Comparative perspectives on the regulation of large language models

Curated on Posted on by Stefaan Verhulst

Editorial to Special Issue by Cristina Poncibò and Martin Ebers: “Large language models (LLMs) represent one of the most significant technological advancements in recent decades, offering transformative capabilities in natural language processing and content generation. Their development has far-reaching implications across technological, economic and societal domains, simultaneously creating opportunities for innovation and posing profound challenges for governance and regulation. As LLMs become integral to various sectors, from education to healthcare to entertainment, regulators are scrambling to establish frameworks that ensure their safe and ethical use.

Our issue primarily examines the private ordering, regulatory responses and normative frameworks for LLMs from a comparative law perspective, with a particular focus on the European Union (EU), the United States (US) and China. An introductory part preliminarily explores the technical principles that underpin LLMs as well as their epistemological foundations. It also addresses key sector-specific legal challenges posed by LLMs, including their implications for criminal law, data protection and copyright law…(More)”.

The Future of Jobs Report 2025

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Report by the World Economic Forum: “Technological change, geoeconomic fragmentation, economic uncertainty, demographic shifts and the green transition – individually and in combination are among the major drivers expected to shape and transform the global labour market by 2030. The Future of Jobs Report 2025 brings together the perspective of over 1,000 leading global employers—collectively representing more than 14 million workers across 22 industry clusters and 55 economies from around the world—to examine how these macrotrends impact jobs and skills, and the workforce transformation strategies employers plan to embark on in response, across the 2025 to 2030 timeframe…(More)”.

The People Say

Curated on Posted on by Stefaan Verhulst

About: “The People Say is an online research hub that features first-hand insights from older adults and caregivers on the issues most important to them, as well as feedback from experts on policies affecting older adults. 

This project particularly focuses on the experiences of communities often under-consulted in policymaking, including older adults of color, those who are low income, and/or those who live in rural areas where healthcare isn’t easily accessible. The People Say is funded by The SCAN Foundation and developed by researchers and designers at the Public Policy Lab.

We believe that effective policymaking listens to most-affected communities—but policies and systems that serve older adults are typically formed with little to no input from older adults themselves. We hope The People Say will help policymakers hear the voices of older adults when shaping policy…(More)”

In the hands of a few: Disaster recovery committee networks

Curated on Posted on by Stefaan Verhulst

Paper by Timothy Fraser, Daniel P. Aldrich, Andrew Small and Andrew Littlejohn: “When disaster strikes, urban planners often rely on feedback and guidance from committees of officials, residents, and interest groups when crafting reconstruction policy. Focusing on recovery planning committees after Japan’s 2011 earthquake, tsunami, and nuclear disasters, we compile and analyze a dataset on committee membership patterns across 39 committees with 657 members. Using descriptive statistics and social network analysis, we examine 1) how community representation through membership varied among committees, and 2) in what ways did committees share members, interlinking members from certain interests groups. This study finds that community representation varies considerably among committees, negatively related to the prevalence of experts, bureaucrats, and business interests. Committee membership overlap occurred heavily along geographic boundaries, bridged by engineers and government officials. Engineers and government bureaucrats also tend to be connected to more members of the committee network than community representatives, giving them prized positions to disseminate ideas about best practices in recovery. This study underscores the importance of diversity and community representation in disaster recovery planning to facilitate equal participation, information access, and policy implementation across communities…(More)”.

Participatory seascape mapping: A community-based approach to ocean governance and marine conservation

Curated on Posted on by Stefaan Verhulst

Paper by Isabel James: “Despite the global proliferation of ocean governance frameworks that feature socioeconomic variables, the inclusion of community needs and local ecological knowledge remains underrepresented. Participatory mapping or Participatory GIS (PGIS) has emerged as a vital method to address this gap by engaging communities that are conventionally excluded from ocean planning and marine conservation. Originally developed for forest management and Indigenous land reclamation, the scholarship on PGIS remains predominantly focused on terrestrial landscapes. This review explores recent research that employs the method in the marine realm, detailing common methodologies, data types and applications in governance and conservation. A typology of ocean-centered PGIS studies was identified, comprising three main categories: fisheries, habitat classification and blue economy activities. Marine Protected Area (MPA) design and conflict management are the most prevalent conservation applications of PGIS. Case studies also demonstrate the method’s effectiveness in identifying critical marine habitats such as fish spawning grounds and monitoring endangered megafauna. Participatory mapping shows particular promise in resource and data limited contexts due to its ability to generate large quantities of relatively reliable, quick and low-cost data. Validation steps, including satellite imagery and ground-truthing, suggest encouraging accuracy of PGIS data, despite potential limitations related to human error and spatial resolution. This review concludes that participatory mapping not only enriches scientific research but also fosters trust and cooperation among stakeholders, ultimately contributing to more resilient and equitable ocean governance…(More)”.

SciAgents: Automating Scientific Discovery Through Bioinspired Multi-Agent Intelligent Graph Reasoning

Curated on Posted on by Stefaan Verhulst

Paper by Alireza Ghafarollahi, and Markus J. Buehler: “A key challenge in artificial intelligence (AI) is the creation of systems capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex patterns, and uncovering previously unseen connections in vast scientific data. In this work, SciAgents, an approach that leverages three core concepts is presented: (1) large-scale ontological knowledge graphs to organize and interconnect diverse scientific concepts, (2) a suite of large language models (LLMs) and data retrieval tools, and (3) multi-agent systems with in-situ learning capabilities. Applied to biologically inspired materials, SciAgents reveals hidden interdisciplinary relationships that were previously considered unrelated, achieving a scale, precision, and exploratory power that surpasses human research methods. The framework autonomously generates and refines research hypotheses, elucidating underlying mechanisms, design principles, and unexpected material properties. By integrating these capabilities in a modular fashion, the system yields material discoveries, critiques and improves existing hypotheses, retrieves up-to-date data about existing research, and highlights strengths and limitations. This is achieved by harnessing a “swarm of intelligence” similar to biological systems, providing new avenues for discovery. How this model accelerates the development of advanced materials by unlocking Nature’s design principles, resulting in a new biocomposite with enhanced mechanical properties and improved sustainability through energy-efficient production is shown…(More)”.

Protecting civilians in a data-driven and digitalized battlespace: Towards a minimum basic technology infrastructure

Curated on Posted on by Stefaan Verhulst

Paper by Ann Fitz-Gerald and Jenn Hennebry: “This article examines the realities of modern day warfare, including a rising trend in hybrid threats and irregular warfare which employ emerging technologies supported by digital and data-driven processes. The way in which these technologies become applied generates a widened battlefield and leads to a greater number of civilians being caught up in conflict. Humanitarian groups mandated to protect civilians have adapted their approaches to the use of new emerging technologies. However, the lack of international consensus on the use of data, the public and private nature of the actors involved in conflict, the transnational aspects of the widened battlefield, and the heightened security risks in the conflict space pose enormous challenges for the protection of civilians agenda. Based on the dual-usage aspect of emerging technologies, the challenges associated with regulation and the need for those affected by conflict to demonstrate resilience towards, and knowledge of, digital media literacy, this paper proposes the development of guidance for a “minimum basic technology infrastructure” which is supported by technology, regulation, and public awareness and education…(More)”.

Once It Has Been Trained, Who Will Own My Digital Twin?

Curated on Posted on by Stefaan Verhulst

Article by Todd Carpenter: “Presently, if one ignores the hype around Generative AI systems, we can recognize that software tools are not sentient. Nor can they (yet) overcome the problem of coming up with creative solutions to novel problems. They are limited in what they can do by the training data that they are supplied. They do hold the prospect for making us more efficient and productive, particularly for wrote tasks. But given enough training data, one could consider how much farther this could be taken. In preparation for that future, when it comes to the digital twins, the landscape of the ownership of the intellectual property (IP) behind them is already taking shape.

Several chatbots have been set up to replicate long-dead historical figures so that you can engage with them in their “voice”.  Hellohistory is an AI-driven chatbot that provides people the opportunity to, “have in-depth conversations with history’s greatest.” A different tool, Historical Figures Chat, was widely panned not long after its release in 2023, and especially by historians who strongly objected. There are several variations on this theme of varying quality. Of course, with all things GenAI, they will improve over time and many of the obvious and problematic issues will be resolved either by this generation of companies or the next. Whether there is real value and insight to be gained, apart from the novelty, of engaging with “real historical figures” is the multi-billion dollar question. Much like the World Wide Web in the 1990s, very likely there is value, but it will be years before it can be clearly discerned what that value is and how to capitalize upon it. In anticipation of that day, many organizations are positioning themselves to capture that value.

While many universities have taken a very liberal view of ownership of the intellectual property of their students and faculty — far more liberal than many corporations might — others are quite more restrictive…(More)”.

Philanthropy by the Numbers

Curated on Posted on by Stefaan Verhulst

Essay by Aaron Horvath: “Foundations make grants conditional on demonstrable results. Charities tout the evidentiary basis of their work. And impact consultants play both sides: assisting funders in their pursuit of rational beneficence and helping grantees translate the jumble of reality into orderly, spreadsheet-ready metrics.

Measurable impact has crept into everyday understandings of charity as well. There’s the extensive (often fawning) news coverage of data-crazed billionaire philanthropists, so-called thought leaders exhorting followers to rethink their contributions to charity, and popular books counseling that intuition and sentiment are poor guides for making the world a better place. Putting ideas into action, charity evaluators promote research-backed listings of the most impactful nonprofits. Why give to your local food bank when there’s one in Somerville, Massachusetts, with a better rating?

Over the past thirty years, amid a larger crisis of civic engagement, social isolation, and political alienation, measurable impact has seeped into our civic imagination and become one of the guiding ideals for public-spirited beneficence. And while its proponents do not always agree on how best to achieve or measure the extent of that impact, they have collectively recast civic engagement as objective, pragmatic, and above the fray of politics—a triumph of the head over the heart. But how did we get here? And what happens to our capacity for meaningful collective action when we think of civic life in such depersonalized and quantified terms?…(More)”.

To Whom Does the World Belong?

Curated on Posted on by Stefaan Verhulst

Essay by Alexander Hartley: “For an idea of the scale of the prize, it’s worth remembering that 90 percent of recent U.S. economic growth, and 65 percent of the value of its largest 500 companies, is already accounted for by intellectual property. By any estimate, AI will vastly increase the speed and scale at which new intellectual products can be minted. The provision of AI services themselves is estimated to become a trillion-dollar market by 2032, but the value of the intellectual property created by those services—all the drug and technology patents; all the images, films, stories, virtual personalities—will eclipse that sum. It is possible that the products of AI may, within my lifetime, come to represent a substantial portion of all the world’s financial value.

In this light, the question of ownership takes on its true scale, revealing itself as a version of Bertolt Brecht’s famous query: To whom does the world belong?

Questions of AI authorship and ownership can be divided into two broad types. One concerns the vast troves of human-authored material fed into AI models as part of their “training” (the process by which their algorithms “learn” from data). The other concerns ownership of what AIs produce. Call these, respectively, the input and output problems.

So far, attention—and lawsuits—have clustered around the input problem. The basic business model for LLMs relies on the mass appropriation of human-written text, and there simply isn’t anywhere near enough in the public domain. OpenAI hasn’t been very forthcoming about its training data, but GPT-4 was reportedly trained on around thirteen trillion “tokens,” roughly the equivalent of ten trillion words. This text is drawn in large part from online repositories known as “crawls,” which scrape the internet for troves of text from news sites, forums, and other sources. Fully aware that vast data scraping is legally untested—to say the least—developers charged ahead anyway, resigning themselves to litigating the issue in retrospect. Lawyer Peter Schoppert has called the training of LLMs without permission the industry’s “original sin”—to be added, we might say, to the technology’s mind-boggling consumption of energy and water in an overheating planet. (In September, Bloomberg reported that plans for new gas-fired power plants have exploded as energy companies are “racing to meet a surge in demand from power-hungry AI data centers.”)…(More)”.