Funding the Future: Grantmakers Strategies in AI Investment

Curated on Posted on by Stefaan Verhulst

Report by Project Evident: “…looks at how philanthropic funders are approaching requests to fund the use of AI… there was common recognition of AI’s importance and the tension between the need to learn more and to act quickly to meet the pace of innovation, adoption, and use of AI tools.

This research builds on the work of a February 2024 Project Evident and Stanford Institute for Human-Centered Artificial Intelligence working paper, Inspiring Action: Identifying the Social Sector AI Opportunity Gap. That paper reported that more practitioners than funders (by over a third) claimed their organization utilized AI. 

“From our earlier research, as well as in conversations with funders and nonprofits, it’s clear there’s a mismatch in the understanding and desire for AI tools and the funding of AI tools,” said Sarah Di Troia, Managing Director of Project Evident’s OutcomesAI practice and author of the report. “Grantmakers have an opportunity to quickly upskill their understanding – to help nonprofits improve their efficiency and impact, of course, but especially to shape the role of AI in civil society.”

The report offers a number of recommendations to the philanthropic sector. For example, funders and practitioners should ensure that community voice is included in the implementation of new AI initiatives to build trust and help reduce bias. Grantmakers should consider funding that allows for flexibility and innovation so that the social and education sectors can experiment with approaches. Most importantly, funders should increase their capacity and confidence in assessing AI implementation requests along both technical and ethical criteria…(More)”.

A Roadmap to Accessing Mobile Network Data for Statistics

Curated on Posted on by Stefaan Verhulst

Guide by Global Partnership for Sustainable Development Data: “… introduces milestones on the path to mobile network data access. While it is aimed at stakeholders in national statistical systems and across national governments in general, the lessons should resonate with others seeking to take this route. The steps in this guide are written in the order in which they should be taken, and some readers who have already embarked on this journey may find they have completed some of these steps. 

This roadmap is meant to be followed in steps, and readers may start, stop, and return to points on the path at any point. 

The path to mobile network data access has three milestones:

  1. Evaluating the opportunity – setting clear goals for the desired impact of data innovation.
  2. Engaging with stakeholders – getting critical stakeholders to support your cause.
  3. Executing collaboration agreements – signing a written agreement among partners…(More)”

Announcing the Youth Engagement Toolkit for Responsible Data Reuse: An Innovative Methodology for the Future of Data-Driven Services

Curated on Posted on by Stefaan Verhulst

Blog by Elena Murray, Moiz Shaikh, and Stefaan G. Verhulst: “Young people seeking essential services — whether mental health support, education, or government benefits — often face a critical challenge: they are asked to share their data without having a say in how it is used or for what purpose. While the responsible use of data can help tailor services to better meet their needs and ensure that vulnerable populations are not overlooked, a lack of trust in data collection and usage can have the opposite effect.

When young people feel uncertain or uneasy about how their data is being handled, they may adopt privacy-protective behaviors — choosing not to seek services at all or withholding critical information out of fear of misuse. This risks deepening existing inequalities rather than addressing them.

To build trust, those designing and delivering services must engage young people meaningfully in shaping data practices. Understanding their concerns, expectations, and values is key to aligning data use with their preferences. But how can this be done effectively?

This question was at the heart of a year-long global collaboration through the NextGenData project, which brought together partners worldwide to explore solutions. Today, we are releasing a key deliverable of that project: The Youth Engagement Toolkit for Responsible Data Reuse:

Based on a methodology developed and piloted during the NextGenData project, the Toolkit describes an innovative methodology for engaging young people on responsible data reuse practices, to improve services that matter to them…(More)”.

International Guidelines on People Centred Smart Cities

Curated on Posted on by Stefaan Verhulst

UN-Habitat: “…The guidelines aim to support national, regional and local governments, as well as relevant stakeholders, in leveraging digital technology for a better quality of life in cities and human settlements, while mitigating the associated risks to achieve global visions of sustainable urban development, in line with the New Urban Agenda, the 2030 Agenda for Sustainable Development and other relevant global agendas.
The aim is to promote a people-centred smart cities approach that is consistent with the purpose and the principles of the Charter of the United Nations, including full respect for international law and the Universal Declaration of Human Rights, to ensure that innovation and digital technologies are used to help cities and human settlements in order to achieve the Sustainable Development Goals and the New Urban Agenda.
The guidelines serve as a reference for Member States to implement people-centred smart city approaches in the preparation and implementation of smart city regulations, plans and strategies to promote equitable access to, and life-long education and training of all people in, the opportunities provided by data, digital infrastructure and digital services in cities and human settlements, and to favour transparency and accountability.
The guidelines recognize local and regional governments (LRGs) as pivotal actors in ensuring closing digital divides and localizing the objectives and principles of these guidelines as well as the Global Digital Compact for an open, safe, sustainable and secure digital future. The guidelines are intended to complement existing global principles on digital development through a specific additional focus on the key role of local and regional governments, and local action, in advancing people-centred smart city development also towards the vision of global digital compact…(More)”.

Disinformation: Definitions and examples

Curated on Posted on by Stefaan Verhulst

Explainer by Perthusasia Centre: “Disinformation has been a tool of manipulation and control for centuries, from ancient military strategies to Cold War propaganda. With the rapid advancement of technology,
it has evolved into a sophisticated and pervasive security threat that transcends traditional boundaries.

This explainer takes the definitions and examples from our recent Indo-Pacific Analysis Brief, Disinformation and cognitive warfare by Senior Fellow Alana Ford, and creates an simple, standalone guide for quick reference…(More)”.

Diversifying Professional Roles in Data Science

Curated on Posted on by Stefaan Verhulst

Policy Briefing by Emma Karoune and Malvika Sharan: The interdisciplinary nature of the data science workforce extends beyond the traditional notion of a “data scientist.” A successful data science team requires a wide range of technical expertise, domain knowledge and leadership capabilities. To strengthen such a team-based approach, this note recommends that institutions, funders and policymakers invest in developing and professionalising diverse roles, fostering a resilient data science ecosystem for the future. 


By recognising the diverse specialist roles that collaborate within interdisciplinary teams, organisations can leverage deep expertise across multiple skill sets, enhancing responsible decision-making and fostering innovation at all levels. Ultimately, this note seeks to shift the perception of data science professionals from the conventional view of individual data scientists to a competency-based model of specialist roles within a team, each essential to the success of data science initiatives…(More)”.

Future of AI Research

Curated on Posted on by Stefaan Verhulst

Report by the Association for the Advancement of Artificial Intelligence:  “As AI capabilities evolve rapidly, AI research is also undergoing a fast and significant transformation along many dimensions, including its topics, its methods, the research community, and the working environment. Topics such as AI reasoning and agentic AI have been studied for decades but now have an expanded scope in light of current AI capabilities and limitations. AI ethics and safety, AI for social good, and sustainable AI have become central themes in all major AI conferences. Moreover, research on AI algorithms and software systems is becoming increasingly tied to substantial amounts of dedicated AI hardware, notably GPUs, which leads to AI architecture co-creation, in a way that is more prominent now than over the last 3 decades. Related to this shift, more and more AI researchers work in corporate environments, where the necessary hardware and other resources are more easily available, compared to academia, questioning the roles of academic AI research, student retention, and faculty recruiting. The pervasive use of AI in our daily lives and its impact on people, society, and the environment makes AI a socio-technical field of study, thus highlighting the need for AI researchers to work with experts from other disciplines, such as psychologists, sociologists, philosophers, and economists. The growing focus on emergent AI behaviors rather than on designed and validated properties of AI systems renders principled empirical evaluation more important than ever. Hence the need arises for well-designed benchmarks, test methodologies, and sound processes to infer conclusions from the results of computational experiments. The exponentially increasing quantity of AI research publications and the speed of AI innovation are testing the resilience of the peer-review system, with the immediate release of papers without peer-review evaluation having become widely accepted across many areas of AI research. Legacy and social media increasingly cover AI research advancements, often with contradictory statements that confuse the readers and blur the line between reality and perception of AI capabilities. All this is happening in a geo-political environment, in which companies and countries compete fiercely and globally to lead the AI race. This rivalry may impact access to research results and infrastructure as well as global governance efforts, underscoring the need for international cooperation in AI research and innovation.

In this overwhelming multi-dimensional and very dynamic scenario, it is important to be able to clearly identify the trajectory of AI research in a structured way. Such an effort can define the current trends and the research challenges still ahead of us to make AI more capable and reliable, so we can safely use it in mundane but also, most importantly, in high-stake scenarios.

This study aims to do this by including 17 topics related to AI research, covering most of the transformations mentioned above. Each chapter of the study is devoted to one of these topics, sketching its history, current trends and open challenges…(More)”.

Legitimacy: Working hypotheses

Curated on Posted on by Stefaan Verhulst

Report by TIAL: “Today more than ever, legitimacy is a vital resource for institutions seeking to lead and sustain impactful change. Yet, it can be elusive.

What does it truly mean for an institution to be legitimate? This publication delves into legitimacy as both a practical asset and a dynamic process, offering institutional entrepreneurs the tools to understand, build, and sustain it over time.

Legitimacy is not a static quality, nor is it purely theoretical. Instead, it’s grounded in the beliefs of those who interact with or are governed by an institution. These beliefs shape whether people view an institution’s authority as rightful and worth supporting. Drawing from social science research and real-world insights, this publication provides a framework to help institutional entrepreneurs address one of the most important challenges of institutional design: ensuring their legitimacy is sufficient to achieve their goals.

The paper emphasizes that legitimacy is relational and contextual. Institutions gain it through three primary sources: outcomes (delivering results), fairness (ensuring just processes), and correct procedures (following accepted norms). However, the need for legitimacy varies depending on the institution’s size, scope, and mission. For example, a body requiring elite approval may need less legitimacy than one relying on mass public trust.

Legitimacy is also dynamic—it ebbs and flows in response to external factors like competition, crises, and shifting societal narratives. Institutional entrepreneurs must anticipate these changes and actively manage their strategies for maintaining legitimacy. This publication highlights actionable steps for doing so, from framing mandates strategically to fostering public trust through transparency and communication.

By treating legitimacy as a resource that evolves over time, institutional entrepreneurs can ensure their institutions remain relevant, trusted, and effective in addressing pressing societal challenges.

Key takeaways

  • Legitimacy is the belief by an audience that an institution’s authority is rightful.
  • Institutions build legitimacy through outcomes, fairness, and correct procedures.
  • The need for legitimacy depends on an institution’s scope and mission.
  • Legitimacy is dynamic and shaped by external factors like crises and competition.
  • A portfolio approach to legitimacy—balancing outcomes, fairness, and procedure—is more resilient.
  • Institutional entrepreneurs must actively manage perceptions and adapt to changing contexts.
  • This publication offers practical frameworks to help institutional entrepreneurs build and sustain legitimacy…(More)”.

The Data Innovation Toolkit

Curated on Posted on by Stefaan Verhulst

Toolkit by Maria Claudia Bodino, Nathan da Silva Carvalho, Marcelo Cogo, Arianna Dafne Fini Storchi, and Stefaan Verhulst: “Despite the abundance of data, the excitement around AI, and the potential for transformative insights, many public administrations struggle to translate data into actionable strategies and innovations. 

Public servants working with data-related initiatives, need practical, easy-to-use resources designed to enhance the management of data innovation initiatives. 

In order to address these needs, the iLab of DG DIGIT from the European Commission is developing an initial set of practical tools designed to facilitate and enhance the implementation of data-driven initiatives. The main building blocks of the first version of the of the Digital Innovation Toolkit include: 

  1. A Repository of educational materials and resources on the latest data innovation approaches from public sector, academia, NGOs and think tanks 
  2. An initial set of practical resources, some examples: 
  3. Workshop Templates to offer structured formats for conducting productive workshops that foster collaboration, ideation, and problem-solving. 
  4. Checklists to ensure that all data journey aspects and steps are properly assessed. 
  5. Interactive Exercises to engage team members in hands-on activities that build skills and facilitate understanding of key concepts and methodologies. 
  6. Canvas Models to provide visual frameworks for planning and brainstorming….(More)”.

How tax data unlocks new insights for industrial policy

Curated on Posted on by Stefaan Verhulst

OECD article: “Value-added tax (VAT) is a consumption tax applied at each stage of the supply chain whenever value is added to goods or services. Businesses collect and remit VAT. The VAT data that are collected represent a breakthrough in studying production networks because they capture actual transactions between firms at an unprecedented level of detail. Unlike traditional business surveys or administrative data that might tell us about a firm’s size or industry, VAT records show us who does business with whom and for how much.

This data is particularly valuable because of its comprehensive coverage. In Estonia, for example, all VAT-registered businesses must report transactions above €1,000 per month, creating an almost complete picture of significant business relationships in the economy.

At least 15 countries now have such data available, including Belgium, Chile, Costa Rica, Estonia, and Italy. This growing availability creates opportunities for cross-country comparison and broader economic insights…(More)”.