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World Disasters Report 2026: Truth, Trust and Humanitarian Action in the Age of Harmful Information
Deep Insights

Charlotte Lindsey Curtet (ed.)

International Federation of Red Cross and Red Crescent Societies (ICRC) (2026), 372 pp.

"The World Disasters Report 2026 calls on governments, humanitarian actors, media, technology companies and communities, to recognise that the trustworthiness of information is a matter of life and death. Just as we plan for logistics, shelter and health care in emergencies, we must also plan for th ... e information environment. This requires investing in community engagement, prioritizing listening over speaking, building resilience against harmful narratives and consistently upholding humanity, neutrality, impartiality and independence in every interaction and message. In 2024, 32 Red Cross and Red Crescent volunteers and staff were killed while on duty; in 2025, a further 27 lives were lost. This is a painful reminder of the risks borne by those who put humanity first, often in the most dangerous circumstances. Their deaths underscore the urgent need to protect humanitarian staff and volunteers, and to safeguard the space they need to save lives. Anything that deepens mistrust, fuels hostility or turns the emblem of protection into a target must be confronted with urgency. Honouring their memory compels us to meet this crisis with urgency and resolve. Hope must also be part of our response. Harmful information thrives on fear and confusion, but hope – rooted in trust, solidarity and human dignity – can be just as contagious. Balancing threats with hope and fostering narratives of agency and possibility offers a vital counterforce. Around the world, communities respond to crises not only with resilience but also with creativity and compassion, often leading the way in finding solutions. By amplifying authentic stories and voices, we do more than counter falsehoods: we inspire action, strengthen trust and remind people that even in the darkest moments, there are paths forward. The IFRC and its member Red Cross and Red Crescent Societies have always worked at the heart of communities, earning trust through presence, transparency and respect. In today’s information crisis, this role matters more than ever. Our commitment is clear and unwavering: act with humanity and based on evidence, uphold trust and put people in need first – so that in moments of fear and uncertainty, the voices that carry furthest are those that heal, aid and protect. Each of us has a role to play. By staying informed, questioning, verifying and amplifying only what is trustworthy and constructive, we strengthen the information environment and ensure that hope speaks louder than harm." (Foreword) more

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The Essential Convergence: Global Compact on Extreme AI Risks

Sundeep Waslekar, Ilmas Futehally, Jayantika Kutty

Mumbai: Strategic Foresight Group (2026), 90 pp.

"Supply-Side Governance: Progress and Limitations: Most existing AI governance frameworks focus on the supply side of the technology ecosystem. These measures regulate developers, model providers, and infrastructure operators responsible for building advanced systems. Supply-side mechanisms include: ... pre-deployment safety testing and red-teaming; model evaluation and capability assessments; transparency and reporting obligations; incident response mechanisms; restrictions on certain high-risk uses. Several jurisdictions are experimenting with these tools in different combinations. China has implemented regulatory standards for generative AI systems; the European Union has adopted a risk based regulatory framework; Brazil and South Korea are developing legislative approaches; and the United States has introduced a mixture of executive measures and sectoral rules. These frameworks represent important progress. However, they face two structural limitations. First, supply-side regulation depends heavily on the cooperation of a small number of developer states. Second, the growing distribution of AI models, through open-weight releases, cloud APIs, and downstream applications, means that many systems reach global markets beyond the jurisdiction where they were originally developed. This reality limits the effectiveness of purely supply-side approaches. Demand-Side Governance: A New Dimension of AI Regulation: The paper introduces a second dimension of governance that has received far less attention: demand-side oversight. Demand-side governance shifts the locus of control from the point of creation to the point of deployment. Instead of relying solely on developer-state regulations, importing countries can establish safety requirements for any AI systems operating within their markets. These requirements may include risk assessments, certification standards, procurement rules, insurance obligations, and infrastructure safeguards. The central insight is that states controlling large consumer markets, digital infrastructure, financial systems, or public procurement channels possess significant leverage over global AI deployment, even if they do not develop frontier models themselves. This demand-side leverage can reshape incentives across the global AI ecosystem. Developers seeking access to major markets must comply with the safety conditions imposed by importing states. This approach represents a strategic shift in global AI governance: from a developer-centric model to a market-driven model of safety enforcement. Countries across different regions possess different forms of demand-side power. Brazil and South Africa represent large emerging markets; the United Arab Emirates plays a major role in AI infrastructure investment; South Korea combines technological capability with advanced regulatory institutions. When coordinated, these forms of leverage could help establish global safety norms. The Case for a Global Compact: Given the limitations of purely national approaches, the paper proposes the development of a Global Compact on Extreme AI Risks. The Compact would not aim to harmonise all aspects of AI regulation. Instead, it would focus narrowly on the most severe risk categories and establish shared mechanisms for prevention, monitoring, and response. Five institutional pillars form the backbone of the proposed Compact. The five pillars in the Global Compact should not be treated as isolated measures but designed as an interoperable system in which each pillar reinforces and informs the others through shared definitions, compatible standards, and coordinated implementation mechanisms. To address extreme risks effectively, the Compact should rest on a small set of guiding principles: a human-centric principle to ensure protection of humanity and human dignity as the primary objective; technological neutrality so that safeguards apply across methods and architectures rather than specific tools; interoperability to enable national and regional AI frameworks to exchange information, align risk classifications, and coordinate responses; and mutual cooperation to institutionalize cross-border collaboration in prevention, incident reporting, and crisis management. These can be complemented by principles of proportional risk governance, scientific integrity, and shared responsibility, creating a coherent normative base that allows diverse governance models to function together as a connected global safety architecture." (Executive summary, pages 5-6) more

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Navigating risks and rewards: How South African journalists use AI in the newsroom

Karen Allen, Herman Wasserman, Nande Mbekela

Johannesburg; Stellenbosch: Konrad-Adenauer-Stiftung (KAS), Media Programme Sub-Saharan Africa; Centre for Information Integrity in Africa (CINIA) (2026), 33 pp.

"This study demonstrates impressively how widely AI is already used in South African newsrooms – often, however, without systematic training, without editorial guidelines, and without tools adapted to African languages and contexts. The interviews make it clear that journalists stand between curio ... more

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Countering Digital Scams: Stemming the Tide on an Urgent Development Challenge

Megan Roberts, Vitalii Zakhozhyi

UNDP (2026), 14 pp.

"Digital scams have become a global development challenge, inflicting costs of up to one trillion dollars annually. Beyond financial losses, scams inflict emotional harm and erode trust in digital systems, weakening confidence in governments, financial institutions, and online services. As countries ... more

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From Crisis to Renewal: Addressing AI’s Impact on Our Information Ecosystem

Lena-Maria Böswald, Roa Powell, Tyreese Calnan

Berlin: Interface – Tech Analysis and Policy Ideas for Europe (2026), 18 pp.

"As AI summaries summarise information directly within search results, they can significantly reduce traffic to news publishers. Evidence suggests users are less likely to click through to original sources when AIOs are present on Google, threatening the financial viability of journalism. These impa ... cts from AI summaries and AIOs in particular are unlikely to be evenly distributed and will play out in different ways across the news sector across Europe, with smaller and ad-funded outlets particularly vulnerable, raising concerns about declining media plurality. At the same time, AI-generated summaries often fail to provide accurate and diverse information. Research shows that AI tools disproportionately rely on a narrow set of sources, marginalising smaller publishers. In addition, persistent issues with accuracy – including misleading or incorrect outputs – risk distorting public understanding and weakening trust in information systems. Current regulatory frameworks in both the EU and UK are struggling to address these challenges effectively. While multiple legal instruments are relevant and already in place – including competition law, platform regulation, copyright, and AI governance – none are fully equipped to respond quickly and comprehensively to the harms of monopolisation and the lack of remuneration for media outlets posed by AI summaries. We argue that competition policy offers the most effective and immediate route to intervention, with digital regulation serving as a secondary lever. The UK’s approach, based on flexible, case-specific competition rules, enables faster action through tailored conduct requirements for dominant firms like Google. In contrast, the EU’s framework is broader but slower, relying more heavily on traditional, time-intensive antitrust investigations and ongoing debates around copyright and remuneration for publishers. Both systems offer complementary strengths, and policymakers should learn from each other’s approaches. We therefore recommend a “competition-first” policy package to ensure fairer outcomes. Key measures include enforcing fair ranking and attribution practices, preventing unauthorised use of publisher content, and potentially requiring platforms to compensate news organisations. However, competition policy alone is not the key. We therefore propose additional long-term interventions, including greater transparency through “nutrition labels” for AI-generated content and increased public or democratic funding for journalism. These measures aim to strengthen the resilience and independence of the news sector, ensuring that trustworthy information remains accessible in an information ecosystem shaped by AI. more

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SAFE AI: A Governance Framework for Humanitarians using AI. How to turn SAFE AI principles into practical action

Helen McElhinney, Anjali Mazumder, Michael Tjalve, Suzy Madigan, Sarah Spencer

CDAC Network; Alan Turing Institute; Humanitarian AI Advisory (2026), 93 pp.

"The SAFE AI Framework is designed to support humanitarian organisations on their AI journey, and navigate the risks raised. Organisations procuring AI systems or designing AI projects will benefit from each tool within this framework, which is intended as a practical approach to using, designing, p ... more

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The Local News Playbook: Creating Value for a Sustainable Future
Deep Insights

London; Miami: FT Strategies; Knight Foundation (2026), 105 pp.

"Drawing on global interviews with newsroom leaders, a cross-market survey of exemplary organisations, and FT Strategies’ work with more than 1,000 media businesses worldwide, the playbook identifies the core drivers that distinguish financially sustainable, community-rooted local news. It reframe ... more

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How Russia Is Reshaping Command and Control for AI-Enabled Warfare

Kateryna Bondar

Washington, DC: Center for Strategic and International Studies (CSIS) (2026), 20 pp.

"This paper examines how Russia is transforming its command and control (C2) architecture under wartime pressure, how these changes shape the country’s incremental move toward battlefield-required software solutions, and what lessons U.S. policymakers can learn from Russia’s experiences. Focusin ... g on both strategic ambitions and battlefield practice, the takeaways below summarize how automated C2 systems, unmanned platform management software, and emerging AI applications are being developed, adapted, and scaled within Russia’s military ecosystem. 1. Russia is no longer prioritizing the construction of a single, comprehensive automated C2 architecture comparable to Western joint concepts; instead, it is reallocating effort toward tactical, task-specific software, driven by battlefield necessity. Prolonged, high-intensity combat in Ukraine exposed the limits of centralized, system-wide C2 modernization and elevated the importance of accelerating the tactical kill chain. The emergence of systems such as the “Svod” Tactical Situational Awareness Complex and other integrated reconnaissance-strike tools reflects a pragmatic shift in which operational control of unmanned systems and real-time battlefield management now deliver greater military value than achieving end-to-end C2 integration. 2. Because unmanned systems now conduct up to 80 percent of Russian fire missions, the center of gravity in C2 innovation has shifted toward software that manages drones and integrates them with artillery and other fire units. Civilian engineers and volunteer developers have focused on closing this gap by building tools that provide situational awareness, automate fire correction, and link unmanned aircraft systems (UAS) operators directly to firing units. Russia’s “Glaz/Groza” software complex demonstrates this trend, functioning as a unified reconnaissance-strike workflow that converts drone footage into targeting data and compresses the time from detection to impact from hours to minutes. 3. The Russian military assesses its AI capabilities for visual and audio data processing as relatively mature, placing computer vision, sensor fusion, and signal analysis at technology readiness level (TRL) 6–9, while natural-language processing remains at an early, experimental stage, TRL 1–3. This disparity reflects a deliberate prioritization of AI applications that deliver immediate battlefield utility—such as target recognition, guidance, and autonomous terminal functions for unmanned systems—and where abundant data and combat validation are available. By contrast, text analysis AI, which underpins document processing and higher-level C2 decision support, remains constrained by immature architectures, limited certified software, and organizational barriers, slowing progress toward fully AI-enabled command workflows. 4. Within Russian C2 systems, AI is primarily envisioned as a support function rather than a replacement for human decisionmaking. Russian military doctrine assigns AI two core roles: enhancing the processing and interpretation of sensor data and providing predictive decision support through forecasting, scenario generation, and recommendations for commanders. Across strategic and tactical levels, AI is intended to augment situational awareness and analytical capacity, while formal authority and responsibility for decisions remain firmly with human commanders. 5. Russia began its C2 digitalization effort by building a dense layer of standards governing terminology, system architecture, hardware-software integration, and information management. This standardization drive, coupled with the transition to the domestically controlled Astra Linux operating system, reflects an attempt to create a unified technical foundation capable of supporting data integration, interoperability, and future AI insertion across the command hierarchy. While this framework provides structural coherence, it has not, on its own, resolved deeper institutional and methodological constraints that continue to limit system-wide C2 integration. 6. To enable AI-driven tactical software, the Russian military launched a systematic data collection effort in 2025 focused on unmanned operations and strike outcomes. The emerging data infrastructure aggregates UAS video feeds, operator telemetry, strike effects, and individual pilot performance metrics, each linked to unique personal identifiers. These datasets serve multiple functions simultaneously: operational analysis, training evaluation, and the creation of labeled data for AI model development, establishing a feedback loop that ties battlefield performance directly to software refinement. 7. Despite efforts to reduce dependence on foreign commercial technologies, Russia’s military AI development remains heavily reliant on open-weight models and civilian software ecosystems. The transition from tools such as AlpineQuest and Discord toward domestic alternatives like ZOV Maps and Astra-based platforms reflects a push for security and sovereignty at the application layer. At the same time, Russian developers actively adapt open-weight and commercially available AI models, including Mistral, Qwen, LLaMA, YOLO, and related architectures, for military use, embedding them into on-premise, tightly controlled environments. This hybrid approach allows Russia to mitigate sanctions and accelerate AI adoption without building foundational models from scratch." (Executive summary) more

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Generative AI and democracy: Study on advantages and risks of the use of generative artificial intelligence in public debate and democratic processes

Natali Helberger, Claes de Vreese, Gionata Bouche, Agustin Ferrari Braun, Max van Drunen, Simon Kruschinski, Nicolas Mattis, Sophie Morosoli, Laurens Naudts, Charis Papaevangelou, Theresa Seipp, Fabio Votta, Teresa Weikmann

Strasbourg: Council of Europe, Steering Committee on Democracy (CDDM) (2026), 77 pp.

"The key finding of this report is that it is not enough to make sure that the technology is safe and no risk to human rights and public values. GenAI’s impact and potential for the realisation of fundamental rights depends on the societal, organisation and regulatory context in which it operates, ... the possibility for institutions to make value-driven choices and regulators that actively promote public innovation where the interests of society as a whole outweigh purely economic interests of a concentrated handful of technology companies. This report has made the argument that GenAI and its implications for human rights and democracy must be seen in the context of the configurations of infrastructural and political power, and who is able and entitled to decide the course and character of innovation. [...] The report makes a number of recommendations to the Council of Europe: 1. Provide substantive guidance and standardisation: As a human rights organisation, the Council of Europe is particularly well prepared to develop more substantive guidance and identify, concretise and monitor risks to democracy, human rights and political equality, be that in the way GenAI is used in democratic practices like elections, the more structural implications for democratic institutions (such as the free press) as well as the democratic governance of AI. Next to a focus on risks, the Council of Europe can also usefully develop guidance how AI can advance democracy and human rights and develop a value-driven interpretation of “public interest innovation” to inform States, companies and standardisation processes. 2. Incentivise and enable public interest innovation: Next to the risked-based approach to AI that is also enshrined in the Council of Europe’s Framework Convention, the Council of Europe could develop guidance on policies and governance approaches that enable and incentivise public interest innovation. It could help identify the democratic and human rights implications of procurement choices, and develop narratives to prioritize value-oriented innovation, open-source datasets, decentralisation and interoperability above the promotion of scale and innovation driven by a concentrated number of technology companies. 3. Strengthen democratic resilience and ability to govern: The Council of Europe, and the CDDEM specifically, could have an important role in exploring mechanisms and regulatory solutions to map and remedy existing dependencies and identify mission-critical elements of a European digital ecosystem, for example through monitoring the use of GenAI in elections, stimulating the development of public interest information infrastructures and strengthening the ability of states to develop democratic and inclusive ways of governing GenAI. Next to digital autonomy, empowering public accountability actors like civil society, equality bodies, academics or investigative reporters to participate in the governance of the digital transformation are critical conditions for strengthening democratic resilience. Finally, democratic resilience also means enabling more meaningful citizen engagement, including of otherwise often marginalised groups, for example through transparency, literacy and meaningful participation in decision making." (Executive summary) more

Médias et démocratie: Enjeux et perspectives pour la philanthropie

Catherine Malaval, Gilles Marchand, Sabine Lenglet, Anne Cornilleau

Société de la Fondation de France, Observatoire Philanthropie (2026), 46 pp.

"À l’ère des algorithmes et de l’intelligence artificielle générative, l’enjeu démocratique n’est plus seulement l’accès à l’information, mais la capacité collective à identifier et reconnaître les acteurs de confiance qui en garantissent la production. Lorsque les images, les ... more

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Usos problemáticos de dispositivos digitales en la infancia y adolescencia en América Latina: Desigualdad, bienestar y apoyo familiar

Matías Dodel, Ariel Tófalo, Rolando Pérez, David Torres, Jazmín Mazó Torrico

Santiago de Chile: Comisión Económica para América Latina y el Caribe (CEPAL); Kids Online Red América Latina (2026), 42 pp.

"Este estudio aporta datos clave para diseñar políticas públicas y marcos regulatorios que promuevan el bienestar integral de niñas, niños y adolescentes en América Latina. Los hallazgos revelan que los usos problemáticos de las tecnologías no obedecen únicamente al tiempo frente a las pant ... more

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World Development Report 2026: The Promise of Artificial Intelligence
Deep Insights

Washington, DC: World Bank (2026), xxxi, 341 pp.

"This Report is the first comprehensive assessment of what artificial intelligence (AI) means for 6.8 billion people living in low- and middle-income countries. It argues that AI represents a historic opportunity for these countries, potentially enabling them to overcome development challenges that ... have defied solution for decades. Given the scarcity of information on AI’s use in developing countries, the Report sets the ball rolling on closing the gap. It uncovers new facts about how businesses and governments in developing countries are using AI—and identifies the main obstacles to greater and more productive use. AI is a general-purpose technology, or GPT. That puts it in rare company. Steam power. Electricity. Computers and the internet. Each transformed not just one sector, but entire economies, and did so continuously, over decades. Each also followed a pattern: slow and uncertain at first, but eventually reshaping how economies produce and how societies function. AI is following a similar pattern, but on a much faster timeline. It took about 80 years for the steam engine to reach lower-income countries, 40 years for electricity, and 20 years for the internet.1 By contrast, middle-income countries accounted for half of ChatGPT’s global traffic within six months of its launch.2 Rapid diffusion on such a scale has not been seen before. But history also teaches us that the countries that benefited most from previous GPTs were not always the ones that came up with the underlying technology. Those that benefited had built the necessary foundations and moved fast to develop applications on top of them. The countries that did not invest in the infrastructure, skills, and institutions that such technologies required to function benefited less and felt the most pain from disruption. This lesson is directly relevant to AI: The winning approach will take advantage of the new technologies, not seek refuge from them. In only a few years, AI has evolved from making predictions to generating content from text, audio, and video to now autonomously executing complex tasks. As it becomes more powerful and pervasive, its value as a tool for development depends on three factors. The first is capabilities. Unlike computers or the internet, AI can perform complex thinking tasks that guide decision-making and usually require human expertise, such as diagnosing diseases, forecasting weather, or advising farmers. These skills are often in short supply in developing countries, so AI has the potential to fill important gaps. The second is concentration. The most advanced AI models, the chips they rely on, and the data centers that run them are controlled by a small number of companies in just a few economies. This concentration creates dependency risks and affects whether the AI tools available will meet developing countries’ needs. However, this concentration also allows countries to customize AI models without having to spend billions of dollars creating the most advanced AI systems from scratch. The third is complements: the foundations that allow AI to be used safely and effectively. AI works best where reliable infrastructure, good education systems, and strong institutions are present. Developing countries often have shortages in all three. AI, moreover, needs to be customized to the local context because it learns from the data upon which it is trained. How quickly countries build these complements—and how well governments and businesses reorganize to use AI productively—will determine how much and how fast AI improves development. In that respect, AI is no different from GPTs that have come before. Ten years ago, World Development Report 2016: Digital Dividends called these prerequisites the analog complements to digital technologies. Today, AI requires both strong analog and digital complements to deliver its full benefits." (Overview, pages 1-2) more

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Safer platforms, stronger participation: Mapping gender-based violence online in Syria

Bonn: Deutsche Welle DW Akademie (2026), 57 pp.

"Findings show that Gender-Based Violence Online( GBVO) in Syria is normalized and systemic, not merely isolated incidents, functioning as a mechanism of social control that reinforces patriarchal power and restricts civic participation. It takes overlapping forms, including sexual blackmail, harass ... more

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Relational Futures: Indigenous Sovereignty and the Governance of Artificial Intelligence (AI)

Bronwyn Carlson, Tamika Worrell

Macquarie University (2026), 30 pp.

"Artificial intelligence must be governed as a relational and institutional force, not simply a technical system. Effective policy requires Indigenous leadership, enforceable standards, and a commitment to sovereignty, accountability, and community wellbeing. Failure to act risks embedding inequalit ... more

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Environmental Cost of AI's Energy Use: Carbon, Water and Land Footprints

Miriam Aczel, Sanaz Chamanara, Mir Matin, Aria Farsi, Tshilidzi Marwala, Kaveh Madani

Richmond Hill, Ontario (CA): United Nations University Institute for Water, Environment and Health (UNU-INWEH) (2026), 55 pp.

"[...] The study reveals some striking numbers. In 2025, data centers—the physical backbone of AI—consumed an estimated 448 TWh of electricity. If data centers were a country, that level of electricity use would rank it 11th globally. On current trajectories, data center electricity demand could ... roughly double to 945 TWh by 2030, nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria, together home to more than 650 million people. Producing that much electricity would have a carbon footprint of 399 million tonnes CO2e, requiring 6.7 billion trees grown over 10 years to offset—roughly twice the number of trees in the United Kingdom. The associated water footprint of 9.3 trillion liters would be equivalent to the annual domestic water needs of all 1.3 billion residents of Sub-Saharan Africa. The land footprint associated with this electricity would exceed 14,500 km², nearly 10 times the size of Mexico City. AI is now one of the most significant drivers of that data center growth. In 2025, AI workloads alone accounted for around 20% of total data center electricity use, and if that share rises to 40% by 2030 as projected, its electricity demand could reach roughly 378 TWh—enough to meet the residential electricity needs of the entire population of Sub-Saharan Africa for over 2 years. AI’s environmental impacts are shaped not only by data center growth and electricity supply mixes, but also by the escalating cost of building ever-larger models. For example, GPT-3 training consumed an estimated 1.3 GWh of electricity over 34 days, while GPT-4 is estimated to have consumed 50 to 70 GWh over 100 days, roughly 40 to 55 times GPT-3. Yet training is only part of the picture as AI’s operational footprint is increasingly driven by inference. Once models are deployed, billions of everyday interactions account for the bulk of energy use, with inference estimated at roughly 80–90% of total energy consumption. [...] The report identifies priority implications for key stakeholders. Governments must integrate AI infrastructure into energy system planning, carbon accounting, water governance and land use permitting. This requires standardized environmental footprint reporting so impacts can be verified and compared across providers and jurisdictions. Industry and AI developers should treat model selection, default outputs, and routing decisions as footprint determinants, while also improving efficiency-by-design. Users and deploying organizations also shape impacts through volume, frequency, and modality choices. They should adopt “fit-for-purpose” use: selecting the lightest model and lowestenergy format that meets the task and limiting high-cost features when not needed. Data center operators and utilities should recognize siting and procurement as environmental footprint decisions, apply environmental impact screening and cumulative impact assessment. They should implement transparent mitigation and community safeguards where expansion occurs. Investors and financiers should treat electricity, carbon, water, and land footprints as material risks for AI infrastructure portfolios and use comparable footprint metrics in due diligence." (Executive summary, pages 12-13) more

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The State of Media Development 2026: Funding, local ownership and adaptation in international media development

Ines Drefs, Rose Kimani, Dennis Reineck, Martin Scott

Bonn: Deutsche Welle DW Akademie (2026), 85 pp.

"With resources drying up, not least because the U.S. administration has pulled the plug on international development funding, a rise in authoritarianism and another large-scale tech reset looming with AI, media development organizations are struggling to meet the challenges. According to data colle ... more

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Safety by Design: Pathways to Safer Social Media Platforms

Berlin: HateAid (2026), 18 pp.

"Europe’s approach to platform regulation is uniquely rooted in its commitment to democratic values, the rule of law, and fundamental human rights. To defend these principles and safeguard its digital sovereignty, the EU must assert the user rights enshrined in its legislation—resisting both the ... more

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Safeguarding Media Freedom in the Age of Big Tech Platforms and AI: Policy Manual

Anya Schiffrin, Bojana Kostic, Iva Nenadic, Julia Haas, Natali Helberger, Natali, Max van Drunen

Vienna: OSCE Representative on Freedom of the Media (2025), 147 pp.

"With this Policy Manual, we provide guidance for building an information space free from oligopolistic control, resilient to manipulation, and supportive of independent, pluralistic media. This Policy Manual proposes both structural reforms and targeted mitigation measures – focusing on media vis ... more

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Two Decades of Progress Towards Legal Recognition of Community Media Worldwide

Paris: UNESCO (2025), 6 pp.

"Nearly half of all countries now recognize community media, underscoring its importance in amplifying local voices and fostering pluralism and diversity in the media ecosystem. UNESCO's latest global mapping reveals encouraging progress over the past two decades, with more countries adopting suppor ... more

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Digital Disinformation Trends in Latin America: Organisation, Goals, and Policy Pushback

Jesus A. Renzullo N.

Hamburg: GIGA (2025), 31 pp.

"The topic of digital disinformation in Latin America has gained significant traction in recent decades as polarisation increases in the region, trust in institutions erodes, and the arrival of digital propaganda to countries including Brazil, Argentina, Costa Rica, and Mexico threatens the democrat ... more

World Disasters Report 2026: Truth, Trust and Humanitarian Action in the Age of Harmful Information Deep Insights

The Local News Playbook: Creating Value for a Sustainable Future Deep Insights

World Development Report 2026: The Promise of Artificial Intelligence Deep Insights

World Disasters Report 2026: Truth, Trust and Humanitarian Action in the Age of Harmful Information
Deep Insights

The Local News Playbook: Creating Value for a Sustainable Future
Deep Insights

World Development Report 2026: The Promise of Artificial Intelligence
Deep Insights