The Global Data Barometer 2nd edition: A Shared Compass for Navigating the Data Landscape


Report by the Global Data Barometer: “Across the globe, we’re at a turning point. From artificial intelligence and digital governance to public transparency and service delivery, data is now a fundamental force shaping how our societies function and who they serve. It holds tremendous promise to drive inclusive growth, foster accountability, and support urgent action on global challenges. And yet, access to high-quality, usable data is becoming increasingly constrained.

Some, like Verhulst (2024), have begun calling this moment a “data winter,” a period marked by shrinking openness, rising inequality in access, and growing fragmentation in how data is governed and used. This trend poses a risk not just to innovation but to the democratic values that underpin trust, participation, and accountability.

In this complex landscape, evidence matters more than ever. That is why we are proud to launch the Second Edition of the Global Data Barometer (GDB), a collaborative and comparative study that tracks the state of data for the public good across 43 countries, with a focused lens on Latin America and the Caribbean (LAC) and Africa…

The Barometer tracks countries across four dimensions: governance, capabilities, and availability, while also exploring key cross-cutting areas like AI readiness, inclusion, and data use. Here are some of the key takeaways:

  • The Implementation Gap

Many countries have adopted laws and frameworks for data governance, but there is a stark gap between policy and practice. Without strong institutions and dedicated capacity, even well-designed frameworks fall short.

  • The Role of Skills and Infrastructure

Data does not flow or translate into value without people and systems in place. Across both Latin America and the Caribbean and Africa, we see underinvestment in public sector skills, training, and the infrastructure needed to manage and reuse data effectively.

  • AI Is Moving Faster Than Governance

AI is increasingly present in national strategies, but very few countries have clear policies to guide its ethical use. Governance frameworks rarely address issues like algorithmic bias, data quality, or the accountability of AI-driven decision-making.

  • Open Data Needs Reinvestment

Many countries once seen as open data champions are struggling to sustain their efforts. Legal mandates are not always matched by technical implementation or resources. As a result, open data initiatives risk losing momentum.

  • Transparency Tools Are Missing

Key datasets that support transparency and anti-corruption, such as lobbying registers, beneficial ownership data, and political finance records, are often missing or fragmented. This makes it hard to follow the money or hold institutions to account.

  • Inclusion Is Still Largely Symbolic

Despite commitments to equity, inclusive data governance remains the exception. Data is rarely published in Indigenous or widely spoken non-official languages. Accessibility for persons with disabilities is often treated as a recommendation rather than a requirement.

  • Interoperability Remains a Barrier

Efforts to connect datasets across government, such as on procurement, company data, or political integrity, are rare. Without common standards or identifiers, it is difficult to track influence or evaluate policy impact holistically…(More)”.

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


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


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)”.

Where Cloud Meets Cement


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


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)”.

Can We Trust Social Science Yet?


Essay by Ryan Briggs: “Everyone likes the idea of evidence-based policy, but it’s hard to realize it when our most reputable social science journals are still publishing poor quality research.

Ideally, policy and program design is a straightforward process: a decision-maker faces a problem, turns to peer-reviewed literature, and selects interventions shown to work. In reality, that’s rarely how things unfold. The popularity of “evidence-based medicine” and other “evidence-based” topics highlights our desire for empirical approaches — but would the world actually improve if those in power consistently took social science  evidence seriously? It brings me no joy to tell you that, at present, I think the answer is usually “no.”

Given the current state of evidence production in the social sciences, I believe that many — perhaps most — attempts to use social scientific evidence to inform policy will not lead to better outcomes. This is not because of politics or the challenges of scaling small programs. The problem is more immediate. Much of social science research is of poor quality, and sorting the trustworthy work from bad work is difficult, costly, and time-consuming.

But it is necessary. If you were to randomly select an empirical paper published in the past decade — including any studies from the top journals in political science or economics — there is a high chance that its findings may be inaccurate. And not just off by a little: possibly two times as large, or even incorrectly signed. As an academic, this bothers me. I think it should bother you, too. So let me explain why this happens…(More)”.

Simulating Human Behavior with AI Agents


Brief by The Stanford Institute for Human-Centered AI (HAI): “…we introduce an AI agent architecture that simulates more than 1,000 real people. The agent architecture—built by combining the transcripts of two-hour, qualitative interviews with a large language model (LLM) and scored against social science benchmarks—successfully replicated real individuals’ responses to survey questions 85% as accurately as participants replicate their own answers across surveys staggered two weeks apart. The generative agents performed comparably in predicting people’s personality traits and experiment outcomes and were less biased than previously used simulation tools.

This architecture underscores the benefits of using generative agents as a research tool to glean new insights into real-world individual behavior. However, researchers and policymakers must also mitigate the risks of using generative agents in such contexts, including harms related to over-reliance on agents, privacy, and reputation…(More)”.

Public AI White Paper – A Public Alternative to Private AI Dominance


White paper by the Bertelsmann Stiftung and Open Future: “Today, the most advanced AI systems are developed and controlled by a small number of private companies. These companies hold power not only over the models themselves but also over key resources such as computing infrastructure. This concentration of power poses not only economic risks but also significant democratic challenges.

The Public AI White Paper presents an alternative vision, outlining how open and public-interest approaches to AI can be developed and institutionalized. It advocates for a rebalancing of power within the AI ecosystem – with the goal of enabling societies to shape AI actively, rather than merely consume it…(More)”.

From Software to Society — Openness in a changing world


Report by Henriette Litta and Peter Bihr: “…takes stock and looks to the future: What does openness mean in the digital age? Is the concept still up to date? The study traces the development of openness and analyses current challenges. It is based on interviews with experts and extensive literature research. The key insights at a glance are:

Give Openness a purpose. Especially in times of increasing injustice, surveillance and power monopolies, a clear framework for meaningful openness is needed, as this is often lacking. Companies market ‘open’ products without enabling co-creation. Political actors invoke openness without strengthening democratic control. This is particularly evident when dealing with AI. AI systems are complex and are often dominated by a few tech companies – which makes opening them up a fundamental challenge. The dominance of some tech companies is also massively exploited, which can lead to the censorship of other opinions.

Protect Openness by adding guard rails. Those who demand openness must also be prepared to get involved in political disputes – against a market monopoly, for example. According to Litta and Bihr, this requires new licence models that include obligations to return and share, as well as stricter enforcement of antitrust law and data protection. Openness therefore needs rules…(More)”.

Addressing Digital Harms in Conflict


Report by Henriette Litta and Peter Bihr: “…takes stock and looks to the future: What does openness mean in the digital age? Is the concept still up to date? The study traces the development of Openness and analyses current challenges. It is based on interviews with experts and extensive literature research. The key insights at a glance are:

  • Give Openness a purpose.
  • Protect Openness by adding guard rails.
  • Open innovation and infrastructure need investments.
  • Openness is not neutral.
  • Market domination needs to be curtailed…(More)”.