Book by Fenwick McKelvey: “How computer models became fundamental to political practice—from winning elections to global affairs—and how we imagine political futures as a computing problem.

For more than six decades, the public has been promised that computers will revolutionize politics, both nationally and internationally. In SimPolitics, Fenwick McKelvey traces the entwined history of politics and computers from the 1960s to the late 1980s. He shows how programmers, consultants, academics, political scientists, and peace activists all worked—sometimes in tandem, sometimes not—to build simulations to win campaigns, predict coups, forecast the future, and render politics as legible as a spreadsheet.

Drawing on novel archival and historical research, McKelvey recounts the history of efforts to simulate politics by building models of elections, voters, and international relations. Comparing attempts in the United States to simulate domestic electoral politics and international affairs, he reveals the unexamined connections and conflicts between the two projects. His book provides a helpful guide to taking stock of exaggerated claims that AI and technology will fix politics, while presenting the long history of such promised technological fixes…(More)”.

Book by Ahana Datta Fasel: “Even the most elite hackers use common technologies to steal state secrets, which help intelligence agencies to catch them. Are these hackers simply reckless, or do their operations reveal something deeper about their nation-state patrons?

Over a globally interconnected Internet, nations must constantly toe the delicate line of maintaining stability–developing shared tech protocols that they themselves must also break, in order to spy. This is the paradox at the heart of cyber espionage: states need to cooperate if they are to compete. As the US and China vie for strategic advantage through a new form of statecraft in cyber space, an intensifying cat-and-mouse game makes cyber security more difficult, more expensive and more unpredictable for us all.

Full Stack Spies examines the dynamic, interdependent relationships that hackers, cyber defenders, tech giants and nation states forge, leverage and exploit to amass cyber power against a wide range of targets in geopolitics, global trade and finance, the armed forces, and critical infrastructure. But this jostling for cyber dominance makes spying online harder–and, more crucially, undermines long-term trust in cyber space, destabilising the foundations of digital societies..(More)”.

Paper by Geoff Mulgan: “I summarise the perspectives of different disciplines – economics, psychology, computer science, business studies, organisation studies, political science, history, law, international relations, anthropology, design and complexity. In each case I make short suggestions on what would be useful from each, before turning to what a more synthetic approach might look like, in particular using insights from biology and computation to see organisations as living things and addressing the dynamics of ecosystems of organisations which compete and cooperate.

The paper asks of the people working in academic disciplines: how are you engaging with, and learning from, other disciplines? And how could your knowledge be useful to a world that badly needs to reform its public institutions at every level, from the local to the global?…(More)”.

Blog by Stefaan Verhulst and Adam Zable: “The world’s relationship to data is changing rapidly. Artificial intelligence has generated significant excitement for its potential to help solve public problems, improve decision-making, and create new forms of economic and social value. At the same time, it has intensified longstanding debates around access, ownership, attribution, privacy, labor rights, security, and the responsible reuse of public-interest data. Questions that once sat at the margins of data policy have moved to the center.

Governments, international organizations, civil society groups, and companies are responding with a growing range of governance approaches, from executive orders and regulatory frameworks to international agreements, industry standards, and new institutional models. Yet it remains difficult to distinguish short-term developments from deeper structural shifts. While discussion often focuses on the latest AI breakthrough, the more important question for policymakers is how these technologies are reshaping the systems, assumptions, and governance models that determine how data is accessed, shared, and used.

To better understand these changes, The GovLab convened two forecasting studios bringing together experts working in data governance, digital policy, open science, AI governance, and public-sector innovation. Participants explored emerging trends in data access, governance, and reuse, examined the forces driving those trends, and considered what they may mean for the future of open data and public-interest data ecosystems.

The discussions identified seven signals that point to significant changes already underway. These signals suggest that the future of data governance will be shaped by advances in AI alongside evolving expectations around trust, stewardship, infrastructure, sovereignty, reciprocity, and public value. They offer a starting point for understanding how data policy may need to evolve in the years ahead. A longer version of this analysis, with a full list of studio participants and more detailed discussion of each signal, will be published separately…(More)”.

Book by Jibu Elias: “Artificial intelligence has been affecting the way people think, work and create, and the questions that have arisen in its wake are as pressing as they are uncomfortable. Who benefits from this new technology? Who is left behind? And what happens when the tools we build begin to govern us?
In an age where humans are dazzled by machines that seem to think, Jibu Elias -researcher, writer and advisor on AI governance-peels back the glossy surface to reveal systems driven more by prediction than true intelligence; and a world where algorithms redesign economies, redraw social boundaries and challenge the very idea of human agency. Drawing on nearly a decade of experience across the Indian and the global AI governance landscape, Elias points squarely at the widening gaps between promises and reality: from mass job displacements and deepening biases embedded in AI systems to the rapid consolidation of power by tech giants shaping our future and the heavy environmental costs of unregulated innovation.
Moving beyond Silicon Valley optimism, The New Divide is a vital perspective from the Global South. There is a very small window of action open to us in the face of the rapidly accelerating use of AI. Ethical governance and regulation are imperative, and we need guidelines now. This book is a call to action. As AI reshapes what it means to be human, we must reclaim control. Before it’s too late…(More)”.

Article by Maximilian Henning: “…The tool Blanchett launched – called the “Human Consent Registry” – allows people to signal whether they give permission for AI companies to use their likeness, or whether they would prefer to be asked or paid first.

These preferences are then put into a machine-readable form that AI can, in theory, easily read. But crucially, the registry is meant to be voluntary, which means AI companies would have to agree to adhere to people’s preferences.

Blanchett acknowledged this key limitation on Tuesday.

“A registry will not solve all the problems overnight. But every standard starts somewhere,” she said.

She also pointed out that while the registry is voluntary for now, it could become “part of the practical infrastructure” to assist binding laws and rules later on. It could, for example, give regulators evidence to enforce consequences if consent is not respected, she said.

The right to your face

Under the EU’s AI Act, AI companies must respect a person’s request not to use their creative work for AI training. The Commission is currently leading talks between tech giants and copyright holders over adding technical mechanisms for this, though these talks are making little progress.

Still, Blanchett’s registry will soon also allow people to say whether AI can use their work, and it could conceivably become one such mechanism.

The situation is more complicated regarding people’s identities, which the registry also aims to protect. Denmark is moving towards giving its citizens a say over AI deepfakes, with Cyprus following suit. However, so far, these are national initiatives, not EU-wide.

And the issue is legally complicated, touching on existing rules on privacy or platform regulation, while copyright rules aim to protect artistic works rather than faces or voices.

EU aware of a problem

The European Commission has recently announced it is working on a law governing how people can licence their creative work to AI companies – and acknowledged that artists face tricky issues in this field.

“Performers face certain challenges in relation to AI-generated imitations of their personal characteristics and performances (‘impersonifications’), which raise complex questions going beyond copyright protection,” said a public consultation on the new legal initiative…(More)”.

Press Release: “As artificial intelligence increasingly relies on language and cultural data, Indigenous communities face unprecedented opportunities and significant risks. While Indigenous languages and cultural knowledge can help shape more inclusive digital futures, too often communities have limited influence over how their data is collected, governed, used, or shared.

To address this challenge, The GovLab, Microsoft, and UNESCO are launching the New Commons Incubator for Indigenous Languages and Culture, a new initiative designed to support Indigenous-led efforts to develop data commons that preserve, steward, and responsibly govern language and cultural resources in the AI era.

Data commons are shared governance frameworks that enable communities to collectively decide how their data is managed, accessed, and used while ensuring that benefits flow back to the communities themselves. By supporting the development of Indigenous-led data commons, the Incubator seeks to strengthen community agency, support language revitalization, and ensure that Indigenous peoples can participate in shaping the future of AI on their own terms.

The Incubator is a capacity-building initiative that provides mentorship, training, technical guidance, and proposal development support. Participants will receive an in-person opportunity to collaborate and network with other participants, followed by six months of workshops, one-on-one clinics, expert mentorships, and peer learning opportunities. The program is designed to help teams prepare stronger proposals and will end with a final showcase where participants present these to potential funders, partners, and collaborators…(More)”.

Book by David Hand: “Statistics and data science aim to extract understanding from data and guide decision-making. However, before applying any analytical tools, we need absolute clarity about what we want to know or accomplish. Ambiguous objectives inevitably lead to mistaken conclusions and flawed actions. This book investigates the deeper challenges of formulating clear questions and matching analytical methods to those questions – issues that apply as much to elementary statistical tools as to sophisticated techniques. Rather than focusing on standard statistical misuses or data provenance issues, this work examines the critical step of ensuring your analysis actually answers the question you mean to ask.

Drawing from collaborative work across finance, medicine, government, manufacturing, defence, and other fields, the book deliberately emphasises basic and familiar tools so the fundamental issues are accessible to everyone. Following John Tukey’s insight about the simplest problems of data analysis, the most detailed discussions centre on averages and comparisons between distributions, though the principles apply with even greater force to advanced methods that fewer people fully understand.

Key Features: 

• Focusses on question formulation rather than computational techniques, addressing the step that precedes all successful data analysis

• Emphasises basic statistical tools (averages, comparisons) to make fundamental challenges visible to all practitioners

• Contains 130 text boxes presenting essential ideas in non-technical language, creating a “two-in-one” book accessible to both mathematical and non-mathematical readers

• Provides real-world examples drawn from diverse fields including finance, healthcare, government, manufacturing, and defence

• Offers a deep-dive analysis of a specific comparison method to illustrate the care required for precise statistical reasoning

• Presents a progression from general principles through detailed mathematical exploration to practical applications across various analytical scenarios

This book serves as an essential guide for statisticians, data scientists, researchers, and anyone who uses data to make decisions. Whether you’re a practitioner seeking to improve your analytical approach or a student learning to think critically about statistical questions, this work will help you use data analytical tools more effectively and avoid the costly mistakes that arise from asking the wrong questions of your data…(More)”.

Report by the University of Edinburgh: “… has recommendations for the Scottish and UK governments on steps that can be taken to ensure AI is developed and used in ways that create trust and deliver real benefits.

The report, Governing the Future: Recommendations from the Edinburgh Data and AI Exchange, brings together proposals on AI skills, national infrastructure, health data governance and democratic oversight…

A key recommendation for the UK Government is to establish a standing citizens’ assembly on AI and society.

A citizens’ assembly is a group made up of members of the public, selected through a process of random sampling designed to reflect the demographic makeup of the wider population, to explore societal issues and make policy recommendations.

The report argues this should be a permanent, properly resourced mechanism through which the public has a genuine and continuing role in shaping decisions about AI.

This mirrors the findings of a 2025 Ada Lovelace Institute survey, which found that 60 per cent of UK adults do not feel they have meaningful input on government decisions about AI.

Dr Morgan Currie, Senior Lecturer in Data and Society at the School of Social and Political Science, spoke at the event. 

She said: “This report reflects what I heard at the Exchange and over and over again in my own research – that people want a say in the governance of technologies affecting them in their daily life, at their work, and increasingly in their interactions with government services. They want to reimagine technology for socially and environmental beneficial ends, beyond the narrow visions on offer by foreign-owned Big Tech.”..(More)”.

Article by Thomas Brent: “Latvia has introduced an element of citizen engagement to the evaluation of nationally funded research grants. The aim is to both create more connections between science and society, and to improve the quality of its evaluations. 

The move comes as research funders across Europe are experimenting with ways to improve evaluation processes in the face of a sharpened focus on science’s impact on society. 

Evaluators of grant applications submitted to Latvia’s Fundamental and Applied Research Programme (FLPP), the country’s main research funder, will this year have the option of consulting citizen feedback on challenges the public thinks science should focus on to inform their decisions. 

“In recent years, both public discussions and policy-level debates in Latvia have highlighted the importance of demonstrating how publicly funded research contributes to society, the economy and the resolution of real-world challenges,” said a source at the Latvian Council of Science (LCS), which manages the FLPP. 

“At the same time, research institutions themselves expressed interest in improving the project evaluation framework while continuing to ensure that funding is awarded to the highest-quality projects,” the source added. 

The citizen input comes from a survey that was conducted between 25 February and 16 March 2025, to which 1,737 people responded. It gathered information on what the public views as problem areas for Latvia, and the role of science and technology in providing solutions to these problems. 

A summary of these responses has been included as an annex to the FLPP 2026 call for proposals that evaluators can refer to, purely in an advisory manner, when judging proposals. 

Results from the survey show that the main problem areas identified by the public were in healthcare and public health, followed by the development of new treatment methods and medicines, and then digital technology, data security and cyber security. At the bottom of the list was research aimed at acquiring new knowledge about the universe, matter and the laws of nature…(More)”.