatsoever is prohibited.Biblioteca Nazionale Centrale di Firenze

A thrilling new exhibition at the Fondazione Prada brings the Doomsday Clock back into focus. Featuring hundreds of diagrams from the past millennium, ranging from financial charts to maps of volcanic eruptions, the exhibition provides the kind of survey that brings definition to an entire category of visual communication. Each work benefits from its association with others that are manifestly different in form and function…(More)”.

Why AI hardware needs to be open

Curated on Posted on by Stefaan Verhulst

Article by Ayah Bdeir: “Once again, the future of technology is being engineered in secret by a handful of people and delivered to the rest of us as a sealed, seamless, perfect device. When technology is designed in secrecy and sold to us as a black box, we are reduced to consumers. We wait for updates. We adapt to features. We don’t shape the tools; they shape us. 

This is a problem. And not just for tinkerers and technologists, but for all of us.

We are living through a crisis of disempowerment. Children are more anxious than ever; the former US surgeon general described a loneliness epidemic; people are increasingly worried about AI eroding education. The beautiful devices we use have been correlated with many of these trends. Now AI—arguably the most powerful technology of our era—is moving off the screen and into physical space. 

The timing is not a coincidence. Hardware is having a renaissance. Every major tech company is investing in physical interfaces for AI. Startups are raising capital to build robots, glasses, wearables that are going to track our every move. The form factor of AI is the next battlefield. Do we really want our future mediated entirely through interfaces we can’t open, code we can’t see, and decisions we can’t influence? 

This moment creates an existential opening, a chance to do things differently. Because away from the self-centeredness of Silicon Valley, a quiet, grounded sense of resistance is reactivating. I’m calling it the revenge of the makers. 

In 2007, as the iPhone emerged, the maker movement was taking shape. This subculture advocates for learning-through-making in social environments like hackerspaces and libraries. DIY and open hardware enthusiasts gathered in person at Maker Faires—large events where people of all ages tinkered and shared their inventions in 3D printing, robotics, electronics, and more. Motivated by fun, self-fulfillment, and shared learning, the movement birthed companies like MakerBot, Raspberry Pi, Arduino, and (my own education startup) littleBits from garages and kitchen tables. I myself wanted to challenge the notion that technology had to be intimidating or inaccessible, creating modular electronic building blocks designed to put the power of invention in the hands of everyone…(More)”

5 Ways Cooperatives Can Shape the Future of AI

Curated on Posted on by Stefaan Verhulst

Article by Trebor Scholz and Stefano Tortorici: “Today, AI development is controlled by a small cadre of firms. Companies like OpenAI, Alphabet, Amazon, Meta, and Microsoft dominate through vast computational resources, massive proprietary datasets, deep pools of technical talent, extractive data practices, low-cost labor, and capital that enables continuous experimentation and rapid deployment. Even open-source challengers like DeepSeek run on vast computational muscle and industrial training pipelines.

This domination brings problems: privacy violation and cost-minimizing labor strategies, high environmental costs from data centers, and evident biases in models that can reinforce discrimination in hiring, healthcare, credit scoring, policing, and beyond. These problems tend to affect the people who are already too often left out. AI’s opaque algorithms don’t just sidestep democratic control and transparency—they shape who gets heard, who’s watched, and who’s quietly pushed aside.

Yet, as companies consider using this technology, it can seem that there are few other options. As such, it can seem that they are locked into these compromises.

A different model is taking shape, however, with little fanfare, but with real potential. AI cooperatives—organizations developing or governing AI technologies based on cooperative principles—offer a promising alternative. The cooperative movement, with its global footprint and diversity of models, has been successful from banking and agriculture to insurance and manufacturing. Cooperatives enterprises, which are owned and governed by their members, have long managed infrastructure for the public good.

A handful of AI cooperatives offer early examples of how democratic governance and shared ownership could shape more accountable and community-centered uses of the technology. Most are large agricultural cooperatives that are putting AI to use in their day-to-day operations, such as IFFCO’s DRONAI program (AI for fertilization), FrieslandCampina (dairy quality control), and Fonterra (milk production analytics). Cooperatives must urgently organize to challenge AI’s dominance or remain on the sidelines of critical political and technological developments.​

There is undeniably potential here, for both existing cooperatives and companies that might want to partner with them. The $589 billion drop in Nvidia’s market cap DeepSeek triggered shows how quickly open-source innovation can shift the landscape. But for cooperative AI labs to do more than signal intent, they need public infrastructure, civic partnerships, and serious backing…(More)”.

AGI vs. AAI: Grassroots Ingenuity and Frugal Innovation Will Shape the Future

Curated on Posted on by Stefaan Verhulst

Article by Akash Kapur: “Step back from the day-to-day flurry surrounding AI, and a global divergence in narratives is becoming increasingly clear. In Silicon Valley, New York, and London, the conversation centers on the long-range pursuit of artificial general intelligence (AGI)—systems that might one day equal or surpass humans at almost everything. This is the moon-shot paradigm, fueled by multi-billion-dollar capital expenditure and almost metaphysical ambition.

In contrast, much of the Global South is converging on something more grounded: the search for near-term, proven use cases that can be deployed with today’s hardware, and limited budgets and bandwidth. Call it Applied AI, or AAI. This quest for applicability—and relevance—is more humble than AGI. Its yardstick for success is more measured, and certainly less existential. Rather than pose profound questions about the nature of consciousness and humanity, Applied AI asks questions like: Does the model fix a real-world problem? Can it run on patchy 4G, a mid-range GPU, or a refurbished phone? What new yield can it bring to farmers or fishermen, or which bureaucratic bottleneck can it cut?

One way to think of AAI is as intelligence that ships. Vernacular chatbots, offline crop-disease detectors, speech-to-text tools for courtrooms: examples of similar applications and products, tailored and designed for specific sectors, are growing fast. In Africa, PlantVillage Nuru helps Kenyan farmers diagnose crop diseases entirely offline; South-Africa-based Lelapa AI is training “small language models” for at least 13 African languages; and Nigeria’s EqualyzAI runs chatbots that are trained to provide Hausa and Yoruba translations for customers…(More)”.

A.I. Is Starting to Wear Down Democracy

Curated on Posted on by Stefaan Verhulst

Article by Steven Lee Myers and Stuart A. Thompson: “Since the explosion of generative artificial intelligence over the last two years, the technology has demeaned or defamed opponents and, for the first time, officials and experts said, begun to have an impact on election results.

Free and easy to use, A.I. tools have generated a flood of fake photos and videos of candidates or supporters saying things they did not or appearing in places they were not — all spread with the relative impunity of anonymity online.

The technology has amplified social and partisan divisions and bolstered antigovernment sentiment, especially on the far right, which has surged in recent elections in Germany, Poland and Portugal.

In Romania, a Russian influence operation using A.I. tainted the first round of last year’s presidential election, according to government officials. A court there nullified that result, forcing a new vote last month and bringing a new wave of fabrications. It was the first major election in which A.I. played a decisive role in the outcome. It is unlikely to be the last.

As the technology improves, officials and experts warn, it is undermining faith in electoral integrity and eroding the political consensus necessary for democratic societies to function.

Madalina Botan, a professor at the National University of Political Studies and Public Administration in Romania’s capital, Bucharest, said there was no question that the technology was already “being used for obviously malevolent purposes” to manipulate voters.

“These mechanics are so sophisticated that they truly managed to get a piece of content to go very viral in a very limited amount of time,” she said. “What can compete with this?”

In the unusually concentrated wave of elections that took place in 2024, A.I. was used in more than 80 percent, according to the International Panel on the Information Environment, an independent organization of scientists based in Switzerland.

It documented 215 instances of A.I. in elections that year, based on government statements, research and news reports. Already this year, A.I. has played a role in at least nine more major elections, from Canada to Australia…(More)”.

AI Scraping Bots Are Breaking Open Libraries, Archives, and Museums

Curated on Posted on by Stefaan Verhulst

Article by Emanuel Maiberg: “The report, titled “Are AI Bots Knocking Cultural Heritage Offline?” was written by Weinberg of the GLAM-E Lab, a joint initiative between the Centre for Science, Culture and the Law at the University of Exeter and the Engelberg Center on Innovation Law & Policy at NYU Law, which works with smaller cultural institutions and community organizations to build open access capacity and expertise. GLAM is an acronym for galleries, libraries, archives, and museums. The report is based on a survey of 43 institutions with open online resources and collections in Europe, North America, and Oceania. Respondents also shared data and analytics, and some followed up with individual interviews. The data is anonymized so institutions could share information more freely, and to prevent AI bot operators from undermining their counter measures.  

Of the 43 respondents, 39 said they had experienced a recent increase in traffic. Twenty-seven of those 39 attributed the increase in traffic to AI training data bots, with an additional seven saying the AI bots could be contributing to the increase. 

“Multiple respondents compared the behavior of the swarming bots to more traditional online behavior such as Distributed Denial of Service (DDoS) attacks designed to maliciously drive unsustainable levels of traffic to a server, effectively taking it offline,” the report said. “Like a DDoS incident, the swarms quickly overwhelm the collections, knocking servers offline and forcing administrators to scramble to implement countermeasures. As one respondent noted, ‘If they wanted us dead, we’d be dead.’”…(More)”