Insights

Spain's high-speed rail (HSR) network, driven by political and territorial integration goals, expanded rapidly beyond actual passenger demand, resulting in low utilization and weak economic returns. Despite relatively low construction costs, most corridors yield negative social returns due to insufficient ridership. The network is primarily funded by public and EU sources, with post-2020 competition improving fares and service but challenging operator finances. Spain's case highlights that while strong institutions and liberalization improve efficiency, sustainable HSR investment requires demand-focused planning.
Spain
When Speed Outruns Demand: Political Drivers and Economic Outcomes of High-Speed Rail in Spain
Democratic erosion is often analyzed through the lens of supply-side factors like authoritarian leaders and geopolitical shifts, but these overlook the demand-side drivers rooted in societal conditions. Current political turbulence, marked by conflicts and unstable alliances, stems from deeper social realities—people's experiences of insecurity, lack of respect, and diminished hope for a shared future. This underlying social environment shapes political dynamics and contributes fundamentally to today's destabilizing trends.
Africa, Latin America | Health
The Demand Side of Our New Political Reality
Italy’s parliamentary adoption of AI reflects a broader global trend where highly developed countries implement AI tools without a unified regulatory framework, resulting in fragmented approaches shaped by individual parliaments. AI applications vary from internal support for legislative processes to tools enhancing transparency and public participation. Examples include AI-assisted transcription, automated debate classification, vote sequencing, drafting aid, and sentiment analysis of bills. Different countries prioritize distinct AI roles: Chile focuses on legislative simplification, Brazil on popular participation. The Inter-Parliamentary Union highlights three potential futures: AI as a human decision co-pilot, AI-driven evidence-based legislatures, or executive-concentrated AI sidelining parliaments. Strategic AI adoption thus significantly influences parliamentary function and democracy.
Education
Can AI Strengthen Democracy? Italy’s Parliament Offers a Test Case
Collective Intelligence for Deliberative Democracy (CI4DD) integrates artificial intelligence with human-computer systems to enhance participatory democratic processes. This approach emphasizes human-centered design to ensure stakeholders actively shape trustworthy deliberative democracy tools and workflows. The chapter outlines key concepts, presents a co-design methodology addressing challenges and user needs, and showcases two case studies where AI-supported solutions were collaboratively developed and tested within civic organizations.
Education
Human/AI Collective Intelligence for Deliberative Democracy: A Human-Centred Design Approach
Computer programming is undergoing a radical transformation as coding shifts from manual work to a conversational process between developers and AI-powered bots. This automation threatens major economic impacts by potentially replacing high-paid human programmers, historically seen as highly skilled and secure in their jobs. Despite this, many developers are excited by dramatic productivity gains—some reporting 10 to 100 times their previous output—though uncertainty remains about the future role of programmers as AI reshapes the profession fundamentally.
Coding After Coders: The End of Computer Programming as We Know It
Artificial intelligence (AI) enhances scientific productivity by augmenting, rather than automating, knowledge production through improved search over complex combinatorial spaces. The impact of AI varies across scientific domains and stages of research workflows, with tools like AlphaFold demonstrating strong design capabilities in data-rich fields. Human judgment remains crucial for tasks requiring inference, context, and balancing trade-offs, especially in data-scarce environments. Productivity gains from AI are nonlinear and depend on the proportion of AI-expert scientists, highlighting the importance of complementary skills training and organizational design.
Education
AI in Science
Emerging economies face a complex global technology governance landscape as AI, quantum computing, and synthetic biology become national security concerns, challenging access to knowledge and international collaboration. While geopolitical tensions strain partnerships, fields like health and climate offer opportunities for cooperation, exemplified by vaccine production during COVID-19. Premature import substitution policies risk strengthening entrenched firms and harming consumers. Effective industrial policy requires transparent, accountable governance to avoid politicized resource allocation. Strategic international collaboration and tailored development approaches are crucial for emerging economies to build technological sovereignty and advance their capabilities.
Algeria, Angola, Armenia, Australia, Austria, Azerbaijan, Bahrain, Bangladesh, Barbados, Belgium, Benin, Bolivia, Botswana, Brunei Darussalam, Bulgaria, Burkina Faso, Cambodia, Chad, Chile, Colombia, Costa Rica, Czech Republic, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Estonia, Eswatini, Ethiopia, Finland, Gabon, Georgia, Germany, Ghana, Greece, Guatemala, Guinea, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Ireland, Israel, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kyrgyz Republic, Latvia, Lebanon, Lesotho, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Mali, Malta, Mauritania, Moldova, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nepal, Netherlands, New Zealand, Nigeria, Norway, Oman, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Republic of Korea, Romania, Russian Federation, Rwanda, Saudi Arabia, Senegal, Serbia, Seychelles, Singapore, Slovakia, South Africa, Spain, Sweden, Switzerland, Taiwan, China, Tajikistan, Tanzania, Thailand, Trinidad and Tobago, Tunisia, Türkiye, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Venezuela, Viet Nam, Yemen, Zambia, Zimbabwe | Health, ICT, Financial services, Education
Building Bridges—Not Walls—for Technological Sovereignty
The UK's high electricity prices are driven by geopolitical tensions and reliance on costly gas imports, with significant government subsidies supporting renewable energy infrastructure. Contracts for difference guarantee producers fixed prices above market rates to incentivize investment in renewables like wind and nuclear, resulting in environmental levies on consumer bills. Although renewables raise bills upfront, they provide energy security and hedge against volatile fossil fuel prices. Transitioning from gas to renewables reduces dependence on geopolitically risky supply chains. Future solutions include expanding storage capacity and implementing dynamic pricing to reflect real electricity costs, enabling innovation and potential export opportunities.
The UK’s high electricity prices are here to stay. But could they offer an opportunity?
Wales’ Well-being of Future Generations Act, passed in 2015, mandates public bodies to prioritize long-term wellbeing through prevention, cross-sector collaboration, and focusing beyond economic growth to health, equality, and environmental resilience. Community-based initiatives, such as local area coordination and ecotherapy, demonstrate how preventive support improves health outcomes and social connections, reducing pressure on crisis services. However, political short-termism and election cycles challenge sustained investment and cultural change needed to embed this approach. Success depends on continued leadership and funding to shift from reactive fixes to fostering sustainable wellbeing amid overlapping social and environmental crises.
Health
Can Wales’ wellbeing law survive the pressures of the next Senedd election?
Healthcare systems face rising costs due to aging populations, chronic diseases, labor shortages, and inefficiencies, with global spending projected to nearly double by 2040. Strategic productivity improvements utilizing AI, robotics, and quantum technology could reduce costs by up to $5.1 trillion annually, a 22% reduction. AI is evolving from task support to workflow orchestration, robotics is expanding automation in clinical and administrative tasks, and quantum tech promises advances in computing and diagnostics. Achieving these improvements requires major systemic changes, including increased tech investment, workforce training, aligned incentives, adaptive regulation, and cultural readiness, enabling a scalable, people-centered productivity reset without compromising care quality.
Financial services, Health, Education
A health productivity reset using AI, robotics, and quantum
Shipbuilding is vital for competitiveness, economic security, and energy efficiency, yet policy decisions often rely on incomplete and inconsistent data. Four main data challenges hinder effective policy: inconsistent statistical definitions, limited insight into value creation and productivity drivers, delayed recognition of emerging skills needs, and lack of standardized metrics for technological advancement and decarbonization. Strengthening shipbuilding data through improved definitions, labor intelligence, and innovation indicators, supported by OECD tools, is essential for better policy targeting, monitoring, and cross-country benchmarking to foster more resilient industrial policies.
Bahrain, Barbados, Belgium, Benin, Bolivia, Bulgaria, Canada, Cape Verde, Chile, Colombia, Denmark, Egypt, El Salvador, Estonia, Ethiopia, Finland, Gabon, Georgia, Germany, Ghana, Greece, Haiti, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kenya, Latvia, Lithuania, Luxembourg, Malta, Moldova, Mozambique, Netherlands, New Zealand, Norway, Oman, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Republic of Korea, Russian Federation, Saudi Arabia, Senegal, Seychelles, Singapore, Slovakia, Spain, Sweden, Taiwan, China, Tanzania, Thailand, Trinidad and Tobago, Tunisia, Uganda, Ukraine, United Arab Emirates, United Kingdom, Venezuela, Viet Nam | ICT, Education
Why data matters for shipbuilding industrial policy
Seven in 10 social media images and 80% of content recommendations are AI-generated, with nearly half of business-related content expected to be AI-driven by 2026. However, AI tools often neglect non-English speakers. Meta’s Oversight Board faces challenges in scaling oversight to address the rapid, multilingual surge of AI content and related harms. Experts emphasize the need for a diverse, globally representative board supported by enhanced research, regional advisory bodies, and faster response mechanisms. The board reviews only significant cases appealing content moderation decisions on Meta platforms, relying on global staff and translation to inform its rulings.
Meta’s Oversight Board races to govern the AI surge
Peter Thiel predicted that technology could bypass traditional politics by enabling unilateral world change without needing broad public approval. Today, as A.I. advances through companies like Nvidia, Microsoft, and OpenAI, questions arise about how technology is reshaping or even supplanting politics and elections. A.I. may concentrate market, political, and cultural power, potentially weakening democratic oversight and increasing inequality. Concerns persist that A.I.-driven control could shift governance and regulation from public institutions to private corporations or political factions.
A.I. Is Coming for Politics
National statistical systems face challenges in data accessibility and interpretability, limiting the impact of official statistics. While large language models (LLMs) and generative AI tools can synthesize text, they often produce inaccurate statistical figures. StatGPT, developed by the IMF Statistics Department, addresses this by using LLMs to generate precise structured queries to official statistical APIs, ensuring users receive exact published data through natural language interaction. This approach enhances reliability and accessibility of official statistics, promoting trust and usability in an AI-driven environment.
StatGPT: AI for Official Statistics
Achieving lasting financial health requires both improved financial education and supportive systems such as accessible financial services and welfare programs. Many young adults, like Marisa in Italy, understand saving's importance but struggle to prioritize long-term security amid daily financial pressures and lack practical guidance. Italy’s Uwelfare project targets university students—often overlooked by traditional financial and social protection systems—to bridge this gap by combining tailored education, awareness-raising, and facilitated access to pension funds with incentives. This integrated approach aims to establish saving habits early, improving financial resilience and retirement outcomes over time.
Education, Financial services
What Would It Take for Financial Education to Lead to Lasting Financial Health?
A multimodal large language model was tested in a realistic medical training simulation to manage entire clinical encounters, including diagnosing, ordering tests, administering treatments, and escalating care. The AI stabilized patients and completed cases at rates comparable to or exceeding medical students, performing faster and with diagnostic accuracy similar to an experienced emergency physician. It prioritized informative tests early, updated diagnosis confidence appropriately, and mirrored expert clinical reasoning. However, the AI communicated less with patients and ordered more tests than physicians, highlighting the need for human oversight. These results suggest AI's promise as workflow support but not as a replacement for clinicians.
Can AI Manage an Entire Medical Decision Process?
Generative AI tools like ChatGPT have reduced routine coding questions on platforms such as Stack Overflow, with common queries dropping by 13.4% post-ChatGPT launch. However, novel, previously unseen questions involving new combinations of technical domains have increased by 3.9%, indicating that human expertise remains essential for solving new coding challenges. This “selective substitution” suggests AI handles routine issues, while humans focus on innovative problems. The shift may reduce general traffic on coding forums but increases specialization, raising concerns about the future availability of training data for AI, which initially depends on human-generated content.
Education
Will LLMs Replace Coders? Not Entirely
ESG (Environmental, Social, and Governance) originated from UN efforts to engage investors on global issues like climate change and human rights. Initially, it aimed to connect non-traditional factors with long-term financial performance, encouraging a "win-win" where sustainability aligned with economic gain. However, tension exists between focusing solely on financial materiality versus broader societal impact, such as reducing human rights violations or emissions. Over time, ESG has become politicized, complicating business adoption. The ethical debate highlights the need to clarify ESG’s goals—whether prioritizing shareholder value or meaningful global change—and to understand diverse perspectives shaping its future direction.
Financial services
The Ethics of ESG | Eric Orts
The Middle East conflict disrupts energy supplies, notably through the Strait of Hormuz and attacks on Gulf oil infrastructure, causing global oil and gas prices to surge. Higher energy costs increase food production and transportation expenses, impacting food prices worldwide. Developing countries are especially vulnerable as they depend heavily on food imports, with international price rises quickly translating into local price hikes within a month. Wheat prices tend to be highly sensitive, while crops like sorghum, primarily produced and consumed locally in developing nations, are less affected. Political factors also influence the extent of domestic price changes. To mitigate food insecurity, developing nations should strengthen local food production, improve storage and transport, and support vulnerable populations through targeted policies.
Bangladesh, Egypt, Ethiopia, Ghana, Kenya, Nigeria, Pakistan, Russian Federation, Ukraine | Financial services
Why developing nations could be the first to suffer as the Middle East conflict raises food prices
Graduates facing a tough job market are increasingly turning to entrepreneurship, driven by opportunities in technology, shifting consumer values, and sustainability. Success demands thorough market research, resilience, risk-taking, and learning from failure. However, challenges such as rising costs, unequal access to capital—especially for women and minorities—and the need for strong networks persist. AI and social consciousness offer unique advantages for new ventures, which should align profit goals with societal impact. Bootstrapping and leveraging support like grants or competitions are crucial for funding, while networking remains key to growth and overcoming obstacles.
Financial services, Education
The graduate jobs market is tough right now. An entrepreneurship expert explains how to go it alone

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