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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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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

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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AI in Africa: A Landscape Study

Rachel Adams, Fola Adeleke, Leah Junck, Samule Segun, Ayantola Alayande, Selamawit Abdella, Mark Gaffley, Fabio Andres Diaz Pabon, Funbi Salami

Global Center on AI Governance; African Observatory on Responsible AI (2025), 44 pp.

"Though comprehensive AI regulation is still nascent in Africa, there is an increased focus on national AI strategies, ethical guidelines and international collaborations. Over 40 countries have already established data protection and privacy laws, creating opportunities for harmonised regulations a ... nd a supportive environment for AI innovation. Key continental governance instruments and initiatives also include the African Union’s AI Strategy, the African Continental Free Trade Area and the African Commission on Human and Peoples’ Rights. This report found that the increasing application of AI in key sectors across Africa, such as health, education, finance, agriculture, public services and the environment, necessitates a collaborative approach to ethical AI development and use. This requires addressing persistent infrastructural gaps, developing regional regulatory frameworks, investments in AI research and capacity building efforts as well as promoting multi-stakeholder AI governance initiatives. Key strategies identified include joint investment and funding, pooling resources and supporting sustainable and fair open-source projects, which will help direct efforts toward innovation and regional independence. Open Source AI models are particularly important in Africa where local tech startups can leverage global open-source initiatives to build context-specific solutions. However, concerns regarding data ownership, privacy and ethical AI deployment call for more robust policies for open source AI on the continent. To foster responsible AI innovation, African countries should establish comprehensive AI governance frameworks while adhering to existing laws as well as strengthen regulatory institutions to provide oversight over AI technologies. Regulatory sandboxing also offers a viable approach to enable sage experimentation with appropriate oversight. Regional and international cooperation as well as leveraging public-private partnerships can promote funding for expanding AI research and development initiatives, resolve talent shortages and promote infrastructure development. Africa has a unique opportunity to leverage AI, along with its resources and local young talent, for socioeconomic development. However, to ensure inclusivity and sustainable innovation, it is essential to address infrastructure challenges and establish regulatory frameworks that protect societal wellbeing. Embracing collaborative efforts, including open source initiatives, regional and international partnerships are critical for achieving the continent’s ambitious goals without leaving anyone behind." (Executive Summaty, page 3) 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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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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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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Terms of (dis)service: Comparing misinformation policies in text-generative AI chatbot

Maria Giovanna Sessa

Eu DisinfoLab (2025), 8 pp.

"● In the 11 chatbots considered, references to misinformation vary (and sometimes are missing). Even when the term is mentioned, it is rarely defined. This is not uncommon: what some platforms call ‘deletion’, others call ‘termination’, though potential nuances remain unclear. Additionall ... y, it is unspecified who enforces practices, how long suspensions last, and what distinguished warnings, suspensions, and terminations. On another note, more stringent prohibitions generally focus on hate speech, highlighting the illegal nature of the issue. ● Overall, ToS violation detection and content moderation processes are unclear. Some platforms mention dedicated moderation teams and processes – typically a mix of automated and human reviews – but the details remain vague. There is no transparency regarding the resources invested in content moderation, including the number of personnel, their locations and language coverage, and the timeline for action. ● Given our focus on misinformation, we concentrated on content reporting. Nevertheless, it is evident that platforms prioritise reporting breaches of and vulnerabilities in their architecture over content-related concerns. ● Law compliance is usually referenced in broad terms as adherence to “all applicable legislation”. Platforms primarily emphasise privacy and data protection, the prohibition of illegal activities (with a particular focus on child protection), restrictions on reverse-engineering platform functions, and using the services for biometric identification. Notably, there is a perception that users bear greater responsibility for providing accurate data and avoiding platform abuse than the platforms themselves do in terms of accountability. This impression arises because the ToS are detailed regarding user obligations but more superficial about platform responsibilities. Uncertainty remains regarding platform incentives and their actual capacity to enforce these rules. ● Most platforms specify that fact-checking is the user’s responsibility as if trying to exempt themselves from liability related to providing false and inaccurate answers. However, it is worth noting that the general provisions of the EU’s Digital Services Act (DSA) require online platforms to remove illegal content expeditiously once they have actual knowledge of its illegality. ● If current platform approaches to misinformation already seem inadequate, there are valid concerns that the situation will deteriorate further. The cross-platform trend of dismantling safety policies and moderation teams reinforces these fears. Examples pointing in this direction include OpenAI’s decision to remove some content warnings on ChatGPT, and xAI’s introduction of “Unhinged Mode” in Grok-2, a beta feature described as intentionally “objectionable, inappropriate, and offensive, much like an amateur stand-up comic who is still learning the craft.” (Concluding remarks, page 8) 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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How-to note: Co-designing AI solutions with crisis-affected communities (beta version)

Sarah W. Spencer, Helen McElhinney, Michael Tjalve, Anjali Mazumder

CDAC Network; Alan Turing Institute; Humanitarian Advisory AI (2025), 17 pp.

"This how-to note offers practical guidance for humanitarian actors seeking to co-design AI solutions with crisis-affected communities. This is related to, though not intended to support the technical co-design of AI models, though there is a significant amount of research on this subject. This how- ... 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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Trust, Responsibility, and Digital Governance: Regulation of AI and Blockchain Technology from a Capacity-Based Perspective

Sebastian Bücker, Marcus Düwell, Andreas Kaminski, Michael Leyer (eds.)

Bielefeld: transcript Verlag (2025), 229 pp.

"Numerous ethical guidelines and regulatory frameworks have been developed to assess and shape digital systems. However, these efforts often rest on the dubious assumption that individuals and organisations possess the necessary capacities to assess such systems in terms of justice, reliability, and ... 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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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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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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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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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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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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Just Hiring! How to counter discrimination in AI-powered software for recruitment. A toolkit for software developers

M. Daviet, N. Baranowska, A. Mueller, C. Rus, C. Castillo, J. Saldivar, A. Gatzioura

FINDHR Fairness and Intersectional Non-Discrimination in Human Recommendation (2025), 86 pp.

"In this Toolkit, we offer introductory information and technical recommendations on how to mitigate the risk of discrimination in software development of systems used for recruitment. This Toolkit addresses software developers and product managers working or interested in this field, and it intends ... more

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Just Hiring! How to counter discrimination in AI-assisted recruiting within your organisation. A toolkit for HR professionals

M. Daviet, A. Mueller, N. Baranowska, C. Castillo, J. Saldivar, A. Gatzioura

FINDHR Fairness and Intersectional Non-Discrimination in Human Recommendation (2025), 73 pp.

"In this Toolkit, we offer introductory information and concrete recommendations on how to mitigate the risk of discrimination in algorithmic hiring systems within organisations. This Toolkit addresses HR professionals and recruiting agencies and intends to help them gain a better understanding of w ... more

Inteligencia Artificial: Guía de uso para informativos en radio comunitaria 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

Inteligencia Artificial: Guía de uso para informativos en radio comunitaria
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