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Human Development Report 2025: A Matter of Choice. People and Possibilities in the Age of AI
Deep Insights

Pedro Conceição et al.

New York: UNDP (2025), xi, 307 pp.

"This year’s Human Development Report examines what distinguishes this new era of AI from previous digital transformations and what those differences could mean for human development (chapter 1), including how AI can enhance or subvert human agency (chapter 2). People are already interacting with ... more

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State of Internet Freedom in Africa 2025: Navigating the Implications of AI on Digital Democracy in Africa

CIPESA (2025), 74 pp.

"While AI offers potential benefits across various sectors, its deployment by businesses and governments and application by individuals present new opportunities while raising significant concerns. More specifically, most African countries do not have legal or regulatory measures on the ethical and ... more

Developing an Artificial Intelligence Maturity Assessment Framework for South Africa. First Annual AI Maturity Assessment 2025

Bonn; Eschborn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward – Artificial Intelligence for All; University of the Western Cape (UWC) (2025), 107 pp.

"The South African AI MAF serves as a foundational tool for guiding the country’s progress towards AI maturity and is tailored to the country’s unique socioeconomic, cultural, and technological realities. It furthermore aligns with broader continental ambitions (i.e. African Union’s 2024 Conti ... nental AI Strategy), which reflects a strong commitment to leveraging AI for sustainable development. This implies the ethical and inclusive development and implementation of AI in ways that address local challenges. In South Africa, GIZ, through the FAIR Forward project, has collaborated closely with the Council for Scientific and Industrial Research (CSIR), the South African Institute of Chartered Accountants (SAICA) and researchers from the University of the Western Cape (UWC) to develop the AI Maturity Assessment Framework (AI MAF) for South Africa. A design-science methodology was applied to develop the AI MAF for South Africa. The approach involved a structured literature review process, co-design workshops with cross-sectoral stakeholders, expert interviews, validation workshops and external expert review. This first version of the AI MAF consists of eight domains: Domain 1: International and Continental Profile as AI Leader Domain 2: An Enabling Regulatory Environment Domain 3: Citizen Engagement With and Empowerment Through AI Domain 4: Education and Workforce Enablement Domain 5: Innovation and Research Domain 6: Growth of the AI Ecosystem Domain 7: Data and Digital Infrastructure Domain 8: Security and Privacy Each domain includes sub-domains with specific indicators. A total of 68 indicators are included in this 2025 instrument, aimed at reflecting the country’s unique socioeconomic, cultural, and technological realities. An assessment instrument (rubric) to measure the level of maturity of these eight domains was adapted from the maturity measurement scale set out in ISO 37004 (Governance Maturity Model – Guidance). It reflects the structured progression of the ISO standards, employing a maturity scale that ranges from Level 0 (No evidence) to Level 5 (Continual optimisation or improvement). It is grounded in the principle of evidence-based assessment, evaluating maturity through the lens of activities and inputs (Levels 1–2) that lead to measurable outcomes and impact (Levels 3–5). The application of this instrument in the first iteration of assessing AI maturity in South Africa indicated that the country is in the early stages of AI maturity, with seven of the eight domains assessed at Levels 1–2 on the maturity scale, and only one domain reaching Level 3. This suggests that all domains demonstrate some level of foundational ‘input activities’, signalling a positive intent and growing awareness of the importance and relevance of AI, with some initial movement towards demonstrating positive outcomes. Overall, the generally low maturity scores indicate that progress across the domains is fragmented. This could be attributed to still limited strategic ecosystem coordination, targeted investment and capability building. The evidence-based approach enables a reflection of the South African landscape and supports strategic alignment across government, industry, and academia. The framework and interactive dashboard – developed through this project to enable accessible visualisation of the data – serve as foundational reference points for supporting South Africa’s evolving AI ecosystem. An AI agent developed as part of the initiative facilitates regular updates, helping ensure that the AI MAF remains a relevant strategic tool." (Executive summary, pages 8-10) more

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2024-25 Annual Report: Dynamic Coalition on the Sustainability of Journalism and News Media

Waqas Naeem, Daniel O’Maley, Courtney C. Radsch, Aws Al-Saadi, Lei Ma, Nompilo Simanje

Internet Governance Forum; Dynamic Coalition for the Sustainability of Journalism and News Media; Global Forum for Media Development (GFMD) (2025), 50 pp.

"[...] Just as AI technologies are disrupting the business model of the Internet, they will also have a significant impact on the financial sustainability of the news media. The ability of AI tools to generate and aggregate content and produce news-style summaries might altogether bypass the news me ... more

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Information Ecosystems and Troubled Democracy: The State of Knowledge on News Media, AI, and Data Governance

Robin Mansell, Flavia Durach, Matthias C. Kettemann, Théophile Lenoir, Rob Procter, Gyan Prakash Tripathi, Emily Tucker

Göteborg: Nordicom, University of Gothenburg; Observatory on Information and Democracy (2025), 305 pp.

"A critical assessment of why today’s information ecosystems are troubling for democracy, this book, based on research in the Global North and Global Majority World, examines changes in news media, artificial intelligence, and data governance. It focuses on measures to improve the quality of publi ... 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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AI With Purpose: How Foundations and Nonprofits are Thinking About and Using Artificial Intelligence

Elisha Smith Arrillaga, Seara Grundhoefer, Christina Im

Center for Effective Philanthropy (CEP) (2025), 39 pp.

"While AI is widely used by nonprofits and foundations alike — most often for internal productivity and communications purposes — leaders share common concerns about AI in their work. They also agree that foundations do not currently have a strong grasp of nonprofits’ AI-related needs. Perhaps ... more

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The State of Large Language Models for African Languages: Progress and Challenges

Kedir Yassin Hussen, Walelign Tewabe Sewunetie, Abinew Ali Ayele, Sukairaj Hafiz Imam, Eyob Nigussie Alemu, Shamsuddeen Hassan Muhammad, Seid Muhie Yimam

arXiv.org (2025), 25 pp.

"Large Language Models (LLMs) are transforming Natural Language Processing (NLP), but their benefits are largely absent for Africa’s 2,000 low-resource languages. This paper comparatively analyzes African language coverage across six LLMs, eight Small Language Models (SLMs), and six Specialized SL ... 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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Patterns of Inclusion: How Gender Matters for Automation, Artificial Intelligence and the Future of Work

Elisabeth Kelan

Oxford; 9781032669892 (pbk): Routledge (2025), xiv, 169 pp.

"It is widely presumed that digitalisation, automation and artificial intelligence (AI) shape the future of work. Yet gender is rarely considered in those debates. This path-breaking book, written by a leading thinker on gender, inclusion and organisations, Elisabeth Kelan, is based on in-depth rese ... more

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AI and Data Science Bootcamp for Women and Minoritised Groups: Impact Report

Luisa Olaya, Deshni Govender, Abeera Dubey, Jocelyn Mukamisha, Mary Seiwah

Bonn; Eschborn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward; Intel (2025), vii, 35 pp.

"The AI and Data Science Bootcamp for Women and Minoritised Groups was designed to actively address the diversity gap in the AI field by lowering the entry barriers that women and minoritised groups face and empowering them with advanced technical and personal development skills to succeed in the AI ... more

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Künstliche Intelligenz im medialen Diskurs: Wird soziale Gerechtigkeit ausgeblendet?

Elke Grittmann, Lina Brink, Peter Kann

Frankfurt am Main: Otto Brenner Stiftung (2025), 84 pp.

[.] Auf Basis von über 2.000 Artikeln aus neun reichweitenstarken Print- und Onlinemedien untersuchen die Autor*innen, welche Themen in der Berichterstattung über KI gesetzt, wie Bezüge zu Fragen sozialer Gerechtigkeit hergestellt werden, welche narrativen Muster sich zeigen und welche Akteur*inn ... 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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The Influence Evolution: Harnessing AI Innovation While Preserving Human Connection in Social Media

Katja Muñoz, Maria Pericàs Riera

German Council on Foreign Relations (DGAP) (2025), 10 pp.

"Social media stands at a pivotal juncture where technology and humanity converge. From productivity tools to fully autonomous AI agents, we are witnessing a fundamental shift in how content is created, distributed, and consumed. This evolution presents dual futures: one in which AI influencers and ... more

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Artificial Humanities: A Fictional Perspective on Language in AI

Nina Beguš

Ann Arbor: University of Michigan Press (2025), 283 pp.

"Artificial Humanities explores how the humanities-literature, history, and art-can deepen our understanding of artificial intelligence and its development. By examining fictional representations of AI in parallel with actual technological developments, Nina Beguš presents a novel interdisciplinary ... more

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Key Questions for AI in Public Institutions: Prompts and Resources to Spark Critical Conversation
Key Guides

Tanja Dreher, Georgia van Toorn

Sydney: University of New South Wales (UNSW), UARC Centre of Excellence for Automated Decision-Making and Society. (2025), 30 pp.

""In this think piece we sketch the impacts and implications of corporate AI for institutions with a public interest orientation. We focus on public universities and social services as vital public institutions that have been widely understood as essential to democracy and social justice. Through a ... 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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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 (2025), 18 pp.

"AI-driven search-summary features, with Google's AI Overviews (AIOs) being the most promiment example, are rapidly transforming how people access news, with profound implications for our information ecosystem. While AI holds potential to improve access to information, its current deployment risks u ... ndermining the sustainability, diversity, and reliability of news. 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 impacts 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." (Executive summary) 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

Human Development Report 2025: A Matter of Choice. People and Possibilities in the Age of AI Deep Insights

Key Questions for AI in Public Institutions: Prompts and Resources to Spark Critical Conversation Key Guides

The Routledge Handbook of Artificial Intelligence and Philanthropy Deep Insights

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

Human Development Report 2025: A Matter of Choice. People and Possibilities in the Age of AI
Deep Insights

Key Questions for AI in Public Institutions: Prompts and Resources to Spark Critical Conversation
Key Guides

The Routledge Handbook of Artificial Intelligence and Philanthropy
Deep Insights

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