Synthetic Data, Synthetic Media, and Surveillance


Paper by Aaron Martin and Bryce Newell: “Public and scholarly interest in the related concepts of synthetic data and synthetic media has exploded in recent years. From issues raised by the generation of synthetic datasets to train machine learning models to the public-facing, consumer availability of artificial intelligence (AI) powered image manipulation and creation apps and the associated increase in synthetic (or “deepfake”) media, these technologies have shifted from being niche curiosities of the computer science community to become topics of significant public, corporate, and regulatory import. They are emblematic of a “data-generation revolution” (Gal and Lynskey 2024: 1091) that is already raising pressing questions for the academic surveillance studies community. Within surveillance studies scholarship, Fussey (2022: 348) has argued that synthetic media is one of several “issues of urgent societal and planetary concern” and that it has “arguably never been more important” for surveillance studies “researchers to understand these dynamics and complex processes, evidence their implications, and translate esoteric knowledge to produce meaningful analysis.” Yet, while fields adjacent to surveillance studies have begun to explore the ethical risks of synthetic data, we currently perceive a lack of attention to the surveillance implications of synthetic data and synthetic media in published literature within our field. In response, this Dialogue is designed to help promote thinking and discussion about the links and disconnections between synthetic data, synthetic media, and surveillance…(More)”

AI could help scale humanitarian responses. But it could also have big downsides


Article by Thalia Beaty: “As the International Rescue Committee copes with dramatic increases in displaced people in recent years, the refugee aid organization has looked for efficiencies wherever it can — including using artificial intelligence.

Since 2015, the IRC has invested in Signpost — a portfolio of mobile apps and social media channels that answer questions in different languages for people in dangerous situations. The Signpost project, which includes many other organizations, has reached 18 million people so far, but IRC wants to significantly increase its reach by using AI tools — if they can do so safely.

Conflict, climate emergencies and economic hardship have driven up demand for humanitarian assistance, with more than 117 million people forcibly displaced in 2024, according to the United Nations refugee agency. The turn to artificial intelligence technologies is in part driven by the massive gap between needs and resources.

To meet its goal of reaching half of displaced people within three years, the IRC is testing a network of AI chatbots to see if they can increase the capacity of their humanitarian officers and the local organizations that directly serve people through Signpost. For now, the pilot project operates in El Salvador, Kenya, Greece and Italy and responds in 11 languages. It draws on a combination of large language models from some of the biggest technology companies, including OpenAI, Anthropic and Google.

The chatbot response system also uses customer service software from Zendesk and receives other support from Google and Cisco Systems.

If they decide the tools work, the IRC wants to extend the technical infrastructure to other nonprofit humanitarian organizations at no cost. They hope to create shared technology resources that less technically focused organizations could use without having to negotiate directly with tech companies or manage the risks of deployment…(More)”.

Rethinking the Measurement of Resilience for
Food and Nutrition Security


Paper by John M. Ulimwengu: “This paper presents a novel framework for assessing resilience in food systems, focusing on three dynamic metrics: return time, magnitude of deviation, and recovery rate. Traditional resilience measures have often relied on static and composite indicators, creating gaps in understanding the complex responses of food systems to shocks. This framework addresses these gaps, providing a more nuanced assessment of resilience in agrifood sectors. It highlights how integrating dynamic metrics enables policymakers to design tailored, sector-specific interventions that enhance resilience. Recognizing the data intensity required for these metrics, the paper indicates how emerging satellite imagery and advancements in artificial intelligence (AI) can make data collection both high-frequency and location-specific, at a fraction of the cost of traditional methods. These technologies facilitate a scalable approach to resilience measurement, enhancing the accuracy, timeliness, and accessibility of resilience data. The paper concludes with recommendations for refining resilience tools and adapting policy frameworks to better respond to the increasing challenges faced by food systems across the world…(More)”.

The Collaboration Playbook: A leader’s guide to cross-sector collaboration


Playbook by Ian Taylor and Nigel Ball: “The challenges facing our societies and economies today are so large and complex that, in many cases, cross-sector collaboration is not a choice, but an imperative. Yet collaboration remains elusive for many, often being put into the ‘too hard’ category. This playbook offers guidance on how we can seize collaboration opportunities successfully and rise to the challenges.

The recommendations in the playbook were informed by academic literature and practitioner experience. Rather than offer a procedural, step-by-step guide, this playbook offers provoking questions and frameworks that applies to different situations and objectives. While formal aspects such as contracts and procedures are well understood, it was found that what was needed was guidance on the intangible elements, sometimes referred to as ‘positive chemistry’. The significance of aspects like leadership, trust, culture, learning and power in cross-sector collaborations can be the game-changers for productive endeavours but are hard to get right.

Structured around these five key themes, the playbook presents 18 discreet ‘plays’ for effective collaboration. The plays allow the reader to delve into specific areas of interest to gain a deeper understanding of what it means for their collaborative work.

The intention of the playbook is to provide a resource that informs and guides cross-sector leaders. It will be especially relevant for those working in, and partnering with, central and local government in an effort to improve social outcomes…(More)”.

Rethinking Theories of Governance


Book by Christopher Ansell: “Are theories of governance useful for helping policymakers and citizens meet and tackle contemporary challenges? This insightful book reflects on how a theory becomes useful and evaluates a range of theories according to whether they are warranted, diagnostic, and dialogical.

By arguing that useful theory tells us what to ask, not what to do, Christopher Ansell investigates what it means for a theory to be useful. Analysing how governance theories address a variety of specific challenges, chapters examine intractable public problems, weak government accountability, violent conflict, global gridlock, poverty and the unsustainable exploitation of our natural resources. Finding significant tensions between state- and society-centric perspectives on governance, the book concludes with a suggestion that we refocus our theories of governance on possibilities for state-society synergy. Governance theories of the future, Ansell argues, should also strive for a more fruitful dialogue between instrumental, critical and explanatory perspectives.

Examining both the conceptual and empirical basis of theories of governance, this comprehensive book will be an invigorating read for scholars and students in the fields of public administration, public policy and planning, development studies, political science and urban, environmental and global governance. By linking theories of governance to concrete societal challenges, it will also be of use to policymakers and practitioners concerned with these fields…(More)”.

The Next Phase of the Data Economy: Economic & Technological Perspectives


Paper by Jad Esber et al: The data economy is poised to evolve toward a model centered on individual agency and control, moving us toward a world where data is more liquid across platforms and applications. In this future, products will either utilize existing personal data stores or create them when they don’t yet exist, empowering individuals to fully leverage their own data for various use cases.

The analysis begins by establishing a foundation for understanding data as an economic good and the dynamics of data markets. The article then investigates the concept of personal data stores, analyzing the historical challenges that have limited their widespread adoption. Building on this foundation, the article then considers how recent shifts in regulation, technology, consumer behavior, and market forces are converging to create new opportunities for a user-centric data economy. The article concludes by discussing potential frameworks for value creation and capture within this evolving paradigm, summarizing key insights and potential future directions for research, development, and policy.

We hope this article can help shape the thinking of scholars, policymakers, investors, and entrepreneurs, as new data ownership and privacy technologies emerge, and regulatory bodies around the world mandate open flows of data and new terms of service intended to empower users as well as small-to-medium–sized businesses…(More)”.

The Emergence of National Data Initiatives: Comparing proposals and initiatives in the United Kingdom, Germany, and the United States


Article by Stefaan Verhulst and Roshni Singh: “Governments are increasingly recognizing data as a pivotal asset for driving economic growth, enhancing public service delivery, and fostering research and innovation. This recognition has intensified as policymakers acknowledge that data serves as the foundational element of artificial intelligence (AI) and that advancing AI sovereignty necessitates a robust data ecosystem. However, substantial portions of generated data remain inaccessible or underutilized. In response, several nations are initiating or exploring the launch of comprehensive national data strategies designed to consolidate, manage, and utilize data more effectively and at scale. As these initiatives evolve, discernible patterns in their objectives, governance structures, data-sharing mechanisms, and stakeholder engagement frameworks reveal both shared principles and country-specific approaches.

This blog seeks to start some initial research on the emergence of national data initiatives by examining three national data initiatives and exploring their strategic orientations and broader implications. They include:

Collective Intelligence: The Rise of Swarm Systems and their Impact on Society


Book edited by Uwe Seebacher and Christoph Legat: “Unlock the future of technology with this captivating exploration of swarm intelligence. Dive into the future of autonomous systems, enhanced by cutting-edge multi-agent systems and predictive research. Real-world examples illustrate how these algorithms drive intelligent, coordinated behavior in industries like manufacturing and energy. Discover the innovative Industrial-Disruption-Index (IDI), pioneered by Uwe Seebacher, which predicts industry disruptions using swarm intelligence. Case studies from media to digital imaging offer invaluable insights into the future of industrial life cycles.

Ideal for AI enthusiasts and professionals, this book provides inspiring, actionable insights for the future. It redefines artificial intelligence, showcasing how predictive intelligence can revolutionize group coordination for more efficient and sustainable systems. A crucial chapter highlights the shift from the Green Deal to the Emerald Deal, showing how swarm intelligence addresses societal challenges…(More)”.

Civic Engagement & Policymaking Toolkit


About: “This toolkit serves as a guide for science centers and museums and other science engagement organizations to thoughtfully identify and implement ways to nurture civic experiences like these across their work or deepen ongoing civic initiatives for meaningful change within their communities…

This toolkit outlines a Community Science Approach, Civic Engagement & Policymaking, where science and technology are factors in collective civic action and policy decisions to meet community goals. It includes:

  • Guidance for your team on how to get started with this work,
  • An overview of what Civic Engagement & Policymaking as a Community Science Approach can entail,
  • Descriptions of four roles your organization can play to authentically engage with communities on civic priorities,
  • Examples of real collaborations between science engagement organizations and their partners that advance community priorities,
  • Tools, guides, and other resources to help you prepare for new civic engagement efforts and/or expand or deepen existing civic engagement efforts…(More)”.

Garden city: A synthetic dataset and sandbox environment for analysis of pre-processing algorithms for GPS human mobility data



Paper by Thomas H. Li, and Francisco Barreras: “Human mobility datasets have seen increasing adoption in the past decade, enabling diverse applications that leverage the high precision of measured trajectories relative to other human mobility datasets. However, there are concerns about whether the high sparsity in some commercial datasets can introduce errors due to lack of robustness in processing algorithms, which could compromise the validity of downstream results. The scarcity of “ground-truth” data makes it particularly challenging to evaluate and calibrate these algorithms. To overcome these limitations and allow for an intermediate form of validation of common processing algorithms, we propose a synthetic trajectory simulator and sandbox environment meant to replicate the features of commercial datasets that could cause errors in such algorithms, and which can be used to compare algorithm outputs with “ground-truth” synthetic trajectories and mobility diaries. Our code is open-source and is publicly available alongside tutorial notebooks and sample datasets generated with it….(More)”