Beyond AI and Copyright

Curated on Posted on by Stefaan Verhulst

White Paper by Paul Keller: “…argues for interventions to ensure the sustainability of the information ecosystem in the age of generative AI. Authored by Paul Keller, the paper builds on Open Future’s ongoing work on Public AI and on AI and creative labour, and proposes measures aimed at ensuring a healthy and equitable digital knowledge commons.

Rather than focusing on the rights of individual creators or the infringement debates that dominate current policy discourse, the paper frames generative AI as a new cultural and social technology—one that is rapidly reshaping how societies access, produce, and value information. It identifies two major structural risks: the growing concentration of control over knowledge, and the hollowing out of the institutions and economies that sustain human information production.

To counter these risks, the paper calls for the development of public AI infrastructures and a redistributive mechanism based on a levy on commercial AI systems trained on publicly available information. The proceeds would support not only creators and rightholders, but also public service media, cultural heritage institutions, open content platforms, and the development of Public AI systems…(More)”.

Data Collection and Analysis for Policy Evaluation: Not for Duty, but for Knowledge

Curated on Posted on by Stefaan Verhulst

Paper by Valentina Battiloro: “This paper explores the challenges and methods involved in public policy evaluation, focusing on the role of data collection and use. The term “evaluation” encompasses a variety of analyses and approaches, all united by the intent to provide a judgment on a specific policy, but which, depending on the precise knowledge objective, can translate into entirely different activities. Regardless of the type of evaluation, a brief overview of which is provided, the collection of information represents a priority, often undervalued, under the assumption that it is sufficient to “have the data.“ Issues arise concerning the precise definition of the design, the planning of necessary information collection, and the appropriate management of timelines. With regard to administrative data, a potentially valuable source, a number of unresolved challenges remain due to a weak culture of data utilization. Among these are the transition from an administrative data culture to a statistical data culture, and the fundamental issue of microdata accessibility for research purposes, which is currently hindered by significant barriers…(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)”.

Companies Are Missing The Chance To Improve The World With Their Data

Curated on Posted on by Stefaan Verhulst

Article by Nino Letteriello: “This September will mark two years since the Data Governance Act officially became applicable across the European Union. This regulation, part of the broader European data strategy, focuses primarily on data sharing between public and private entities and the overall development of a data-driven economy.

Although less known than its high-profile counterparts—the Data Act and especially the Artificial Intelligence Act—the Data Governance Act introduces a particularly compelling concept: data altruism.

Data altruism refers to the voluntary sharing of data—by individuals or companies—without expecting any reward for purposes of general interest. Such data has immense potential to advance research and drive innovation in areas like healthcare, environmental sustainability and mobility…The absence of structured research into corporate resistance to data donation suggests that the topic remains niche—mostly embraced by tech giants with strong data capabilities and CSR programs, like Meta for Good and Google AI for Good—but still virtually unknown to most companies.

Before we talk about resistance to data donation, perhaps we should explore the level of awareness companies have about the impact such donations could have.

And so, in trying to answer the question I posed at the beginning of this article, perhaps the most appropriate response is yet another question: Do companies even realize that the data they collect, generate and manage could be a vital resource for building a better world?

And if they were more aware of the different ways they could do good with data—would they be more inclined to act?

Despite the existence of the Data Governance Act and the Data Act, these questions remain largely unanswered. But the hope is that, as data becomes more democratized within organizations and as social responsibility and sustainability take center stage, “Data for Good” will become a standard theme in corporate agendas.

After all, private companies are the most valuable and essential data providers and partners for this kind of transformation—and it is often we, the people, who provide them with the very data that could help change our world…(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)”

The Global A.I. Divide

Curated on Posted on by Stefaan Verhulst

Article by Adam Satariano and Paul Mozur: “Last month, Sam Altman, the chief executive of the artificial intelligence company OpenAI, donned a helmet, work boots and a luminescent high-visibility vest to visit the construction site of the company’s new data center project in Texas.

Bigger than New York’s Central Park, the estimated $60 billion project, which has its own natural gas plant, will be one of the most powerful computing hubs ever created when completed as soon as next year.

Around the same time as Mr. Altman’s visit to Texas, Nicolás Wolovick, a computer science professor at the National University of Córdoba in Argentina, was running what counts as one of his country’s most advanced A.I. computing hubs. It was in a converted room at the university, where wires snaked between aging A.I. chips and server computers.

“Everything is becoming more split,” Dr. Wolovick said. “We are losing.”

Artificial intelligence has created a new digital divide, fracturing the world between nations with the computing power for building cutting-edge A.I. systems and those without. The split is influencing geopolitics and global economics, creating new dependencies and prompting a desperate rush to not be excluded from a technology race that could reorder economies, drive scientific discovery and change the way that people live and work.

The biggest beneficiaries by far are the United States, China and the European Union. Those regions host more than half of the world’s most powerful data centers, which are used for developing the most complex A.I. systems, according to data compiled by Oxford University researchers. Only 32 countries, or about 16 percent of nations, have these large facilities filled with microchips and computers, giving them what is known in industry parlance as “compute power.”..(More)”.

How to Make Small Beautiful: The Promise of Democratic Innovations

Curated on Posted on by Stefaan Verhulst

Paper by Christoph Niessen & Wouter Veenendaal: “Small states are on average more likely to be democracies and it is often assumed that democracy functions better in small polities. ‘Small is beautiful’, proponents say. Yet, empirical scholarship shows that, while smallness comes with socio-political proximity, which facilitates participation and policy implementation, it also incentivizes personalism, clientelism and power concentration. Largeness, instead, comes with greater socio-political distance, but strengthens institutional checks and entails scale advantages. In this article, we depart from this trade-off and, wondering ‘how to make small beautiful’, we examine a potential remedy: democratic innovations. To do so, we first show that representative institutions were adopted in small polities by replication rather than by choice, and that they can aggravate the democratic problems associated with smallness. Subsequently, we draw on four usages of direct and deliberative democratic practices in small polities to explore which promises they offer to correct some of these pitfalls…(More)”.

National engagement on public trust in data use for single patient record and GP health record published

Curated on Posted on by Stefaan Verhulst

HTN Article: “A large-scale public engagement report commissioned by NHSE on building and maintaining public trust in data use across health and care has been published, focusing on the approach to creating a single patient record and the secondary use of GP data.

It noted “relief” and “enthusiasm” from participants around not having to repeat their health history when interacting with different parts of the health and care system, and highlighted concerns about data accuracy, privacy, and security.

120 participants were recruited for tier one, with 98 remaining by the end, for 15 hours of deliberation over three days in locations including Liverpool, Leicester, Portsmouth, and South London. Inclusive engagement for tier two recruited 76 people from “seldom heard groups” such as those with health needs or socially marginalised groups for interviews and small group sessions. A nationally representative ten-minute online survey with 2,000 people was also carried out in tier three.

“To start with, the concept of a single patient record was met with relief and enthusiasm across Tier 1 and Tier 2 participants,” according to the report….

When it comes to GP data, participants were “largely unaware” of secondary uses, but initially expressed comfort in the idea of it being used for saving lives, improving care, prevention, and efficiency in delivery of services. Concerns were broadly similar to those about the single patient record: concerns about data breaches, incorrect data, misuse, sensitivity of data being shared, bias against individuals, and the potential for re-identification. Some participants felt GP data should be treated differently because “it is likely to contain more intimate information”, offering greater risk to the individual patient if data were to be misused. Others felt it should be included alongside secondary care data to ensure a “comprehensive dataset”.

Participants were “reassured” overall by safeguards in place such as de-identification, staff training in data handling and security, and data regulation such as GDPR and the Data Protection Act. “There was a widespread feeling among Tier 1 and Tier 2 participants that the current model of the GP being the data controller for both direct care and secondary uses placed too much of a burden on GPs when it came to how data is used for secondary purposes,” findings show. “They wanted to see a new model which would allow for greater consistency of approach, transparency, and accountability.” Tier one participants suggested this could be a move to national or regional decision-making on secondary use. Tier three participants who only engaged with the topic online were “more resistant” to moving away from GPs as sole data controllers, with the report stating: “This greater reluctance to change demonstrates the need for careful communication with the public about this topic as changes are made, and continued involvement of the public.”..(More)”.

The war over the peace business

Curated on Posted on by Stefaan Verhulst

Article by Tekendra Parmar: “At the second annual AI+ Expo in Washington, DC, in early June, war is the word of the day.

As a mix of Beltway bureaucrats, military personnel, and Washington’s consultant class peruse the expansive Walter E. Washington Convention Center, a Palantir booth showcases its latest in data-collection suites for “warfighters.” Lockheed Martin touts the many ways it is implementing AI throughout its weaponry systems. On the soundstage, the defense tech darling Mach Industries is selling its newest uncrewed aerial vehicles. “We’re living in a world with great-power competition,” the presenter says. “We can’t rule out the possibility of war — but the best way to prevent a war is deterrence,” he says, flanked by videos of drones flying through what looked like the rugged mountains and valleys of Kandahar.

Hosted by the Special Competitive Studies Project, a think tank led by former Google CEO Eric Schmidt, the expo says it seeks to bridge the gap between Silicon Valley entrepreneurs and Washington policymakers to “strengthen” America and its allies’ “competitiveness in critical technologies.”

One floor below, a startup called Anadyr Horizon is making a very different sales pitch, for software that seeks to prevent war rather than fight it: “Peace tech,” as the company’s cofounder Arvid Bell calls it. Dressed in white khakis and a black pinstripe suit jacket with a dove and olive branch pinned to his lapel (a gift from his husband), the former Harvard political scientist begins by noting that Russia’s all-out invasion of Ukraine had come as a surprise to many political scientists. But his AI software, he says, could predict it.

Long the domain of fantasy and science fiction, the idea of forecasting conflict has now become a serious pursuit. In Isaac Asimov’s 1950s “Foundation” series, the main character develops an algorithm that allows him to predict the decline of the Galactic Empire, angering its rulers and forcing him into exile. During the coronavirus pandemic, the US State Department experimented with AI fed with Twitter data to predict “COVID cases” and “violent events.” In its AI audit two years ago, the State Department revealed that it started training AI on “open-source political, social, and economic datasets” to predict “mass civilian killings.” The UN is also said to have experimented with AI to model the war in Gaza…(More)”… ..See also Kluz Prize for PeaceTech (Applications Open)