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AlgorithmWatch’s guidelines to use generative AI responsibly

Oliver Marsh, Michele Loi

Berlin: Algorithm Watch (2026)

"Whether you use ChatGPT, Claude or Gemini, Copilot or Perplexity – generative AI poses massive problems: many results are inaccurate and politically problematic, the systems’ energy and water consumption is enormous. At the same time, they have become an integral part of everyday life. Algorith ... more

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The People-Centered AI Playbook. Playbook Capsule

Dalberg Data Insights (2026), 44 pp.

"This people-centered playbook [...] is designed to give you the essentials of AI adoption in a quick, accessible format, with core concepts, foundational steps, and key frameworks without overwhelming detail. Built for impact-driven teams in low-resource or non-tech-first contexts, it answers the m ... 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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Toward AI Governance Alignment in Africa, Middle East, and Türkiye (AMET) Region

Emma Ruttkamp-Bloem, Fola Adeleke, Jake Effoduh, Kebene Wodajo, Nagla Rizk, Olubayo Adekanmbi, Rachel Adams, Rami Alkarmi, Seani Rananga, Seydina Ndiaye, Shikoh Gitau, Tami Koroye

Global Center on AI Governance (GCG) (2026), 54 pp.

"The analysis begins by identifying the core “centric approaches” that guide Artificial Intelligence (AI) national strategies. These include security-anchored models driven by state control, innovation-led frameworks that prioritise competitiveness, rights-based regimes centred on fundamental pr ... otections, and developmental approaches focused on public service delivery and technological catch-up. Each approach expresses incentives, risk perceptions and administrative capacities. Out of these foundational choices, there are different groupings. Various regions within AMET are adopting recognisable patterns of regulation that reflect their political economies, institutional structures and geopolitical positions. These groupings are not static categories, but evolving alignments shaped by domestic pressures, supply-chain dependencies and shifting global power dynamics. Across all regions, a set of cross-cutting issues consistently shapes the regulatory landscape. Data protection and interoperability remain central, alongside growing demands for accountability, explainability and robust auditing. Standards and certification are emerging as tools for both trustbuilding and geopolitical influence. Sector-specific rules in finance, health, education and public administration are increasingly decisive. Capacity constraints, fiscal limits and uneven institutional strength continue to define what is realistically possible for many governments. Geopolitical tensions and cloud concentration reinforce questions around sovereignty, infrastructure control and long-term strategic autonomy. This report translates these insights into practical implications for states, regional bodies and technology firms. It highlights workable pathways for reconciling innovation with safety, managing cross-border data flows, and building resilient digital infrastructure. It also identifies areas where architecture choices such as regional cloud centres, culturally calibrated testing layers and tiered sovereignty models can support both regulatory goals and developmental priorities. The recommendations emphasise flexible alignment, cooperation through standards, and the need for shared mechanisms that accommodate political diversity while reducing fragmentation. Taken together, the framework provides a stable and operational way of understanding global AI regulation. It clarifies the interests driving different jurisdictions, the pressures that shape convergence or divergence, and the strategic considerations that technology firms and policymakers must navigate as the regulatory environment continues to evolve." (Executive summary) more

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2025 Technology and Innovation Report: Inclusive Artificial Intelligence for Development

New York: United Nations Conference on Trade and Development (UNCTAD) (2025), xiii, 168 pp.

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Intelligence artificielle et emploi en Afrique: Analyse des impacts de la digitalisation du travail

Ibrahim Kalil Konaté, Michel Boukar

Robert Beugré Mambé (preface)

Paris: L'Harmattan (2025), 267 pp.

"Ce livre étudie les effets de l’intelligence artificielle (IA) et de la digitalisation sur l’emploi en Afrique, en usant d’une méthodologie à deux articulations. D’une part, l’analyse des effets directs de l’IA : destruction d’emplois traditionnels dans des secteurs-clés (agricult ... more

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Intelligence artificielle et robotique autonome: Enjeux et défis contemporains dans l’espace francophone

Etienne Damome, Moustapha Ben Ismïila Diaby (eds.)

Paris: L'Harmattan (2025), 358 pp.

"Cet ouvrage propose une analyse nuancée des transformations induites par l'IA et la robotique autonome dans l'espace francophone. Il insiste sur son potentiel à façonner durablement les sociétés contemporaines. S'appuyant sur des exemples concrets et des études de cas, l'ouvrage fournit un ca ... more

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Thinking with AI: Machine Learning the Humanities

Hannes Bajohr (ed.)

London: Open Humanities Press (2025), 269 pp.

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Considerations and Practical Applications for Using Artificial Intelligence (AI) in Evaluations

D. Cekova, L. Corsetti, S Ferretti, S. Vaca

Rome: CGIAR Independent Advisory and Evaluation Service (IAES) (2025), 42 pp.

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AI for Good Innovate for Impact. Interim Report 2025

Geneva: ITU (2025), xxxiv, 828 pp.

"Artificial intelligence (AI) is reshaping the way we address complex societal challenges, offering new possibilities in areas such as healthcare, climate resilience, education, and digital inclusion. The Innovate for Impact project was launched in 2024 to identify, support, and showcase practical A ... more

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United Nations Activities on Artificial Intelligence (AI)

Geneva: ITU (2025), xvi, 500 pp.

"If 2023 was the year of generative artificial intelligence, 2024 was marked by the rapid expansion and adoption of AI, driving waves of innovation across nearly every conceivable domain. The United Nations system has kept an encouraging pace, redoubling efforts to harness the power and potential of ... more

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The Routledge Handbook of Artificial Intelligence and Philanthropy
Deep Insights

Milos Maricic, Giuseppe Ugazio (eds.)

London; New York: Routledge (2025), xxv, 57o pp.

"The Routledge Handbook of Artificial Intelligence and Philanthropy acts as a catalyst for the dialogue between two ecosystems with much to gain from collaboration: artificial intelligence (AI) and philanthropy. Bringing together leading academics, AI specialists, and philanthropy professionals, it ... more

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How Do You Explain ChatGPT to a Community Health Worker?

Wayan Vota

ICTworks, December 2 (2025)

"I’ve been diving deep into groundbreaking research on community health worker (CHW) perceptions of AI applications in rural India. The truth is more complex than the rosy predictions flooding our sector about artificial intelligence transforming global health. The findings expose a troubling gap ... more

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Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs)
Key Guides

Hamburg: Hamburg Sustainability Conference; UNDP (2025), 7 pp.

"As global stakeholders from governments, international organizations, the private sector, academia, and civil society, we convene in Hamburg to shape a human-centric, human-rights-based, inclusive, open, sustainable, and responsible AI future. We commit to advancing AI for the SDGs, aligning with o ... more

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Antiqua et nova: Note über das Verhältnis von künstlicher Intelligenz und menschlicher Intelligenz

Dikasterium für die Glaubenslehre, Dikasterium für die Kultur und die Bildung

Bonn: Sekretariat der Deutschen Bischofskonferenz (2025), 83 pp.

"Es ist daher von entscheidender Bedeutung, einzelne Anwendungen in bestimmten Kontexten kritisch zu bewerten, um festzustellen, ob sie die Würde und Berufung des Menschen und das Gemeinwohl fördern oder nicht. Wie bei vielen Technologien sind die Auswirkungen der verschiedenen KI-Anwendungen zu B ... more

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Digital Progress and Trends Report 2025: Strengthening AI Foundations

Washington, DC: World Bank (2025), xix, 111 pp.

"The recent rapid evolution of artificial intelligence (AI) has outpaced society's ability to fully grasp its implications. Unlike technological shifts that have unfolded over decades, AI's integration is accelerating at an unprecedented speed and scale. Along with AI's immense opportunities come ne ... more

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An Autonomy-Based Classification: AI Agents, Liability and Lessons from the Automated Vehicles Act

Lisa Soder, Julia Smakman, Connor Dunlop, Oliver Sussman

Berlin: Interface; Ada Lovelace Institute (2025), 28 pp.

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Artificial Intelligence Index Report 2025
Deep Insights

Nestor Maslej, Loredana Fattorini et al.

Stanford: Stanford University, Institute for Human-Centered AI (2025), 456 pp.

"Welcome to the eighth edition of the AI Index report. The 2025 Index is our most comprehensive to date and arrives at an important moment, as AI’s influence across society, the economy, and global governance continues to intensify. New in this year’s report are in-depth analyses of the evolving ... more

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Inteligencia Artificial: Guía de uso para informativos en radio comunitaria
Key Guides

Tito Ballesteros López

Red de Emisoras Comunitarias del Magdalena Medio (AREDMAG) (2025), 24 pp.

"La guía que aquí presentamos propone caminos prácticos para incorporar la IA en los noticieros radiales, desde la redacción automatizada hasta la interacción con los oyentes en tiempo real, pasando por la generación de contenidos sonoros, el monitoreo de fuentes y el análisis de impacto. Cad ... more

The Routledge Handbook of Artificial Intelligence and Philanthropy Deep Insights

Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs) Key Guides

Artificial Intelligence Index Report 2025 Deep Insights

Inteligencia Artificial: Guía de uso para informativos en radio comunitaria Key Guides

The Routledge Handbook of Artificial Intelligence and Philanthropy
Deep Insights

Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs)
Key Guides

Artificial Intelligence Index Report 2025
Deep Insights

Inteligencia Artificial: Guía de uso para informativos en radio comunitaria
Key Guides