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Justicia algorítmica en América Latina y el Caribe: Investigación, políticas públicas y ética de la inteligencia artificial

Consejo Latinoamericano de Ciencias Sociales (CLACSO); CIESPAL; UNESCO (2026), 105 pp.

"El volumen reúne los policy briefs elaborados en el marco de la convocatoria Justicia Algorítmica. Una inteligencia artificial ética para América Latina y el Caribe, lanzada conjuntamente por UNESCO Ecuador y el Consejo Latinoamericano de Ciencias Sociales (CLACSO), en el marco de una colaborac ... ión intensa, sostenida y productiva que ambas instituciones han consolidado en los últimos años. A ella se sumó El Centro Internacional de Estudios Superiores de Comunicación para América Latina, CIESPAL, responsable de la edición del libro en alianza con CLACSO y UNESCO, reafirmando la convicción de que la cooperación interinstitucional regional constituye un instrumento fundamental para pensar críticamente la tecnología, fortalecer la cultura democrática y promover políticas públicas capaces de atender a los grupos más vulnerables. Los trabajos seleccionados y aquí publicados son el resultado de un proceso riguroso, sistemático y situado: se recibieron 35 postulaciones, evaluadas en primera instancia por un Comité Internacional integrado por nueve especialistas provenientes de Ecuador, Argentina, Brasil y Francia. Posteriormente, UNESCO y CLACSO realizaron la revisión final atendiendo a la calidad técnica y científica, la coherencia metodológica, la consistencia del plan de trabajo y la pertinencia de los temas en relación con la Recomendación sobre la Ética de la IA y el equilibrio regional. El proceso concluyó con la selección de cinco propuestas, varias de ellas con participación de investigadoras e investigadores con trabajo en y sobre Ecuador. Los policy briefs que conforman este libro abordan problemas urgentes de la agenda regional sobre IA. Uno de los núcleos críticos es la transformación del trabajo y la desigualdad digital, un fenómeno particularmente agudo en América Latina y el Caribe, donde históricas brechas educativas, económicas y territoriales se ven amplificadas por una automatización que concentra oportunidades en sectores altamente especializados y desplaza tareas tradicionalmente realizadas por trabajadores menos calificados. La región enfrenta una doble asimetría: la del acceso desigual a tecnologías avanzadas y la de las capacidades necesarias para utilizarlas de modo significativo, reproduciendo patrones de exclusión que atraviesan género, etnia y condición socioeconómica. Otro foco central es la privacidad y la vigilancia algorítmica, ámbitos donde los riesgos son crecientes. La implementación de sistemas opacos —las conocidas “cajas negras” algorítmicas— que procesan datos personales a gran escala ha generado nuevas formas de discriminación, como el racismo algorítmico, sesgos de género, o modelos predictivos que penalizan a grupos históricamente vulnerados. Los casos de identificación errónea en sistemas de reconocimiento facial o la clasificación automatizada de supuestos “riesgos sociales” muestran que, sin marcos éticos y normativos sólidos, la IA puede reforzar desigualdades en vez de corregirlas." (Introducción, páginas 8-9) 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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Standardization of AI Ethics: Stakeholders, Values and Profit

Nicholas Kluge Corrêa, Julia Maria Mönig (eds.)

Bielefeld: transcript Verlag (2026), 161 pp.

"[...] what a certification could look like is only one of the questions that should be asked when discussing ethical certification of AI. Furthermore, how all potentially concerned parties (stakeholders) can be included, which values might be affected, and what this means for those actors who (righ ... tfully) need and want to profit from AI applications were central questions that the philosophy team of the KI. NRW-flagship project „Zertifizierte KI“ (Certified AI) investigated. Further key questions raised in the contributions and throughout the project period include: Can ethics be standardized? Who audits the auditors? How can auditing institutions be aligned with actual societal concerns? What can an assessment look like for a specific area (e.g., human resources)? How are law and ethics intertwined? Which contribution can philosophy provide, now that there is a European regulation on Artificial Intelligence (e.g., in the discussion whether robots in elderly care should be considered as deceptive technology under the AI Act)? Finally, what role do standardization bodies play in ensuring trustworthy AI? Answers to these questions are presented in this book, as well as in the project’s central outcomes: the 'Catalogue of General Ethical Requirements for AI Certification' and the 'Catalogue of Field-Specific Requirements for AI Certification'. The 'Catalogue of General Ethical Requirements for AI Certification' provides a structured framework for trustworthy AI development, identifying overarching ethical requirements for AI certification and outlining six ethical values: fairness, privacy, robustness, sustainability, transparency, and truthfulness. For each value, the project team researched existing tools, metrics, and approaches to help developers, programmers, and other practitioners build trustworthy AI systems. The 'Catalogue of Field-Specific Requirements for AI Certification' offers a list of requirements, an ethical stakeholder analysis, and a discussion of potential value tensions for six exemplary fields: arts, biometric profiling, industry and critical infrastructure, law enforcement, medicine and care and social media, a list of requirements, an ethical stakeholder analyses and a discussion of potential value tensions. The volume at hand collects the contributions to the final conference of the sub-project philosophy of the KI.NRW-Flagship-Projekt “Zertifizierte KI”. (Introduction, pages 11-12) more

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How to Talk to AI (And How Not To)

Jamie Bartlett

London: Ebury Publishing (2026), 272 pp.

"[...] Most people still don't really understand how AI works, how to make the most of it – or what the dangers are. As some people use it to turbo-charge their productivity at work, others are falling into dangerous conspiracies, delusions and psychosis. In How to Talk to AI, award-winning techno ... 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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Empires of AI: The Rise and Fall of a New Global Order

Niall Ferguson, Lisa Klaassen, Eric Schmidt

Foreign Affairs, October 20 (2026)

"Empires require enormous resources and capital to survive. They begin by exploiting economies of political and military scale and end by exhausting themselves defending their domains. AI is the most capital-intensive imperial project in history, undertaken by two superpowers that are already weighe ... more

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Indic Voice Technologies for an Inclusive Digital India: Toolkit for Developers

Nihar Desai, Sujith P., Harleen Kaur, Dona Mathew, Jyotsna Jayaram, Padmavathi Prasad, Thomas Vallianeth

Bhashini; Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward – Artificial Intelligence for All (2026), 70 pp.

"This toolkit sets out a layered, lifecycle-oriented approach to building inclusive and robust speech artificial intelligence (AI) systems. It brings together strategies for diverse and representative data collection, linguistically informed model training, rigorous quality control, and deployment o ... more

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Advancing Open Source AI in India: Recommendations for Governments & Technology Developers

Aarushi Gupta, Anushka Jain, Urvashi Aneja, Shreeja Sen

Bonn; Delhi; Noida (IN): Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward – Artificial Intelligence for All; NASSCOM (2026), 80 pp.

"[...] this brief positions open source AI as a strategic policy option within India’s evolving AI ecosystem. It unpacks the critical importance of openness for India’s digital future, crystallising the key opportunities it offers to governments and developers alike. In doing so, it also explore ... more

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AI and Digital Journalism Education

Emmanuel Bahindi, Antonio Kisembo, Echeru Rodney Oluma

Kampala: Media Challenge Initiative (2026), 29 pp.

"This paper examines how journalism education must change in the age of artificial intelligence. It documents the adoption gap in which students race ahead of their educators; it maps the curriculum-reform models emerging worldwide, from the techno-humanist pyramid to formal AI-competency requiremen ... more

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Critiquing Generative AI in Africa's Media Ecosystems

Lungile A. Tshuma, Trust Matsilele

London; New York: Routledge (2026), 215 pp.

"The book argues that as technology is a social construct reflecting existing power dynamics, those in the Global South, and in Africa in particular, are bound to be marginalised and have their knowledge, systems overlooked as the Global North dominates technological developments. The birth of AI ha ... more

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Generative artificial intelligence and the transformation of newsroom practices in Kenya: A mixed-methods study of professional and training newsrooms

Tommy Kibera Kiilu, George Ngugi King'ara

Journal of Communication and Media Research, volume 18, issue 2 (2026), pp. 1–14

“The rapid diffusion of generative artificial intelligence (GenAI) is transforming newsroom practices globally, yet empirical evidence from African media contexts remains limited. This study examines how GenAI is reshaping newsroom workflows, professional roles, and ethical practices in Kenya thro ... more

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Digital Media Shadowing Democracy: Technology, Communication, and Power

Auksė Balčytienė, Péter Bajomi-Lázár, Helena Sousa (eds.)

Gothenburg: Nordicom, University of Gothenburg (2026), 282 pp.

"The book’s message is brief: Liberal democracies are at risk. Democratic decay has numerous causes, but technological innovations and profit-driven dynamics are shaping societal relations in ways that intensify disagreements and polarisation, undermining informed citizenship. The growing number o ... more

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Handbook on Data Protection and Privacy for Developers of Artificial Intelligence (AI) in India

Ajey Karthik, Aman Taneja, Sreenidhi Srinivasan, Vidushi Sinha

New Delhi: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); FAIR Forward – Artificial Intelligence for All (2026), 117 pp.

"This Handbook is designed as a practical guide for developers of AI systems, especially from early-stage startups, to navigate data protection obligations and ethical considerations, in a clear and actionable manner. Rather than serving as a comprehensive legal or technical manual, the Handbook co ... more

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Multi‐Method Analysis of Locally Built Artificial Intelligence Models Designed for Journalists in an African Country

Akintunde Babatunde Abdullateef Mohammed Adeola Abdulateef Elega

Media and Communication, volume 14 (2026), 19 pp.

"Artificial intelligence (AI) models for journalism have been built within the Global North context, hence deepening the concerns of the “AI divide” between the North and South. This has compelled organizations in various areas of the Global South to develop journalism‐focused AI models to add ... 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. By contrast, middle-income countries accounted for half of ChatGPT’s global traffic within six months of its launch. 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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Invisible Workers, Visible Harms: Perils and Precarities of AI Labour

Aapti Institute

Bonn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) (2026), 40 pp.

"Across South Asia, Southeast Asia, and Sub-Saharan Africa, data workers operate within fragmented and opaque supply chains characterised by informal employment arrangements, limited social protections, and a profound imbalance of power between workers, vendors, and the global technology firms that ... more

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Six Critical Lenses on AI-Generated Images

Catherine Bouko, Nataliia Laba (eds.)

CRC Press (2026), xvii, 176 pp.

"This book offers six critical, interdisciplinary approaches to AI-generated images. It invites the reader to (re-)imagine relationships between artefacts and media, authorship and agency, creativity and commodification, representation, and visual style. Across the chapters, the book examines three ... more

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Handbook on Anthropology and Artificial Intelligence
Deep Insights

Sahana Udupa, Peter Hervik (eds.)

Cheltenham (UK); Northampton, MA (US): Edward Elgar Publishing (2026), xix, 495 pp.

"This timely Handbook provides a groundbreaking collection of anthropological research on artificial intelligence (AI), examining how anthropology can help to comprehend and critique its development. Evaluating the limits, hopes and fears of AI, leading experts explore its influence as a sociocultur ... more

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Globally, more people expect AI to cause job loss than growth: 37-country survey also finds growing awareness of AI — and growing concern in some places

Laura Silver, Richard Wike, Moira Fagan, Jordan Lippert

Pew Research Center (2026), 49 pp.

"In 34 of 37 countries Pew Research Center surveyed earlier this year, people tend to believe AI will lead to fewer jobs rather than more jobs. Still, opinion on this and other AI-related topics may still be taking shape: In many places, about a fifth of adults or more are unsure how AI will impact ... more

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„Hi, how may I assist you?” Chatbots for Better Service Delivery. Practical Guide, Applications and Principles in Development Cooperation
Key Guides

Daniel Brumund, Prashant Pratap Singh, Lisa Werkmeister

Bonn; Eschborn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) (2026), 48 pp.

"The guide provides lessons-learnt for building AI chatbots and explores: motivations and requirements for developing a chatbot; functional types of AI chatbots suitable for different projects; content and knowledge base behind chatbots; technological architectures for AI chatbots; steering and man ... more

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

Handbook on Anthropology and Artificial Intelligence Deep Insights

„Hi, how may I assist you?” Chatbots for Better Service Delivery. Practical Guide, Applications and Principles in Development Cooperation Key Guides

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

Handbook on Anthropology and Artificial Intelligence
Deep Insights

„Hi, how may I assist you?” Chatbots for Better Service Delivery. Practical Guide, Applications and Principles in Development Cooperation
Key Guides