Data Collaborations How-to-Guide

Curated on Posted on by Stefaan Verhulst

Resource by The Data for Children Collaborative: “… excited to share a consolidation of 5 years of learning in one handy how-to-guide. Our ethos is to openly share tools, approaches and frameworks that may benefit others working in the Data for Good space. We have developed this guide specifically to support organisations working on complex challenges that may have data-driven solutions. The How-to-Guide provides advice and examples of how to plan and execute collaboration on a data project effectively…  

Data collaboration can provide organisations with high-quality, evidence-based insights that drive policy and practice while bringing together diverse perspectives to solve problems. It also fosters innovation, builds networks for future collaboration, and ensures effective implementation of solutions on the ground…(More)”.

Harnessing Mission Governance to Achieve National Climate Targets

Curated on Posted on by Stefaan Verhulst

OECD Report: “To achieve ambitious climate targets under the Paris Agreement, countries need more than political will – they need effective governance. This report examines how a mission-oriented approach can transform climate action. Analysing 15 countries’ climate council assessments, the report reveals that, while many nations are incorporating elements of mission governance, significant gaps remain. It highlights promising examples of whole-of-government approaches, while identifying key challenges, such as limited societal engagement, weak co-ordination, and a lack of focus on experimentation and ecosystem mobilisation. The report argues that national climate commitments effectively function as overarching missions, and thus, can greatly benefit from applying mission governance principles. It recommends integrating missions into climate mitigation efforts, applying these principles to policy design and implementation, and deploying targeted missions to address specific climate challenges. By embracing a holistic, mission-driven strategy, countries can enhance their climate action and achieve their ambitious targets…(More)”.

AI, Innovation and the Public Good: A New Policy Playbook

Curated on Posted on by Stefaan Verhulst

Paper by Burcu Kilic: “When Chinese start-up DeepSeek released R1 in January 2025, the groundbreaking open-source artificial intelligence (AI) model rocked the tech industry as a more cost-effective alternative to models running on more advanced chips. The launch coincided with industrial policy gaining popularity as a strategic tool for governments aiming to build AI capacity and competitiveness. Once dismissed under neoliberal economic frameworks, industrial policy is making a strong comeback with more governments worldwide embracing it to build digital public infrastructure and foster local AI ecosystems. This paper examines how the national innovation system framework can guide AI industrial policy to foster innovation and reduce reliance on dominant tech companies…(More)”.

Legal frictions for data openness

Curated on Posted on by Stefaan Verhulst

Paper by Ramya Chandrasekhar: “investigates legal entanglements of re-use, when data and content from the open web is used to train foundation AI models. Based on conversations with AI researchers and practitioners, an online workshop, and legal analysis of a repository of 41 legal disputes relating to copyright and data protection, this report highlights tensions between legal imaginations of data flows and computational processes involved in training foundation models.

To realise the promise of the open web as open for all, this report argues that efforts oriented solely towards techno-legal openness of training datasets are not enough. Techno-legal openness of datasets facilitates easy re-use of data. But, certain well-resourced actors like Big Tech are able to take advantage of data flows on the open web to internet to train proprietary foundation models, while giving little to no value back to either the maintenance of shared informational resources or communities of commoners. At the same time, open licenses no longer accommodate changing community preferences of sharing and re-use of data and content.
In addition to techno-legal openness of training datasets, there is a need for certain limits on the extractive power of well-resourced actors like BigTech combined with increased recognition of community data sovereignty. Alternative licensing frameworks, such as the Nwulite Obodo License, Kaitiakitanga Licenses, the Montreal License, the OpenRAIL Licenses, the Open Data Commons License, and the AI2Impact Licenses hold valuable insights in this regard. While these licensing frameworks impose more obligations on re-users and necessitate more collective thinking on interoperability,they are nonetheless necessary for the creation of healthy digital and data commons, to realise the original promise of the open web as open for all…(More)”.

Robotics for Global development

Curated on Posted on by Stefaan Verhulst

Report by the Frontier Tech Hub: “Robotics could enable progress on 46% of SDG targets  yet this potential remains largely untapped in low and middle-income countries. 

While technological developments and new-found applications of artificial intelligence (AI) keep captivating significant attention and investments, using robotics to advance the Sustainable Development Goals (SDGs) is consistently overlooked. This is especially true when the focus moves from aerial robotics (drones) to robotic arms, ground robotics, and aquatic robotics. How might these types of robots accelerate global development in the least developed countries? 

We aim to answer this question and inform the UK Foreign, Commonwealth & Development Office’s (FCDO) investment and policy towards robotics in the least developed countries (LDCs). In an emergent space, the UK FCDO has a unique opportunity to position itself as a global leader in leveraging robotics technology to accelerate sustainable development outcomes…(More)”.

Which Data Do Economists Use to Study Corruption ?

Curated on Posted on by Stefaan Verhulst

World Bank paper: “…examines the data sources and methodologies used in economic research on corruption by analyzing 339 journal articles published in 2022 that include Journal of Economic Literature codes. The paper identifies the most commonly used data types, sources, and geographical foci, as well as whether studies primarily investigate the causes or consequences of corruption. Cross-country composite indicators remain the dominant measure, while single country studies more frequently utilize administrative data. Articles in ranked journals are more likely to employ administrative and experimental data and focus on the causes of corruption. The broader dataset of 882 articles highlights the significant academic interest in corruption across disciplines, particularly in political science and public policy. The findings raise concerns about the limited use of novel data sources and the relative neglect of research on the causes of corruption, underscoring the need for a more integrated approach within the field of economics…(More)”.

2025 Ratings for Digital Participation Tools

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People-Powered Report: The latest edition of our Digital Participation Tool Ratings evaluates 30 comprehensive tools that have been used to support digital participation all over the world. This year’s ratings offer more information and insights on each tool to help you select a suitable tool for your context and needs. We also researched how AI tools and features fit into the current digital participation landscape. 

For the last four years, People Powered has been committed to providing governments and organizations with digital participation guidance, to enable people leading participatory programs and citizen engagement efforts to effectively select and use digital participation tools by providing guidance and ratings for tools. These ratings are the latest edition of the evaluations first launched in 2022. Further guidance about how to use these tools is available from our Guide to Digital Participation Platforms and Online Training on Digital Participation…(More)”.

Designing New Institutions and Renewing Existing Ones – A Playbook

Curated on Posted on by Stefaan Verhulst

UNDP Report: “The world has long depended on public institutions to solve problems and meet needs — from running schools to building roads, taking care of public health to defense. Today, global challenges like climate change, election security, forced migration, and AI-induced unemployment demand new institutional responses, especially in the Global South.

The bad news? Many institutions now struggle with public distrust, being seen as too wasteful
and inefficient, unresponsive and ineffective, and sometimes corrupt and outdated.
The good news? Fresh methods and models inspired by innovations in government, business, and civil
society are now available that can help us rethink institutions — making them more public results
oriented, agile, transparent, and fit for purpose. And ready for the future…(More)”.

Getting the Public on Side: How to Make Reforms Acceptable by Design

Curated on Posted on by Stefaan Verhulst

OECD Report: “Public acceptability is a crucial condition for the successful implementation of reforms. The challenges raised by the green, digital and demographic transitions call for urgent and ambitious policy action. Despite this, governments often struggle to build sufficiently broad public support for the reforms needed to promote change. Better information and effective public communication have a key role to play. But policymakers cannot get the public to choose the side of reform without a proper understanding of people’s views and how they can help strengthen the policy process.

Perceptual and behavioural data provide an important source of insights on the perceptions, attitudes and preferences that constitute the “demand-side” of reform. The interdisciplinary OECD Expert Group on New Measures of the Public Acceptability of Reforms was set up in 2021 to take stock of these insights and explore their potential for improving policy. This report reflects the outcomes of the Expert Group’s work. It looks at and assesses (i) the available data and what they can tell policymakers about people’s views; (ii) the analytical frameworks through which these data are interpreted; and (iii) the policy tools through which considerations of public acceptability are integrated into the reform process…(More)”.

The Language Data Space (LDS)

Curated on Posted on by Stefaan Verhulst

European Commission: “… welcomes launch of the Alliance for Language Technologies European Digital Infrastructure Consortium (ALT-EDIC) and the Language Data Space (LDS).

Aimed at addressing the shortage of European language data needed for training large language models, these projects are set to revolutionise multilingual Artificial Intelligence (AI) systems across the EU.

By offering services in all EU languages, the initiatives are designed to break down language barriers, providing better, more accessible solutions for smaller businesses within the EU. This effort not only aims to preserve the EU’s rich cultural and linguistic heritage in the digital age but also strengthens Europe’s quest for tech sovereignty. Formed in February 2024, the ALT-EDIC includes 17 participating Member States and 9 observer Member States and regions, making it one of the pioneering European Digital Infrastructure Consortia.

The LDS, part of the Common European Data Spaces, is crucial for increasing data availability for AI development in Europe. Developed by the Commission and funded by the DIGITAL programme,  this project aims to create a cohesive marketplace for language data. This will enhance the collection and sharing of multilingual data to support European large language models. Initially accessible to selected institutions and companies, the project aims to eventually involve all European public and private stakeholders.

Find more information about the Alliance for Language Technologies European Digital Infrastructure Consortium (ALT-EDIC) and the Language Data Space (LDS)…(More)”