• The OECD policy paper ‘Mapping relevant data collection mechanisms for AI training’ outlines a taxonomy of how data is sourced for training AI systems and highlights implications for governance and privacy.

• Launched at the Tallinn Digital Summit 2025, the Vision Paper proposes a 12-layer framework for governments to adopt “agentic AI” and transition from digital bureaucracy to the “Agentic State.”

• The UK Government’s Regulatory Innovation Office: One Year On assesses how regulatory frameworks are adapting to support innovation-friendly governance across sectors.

• The World Economic Forum’s Shaping the AI Sandbox Ecosystem for the Intelligent Age examines how regulatory sandboxes can support safe innovation in AI ecosystems.

• OpenAI’s Economic Blueprints for South Korea and Japan present strategic recommendations and roadmaps for AI-driven growth, skills development, and industrial transformation across both economies.

• The white-paper Government Efficiency in the Age of AI by Nortal explores how digital infrastructure can accelerate public-sector performance and service delivery.

• The OECD working paper ‘Advancing the Measurement of Investments in Artificial Intelligence’, proposes new metrics to capture AI investment flows across countries.

• The WEF report Elevating Cybersecurity: Ensuring Strategic and Sustainable Impact for CISOs focuses on the evolving role of chief information security officers and strategic cyber-risk management.

• The Center for Democracy & Technology publication Hand-in-Hand 2025: Polling the Public on AI reveals public attitudes toward AI deployment and governance.

• The study ‘Mapping the AI Governance Landscape’ examines global governance frameworks for AI and their interplay with standards, regulations and policy innovation.

• The memo Safety Frameworks and Standards: A Comparative Analysis to Advance Risk Management of Frontier AI from Oxford Internet Institute reviews global approaches to managing frontier AI risks through frameworks and standards.

• This report from the International Telecommunication Union highlights the importance of international AI standards in fostering trust and supporting innovation across sectors like healthcare, energy, and smart mobility.

• The OECD’s Measuring Science and Innovation for Sustainable Growth offers a broad set of indicators to support policy-making for science, innovation and long-term growth.

• The BBC toolkit ‘News Integrity in AI Assistants‘ provides guidance on preserving journalistic integrity as AI-powered assistants become more prevalent.

• The UNCTAD report “Technology Foresight and Technology Assessment for Sustainable Development” examines how global uncertainty, trade tensions, and economic fragmentation are slowing growth and posing major risks for developing countries.

• This report summarises key insights from an international convening on AI governance challenges and opportunities, focusing on the need for coherent, effective, and internationally harmonised practices.

Articles

• “Defining and Evaluating Political Bias in LLMs” introduces a framework with ~500 prompts and five bias-axes to systematically measure political bias in large language models.

• “The impact of advanced AI systems on democracy” assesses how advanced AI systems affect democratic processes by influencing citizens’ ability to make informed choices and potentially disrupting election mechanisms (material impacts).

• “The Illusion of Readiness: Stress Testing Large Frontier Models on Multimodal Medical Benchmarks”: The authors show that even top-performing multimodal medical AI models exhibit brittleness and shortcut learning, meaning high benchmark scores don’t guarantee real­-world clinical readiness.

• “Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation” argues that current AI agent evaluations are inadequate and proposes a “Holistic Agent Leaderboard” to create more comprehensive, meaningful benchmarks for assessing agent behaviour.

• “Who on Earth Is Using Generative AI? Global Trends and Shifts in 2025” surveys global adoption of generative AI across sectors and models its general equilibrium effects on economies, highlighting disparities in access and usage.

• “AI, Health, and Health Care Today and Tomorrow” summarises a summit on AI in health care, focusing on how AI should be developed, evaluated, regulated, disseminated, and monitored to meaningfully improve care.

• “Using generative AI to increase sceptics’ engagement with climate science” finds that generative-AI-edited headlines can boost climate-science engagement among sceptical audiences and shift beliefs towards scientific consensus.

• “Evaluating urbanization effects on biomass density using a hybrid AI model: A case study” Using a hybrid AI model combining Discrete Wavelet Transform with LSTM, the paper links urbanisation metrics with ecological degradation and offers a predictive tool for sustainable land-use planning.

• “Human-centered AI: advancing ethical, transparent, and context-aware systems for sustainable development” outlines a socio-technical framework for Human-Centered AI that aligns technology with human values, emphasising ethical design, transparency, interdisciplinary collaboration, and public participation to ensure AI systems foster trust, equity, and sustainable societal progress.

• “Images of AI: How AI practitioners view the impact of Artificial Intelligence on society, now and in the future” Through surveys and interviews with AI practitioners, this study identifies six metaphoric “images of AI” that reflect how developers and managers perceive AI’s societal role and risks, offering a framework to promote more reflective, responsible, and human-controlled AI design and use.

Blogs

• The WEF blog highlights global disparities in AI governance, urging nations to move beyond principles to enforceable, transparent, and accountable AI regulations.

• This OECD AI blog highlights a new joint OECD–European Commission approach to measure AI investment across R&D, infrastructure, and skills for greater transparency.

• The LSE Impact Blog explores a practical blueprint for conducting AI research that remains both legally and ethically responsible.

• The blog by Prof Verhulst argues that the traditional FAIR principles must evolve into frameworks like FAIR‑R (Readiness for AI) and FAIR² to ensure data is not only open but truly AI-ready—technically, ethically and purpose-driven, tailored to the kind of AI being built and the use-context.

• This blog explores Ukraine’s evolving GovTech model and highlights how innovative public-private partnerships are modernising digital governance.

• This Techplomacy Foundation blog emphasises the importance of AI readiness through global partnerships that align ethics, strategy, and technology.

• This World Economic Forum blog emphasises that cybersecurity is central to national security and calls for stronger international cooperation and AI-driven digital resilience.

• The Imperial College London blog highlights efforts by civil servants to build practical AI capability and apply innovation across government.

• This OECD AI blog emphasises the HAIP Reporting Framework’s role in making AI transparency operational and strengthening global accountability.

• Another LSE Impact Blog examines how political pressures can threaten research integrity in the UK and emphasises the need for safeguards.

• A recent blog post on Imperial College London’s Policy Forum highlights how 20 senior UK civil servants, through the AI Policy Fellowship, are developing practical solutions to integrate AI responsibly into government operations.

• The Reboot Democracy blog highlights Boston’s civic AI experiments as models for enhancing democracy and citizen engagement through technology.

• This Stanford HAI blog warns users to be cautious when sharing personal data with AI chatbots and emphasises the importance of privacy awareness.

• This WEF blog explores how cross-disciplinary collaboration is essential for designing AI that serves humanity and fosters inclusive innovation.

• Civil Service AI & Data Challenge, UK Department for Science, Innovation & Technology
• Government Chief Technology Officer, UK Department for Science, Innovation & Technology
• British Academy/Leverhulme Senior Research Fellowships,The British Academy
• Chief Scientific Advisers (CSAs), UK Government Office for Science
• The Data Stewards Bootcamp in Brussels, The Data Tank & FARI Institute
• Robotics Advisory Group: Expressions of Interest for co-chair and external expert advisors, Department for Science, Innovation and Technology
• Call for Proposals for AI Impact India, IndiaAI Mission