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)”.
Reimagining Data Governance for AI: Operationalizing Social Licensing for Data Reuse
Report by Stefaan Verhulst, Adam Zable, Andrew J. Zahuranec, and Peter Addo: “…introduces a practical, community-centered framework for governing data reuse in the development and deployment of artificial intelligence systems in low- and middle-income countries (LMICs). As AI increasingly relies on data from LMICs, affected communities are often excluded from decision-making and see little benefit from how their data is used. This report,…reframes data governance through social licensing—a participatory model that empowers communities to collectively define, document, and enforce conditions for how their data is reused. It offers a step-by-step methodology and actionable tools, including a Social Licensing Questionnaire and adaptable contract clauses, alongisde real-world scenarios and recommendations for enforcement, policy integration, and future research. This report recasts data governance as a collective, continuous process – shifting the focus from individual consent to community decision-making…(More)”.
Global Citizens’ Assemblies: Pathways for the UN – Principles, Design, and Implementation
Report by Democracy International & Democracy Without Borders: “This report encourages the use of GCAs by different actors and in different settings without making recommendations or expressing preferences on how this should be done. We envision that ultimately there will be a dynamic ecosystem making use of this deliberative format. However, the report particularly discusses the potential for GCAs to be set up by and benefit the UN. As a tool to be used by the UN, this paper recommends that the UN General Assembly (UNGA) applies Article 22 of the UN Charter to establish a dedicated permanent framework to codify procedures and operations, increase efficiency and create synergies. The report recommends that this UN framework should enable UN bodies and entities to set up and operate different ad hoc GCAs as needed.
GCAs are positioned as complementary to other initiatives in the field, such as creating a UN Parliamentary Assembly or a UN World Citizens’ Initiative. They offer a specific pathway for global public deliberation and participation and bridging the gap between citizens and global decision-makers.
While GCAs face practical limitations due to the world’s diversity and scale, they offer a valuable opportunity to foster trust in multilateral institutions and empower citizens to have a voice in global policy-making. By enhancing inclusive deliberation and putting forward actionable outcomes, GCAs have the potential to improve the democratic character of global governance and promote more responsive, citizen-centered approaches to solving planetary challenges…(More)”.
Leading, not lagging: Africa’s gen AI opportunity
Article by Mayowa Kuyoro, Umar Bagus: “The rapid rise of gen AI has captured the world’s imagination and accelerated the integration of AI into the global economy and the lives of people across the world. Gen AI heralds a step change in productivity. As institutions apply AI in novel ways, beyond the advanced analytics and machine learning (ML) applications of the past ten years, the global economy could increase significantly, improving the lives and livelihoods of millions.1
Nowhere is this truer than in Africa, a continent that has already demonstrated its ability to use technology to leapfrog traditional development pathways; for example, mobile technology overcoming the fixed-line internet gap, mobile payments in Kenya, and numerous African institutions making the leap to cloud faster than their peers in developed markets.2 Africa has been quick on the uptake with gen AI, too, with many unique and ingenious applications and deployments well underway…(More)”.
Across McKinsey’s client service work in Africa, many institutions have tested and deployed AI solutions. Our research has found that more than 40 percent of institutions have either started to experiment with gen AI or have already implemented significant solutions (see sidebar “About the research inputs”). However, the continent has so far only scratched the surface of what is possible, with both AI and gen AI. If institutions can address barriers and focus on building for scale, our analysis suggests African economies could unlock up to $100 billion in annual economic value across multiple sectors from gen AI alone. That is in addition to the still-untapped potential from traditional AI and ML in many sectors today—the combined traditional AI and gen AI total is more than double what gen AI can unlock on its own, with traditional AI making up at least 60 percent of the value…(More)”