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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 Protocol Gap: Brazil

Sérgio Spagnuolo, Ester Borges, Bruno Fiaschetti, Paula Miraglia

Journalism Relay Project; Momentum; International Fund for Public Interest Media (IFPIM) (2026), 12 pp.

"An overwhelming majority of news websites in Brazil have either no AI-scraping policy at all or a very permissive approach. As of November 2025, only 7.2% of Brazilian news websites disallow at least one AI crawler through the use of a robots.txt file, even though most news sites (75%) have a robot ... more

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AI is here. Are we ready?

Eva-Maria Verfürth et al.

D+C: Development and Cooperation, issue 4 (2026), pp. 31-58

"AI is already having a profound impact on our daily lives. The key question is who controls the technology. It is not only in conflicts that AI accelerates the spread of deceptively realistic fakes and makes it harder to distinguish reliable information from manipulation. At the same time, it opens ... 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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Grounding Digitalization: Technologies, Materialities, and Spaces

Regula Valérie Burri, Hanna Göbel, Inga Reimers (eds.)

Bielefeld: transcript Verlag (2026), 278 pp.

"Digitalization is usually perceived as an invisible process and its cultural embeddedness as well as its material, spatial, and environmental grounding are often neglected. However, digital technologies and transformations are shaped not only by cultural values, practices, and imaginaries, but also ... more

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Climate Change Communication in Africa

Tendai Chari, Allen Munoriyarwa (eds.)

Oxford: Routledge (2026), xxv, 328 pp.

"From legacy media’s framing of climate narratives to the mobilising potential of digital media, the volume examines the multi-faceted ways in which climate change is mediated through different communication channels and how different media can be harnessed to amplify African voices on climate cha ... more

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Societies at an AI Crossroads: Choices and Value Conflicts

Ignas Kalpokas, Julija Kalpokienė

London; New York: Routledge (2026), 116 pp.

"As contemporary societies undergo profound transformations driven by artificial intelligence and related technologies, a unilinear vision of inevitable ‘progress’ and development increasingly dominates public discourse. This book offers a counterpoint, challenging such deterministic narratives ... 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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Power Hungry: How AI Will Drive Energy Demand

Christian Bogmans, Patricia Gomez Gonzalez, Ganchimeg Ganpurev, Giovanni Melina, Andrea Pescatori, Sneha Thube

Washington, DC: International Monetary Fund (IMF) (2025), 28 pp.

"The development and deployment of large language models like ChatGPT across the world requires expanding data centers that consume vast amounts of electricity. Using descriptive statistics and a multi-country computable general equilibrium model (IMF-ENV), we examine how AI-driven data center growt ... more

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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.

" Guided by the CGIAR-wide Evaluation Framework, integrating AI tools requires a governance approach to balance innovation with ethical responsibility, ensuring transparency, fairness, accountability, and inclusivity. This Technical Note encourages and guides CGIAR evaluators to ethically explore, n ... egotiate, and experiment with AI tools: Explore: Evaluators are invited to discover how AI, especially GenAI, can enhance evaluation efficiency, from scoping and data analysis to reporting. The Note provides practical guidance on AI applications and examples to support creative yet responsible exploration. Negotiate: Integrating AI should be openly discussed with commissioners, stakeholders, and teams. The Note prioritizes jointly defining boundaries, expectations, and ethical parameters (transparency, accountability, and data sensitivity) at each phase of evaluation. Use AI Responsibly: While AI tools are evolving, evaluators are encouraged to pilot and iterate their use. The document supports experimentation through practical tips, prompt examples, and tool selection criteria, all while emphasizing documentation and learning from each use case. Effective AI governance is grounded in core principles: Transparency requires clear documentation of AI tool usage, data sources, model limitations, and decision-making processes. Accountability involves assigning responsibility for AI decisions and outputs and establishing oversight and redress mechanisms. Fairness and inclusion must proactively mitigate bias and discrimination, with particular attention to underrepresented groups and data gaps. Data privacy and security must align with applicable data protection regulations and ensure secure handling practices. Human oversight ensures that evaluators retain control over processes and can intervene as needed. In operationalizing ethical AI governance in CGIAR evaluations, due diligence is required in assessing AI tools for ethical alignment before deployment: reviewing the transparency of vendors, the documentation of models, and their intended use cases. Where relevant, components involving AI—especially those engaging human subjects or sensitive data—should undergo ethics review. AI applications must be adapted to the local and cultural contexts in which evaluations are conducted, as what is suitable in one setting may be inappropriate in another. Additionally, participants should be informed about the use of AI systems and the implications of data collection or processing to ensure informed consent. Ethical AI governance should be embedded in the entire evaluation lifecycle. During the design phase, evaluators should define AI tools to use, why they are selected, and assess risks. In data collection, AI tools should be used in ways that uphold data privacy and protection standards and avoid reinforcing harmful stereotypes or excluding groups. During the analysis phase, the role of AI in supporting interpretation should be documented, with an acknowledgment of limitations or biases. In dissemination, documentation, and reporting, AI’s contribution, limitations, and human validation should be disclosed. By rapid adaptation of content across formats, languages, and complexity levels, AI opens possibilities for broader, more inclusive communication of findings. Finally, the follow-up phases should include a reflection on the ethical implications observed and how these lessons can improve future evaluations." (Executive summary) more

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Practical Machine Learning: A Beginner's Guide with Ethical Insights

Ally S. Nyamawe, Mohamedi M. Mjahidi, Noe Elisa Nnko, Salim A. Diwani, Godbless G. Minja, Kulwa Malyango

Boca Raton: CRC Press; Chapman & Hall (2025), xii, 214 pp.

"The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field. It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application ... 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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La inteligencia artificial: Una mirada pastoral desde América Latina y el Caribe

José Sols Lucía (coord.)

Bogotá: Consejo Episcopal Latinoamericano y Caribeño (CELAM) (2025), 97 pp.

"El trabajo incluye desde nociones generales sobre Inteligencia Artificial hasta propuestas prácticas a los obispos del continente. El sumario incluye antecedentes históricos y evolución de la IA, aspectos éticos, antropológicos y teológicos, recoge el magisterio de la Iglesia, asume el desaf� ... more

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Artificial Intelligence's Impact on Persons with Disabilites in Africa
Deep Insights

Jerry John Kponyo, Bernard Chiira, Christopher Harrison, Hanyurwimfura Damien (eds.)

Kwame Nkrumah University of Science and Technology (KNUST); Assistive Technologies for Disability Trust (AT4D); Next Step Foundation; Tangaza University College; Kenya National Commission for Science, Technology, and Innovation (NACOSTI) (2025), ix, 169 pp.

"Artificial intelligence has the potential to improve the daily lives of Persons with Disabilities (PWDs) in Africa in practical, cumulative ways—transcribing, translating, summarizing, personalizing, and predicting to reduce routine frictions in school, work, health, mobility, and access to publi ... c services. The study surveys this emerging landscape across Kenya, Ghana, Rwanda, and comparator contexts, mapping how AI augments assistive technologies (AT) and mainstream services while clarifying the policy, data, and delivery conditions that determine real-world impact. Across sectors, we find promising AI use cases beyond traditional AT. In education, adaptive tutors, captioning, and sign-language tools can widen access, though localized content and language coverage remain thin. In employment, AI can support job matching, accessible applications, task breakdown, and on-the-job accommodations, especially when paired with employer guidance and incentives. In mental health, chatbots can extend scarce services and offer stigma-free entry points to care; caregiver tools use voice, translation, and simple workflows to ease coordination and stress. Mobility and independent living benefit from computer vision, speech interfaces, and early robotics, with African innovators piloting sign-language avatars, personalized speech recognition, and lower-cost bionics. The potential of these advances is real but uneven—most remain pilots, and scale requires fit-for-purpose data, infrastructure, and financing. One binding constraint is data. Disability is systematically under-counted in official statistics and under-represented or misrepresented in AI training sets, creating a “disability data desert” that limits accuracy for African contexts (from atypical speech and local sign languages to recognition of mobility aids). Without deliberate collection, curation, and governance that center PWDs, models will continue to miss or misread disabled users, with downstream harms in inclusion, safety, and opportunity. Building representative, ethical datasets—especially for African languages and disabilities—emerges as a first-order priority alongside affordable computing and connectivity. Policy momentum is encouraging but incomplete. The African Union’s Continental AI Strategy (2025–2030) explicitly names disability inclusion, calling for accessible datasets, skills, and governance. Ghana’s and Kenya’s AI strategies also advance infrastructure, data sharing, and public-sector adoption, although explicit disability provisions are still maturing. Convergence around rights-based, inclusive AI is visible; however, its delivery depends on procurement standards, budgeting for accessibility, and participation by Organizations of Persons with Disabilities (OPDs) in the design and oversight process. The study’s central conclusion is pragmatic: AI’s near-term value for disability inclusion is unlocked where three conditions meet. First, inclusion by design—co-creation with PWDs and OPDs, localized languages, and multi-modal accessibility baked into products and datasets. Second, enabling rules and rails—national strategies that mandate accessibility in digital services, robust disability-relevant data, and align incentives for inclusive procurement. Third, sustainable delivery—hybrid human-AI service models, community channels, and financing that lower costs for users and caregivers while supporting innovators to move from pilots to scale. Where these conditions hold, AI can measurably widen access to learning, work, and care; where they do not, tools plateau as proofs-of-concept and risks of bias and exclusion grow. Overall, the path to disability-inclusive AI in Africa is clear: invest in representative data and affordable infrastructure; mandate accessibility and accountability; and deliver through locally grounded, human-centered services. Done together, these steps turn today’s pilots into equitable, reliable systems that expand agency and opportunity for millions of Africans with disabilities." (Executive summary) 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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Measuring what matters: How to assess AI’s environmental impact

Geneva: ITU (2025), viii, 21 pp.

This report synthesizes key findings from a diverse range of sources, including academic literature, corporate sustainability initiatives, and emerging environmental tracking tools. Collectively, these documents provide a thorough overview of current methodologies for evaluating the environmental im ... more

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AI-Generated Disinformation in Europe and Africa: Use Cases, Solutions and Transnational Learning

Karen Allen, Christopher Nehring

Johannesburg: Konrad-Adenauer-Stiftung (KAS), Media Programme Sub-Sahara Africa (2025), xii, 158 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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Rethinking Open Source in the Age of Foundational AI Models
Deep Insights

Greg Maly

ICTworks, July 29 (2025)

"As the global artificial intelligence community wrestles with the tension between scale and accessibility, recent work by researchers at Lelapa AI offers a compelling example of what inclusive, efficient AI can look like. Around the world, the push to shrink massive language models into deployable, ... 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.

The Routledge Handbook of Artificial Intelligence and Philanthropy Deep Insights

Artificial Intelligence's Impact on Persons with Disabilites in Africa Deep Insights

Rethinking Open Source in the Age of Foundational AI Models Deep Insights

The Routledge Handbook of Artificial Intelligence and Philanthropy
Deep Insights

Artificial Intelligence's Impact on Persons with Disabilites in Africa
Deep Insights

Rethinking Open Source in the Age of Foundational AI Models
Deep Insights