Making the case for collaborative digital infrastructure to scale regenerative food supply networks

Curated on Posted on by Stefaan Verhulst

Briefing paper from the Food Data Collaboration: “…a call to action to collaborate and invest in data infrastructure that will enable shorter, relational, regenerative food supply networks to scale.

These food supply networks play a vital role in achieving a truly sustainable and resilient food system. By embracing data technology that fosters commons ownership models, collaboration and interdependence we can build a more inclusive and dynamic food ecosystem in which collaborative efforts, as opposed to competitive businesses operating in silos, can achieve transformative scale.

Since 2022, the Food Data Collaboration has been exploring the potential for open data standards to enable shorter, relational, regenerative food supply networks to scale and pave the way towards a healthier, more equitable, and more resilient food future. This paper explores the high level rationale for our approach and is essential reading for anyone keen to know more about the project’s aims, achievements and future development…(More)”.

The Agentic State: How Agentic AI Will Revamp 10 Functional Layers of Public Administration

Curated on Posted on by Stefaan Verhulst

Whitepaper by the Global Government Technology Centre Berlin: “…explores how agentic AI will transform ten functional layers of government and public administration. The Agentic State signifies a fundamental shift in governance, where AI systems can perceive, reason, and act with minimal human intervention to deliver public value. Its impact on  key functional layers of government will be as follows…(More)”.

Unlock Your City’s Hidden Solutions

Curated on Posted on by Stefaan Verhulst

Article by Andreas Pawelke, Basma Albanna and Damiano Cerrone: “Cities around the world face urgent challenges — from climate change impacts to rapid urbanization and infrastructure strain. Municipal leaders struggle with limited budgets, competing priorities, and pressure to show quick results, making traditional approaches to urban transformation increasingly difficult to implement.

Every city, however, has hidden success stories — neighborhoods, initiatives, or communities that are achieving remarkable results despite facing similar challenges as their peers.

These “positive deviants” often remain unrecognized and underutilized, yet they contain the seeds of solutions that are already adapted to local contexts and constraints.

Data-Powered Positive Deviance (DPPD) combines urban data, advanced analytics, and community engagement to systematically uncover these bright spots and amplify their impact. This new approach offers a pathway to urban transformation that is not only evidence-based but also cost-effective and deeply rooted in local realities.

DPPD is particularly valuable in resource-constrained environments, where expensive external solutions often fail to take hold. By starting with what’s already working, cities can make strategic investments that build on existing strengths rather than starting from scratch. Leveraging AI tools that improve community engagement, the approach becomes even more powerful — enabling cities to envision potential futures, and engage citizens in meaningful co-creation…(More)”

Data as Policy

Curated on Posted on by Stefaan Verhulst

Paper by Janet Freilich and W. Nicholson Price II: “A large literature on regulation highlights the many different methods of policy-making: command-and-control rulemaking, informational disclosures, tort liability, taxes, and more. But the literature overlooks a powerful method to achieve policy objectives: data. The state can provide (or suppress) data as a regulatory tool to solve policy problems. For administrations with expansive views of government’s purpose, government-provided data can serve as infrastructure for innovation and push innovation in socially desirable directions; for administrations with deregulatory ambitions, suppressing or choosing not to collect data can reduce regulatory power or serve as a back-door mechanism to subvert statutory or common law rules. Government-provided data is particularly powerful for data-driven technologies such as AI where it is sometimes more effective than traditional methods of regulation. But government-provided data is a policy tool beyond AI and can influence policy in any field. We illustrate why government-provided data is a compelling tool both for positive regulation and deregulation in contexts ranging from addressing healthcare discrimination, automating legal practice, smart power generation, and others. We then consider objections and limitations to the role of government-provided data as policy instrument, with substantial focus on privacy concerns and the possibility for autocratic abuse.

We build on the broad literature on regulation by introducing data as a regulatory tool. We also join—and diverge from—the growing literature on data by showing that while data can be privately produced purely for private gain, they do not need to be. Rather, government can be deeply involved in the generation and sharing of data, taking a much more publicly oriented view. Ultimately, while government-provided data are not a panacea for either regulatory or data problems, governments should view data provision as an understudied but useful tool in the innovation and governance toolbox…(More)”

The Teacher in the Machine: A Human History of Education Technology

Curated on Posted on by Stefaan Verhulst

Book by Anne Trumbore: “From AI tutors who ensure individualized instruction but cannot do math to free online courses from elite universities that were supposed to democratize higher education, claims that technological innovations will transform education often fall short. Yet, as Anne Trumbore shows in The Teacher in the Machine, the promises of today’s cutting-edge technologies aren’t new. Long before the excitement about the disruptive potential of generative AI–powered tutors and massive open online courses, scholars at Stanford, MIT, and the University of Illinois in the 1960s and 1970s were encouraged by the US government to experiment with computers and artificial intelligence in education. Trumbore argues that the contrast between these two eras of educational technology reveals the changing role of higher education in the United States as it shifted from a public good to a private investment.

Writing from a unique insider’s perspective and drawing on interviews with key figures, historical research, and case studies, Trumbore traces today’s disparate discussions about generative AI, student loan debt, and declining social trust in higher education back to their common origins at a handful of elite universities fifty years ago. Arguing that those early educational experiments have resonance today, Trumbore points the way to a more equitable and collaborative pedagogical future. Her account offers a critical lens on the history of technology in education just as universities and students seek a stronger hand in shaping the future of their institutions…(More)”

How Being Watched Changes How You Think

Curated on Posted on by Stefaan Verhulst

Article by Simon Makin: “In 1785 English philosopher Jeremy Bentham designed the perfect prison: Cells circle a tower from which an unseen guard can observe any inmate at will. As far as a prisoner knows, at any given time, the guard may be watching—or may not be. Inmates have to assume they’re constantly observed and behave accordingly. Welcome to the Panopticon.

Many of us will recognize this feeling of relentless surveillance. Information about who we are, what we do and buy and where we go is increasingly available to completely anonymous third parties. We’re expected to present much of our lives to online audiences and, in some social circles, to share our location with friends. Millions of effectively invisible closed-circuit television (CCTV) cameras and smart doorbells watch us in public, and we know facial recognition with artificial intelligence can put names to faces.

So how does being watched affect us? “It’s one of the first topics to have been studied in psychology,” says Clément Belletier, a psychologist at University of Clermont Auvergne in France. In 1898 psychologist Norman Triplett showed that cyclists raced harder in the presence of others. From the 1970s onward, studies showed how we change our overt behavior when we are watched to manage our reputation and social consequences.

But being watched doesn’t just change our behavior; decades of research show it also infiltrates our mind to impact how we think. And now a new study reveals how being watched affects unconscious processing in our brain. In this era of surveillance, researchers say, the findings raise concerns about our collective mental health…(More)”.

Citizen Centricity in Public Policy Making

Curated on Posted on by Stefaan Verhulst

Book by Naci Karkin and Volkan Göçoğlu: “The book explores and positions citizen centricity within conventional public administration and public policy analysis theories and approaches. It seeks to define an appropriate perspective while utilizing popular, independent, and standalone concepts from the literature that support citizen centricity. Additionally, it illustrates the implementation part with practical cases. It ultimately presents a novel and descriptive approach to provide insights into how citizen centricity can be applied in practice. This descriptive novel approach has three essential components: a base and two pillars. The foundation includes new-age public policy making approaches and complexity theory. The first column reflects the conceptual dimension, which comprises supporting concepts from the literature on citizen centricity. The second column represents the practical dimension, a structure supported by academic research that provides practical cases and inspiration for future applications. The descriptive novel approach accepts citizen centricity as a fundamental approach in public policy making and aims to create a new awareness in the academic community on the subject. Additionally, the book provides refreshed conceptual and theoretical backgrounds, along with tangible participatory models and frameworks, benefiting academics, professionals, and graduate students…(More)”.

Where Cloud Meets Cement

Curated on Posted on by Stefaan Verhulst

Report by Hanna Barakat, Chris Cameron, Alix Dunn and Prathm Juneja, and Emma Prest: “This report examines the global expansion of data centers driven by AI and cloud computing, highlighting both their economic promises and the often-overlooked social and environmental costs. Through case studies across five countries, it investigates how governments and tech companies influence development, how communities resist harmful effects, and what support is needed for effective advocacy…(More)”.

Designing Shared Data Futures: Engaging young people on how to re-use data responsibly for health and well-being

Curated on Posted on by Stefaan Verhulst

Report by Hannah Chafetz, Sampriti Saxena, Tracy Jo Ingram, Andrew J. Zahuranec, Jennifer Requejo and Stefaan Verhulst: “When young people are engaged in data decisions for or about them, they not only become more informed about this data, but can also contribute to new policies and programs that improve their health and well-being. However, oftentimes young people are left out of these discussions and are unaware of the data that organizations collect.

In October 2023, The Second Lancet Commission on Adolescent Health and well-being, the United Nations Children’s Fund (UNICEF), and The GovLab at New York University hosted six Youth Solutions Labs (or co-design workshops) with over 120 young people from 36 countries around the world. In addition to co-designing solutions to five key issues impacting their health and well-being, we sought to understand current sentiments around the re-use of data on those issues. The Labs provided several insights about young people’s preferences regarding: 1) the purposes for which data should be re-used to improve health and well-being, 2) the types and sources of data that should and should not be re-used, 3) who should have access to previously collected data, and 4) under what circumstances data re-use should take place. Additionally, participants provided suggestions of what ethical and responsible data re-use looks like to them and how young people can participate in decision making processes. In this paper, we elaborate on these findings and provide a series of recommendations to accelerate responsible data re-use for the health and well-being of young people…(More)”.

Why Generative AI Isn’t Transforming Government (Yet) — and What We Can Do About It

Curated on Posted on by Stefaan Verhulst

Article by Tiago C. Peixoto: “A few weeks ago, I reached out to a handful of seasoned digital services practitioners, NGOs, and philanthropies with a simple question: Where are the compelling generative AI (GenAI) use cases in public-sector workflows? I wasn’t looking for better search or smarter chatbots. I wanted examples of automation of real public workflows – something genuinely interesting and working. The responses, though numerous, were underwhelming.

That question has gained importance amid a growing number of reports forecasting AI’s transformative impact on government. The Alan Turing Institute, for instance, published a rigorous study estimating the potential of AI to help automate over 140 million government transactions in the UK. The Tony Blair Institute also weighed in, suggesting that a substantive portion of public-sector work could be automated. While the report helped bring welcome attention to the issue, its use of GPT-4 to assess task automatability has sparked a healthy discussion about how best to evaluate feasibility. Like other studies in this area, both reports highlight potential – but stop short of demonstrating real service automation.

Without testing technologies in real service environments – where workflows, incentives, and institutional constraints shape outcomes – and grounding each pilot in clear efficiency or well-being metrics, estimates risk becoming abstractions that underestimate feasibility.

This pattern aligns with what Arvind Narayanan and Sayash Kapoor argue in “AI as Normal Technology:” the impact of AI is realized only when methods translate into applications and diffuse through real-world systems. My own review, admittedly non-representative, confirms their call for more empirical work on the innovation-diffusion lag.

In the public sector, the gap between capability and impact is not only wide but also structural…(More)”